Abaixo estão listadas algumas publicações relacionadas aos temas do projeto que são anteriores à sua execução, bem como as correntes.
2026
Oliveira, G. P.; Almeida, B. R.; Justino, Thiago R. C.; Santos, Carlos A. S.; Santos, Alex A.; Philipi, F.
Multifactorial screening for fine-scale selection of CCS industrial clusters and hubs in Brazil Journal Article
Em: Greenhouse Gases: Science and Technology, 2026, ISSN: 2152-3878.
@article{oliveira2026ghg,
title = {Multifactorial screening for fine-scale selection of CCS industrial clusters and hubs in Brazil},
author = {G.P. Oliveira and B.R. Almeida and Thiago R. C. Justino and Carlos A. S. Santos and Alex A. Santos and F. Philipi},
doi = {10.1002/ghg.70008},
issn = {2152-3878},
year = {2026},
date = {2026-11-20},
urldate = {2026-11-20},
journal = {Greenhouse Gases: Science and Technology},
abstract = {As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as akey pathway for large-scale CO2 abatement in hard-to-abate sectors. This paper presents a multifactorial, data-driven framework toscreen and prioritize potential CCS industrial clusters and hubs across Brazilian regions, emphasizing Rio de Janeiro and S\~{a}o Paulo.The method integrates stratified emission density metrics, clustering algorithms (DBSCAN), and geospatial modeling to identifycapture hubs, hypothetically eligible offshore storage wells, and transport corridors. Using emission data from the recognized SEEG database and the Campos and Santos basins as reference sinks, the framework mapped seven industrial capture clusters and nineteen storage clusters from a sample set of emitters from five sectors. The results show that S\~{a}o Paulo and Rio de Janeiro jointly account for over 63% of Brazil’s emission reduction target for industry and energy, with 22% from Rio and 86% from S\~{a}o Paulo at hub level. The analysis provides a geospatial and quantitative foundation for identifying industrial capture clusters at multipleterritorial scales using emission-stratified metrics, selecting macro-structural fields for the formation of offshore storage clustersand analyzing source-to-sink distance charts to assess transportation logistics. The findings contribute to a critical knowledge base to support the future deployment of CCS routes in Brazil and provide a foundation for subsequent feasibility assessments and economic validation. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as akey pathway for large-scale CO2 abatement in hard-to-abate sectors. This paper presents a multifactorial, data-driven framework toscreen and prioritize potential CCS industrial clusters and hubs across Brazilian regions, emphasizing Rio de Janeiro and São Paulo.The method integrates stratified emission density metrics, clustering algorithms (DBSCAN), and geospatial modeling to identifycapture hubs, hypothetically eligible offshore storage wells, and transport corridors. Using emission data from the recognized SEEG database and the Campos and Santos basins as reference sinks, the framework mapped seven industrial capture clusters and nineteen storage clusters from a sample set of emitters from five sectors. The results show that São Paulo and Rio de Janeiro jointly account for over 63% of Brazil’s emission reduction target for industry and energy, with 22% from Rio and 86% from São Paulo at hub level. The analysis provides a geospatial and quantitative foundation for identifying industrial capture clusters at multipleterritorial scales using emission-stratified metrics, selecting macro-structural fields for the formation of offshore storage clustersand analyzing source-to-sink distance charts to assess transportation logistics. The findings contribute to a critical knowledge base to support the future deployment of CCS routes in Brazil and provide a foundation for subsequent feasibility assessments and economic validation.
Tigre, Y. S.; Almeida, B. R.; Silva, J. W. L.; Oliveira, G. P.
Anais do IV simpósio de petróleo e gás do onshore brasileiro, 2026, ISBN: 978-65-272-2662-8.
@proceedings{yhasmim2023,
title = {Classifica\c{c}\~{a}o de Unidades de Injetividade por M\'{e}todos de Binning N\~{a}o-Supervisionados para Armazenamento Geol\'{o}gico de Carbono},
author = {Y. S. Tigre and B.R. Almeida and J.W.L. Silva and G.P. Oliveira},
url = {https://www.even3.com.br/anais/iv-simposio-de-petroleo-e-gas-do-onshore-brasileiro-394735/765961-classificacao-de-unidades-de-injetividade-por-metodos-de-binning-nao-supervisionados-para-armazenamento-geologico/},
isbn = {978-65-272-2662-8},
year = {2026},
date = {2026-08-03},
urldate = {2026-08-03},
abstract = {Na esteira da transi\c{c}\~{a}o energ\'{e}tica e dos processos de descarboniza\c{c}\~{a}o, o presente artigo aborda o problema de classifica\c{c}\~{a}o de dados cuja finalidade \'{e} obter parti\c{c}\~{o}es para uma distribui\c{c}\~{a}o estat\'{i}stica de forma n\~{a}o supervisionada. Os intervalos de classe determinam unidades de injetividade que se identificam com regi\~{o}es geol\'{o}gicas com qualidades distintas para armazenamento permanente de di\'{o}xido de carbono. Dois algoritmos de aprendizado de m\'{a}quina para binning de dados s\~{a}o analisados: Blocos Bayesianos (BB) e Estimadores de Densidade de N\'{u}cleos (KDE). Os resultados obtidos fornecem explicabilidades diferentes para uma distribui\c{c}\~{a}o-base \'{u}nica.},
howpublished = {Anais do IV simp\'{o}sio de petr\'{o}leo e g\'{a}s do onshore brasileiro},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
Na esteira da transição energética e dos processos de descarbonização, o presente artigo aborda o problema de classificação de dados cuja finalidade é obter partições para uma distribuição estatística de forma não supervisionada. Os intervalos de classe determinam unidades de injetividade que se identificam com regiões geológicas com qualidades distintas para armazenamento permanente de dióxido de carbono. Dois algoritmos de aprendizado de máquina para binning de dados são analisados: Blocos Bayesianos (BB) e Estimadores de Densidade de Núcleos (KDE). Os resultados obtidos fornecem explicabilidades diferentes para uma distribuição-base única.
Oliveira, G. P.; Silva, J. W. L.; Marcussi, B. A.; Almeida, B. R.; Silva, L. C.
Geological Carbon Storage in Brazil: Evolution, Milestones, and Opportunities for Computational Science and Engineering Technical Report
2026, ISBN: 978-65-85805-18-6.
@techreport{oliveira2026cse,
title = {Geological Carbon Storage in Brazil: Evolution, Milestones, and Opportunities for Computational Science and Engineering},
author = {G. P. Oliveira and J.W.L. Silva and B. A. Marcussi and B. R. Almeida and L. C. Silva},
editor = {EdUFPB},
url = {https://drive.google.com/file/d/1yUSHHWHYY8ednMtr86Db0g_Y48HcdBfP/view},
isbn = {978-65-85805-18-6},
year = {2026},
date = {2026-03-07},
urldate = {2026-03-07},
abstract = {This report, structured as a systematic mapping study, provides a comprehensive overview of GCS research in Brazil since the early 2000s, viewed through the interdisciplinary lens of computational science and engineering (CSE) practitioners. By adopting this perspective, it aimed at identifying promising opportunities, highlights emerging trends, and proposes potential directions for future research and development, particularly at the intersection of reservoir modeling, computational sciences, and data-centric engineering. CSE, a rapidly evolving multidisciplinary field, leverages high-performance computing to build algorithms and models necessary for solving the GCS community’s most complex challenges.},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
This report, structured as a systematic mapping study, provides a comprehensive overview of GCS research in Brazil since the early 2000s, viewed through the interdisciplinary lens of computational science and engineering (CSE) practitioners. By adopting this perspective, it aimed at identifying promising opportunities, highlights emerging trends, and proposes potential directions for future research and development, particularly at the intersection of reservoir modeling, computational sciences, and data-centric engineering. CSE, a rapidly evolving multidisciplinary field, leverages high-performance computing to build algorithms and models necessary for solving the GCS community’s most complex challenges.
Silva, L. C.
Plugin Development and Management for the Economic Analysis of Conceptual Offshore Production Layouts Masters Thesis
Center of Technology, Federal University of Paraíba, Graduate Program in Mechanical Engineering, 2026.
@mastersthesis{silva2026,
title = {Plugin Development and Management for the Economic Analysis of Conceptual Offshore Production Layouts},
author = {L. C. Silva},
year = {2026},
date = {2026-02-27},
address = {Graduate Program in Mechanical Engineering},
school = {Center of Technology, Federal University of Para\'{i}ba},
abstract = {The development of offshore fields in deep and ultra-deep waters involves substantial capital investment, high technical complexity, and long project cycles, making decisions taken in the early phases critical to the economic viability of the venture. In such projects, reservoir modeling, subsea engineering, and economic analysis are traditionally handled in a fragmented manner, requiring manual data transfers between separate tools and limiting the systematic exploration of development alternatives. This dissertation presents the development of a plugin between the reservoir simulation environment Petrel® and the conceptual engineering platform FLOCO® (Field Layout Concept Optimizer), with the objective of automating data transfer and expanding the technical-economic evaluation capacity of offshore field architectures. In the proposed workflow, the numerical simulators Eclipse® and Intersect®, accessed from within
Petrel, are responsible for full dynamic reservoir simulation, producing production profiles, pressure curves, and productivity indices. These results are extracted by the plugin and transferred to FLOCO, which uses them to replace its internal reservoir engine with an Inverse Distance Weighting (IDW) interpolation, computing reservoir pressure over time directly from the numerically simulated production and injection curves. The developed methodology encompasses three operational workflows. Case 1 corresponds to a fully automated scenario, in which the plugin orchestrates, from within Petrel, both the execution of simulations and the conceptual evaluation in FLOCO. Case 2 adopts a disciplinary decoupling approach: the validated simulation cube is exported as an immutable input to FLOCO, while infrastructure configuration is carried out manually by conceptual or subsea engineering specialists. The results, centered
on the validation of Case 2 as a proof of concept, demonstrate that the proposed integration is technically feasible: the interface developed in Petrel structures and validates the input data, transmission via API preserves the physical and geometric integrity of the model, and
simulation scenarios are replicated automatically and traceably. The application of the plugin significantly accelerates the project screening phase, increases the number of evaluated scenarios, and enables early-stage anticipation of economic indicators associated with different field
architectures.},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
The development of offshore fields in deep and ultra-deep waters involves substantial capital investment, high technical complexity, and long project cycles, making decisions taken in the early phases critical to the economic viability of the venture. In such projects, reservoir modeling, subsea engineering, and economic analysis are traditionally handled in a fragmented manner, requiring manual data transfers between separate tools and limiting the systematic exploration of development alternatives. This dissertation presents the development of a plugin between the reservoir simulation environment Petrel® and the conceptual engineering platform FLOCO® (Field Layout Concept Optimizer), with the objective of automating data transfer and expanding the technical-economic evaluation capacity of offshore field architectures. In the proposed workflow, the numerical simulators Eclipse® and Intersect®, accessed from within
Petrel, are responsible for full dynamic reservoir simulation, producing production profiles, pressure curves, and productivity indices. These results are extracted by the plugin and transferred to FLOCO, which uses them to replace its internal reservoir engine with an Inverse Distance Weighting (IDW) interpolation, computing reservoir pressure over time directly from the numerically simulated production and injection curves. The developed methodology encompasses three operational workflows. Case 1 corresponds to a fully automated scenario, in which the plugin orchestrates, from within Petrel, both the execution of simulations and the conceptual evaluation in FLOCO. Case 2 adopts a disciplinary decoupling approach: the validated simulation cube is exported as an immutable input to FLOCO, while infrastructure configuration is carried out manually by conceptual or subsea engineering specialists. The results, centered
on the validation of Case 2 as a proof of concept, demonstrate that the proposed integration is technically feasible: the interface developed in Petrel structures and validates the input data, transmission via API preserves the physical and geometric integrity of the model, and
simulation scenarios are replicated automatically and traceably. The application of the plugin significantly accelerates the project screening phase, increases the number of evaluated scenarios, and enables early-stage anticipation of economic indicators associated with different field
architectures.
Petrel, are responsible for full dynamic reservoir simulation, producing production profiles, pressure curves, and productivity indices. These results are extracted by the plugin and transferred to FLOCO, which uses them to replace its internal reservoir engine with an Inverse Distance Weighting (IDW) interpolation, computing reservoir pressure over time directly from the numerically simulated production and injection curves. The developed methodology encompasses three operational workflows. Case 1 corresponds to a fully automated scenario, in which the plugin orchestrates, from within Petrel, both the execution of simulations and the conceptual evaluation in FLOCO. Case 2 adopts a disciplinary decoupling approach: the validated simulation cube is exported as an immutable input to FLOCO, while infrastructure configuration is carried out manually by conceptual or subsea engineering specialists. The results, centered
on the validation of Case 2 as a proof of concept, demonstrate that the proposed integration is technically feasible: the interface developed in Petrel structures and validates the input data, transmission via API preserves the physical and geometric integrity of the model, and
simulation scenarios are replicated automatically and traceably. The application of the plugin significantly accelerates the project screening phase, increases the number of evaluated scenarios, and enables early-stage anticipation of economic indicators associated with different field
architectures.
Júnior, V. A. Santos
Irregularly-bounded cross sections’ shape factors from high-order piecewise-polynomials Journal Article
Em: Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 48, não 137, 2026.
@article{junior2026,
title = {Irregularly-bounded cross sections’ shape factors from high-order piecewise-polynomials},
author = {V. A. Santos J\'{u}nior et al.},
editor = {2026-01-30},
doi = {https://doi.org/10.1007/s40430-025-06239-9},
year = {2026},
date = {2026-01-30},
journal = {Journal of the Brazilian Society of Mechanical Sciences and Engineering},
volume = {48},
number = {137},
abstract = {In two-dimensional domains, apertures represent bounded cross-sections that control transport in diverse engineering
applications. While shape factors of regular apertures are well established, those of irregular boundaries remain poorly
determined due to experimental limitations and modeling inadequacies. This paper introduces a Galerkin-based integral
model to compute shape factors for arbitrary apertures, addressing this gap. The approach combines high-order piecewise
polynomial boundary reconstruction with recovery of flow properties through the Poiseuille number, assuming fully devel-
oped laminar flows. We applied the method to four sandstone-derived apertures, with dimensionless areas ranging from
0.085 to 0.170 and hydraulic diameters from 0.076 to 0.163. Computed dimensionless velocities over the apertures varied
between 1.4 × 10^−4 and 6.7 × 10^−4, while Poiseuille numbers spanned 15.8\textendash23.9, approaching the theoretical limit of
24. The resulting shape factors lay between 1.96 and 2.73, showing discrepancies below 5% when compared with finite
element validations. The current approach enhances quantitative understanding of cross-sectional dynamics in fractured
media and provides a practical tool for applications involving ducts, fissures, or cracks across biotechnology, engineering,
and medical contexts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In two-dimensional domains, apertures represent bounded cross-sections that control transport in diverse engineering
applications. While shape factors of regular apertures are well established, those of irregular boundaries remain poorly
determined due to experimental limitations and modeling inadequacies. This paper introduces a Galerkin-based integral
model to compute shape factors for arbitrary apertures, addressing this gap. The approach combines high-order piecewise
polynomial boundary reconstruction with recovery of flow properties through the Poiseuille number, assuming fully devel-
oped laminar flows. We applied the method to four sandstone-derived apertures, with dimensionless areas ranging from
0.085 to 0.170 and hydraulic diameters from 0.076 to 0.163. Computed dimensionless velocities over the apertures varied
between 1.4 × 10^−4 and 6.7 × 10^−4, while Poiseuille numbers spanned 15.8–23.9, approaching the theoretical limit of
24. The resulting shape factors lay between 1.96 and 2.73, showing discrepancies below 5% when compared with finite
element validations. The current approach enhances quantitative understanding of cross-sectional dynamics in fractured
media and provides a practical tool for applications involving ducts, fissures, or cracks across biotechnology, engineering,
and medical contexts.
applications. While shape factors of regular apertures are well established, those of irregular boundaries remain poorly
determined due to experimental limitations and modeling inadequacies. This paper introduces a Galerkin-based integral
model to compute shape factors for arbitrary apertures, addressing this gap. The approach combines high-order piecewise
polynomial boundary reconstruction with recovery of flow properties through the Poiseuille number, assuming fully devel-
oped laminar flows. We applied the method to four sandstone-derived apertures, with dimensionless areas ranging from
0.085 to 0.170 and hydraulic diameters from 0.076 to 0.163. Computed dimensionless velocities over the apertures varied
between 1.4 × 10^−4 and 6.7 × 10^−4, while Poiseuille numbers spanned 15.8–23.9, approaching the theoretical limit of
24. The resulting shape factors lay between 1.96 and 2.73, showing discrepancies below 5% when compared with finite
element validations. The current approach enhances quantitative understanding of cross-sectional dynamics in fractured
media and provides a practical tool for applications involving ducts, fissures, or cracks across biotechnology, engineering,
and medical contexts.
Omoyemi, P. A.; Coutinho, W. P.; Oliveira, G. C. P.
A Simulation-Based Data Envelopment Analysis Tool for Evaluating Geological Carbon Storage Scenarios Conferência
Anais do IX Simpósio Acadêmico de Engenharia de Produção (SAEPRO) da EEL-USP, 2026, ISBN: 978-65-272-2155-5.
@conference{peter2025,
title = {A Simulation-Based Data Envelopment Analysis Tool for Evaluating Geological Carbon Storage Scenarios},
author = {P. A. Omoyemi and W. P. Coutinho and G. C. P. Oliveira},
editor = {Even3},
url = {https://www.even3.com.br/anais/saepro2025-622279/1388077-a-simulation-based-data-envelopment-analysis-tool-for-evaluating-geological-carbon-storage-scenarios/},
isbn = {978-65-272-2155-5},
year = {2026},
date = {2026-01-23},
urldate = {2026-01-23},
booktitle = {Anais do IX Simp\'{o}sio Acad\^{e}mico de Engenharia de Produ\c{c}\~{a}o (SAEPRO) da EEL-USP},
abstract = {A combined approach of numerical simulation and Data Envelopment Analysis (DEA) is presented to analyze the operational efficiency of CO2 storage in rock formations. Ten scenarios were simulated in the UNISIM-II-D model, which is representative of the Namorado Field of Campos Basin, were simulated using the CMG-GEM compositional simulator. Each case varied in rate of injection, number of wells, and well pattern, injecting 100 % CO2 for 50 years and 150 years of shut-in on a post-injection observation. The DEA-CCR (CRS) model, implemented on Python (Pyomo), was used to find efficient cases that yield optimal conversion of injection inputs to storage outputs. Results show that only three of the scenarios realized complete efficiency under CRS, with Artigo Completo 2 potential room for injection design and operational strategy enhancement. Two performance objectives were considered: maximizing storage index of CO2 and minimizing mobile fraction of CO2. The proposed framework demonstrates DEA as an open post-simulation tool for assessment that complements reservoir physics and enables sustainable decision-making for the optimization of CO2 storage in Brazilian reservoirs. This DEA-type screening can guide follow-up, more-fidelity optimization (e.g., MINLP over well counts/rates) and facilitates pragmatic decision making for planning CO2 storage under uncertainty.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
A combined approach of numerical simulation and Data Envelopment Analysis (DEA) is presented to analyze the operational efficiency of CO2 storage in rock formations. Ten scenarios were simulated in the UNISIM-II-D model, which is representative of the Namorado Field of Campos Basin, were simulated using the CMG-GEM compositional simulator. Each case varied in rate of injection, number of wells, and well pattern, injecting 100 % CO2 for 50 years and 150 years of shut-in on a post-injection observation. The DEA-CCR (CRS) model, implemented on Python (Pyomo), was used to find efficient cases that yield optimal conversion of injection inputs to storage outputs. Results show that only three of the scenarios realized complete efficiency under CRS, with Artigo Completo 2 potential room for injection design and operational strategy enhancement. Two performance objectives were considered: maximizing storage index of CO2 and minimizing mobile fraction of CO2. The proposed framework demonstrates DEA as an open post-simulation tool for assessment that complements reservoir physics and enables sustainable decision-making for the optimization of CO2 storage in Brazilian reservoirs. This DEA-type screening can guide follow-up, more-fidelity optimization (e.g., MINLP over well counts/rates) and facilitates pragmatic decision making for planning CO2 storage under uncertainty.
2025
Almeida, B. R.; Justino, T. R. C.; Santos, C. A. S.; Oliveira, G. C. P.; Santos, A. A.; Philipi, F.
Modelagem de hubs e clusters de CCUS no contexto brasileiro: análise geoespacial para serviços prospectivos de transporte e armazenamento Conferência
Encontro de Tecnologia e Inovação (ETRI 2025), 2025, (Oral session.).
@conference{almeida2025etri,
title = {Modelagem de hubs e clusters de CCUS no contexto brasileiro: an\'{a}lise geoespacial para servi\c{c}os prospectivos de transporte e armazenamento},
author = {B. R. Almeida and T. R. C. Justino and C. A. S. Santos and G. C. P. Oliveira and A. A. Santos and F. Philipi},
editor = {Research Centre for Greenhouse Gas Innovation},
year = {2025},
date = {2025-11-04},
booktitle = {Encontro de Tecnologia e Inova\c{c}\~{a}o (ETRI 2025)},
note = {Oral session.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Rodrigues, D. M. T.; Santos, J.; Oliveira, G. P.
Techno-Economic Assessment of Customizable and Ready-To-Deploy CO2 Compression Units for Industrial CCU Systems Conferência
Encontro de Tecnologia e Inovação (ETRI 2025), 2025, (Oral session.).
@conference{matos2025etri,
title = {Techno-Economic Assessment of Customizable and Ready-To-Deploy CO2 Compression Units for Industrial CCU Systems},
author = {D. M. T. Rodrigues and J. Santos and G. P. Oliveira},
editor = {Research Centre for Greenhouse Gas Innovation},
year = {2025},
date = {2025-11-04},
urldate = {2025-11-04},
booktitle = {Encontro de Tecnologia e Inova\c{c}\~{a}o (ETRI 2025)},
abstract = {This paper presents a comprehensive techno-economic analysis of carbon dioxide (CO2) compression as part of the carbon capture and utilization (CCU) value chain processes aiming at future micro facilities applications. The method includes equipment specification and cost estimation models for compressors and related infrastructure. Providing valuable information on performance and economic viability, this study addresses the utilization of captured CO2 as a protagonist in the decarbonization process, adding value to the compound and transforming it into raw material for generating new ventures, especially in small-scale installations. Energy consumption during the compression stages, capital investment requirements, operational and maintenance (O\&M) costs of the system are the main keys to start the feasibility discussion. As a seminal contribution, this study offers a new perspective for small scaled facilities who are interested in promoting sustainable development and achieving their own carbon mitigation goals through CCU initiatives.},
note = {Oral session.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
This paper presents a comprehensive techno-economic analysis of carbon dioxide (CO2) compression as part of the carbon capture and utilization (CCU) value chain processes aiming at future micro facilities applications. The method includes equipment specification and cost estimation models for compressors and related infrastructure. Providing valuable information on performance and economic viability, this study addresses the utilization of captured CO2 as a protagonist in the decarbonization process, adding value to the compound and transforming it into raw material for generating new ventures, especially in small-scale installations. Energy consumption during the compression stages, capital investment requirements, operational and maintenance (O&M) costs of the system are the main keys to start the feasibility discussion. As a seminal contribution, this study offers a new perspective for small scaled facilities who are interested in promoting sustainable development and achieving their own carbon mitigation goals through CCU initiatives.
Santos, Y. R. P.; Gomes, I.; Lima, A.; Oliveira, G. P.
Em: Mechanics of Time-Dependent Materials, vol. 29, iss. 4, pp. 97-120, 2025, ISSN: 1385-2000.
@article{yago2025,
title = {Matrix acidizing impact on the geomechanical properties in carbonate rocks: an experimental approach using acetic acid at different contact times},
author = {Y. R. P. Santos and I. Gomes and A. Lima and G.P. Oliveira},
doi = {10.1007/s11043-025-09834-4},
issn = {1385-2000},
year = {2025},
date = {2025-10-29},
urldate = {2025-10-29},
journal = {Mechanics of Time-Dependent Materials},
volume = {29},
issue = {4},
pages = {97-120},
abstract = {This study aimed to evaluate the geomechanical changes in carbonates after matrix acidizing via acetic acid at different contact times (36/72/108 h). Synthetic carbonate rocks without fractures and with fractures were produced and subjected to matrix acidizing tests. X-ray microcomputed tomography, porosity and permeability tests were performed to identify the dissolution processes. Unconfined compressive strength tests (UCS) were performed on acidified and nonacidified samples to compare their stress\textendashstrain behavior, Young’s modulus and Poisson’s ratio before and after acidification. Petrophysical changes, such as increased porosity and permeability caused by the dissolution of the rock matrix with increasing injected acid, promote the formation of wormholes, affecting their structure. The samples exhibited a gradual decrease in mechanical strength with increasing contact time with acid; they were classified as moderately hard to hard (41.32 MPa to 50.80 MPa for nonacidified rocks) to soft (12.45 MPa to 24.18 MPa) after 36 h of testing; they also progressed from soft to very soft (4.61 MPa to 11.20 MPa and 4.12 MPa to 6.69 MPa) after 72 h and 108 h of acidification, respectively; and they exhibited a change in elastic behavior (brittle) to plastic (ductile) and a reduction in stiffness, as evidenced by a decrease in Young’s modulus, in addition to a reduction in Poisson’s ratio. Evaluating the impact of acid treatment on rock mechanics is essential for determining mechanical degradation after acid treatment to ensure that the stimulation technique does not compromise the integrity of the reservoir to the point at which its collapse.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study aimed to evaluate the geomechanical changes in carbonates after matrix acidizing via acetic acid at different contact times (36/72/108 h). Synthetic carbonate rocks without fractures and with fractures were produced and subjected to matrix acidizing tests. X-ray microcomputed tomography, porosity and permeability tests were performed to identify the dissolution processes. Unconfined compressive strength tests (UCS) were performed on acidified and nonacidified samples to compare their stress–strain behavior, Young’s modulus and Poisson’s ratio before and after acidification. Petrophysical changes, such as increased porosity and permeability caused by the dissolution of the rock matrix with increasing injected acid, promote the formation of wormholes, affecting their structure. The samples exhibited a gradual decrease in mechanical strength with increasing contact time with acid; they were classified as moderately hard to hard (41.32 MPa to 50.80 MPa for nonacidified rocks) to soft (12.45 MPa to 24.18 MPa) after 36 h of testing; they also progressed from soft to very soft (4.61 MPa to 11.20 MPa and 4.12 MPa to 6.69 MPa) after 72 h and 108 h of acidification, respectively; and they exhibited a change in elastic behavior (brittle) to plastic (ductile) and a reduction in stiffness, as evidenced by a decrease in Young’s modulus, in addition to a reduction in Poisson’s ratio. Evaluating the impact of acid treatment on rock mechanics is essential for determining mechanical degradation after acid treatment to ensure that the stimulation technique does not compromise the integrity of the reservoir to the point at which its collapse.
Filho, G. H. C. C.
Riscos Sistêmicos Ambientais e as Duplas Funções de Mitigação das Tecnologias de Inteligência Artificial Conscientes do Carbono Bachelor Thesis
2025.
@bachelorthesis{costafilho2025,
title = {Riscos Sist\^{e}micos Ambientais e as Duplas Fun\c{c}\~{o}es de Mitiga\c{c}\~{a}o das Tecnologias de Intelig\^{e}ncia Artificial Conscientes do Carbono},
author = {G. H. C. C. Filho},
editor = {Undergraduate Program in Data Science and Artificial Intelligence, Center of Informatics, Federal University of Para\'{i}ba},
year = {2025},
date = {2025-10-13},
urldate = {2025-10-13},
abstract = {This dissertation explores the intersection between Artificial Intelligence (AI) and sustainability, focusing on systemic environmental risks, the carbon market, and the development of carbon-aware technologies. The main objective was to analyze how the advancement of AI can exacerbate environmental pressures\textemdashsuch as energy consumption, water use, reliance on critical minerals, and electronic waste generation \textemdash while also contributing to climate change mitigation strategies through its integration into governance mechanisms and the carbon market. The findings reveal AI\'s dual nature, acting both as a driver of environmental risks and a tool for sustainable solutions. The adoption of standardized metrics, robust national and international regulations, and strengthened governance were identified as essential for establishing the paradigm of a carbon-aware AI. Brazil stands out with the potential to lead globally, leveraging its predominantly renewable energy matrix and ongoing regulatory initiatives, despite challenges related to governance and socio-environmental pressures. The conclusions confirm that the study’s objectives were achieved, partially validating the initial hypothesis and emphasizing the need to integrate technology, regulation, and climate justice for a sustainable future.},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
This dissertation explores the intersection between Artificial Intelligence (AI) and sustainability, focusing on systemic environmental risks, the carbon market, and the development of carbon-aware technologies. The main objective was to analyze how the advancement of AI can exacerbate environmental pressures—such as energy consumption, water use, reliance on critical minerals, and electronic waste generation — while also contributing to climate change mitigation strategies through its integration into governance mechanisms and the carbon market. The findings reveal AI's dual nature, acting both as a driver of environmental risks and a tool for sustainable solutions. The adoption of standardized metrics, robust national and international regulations, and strengthened governance were identified as essential for establishing the paradigm of a carbon-aware AI. Brazil stands out with the potential to lead globally, leveraging its predominantly renewable energy matrix and ongoing regulatory initiatives, despite challenges related to governance and socio-environmental pressures. The conclusions confirm that the study’s objectives were achieved, partially validating the initial hypothesis and emphasizing the need to integrate technology, regulation, and climate justice for a sustainable future.
Almeida, B. R.; Justino, T. R. C.; Santos, C. A. S.; Oliveira, G. P.; Santos, A. A.
Geospatial Data Analysis for Source-to-Sink Hub Modeling of High-Prospectivity CCUS Industrial Clusters in Brazil Conferência
Proceedings of the AAPG International Conference & Exhibition (ICE 2025), 2025, (Poster session.).
@conference{almeida2025ice,
title = {Geospatial Data Analysis for Source-to-Sink Hub Modeling of High-Prospectivity CCUS Industrial Clusters in Brazil},
author = {B. R. Almeida and T. R. C. Justino and C. A. S. Santos and G. P. Oliveira and A. A. Santos},
editor = {American Association of Petroleum Geologists},
year = {2025},
date = {2025-10-04},
booktitle = {Proceedings of the AAPG International Conference \& Exhibition (ICE 2025)},
abstract = {CCUS value chain leverages decarbonization in HTA sectors. Hub-and-clusters business models (HCBMs) are emerging worldwide and Brazil has a potential market for CCUS services and technologies. Fine-scale HCBMs in Brazil is a state-of-art and unexplored topic. This poster addresses the formation of a knowledge base and capacity building required for scaling up CCUS projects in Brazil. It discusses data pipeline from scraping to visualization, geospatial clustering, storage networks based on hubs-to-FPSO distances, legacy infrastructure for new services and repurposing, as well as onshore industrial clusters and offshore storage clusters.},
note = {Poster session.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
CCUS value chain leverages decarbonization in HTA sectors. Hub-and-clusters business models (HCBMs) are emerging worldwide and Brazil has a potential market for CCUS services and technologies. Fine-scale HCBMs in Brazil is a state-of-art and unexplored topic. This poster addresses the formation of a knowledge base and capacity building required for scaling up CCUS projects in Brazil. It discusses data pipeline from scraping to visualization, geospatial clustering, storage networks based on hubs-to-FPSO distances, legacy infrastructure for new services and repurposing, as well as onshore industrial clusters and offshore storage clusters.
Rodrigues, D. M. T.; Oliveira, G. P.
Techno-Economic Assessment of CO2 Compression for CCUS Projects in Brazil Proceedings Article
Em: Proceedings of the XXXI National Congress of Mechanical Engineering Students, Brazilian Society of Mechanical Sciences and Engineering 2025.
@inproceedings{2025rodrigues,
title = {Techno-Economic Assessment of CO2 Compression for CCUS Projects in Brazil},
author = {D. M. T. Rodrigues and G. P. Oliveira},
year = {2025},
date = {2025-10-03},
urldate = {2025-10-03},
booktitle = {Proceedings of the XXXI National Congress of Mechanical Engineering Students},
organization = {Brazilian Society of Mechanical Sciences and Engineering},
abstract = {This paper presents a comprehensive techno-economic analysis of carbon dioxide (CO2) compression as part of the carbon, capture, utilization, and storage (CCUS) value chain processes with a specific focus on future ventures in Brazil. The method includes equipment specification and detailed cost estimation models for compressors and related infrastructure, aiming at providing valuable insights into performance and economic feasibility of a capture/transportation system. Key technical and economic parameters are evaluated, such as energy consumption during the compression stages, capital investment requirements, and operating and maintenance (O\&M) costs of the system. As a seminal contribution nationwide, this study offers a new perspective for the hard-to-abate Brazilian industry interested to promoting sustainable development and achieving their carbon mitigation goals through CCUS initiatives.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a comprehensive techno-economic analysis of carbon dioxide (CO2) compression as part of the carbon, capture, utilization, and storage (CCUS) value chain processes with a specific focus on future ventures in Brazil. The method includes equipment specification and detailed cost estimation models for compressors and related infrastructure, aiming at providing valuable insights into performance and economic feasibility of a capture/transportation system. Key technical and economic parameters are evaluated, such as energy consumption during the compression stages, capital investment requirements, and operating and maintenance (O&M) costs of the system. As a seminal contribution nationwide, this study offers a new perspective for the hard-to-abate Brazilian industry interested to promoting sustainable development and achieving their carbon mitigation goals through CCUS initiatives.
Freitas, I. C. S.
Strategies for positioning wells on a quality map Journal Article
Em: Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 47, iss. 10, pp. 462, 2025.
@article{freitas2025,
title = {Strategies for positioning wells on a quality map},
author = {I. C. S. Freitas et al.},
doi = {10.1007/s40430-025-05751-2},
year = {2025},
date = {2025-08-02},
urldate = {2025-08-02},
journal = {Journal of the Brazilian Society of Mechanical Sciences and Engineering},
volume = {47},
issue = {10},
pages = {462},
abstract = {This study proposes an innovative methodology that integrates quality maps (QMs) and hydraulic flow units (HFUs) to optimize well positioning in oil reservoirs. The application of the synthetic model UNISIM-I-D-based on the Namorado Field (Campos Basin)-demonstrated significant technical and economic gains, with emphasis on the significant reduction in water production and the consequent increase in the net present value (NPV). The strategy allowed isolating zones of high water saturation, prioritizing areas with greater oil saturation, which resulted in reduced operating costs associated with the treatment and disposal of produced water. As a result, the best identified well (P3) presented an NPV of over US$ 2.5 billion, approximately 32% higher than the best well in conventional scenarios. The integration between HFUs and QMs proved to be crucial to accurately identify the regions of greatest productivity, while minimizing computational complexity and increasing decision-making efficiency. The findings reinforce the potential of the hybrid methodology in scenarios with high geological heterogeneity, contributing to maximize hydrocarbon recovery and optimize field development strategies. Finally, an extension of this study proposes a more in-depth analysis of drilling costs. When examining the three wells drilled in scenario 2, excellent production is observed; however, the presence of offshore wells significantly increases costs, which suggests that drilling only one well, as proposed in scenario 1, could be more economically advantageous.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study proposes an innovative methodology that integrates quality maps (QMs) and hydraulic flow units (HFUs) to optimize well positioning in oil reservoirs. The application of the synthetic model UNISIM-I-D-based on the Namorado Field (Campos Basin)-demonstrated significant technical and economic gains, with emphasis on the significant reduction in water production and the consequent increase in the net present value (NPV). The strategy allowed isolating zones of high water saturation, prioritizing areas with greater oil saturation, which resulted in reduced operating costs associated with the treatment and disposal of produced water. As a result, the best identified well (P3) presented an NPV of over US$ 2.5 billion, approximately 32% higher than the best well in conventional scenarios. The integration between HFUs and QMs proved to be crucial to accurately identify the regions of greatest productivity, while minimizing computational complexity and increasing decision-making efficiency. The findings reinforce the potential of the hybrid methodology in scenarios with high geological heterogeneity, contributing to maximize hydrocarbon recovery and optimize field development strategies. Finally, an extension of this study proposes a more in-depth analysis of drilling costs. When examining the three wells drilled in scenario 2, excellent production is observed; however, the presence of offshore wells significantly increases costs, which suggests that drilling only one well, as proposed in scenario 1, could be more economically advantageous.
Almeida, B. R.
Multifactorial modeling for screening and selection of industrial CCUS clusters and hubs in Brazil Masters Thesis
Graduate Program in Mechanical Engineering, 2025.
@mastersthesis{2025beatrizmsc,
title = {Multifactorial modeling for screening and selection of industrial CCUS clusters and hubs in Brazil},
author = {B. R. Almeida },
editor = {Center of Technology, Federal University of Para\'{i}ba},
year = {2025},
date = {2025-07-25},
urldate = {2025-07-25},
school = {Graduate Program in Mechanical Engineering},
keywords = {},
pubstate = {published},
tppubtype = {mastersthesis}
}
Justino, T. R. C.; Almeida, B. R.; Santos, C. A. S.; Souza, J. C.; Oliveira, G. P.
Desafios de clusterização de dados geoespaciais para a formação de redes industriais de CCUS Proceedings Article
Em: de Computação, Sociedade Brasileira (Ed.): Anais da VI Escola Regional De Alto Desempenho Da Região Nordeste (ERAD-NE), 2025.
@inproceedings{justino2025,
title = {Desafios de clusteriza\c{c}\~{a}o de dados geoespaciais para a forma\c{c}\~{a}o de redes industriais de CCUS},
author = {T. R. C. Justino and B. R. Almeida and C. A. S. Santos and J. C. Souza and G. P. Oliveira},
editor = {Sociedade Brasileira de Computa\c{c}\~{a}o},
doi = {10.5753/erad-ne.2025.11765},
year = {2025},
date = {2025-07-02},
booktitle = {Anais da VI Escola Regional De Alto Desempenho Da Regi\~{a}o Nordeste (ERAD-NE)},
abstract = {Este artigo discute alguns desafios decorrentes do processo de triagem e identifica\c{c}\~{a}o de clusters e hubs de captura e armazenamento de CO2 no Brasil, com foco em \'{a}reas estrat\'{e}gicas onshore e offshore. Utilizando t\'{e}cnicas de an\'{a}lise de dados geoespaciais, clusteriza\c{c}\~{a}o e algoritmos de roteamento, o estudo mapeou estruturas nos seguintes estados: Rio de Janeiro, S\~{a}o Paulo e Rio Grande do Norte. Apresentamos como a dispers\~{a}o geogr\'{a}fica dos dados e a depend\^{e}ncia de requisi\c{c}\~{o}es por API influenciam a escalabilidade e o desempenho computacional dos algoritmos.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Este artigo discute alguns desafios decorrentes do processo de triagem e identificação de clusters e hubs de captura e armazenamento de CO2 no Brasil, com foco em áreas estratégicas onshore e offshore. Utilizando técnicas de análise de dados geoespaciais, clusterização e algoritmos de roteamento, o estudo mapeou estruturas nos seguintes estados: Rio de Janeiro, São Paulo e Rio Grande do Norte. Apresentamos como a dispersão geográfica dos dados e a dependência de requisições por API influenciam a escalabilidade e o desempenho computacional dos algoritmos.
Souza, J. C.
Triagem de Clusters e Hubs Industriais de CCUS no Nordeste Brasileiro por Análise de Dados Geoespaciais Bachelor Thesis
2025.
@bachelorthesis{cruz2025,
title = {Triagem de Clusters e Hubs Industriais de CCUS no Nordeste Brasileiro por An\'{a}lise de Dados Geoespaciais},
author = {J. C. Souza},
editor = {Undergraduate Program in Data Science and Artificial Intelligence, Center of Informatics, Federal University of Para\'{i}ba},
year = {2025},
date = {2025-05-19},
abstract = {The injection and permanent storage of CO2 are critical operations in the Carbon Capture, Utilization, and Storage (CCUS) chain, essential for offsetting emissions in hard-to-abate sectors such as energy and industry. Brazil’s Northeast region \textendash particularly the states of Bahia (BA), Rio Grande do Norte (RN), Sergipe (SE), and Alagoas (AL) offers a highly favorable scenario for CCUS implementation due to its concentration of industrial hubs, existing oil well infrastructure in highly prospective sedimentary basins, and strategic logistics. This study identifies CCUS clusters and hubs in these states using opportunity metrics based on emission density, transport feasibility, and the reuse of wells with an opportunity index (Ow) greater than 0.3 as CO2 sinks. The Potiguar (RN), Rec\^{o}ncavo (BA), and Sergipe-Alagoas (SE/AL) basins were analyzed, selected for their proven storage capacity. The methodology included mathematical models for screening municipalities by emissions and geospatial analysis. This study contributes to the assessment of the feasibility of scalable geological carbon storage projects in the Northeast, highlighting the integration of legacy infrastructure with new economic opportunities for the oil and gas sector.},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
The injection and permanent storage of CO2 are critical operations in the Carbon Capture, Utilization, and Storage (CCUS) chain, essential for offsetting emissions in hard-to-abate sectors such as energy and industry. Brazil’s Northeast region – particularly the states of Bahia (BA), Rio Grande do Norte (RN), Sergipe (SE), and Alagoas (AL) offers a highly favorable scenario for CCUS implementation due to its concentration of industrial hubs, existing oil well infrastructure in highly prospective sedimentary basins, and strategic logistics. This study identifies CCUS clusters and hubs in these states using opportunity metrics based on emission density, transport feasibility, and the reuse of wells with an opportunity index (Ow) greater than 0.3 as CO2 sinks. The Potiguar (RN), Recôncavo (BA), and Sergipe-Alagoas (SE/AL) basins were analyzed, selected for their proven storage capacity. The methodology included mathematical models for screening municipalities by emissions and geospatial analysis. This study contributes to the assessment of the feasibility of scalable geological carbon storage projects in the Northeast, highlighting the integration of legacy infrastructure with new economic opportunities for the oil and gas sector.
Santos, L. F. C.
PUMLE: A Framework for Data-Driven Applications in Underground Carbon Sequestration Ventures Bachelor Thesis
Undergraduate Program in Data Science and Artificial Intelligence (Federal University of Paraíba), Center of Informatics, 2025.
@bachelorthesis{2025luizfcs2,
title = {PUMLE: A Framework for Data-Driven Applications in Underground Carbon Sequestration Ventures},
author = {L. F. C. Santos},
editor = {Federal University of Para\'{i}ba},
year = {2025},
date = {2025-05-08},
urldate = {2025-05-08},
address = {Center of Informatics},
school = {Undergraduate Program in Data Science and Artificial Intelligence (Federal University of Para\'{i}ba)},
abstract = {PUMLE is a framework designed to seamlessly manage large datasets generated from numerical simulations of CO2 injection into underground reservoirs. Using an architecture inspired by the Medallion model, the workflow covers the key stages of the data lifecycle, from generation through batch simulations to the final storage of results in efficient file formats, prioritizing minimal computational effort. PUMLE is intended to generate high-quality data to support machine learning experiments aimed at predicting the dynamics of CO2 plumes in future Brazilian carbon sequestration projects, particularly those based on techniques aware of the physical phenomenology behind the injection process. Performance metrics indicate that, despite the numerical solution consuming the largest share of processing time, the stages of ingestion, transformation, and storage take only a modest fraction of the total. This tool is expected to facilitate the creation of consistent datasets, providing scalability and reproducibility for training, testing, and prototyping data-driven
solutions focused on the development and monitoring stages of carbon sequestration ventures in heterogeneous domains.},
keywords = {},
pubstate = {published},
tppubtype = {bachelorthesis}
}
PUMLE is a framework designed to seamlessly manage large datasets generated from numerical simulations of CO2 injection into underground reservoirs. Using an architecture inspired by the Medallion model, the workflow covers the key stages of the data lifecycle, from generation through batch simulations to the final storage of results in efficient file formats, prioritizing minimal computational effort. PUMLE is intended to generate high-quality data to support machine learning experiments aimed at predicting the dynamics of CO2 plumes in future Brazilian carbon sequestration projects, particularly those based on techniques aware of the physical phenomenology behind the injection process. Performance metrics indicate that, despite the numerical solution consuming the largest share of processing time, the stages of ingestion, transformation, and storage take only a modest fraction of the total. This tool is expected to facilitate the creation of consistent datasets, providing scalability and reproducibility for training, testing, and prototyping data-driven
solutions focused on the development and monitoring stages of carbon sequestration ventures in heterogeneous domains.
solutions focused on the development and monitoring stages of carbon sequestration ventures in heterogeneous domains.
Santos, L. F. C.; Oliveira, G. P.
Generation-to-Storage Data Framework for Large-Scale Carbon Sequestration Simulation Datasets Proceedings Article
Em: Anais da VI Escola Regional de Banco de Dados, Sociedade Brasileira de Computação, 2025.
@inproceedings{luizfcs2025,
title = {Generation-to-Storage Data Framework for Large-Scale Carbon Sequestration Simulation Datasets},
author = {L. F. C. Santos and G. P. Oliveira},
doi = {10.5753/erbd.2025.7365},
year = {2025},
date = {2025-04-23},
booktitle = {Anais da VI Escola Regional de Banco de Dados},
publisher = {Sociedade Brasileira de Computa\c{c}\~{a}o},
abstract = {Carbon sequestration is a promising CO2 removal technology, particularly for the oil and gas industry. Consequently, monitoring the CO2 injected into deep geological formations is crucial for containment and environmental safety. This paper presents an application of data engineering principles to managing large datasets from numerical flow simulations of underground CO2 injection. By integrating data lifecycle phases with a Medallion-like architecture, the proposed framework delivers consumable assets for physics-informed machine learning experiments. One expects it provides insights into gas plume motion tracking, supporting reservoir monitoring in the post-injection phase of Carbon Capture and Storage (CCS) programs.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Carbon sequestration is a promising CO2 removal technology, particularly for the oil and gas industry. Consequently, monitoring the CO2 injected into deep geological formations is crucial for containment and environmental safety. This paper presents an application of data engineering principles to managing large datasets from numerical flow simulations of underground CO2 injection. By integrating data lifecycle phases with a Medallion-like architecture, the proposed framework delivers consumable assets for physics-informed machine learning experiments. One expects it provides insights into gas plume motion tracking, supporting reservoir monitoring in the post-injection phase of Carbon Capture and Storage (CCS) programs.
Magalhães, R. M.; Machado, T. J.; Santos, M. D.; Oliveira, G. P.
Cell-level deep learning as proxy model for reservoir simulation and production forecasting Journal Article
Em: Journal of Petroleum Exploration and Production Technology, iss. 15, não 39, 2025, ISSN: 2190-0566.
@article{magalhaes2025,
title = {Cell-level deep learning as proxy model for reservoir simulation and production forecasting},
author = {R. M. Magalh\~{a}es and T. J. Machado and M. D. Santos and G. P. Oliveira},
doi = {10.1007/s13202-024-01889-2},
issn = {2190-0566},
year = {2025},
date = {2025-02-12},
urldate = {2025-02-12},
journal = {Journal of Petroleum Exploration and Production Technology},
number = {39},
issue = {15},
abstract = {Optimizing strategies in the Oil and Gas Industry, particularly within reservoir engineering and management, remains a significant challenge due to the prohibitive computational time costs and high resource demands of current simulation methods, even for medium-sized reservoirs. Notably, existing scientific approaches have not leveraged Deep Neural Networks (DNNs) for fine-grained predictions at the grid-cell level. This thesis introduces a novel approach that integrates DNNs with a Design of Experiments framework to develop a proxy model for reservoir simulation software. The methodology includes a robust feature selection process, model design, and training strategy, supplemented by comprehensive statistical evaluations and graphical tools. The proposed proxy models are validated using four distinct industrial scenarios based on the SPE9 black oil benchmark, incorporating production and injection wells across diverse temporal samples. The results demonstrate a significant improvement in computational efficiency without compromising accuracy, achieving over 80% accuracy across all scenarios, and reaching up to 99.9% under specific conditions. These findings highlight the potential of DNN-based proxy models to transform reservoir management practices, offering a scalable and resource-efficient alternative to traditional numerical simulations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Optimizing strategies in the Oil and Gas Industry, particularly within reservoir engineering and management, remains a significant challenge due to the prohibitive computational time costs and high resource demands of current simulation methods, even for medium-sized reservoirs. Notably, existing scientific approaches have not leveraged Deep Neural Networks (DNNs) for fine-grained predictions at the grid-cell level. This thesis introduces a novel approach that integrates DNNs with a Design of Experiments framework to develop a proxy model for reservoir simulation software. The methodology includes a robust feature selection process, model design, and training strategy, supplemented by comprehensive statistical evaluations and graphical tools. The proposed proxy models are validated using four distinct industrial scenarios based on the SPE9 black oil benchmark, incorporating production and injection wells across diverse temporal samples. The results demonstrate a significant improvement in computational efficiency without compromising accuracy, achieving over 80% accuracy across all scenarios, and reaching up to 99.9% under specific conditions. These findings highlight the potential of DNN-based proxy models to transform reservoir management practices, offering a scalable and resource-efficient alternative to traditional numerical simulations.
Lucena, R. M.; Pontes, J.; Brau, F.; Wit, A. De; Mangiavacchi, N.
Effect of an interface undulation on convective dissolution of CO2 Journal Article
Em: Advances in Water Resources, vol. 197, não 104904, 2025, ISSN: 1872-9657.
@article{lucena2025,
title = {Effect of an interface undulation on convective dissolution of CO2},
author = {R. M. Lucena and J. Pontes and F. Brau and A. De Wit and N. Mangiavacchi},
doi = {j.advwatres.2025.104904},
issn = {1872-9657},
year = {2025},
date = {2025-02-05},
journal = {Advances in Water Resources},
volume = {197},
number = {104904},
abstract = {When a partially miscible fluid dissolves into a host phase below it, buoyancy-driven fingering develops when the diffusive boundary solution created is denser than the underlying solvent. In many situations, the interface between the two fluids may present level variations introduced by geometrical irregularities. We study here numerically the influence of this interface undulation on the properties of the convective dissolution and on the resulting transfer flux. Two-dimensional time dependent numerical simulations are performed, assuming that the flow is governed by Darcy’s law, along with the Boussinesq approximation, to account for buoyancy effects introduced by a concentration dependent density. The velocity field is modeled by a vorticity\textendashstream function formulation. The resulting equations are solved through the Taylor\textendashGalerkin Finite Element Method, using a Crank\textendashNicolson time discretization. It is observed that the onset of the fingering instability is delayed in the inclined regions between the peaks and valleys of the undulation and that the fingers develop mainly in the horizontal regions. Additionally, at the valleys, there is an accumulation of the solute and a thickening of the boundary layer caused by the recirculation which induces the nucleation and by the anchoring of the fingering process at that location. This anchoring is maintained up to the later shutdown stages for cases with large interface undulations. While the flux is larger during the diffusive and initial fingering stages, the asymptotic flux is not strongly influenced by the undulation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
When a partially miscible fluid dissolves into a host phase below it, buoyancy-driven fingering develops when the diffusive boundary solution created is denser than the underlying solvent. In many situations, the interface between the two fluids may present level variations introduced by geometrical irregularities. We study here numerically the influence of this interface undulation on the properties of the convective dissolution and on the resulting transfer flux. Two-dimensional time dependent numerical simulations are performed, assuming that the flow is governed by Darcy’s law, along with the Boussinesq approximation, to account for buoyancy effects introduced by a concentration dependent density. The velocity field is modeled by a vorticity–stream function formulation. The resulting equations are solved through the Taylor–Galerkin Finite Element Method, using a Crank–Nicolson time discretization. It is observed that the onset of the fingering instability is delayed in the inclined regions between the peaks and valleys of the undulation and that the fingers develop mainly in the horizontal regions. Additionally, at the valleys, there is an accumulation of the solute and a thickening of the boundary layer caused by the recirculation which induces the nucleation and by the anchoring of the fingering process at that location. This anchoring is maintained up to the later shutdown stages for cases with large interface undulations. While the flux is larger during the diffusive and initial fingering stages, the asymptotic flux is not strongly influenced by the undulation.
2024
Almeida, B. R.; Trajano, A. F.; Avelino, E. L.; Amorim, D. N.; Justino, T. R. C.; Oliveira, G. P.
Annals of the 12º Congresso Brasileiro de P&D em Petróleo, Gás e Biocombustíveis – PDPETRO, ABPG 12º Congresso Brasileiro de P&D em Petróleo, Gás e Biocombustíveis – PDPETRO, Balenário Camboriú, Brazil, 2024.
@conference{rodrigues2024metricas,
title = {M\'{e}tricas de oportunidade para reaproveitamento de po\c{c}os como estrat\'{e}gia de abatimento de CO2 proveniente de clusters e hubs industriais de CCUS},
author = {B. R. Almeida and A. F. Trajano and E. L. Avelino and D. N. Amorim and T. R. C. Justino and G. P. Oliveira},
doi = {10.71190/2024-12-1224716},
year = {2024},
date = {2024-11-01},
urldate = {2024-11-01},
booktitle = {Annals of the 12º Congresso Brasileiro de P\&D em Petr\'{o}leo, G\'{a}s e Biocombust\'{i}veis \textendash PDPETRO},
publisher = {12º Congresso Brasileiro de P\&D em Petr\'{o}leo, G\'{a}s e Biocombust\'{i}veis \textendash PDPETRO},
address = {Balen\'{a}rio Cambori\'{u}, Brazil},
organization = {ABPG},
abstract = {Inje\c{c}\~{a}o e armazenamento permanente de CO2 s\~{a}o opera\c{c}\~{o}es da cadeia de CCUS que visam neutralizar emiss\~{o}es em setores de dif\'{i}cil abatimento, tais como energia e ind\'{u}stria. Nos \'{u}ltimos anos, um novo horizonte de oportunidades come\c{c}ou a se abrir no Brasil para o setor de \'{o}leo e g\'{a}s em resposta \`{a}s tend\^{e}ncias globais pela descarboniza\c{c}\~{a}o de opera\c{c}\~{o}es. Neste cen\'{a}rio, surge a necessidade de se identificar potenciais clusters e hubs de CCUS no pa\'{i}s. Clusters e hubs industriais de CCUS s\~{a}o arranjos geogr\'{a}ficos compostos de fontes emissoras concentradas, um arcabou\c{c}o log\'{i}stico para coleta e transporte do CO2 e cont\^{e}ineres subterr\^{a}neos com alta capacidade de armazenamento do g\'{a}s. O objetivo deste trabalho \'{e} identificar clusters e hubs de CCUS a partir de diversas m\'{e}tricas de oportunidade e da hip\'{o}tese de reaproveitamento da infraestrutura nacional de po\c{c}os de petr\'{o}leo como sumidouros de CO2. Atrav\'{e}s da pr\'{e}-sele\c{c}\~{a}o de quatro bacias de alta prospectividade, analisamos a densidade de emiss\~{o}es por territ\'{o}rio, viabilidade de transporte e oportunidade operacional temporal da infraestrutura legada de po\c{c}os, definindo potenciais arranjos organiz\'{a}veis com base em regi\~{o}es geogr\'{a}ficas intermedi\'{a}rias. Os procedimentos metodol\'{o}gicos contemplaram: modelos matem\'{a}ticos para clusters e hubs, triagem de munic\'{i}pios por densidade de emiss\~{o}es de CO2; clusteriza\c{c}\~{a}o e an\'{a}lise de dados geoespaciais. Apresentamos uma vis\~{a}o inicial sobre a integra\c{c}\~{a}o da infraestrutura legada para armazenamento de CO2 em bacias de alta prospectividade em SP , RJ, BA e RN. De acordo com a metodologia e hip\'{o}teses empregadas, foram identificados 57 clusters locais de captura e 13 clusters locais de armazenamento, ambos com seus respectivos hubs, distribu\'{i}dos pelas 29 regi\~{o}es intermedi\'{a}rias que dividem os quatro estados analisados. Esperamos que este trabalho preliminar contribua para o desenvolvimento de projetos escal\'{a}veis de armazenamento geol\'{o}gico de carbono no pa\'{i}s, para a avalia\c{c}\~{a}o da atratividade da infraestrutura legada de po\c{c}os e para incentivar novos nichos de atividade econ\^{o}mica para players do setor de \'{o}leo e g\'{a}s.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Injeção e armazenamento permanente de CO2 são operações da cadeia de CCUS que visam neutralizar emissões em setores de difícil abatimento, tais como energia e indústria. Nos últimos anos, um novo horizonte de oportunidades começou a se abrir no Brasil para o setor de óleo e gás em resposta às tendências globais pela descarbonização de operações. Neste cenário, surge a necessidade de se identificar potenciais clusters e hubs de CCUS no país. Clusters e hubs industriais de CCUS são arranjos geográficos compostos de fontes emissoras concentradas, um arcabouço logístico para coleta e transporte do CO2 e contêineres subterrâneos com alta capacidade de armazenamento do gás. O objetivo deste trabalho é identificar clusters e hubs de CCUS a partir de diversas métricas de oportunidade e da hipótese de reaproveitamento da infraestrutura nacional de poços de petróleo como sumidouros de CO2. Através da pré-seleção de quatro bacias de alta prospectividade, analisamos a densidade de emissões por território, viabilidade de transporte e oportunidade operacional temporal da infraestrutura legada de poços, definindo potenciais arranjos organizáveis com base em regiões geográficas intermediárias. Os procedimentos metodológicos contemplaram: modelos matemáticos para clusters e hubs, triagem de municípios por densidade de emissões de CO2; clusterização e análise de dados geoespaciais. Apresentamos uma visão inicial sobre a integração da infraestrutura legada para armazenamento de CO2 em bacias de alta prospectividade em SP , RJ, BA e RN. De acordo com a metodologia e hipóteses empregadas, foram identificados 57 clusters locais de captura e 13 clusters locais de armazenamento, ambos com seus respectivos hubs, distribuídos pelas 29 regiões intermediárias que dividem os quatro estados analisados. Esperamos que este trabalho preliminar contribua para o desenvolvimento de projetos escaláveis de armazenamento geológico de carbono no país, para a avaliação da atratividade da infraestrutura legada de poços e para incentivar novos nichos de atividade econômica para players do setor de óleo e gás.
Santos, M. D.; Magalhães, R. M.; Oliveira, G. C. P.; Machado, T. J.
Deep Learning/Proxy Modeling Approaches for Reservoir Simulation and Production Forecasting Apresentação
Rio Oil and Gas e. 2024, 24.09.2024.
@misc{santos2024ROG,
title = {Deep Learning/Proxy Modeling Approaches for Reservoir Simulation and Production Forecasting},
author = {M. D. Santos and R. M. Magalh\~{a}es and G. C. P. Oliveira and T. J. Machado},
editor = {Rio Oil and Gas e. 2024},
year = {2024},
date = {2024-09-24},
abstract = {A significant challenge in oil and gas Industry, especially in reservoir engineering and its management context, is related to the capacity of run optimization strategies. It occurs because the current computational time costs are prohibitive and demand too many resources, even for a medium-size simulation. Perhaps the currently scientific solutions, none of them used deep Learning techniques in low-level granularity for predictions, especially the grid-cell level size approach. This presentation proposes, analyzes, and states a feature selection, a model design, and a training strategy with the application of Deep Learning techniques (DNN and CNN), the Design of Experiment, and all statistical evaluation-based metrics and its graphic tools. This defined process intends to work as a solution to create a proxy model for reservoir numerical software simulation.},
howpublished = {Rio Oil and Gas e. 2024},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
A significant challenge in oil and gas Industry, especially in reservoir engineering and its management context, is related to the capacity of run optimization strategies. It occurs because the current computational time costs are prohibitive and demand too many resources, even for a medium-size simulation. Perhaps the currently scientific solutions, none of them used deep Learning techniques in low-level granularity for predictions, especially the grid-cell level size approach. This presentation proposes, analyzes, and states a feature selection, a model design, and a training strategy with the application of Deep Learning techniques (DNN and CNN), the Design of Experiment, and all statistical evaluation-based metrics and its graphic tools. This defined process intends to work as a solution to create a proxy model for reservoir numerical software simulation.
Fernandes, C. P. B.
2024.
@phdthesis{nokey,
title = {Uma Aplica\c{c}\~{a}o de Programa\c{c}\~{a}o Inteira Mista para o Planejamento \'{O}timo em Opera\c{c}\~{o}es de Perfura\c{c}\~{a}o Direcional},
author = {C. P. B. Fernandes},
year = {2024},
date = {2024-08-31},
abstract = {A crescente demanda por m\'{e}todos eficientes e precisos na explota\c{c}\~{a}o de hidrocarbonetos impulsionou o desenvolvimento de t\'{e}cnicas avan\c{c}adas de perfura\c{c}\~{a}o direcional. Este trabalho aborda essa necessidade ao apresentar uma aplica\c{c}\~{a}o inovadora de Programa\c{c}\~{a}o Linear Inteira Mista (PLIM) para o planejamento \'{o}timo de opera\c{c}\~{o}es de perfura\c{c}\~{a}o direcional. A perfura\c{c}\~{a}o
direcional \'{e} uma t\'{e}cnica fundamental para acessar reservas de petr\'{o}leo que seriam inacess\'{i}veis por m\'{e}todos convencionais, mas seu planejamento requer uma abordagem cuidadosa para maximizar a recupera\c{c}\~{a}o de \'{o}leo e minimizar os custos operacionais. O estudo foca na explota\c{c}\~{a}o de Unidades de Fluxo Hidr\'{a}ulico (HFUs), as quais s\~{a}o regi\~{o}es que compartilham propriedades petrof\'{i}sicas semelhantes e desempenham papel crucial como alvos das trajet\'{o}rias de perfura\c{c}\~{a}o. A metodologia proposta baseia-se no Problema do Caixeiro Viajante (PCV) e no Problema
de Orienta\c{c}\~{a}o de Equipe (POE), duas abordagens cl\'{a}ssicas na teoria da otimiza\c{c}\~{a}o que foram adaptadas para identificar as melhores coordenadas de refer\^{e}ncia para a trajet\'{o}ria de perfura\c{c}\~{a}o. Os resultados mostram que a aplica\c{c}\~{a}o da metodologia proposta aumenta consideravelmente o fator de recupera\c{c}\~{a}o de \'{o}leo, demonstrando sua efic\'{a}cia na otimiza\c{c}\~{a}o das opera\c{c}\~{o}es de perfura\c{c}\~{a}o. Esta pesquisa contribui significativamente para a Engenharia de po\c{c}o, fornecendo uma ferramenta robusta para o planejamento estrat\'{e}gico de po\c{c}os direcionais, e abre caminho para
futuros estudos e aplica\c{c}\~{o}es em contextos ainda mais complexos.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
A crescente demanda por métodos eficientes e precisos na explotação de hidrocarbonetos impulsionou o desenvolvimento de técnicas avançadas de perfuração direcional. Este trabalho aborda essa necessidade ao apresentar uma aplicação inovadora de Programação Linear Inteira Mista (PLIM) para o planejamento ótimo de operações de perfuração direcional. A perfuração
direcional é uma técnica fundamental para acessar reservas de petróleo que seriam inacessíveis por métodos convencionais, mas seu planejamento requer uma abordagem cuidadosa para maximizar a recuperação de óleo e minimizar os custos operacionais. O estudo foca na explotação de Unidades de Fluxo Hidráulico (HFUs), as quais são regiões que compartilham propriedades petrofísicas semelhantes e desempenham papel crucial como alvos das trajetórias de perfuração. A metodologia proposta baseia-se no Problema do Caixeiro Viajante (PCV) e no Problema
de Orientação de Equipe (POE), duas abordagens clássicas na teoria da otimização que foram adaptadas para identificar as melhores coordenadas de referência para a trajetória de perfuração. Os resultados mostram que a aplicação da metodologia proposta aumenta consideravelmente o fator de recuperação de óleo, demonstrando sua eficácia na otimização das operações de perfuração. Esta pesquisa contribui significativamente para a Engenharia de poço, fornecendo uma ferramenta robusta para o planejamento estratégico de poços direcionais, e abre caminho para
futuros estudos e aplicações em contextos ainda mais complexos.
direcional é uma técnica fundamental para acessar reservas de petróleo que seriam inacessíveis por métodos convencionais, mas seu planejamento requer uma abordagem cuidadosa para maximizar a recuperação de óleo e minimizar os custos operacionais. O estudo foca na explotação de Unidades de Fluxo Hidráulico (HFUs), as quais são regiões que compartilham propriedades petrofísicas semelhantes e desempenham papel crucial como alvos das trajetórias de perfuração. A metodologia proposta baseia-se no Problema do Caixeiro Viajante (PCV) e no Problema
de Orientação de Equipe (POE), duas abordagens clássicas na teoria da otimização que foram adaptadas para identificar as melhores coordenadas de referência para a trajetória de perfuração. Os resultados mostram que a aplicação da metodologia proposta aumenta consideravelmente o fator de recuperação de óleo, demonstrando sua eficácia na otimização das operações de perfuração. Esta pesquisa contribui significativamente para a Engenharia de poço, fornecendo uma ferramenta robusta para o planejamento estratégico de poços direcionais, e abre caminho para
futuros estudos e aplicações em contextos ainda mais complexos.
da Silva, José Wilker Lima
Generalized functionals for qualification of geological carbon storage injection sites Tese PhD
2024.
@phdthesis{wilker2024phd,
title = {Generalized functionals for qualification of geological carbon storage injection sites},
author = {Jos\'{e} Wilker Lima da Silva},
editor = {Federal University of Para\'{i}ba},
year = {2024},
date = {2024-07-10},
abstract = {Many nations have pledged to achieve carbon neutrality by 2050 through the implementation of geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework, thus spearheading the Net Zero initiative. The CCUS goal is to capture carbon dioxide (CO2) emissions, recycling them or transporting them through pipelines to underground geological formations for permanent storage. Despite global success in GCS projects, driven by the oil and gas sector, large-scale GCS initiatives are still in their early stages in Brazil. Databases for potential storage sites, including saline aquifers and depleted reservoirs, are in development, as with the regulatory structure. This thesis introduces mathematical models for the systematic selection and ranking of underground CO2 storage sites. The research explores a family of mathematical functionals, each with distinct weighting functions, achieving two main objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions, considering structural traps in caprocks. This methodology is a valuable resource for identifying suitable injection and storage locations. The models were implemented using the Matlab Reservoir Simulation Toolbox (MRST), and a case study using the UNISIM-I-D model for the Namorado Field in the Campos Basin, Brazil, indicates the influence of permeability and porosity as well as sigmoid, exponential or hybrid curves on different interpretations of ideal storage locations, with surpluses that range up to 66% in the best case. The vertical equilibrium model was used to reduce computational cost and Sobol sensitivity analysis to study the individual influence of each parameter. Simulation results corroborate the theoretical analyses. The ultimate objective of the study is to establish a fundamental knowledge base for future GCS projects in Brazil, leveraging legacy well infrastructures.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Many nations have pledged to achieve carbon neutrality by 2050 through the implementation of geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework, thus spearheading the Net Zero initiative. The CCUS goal is to capture carbon dioxide (CO2) emissions, recycling them or transporting them through pipelines to underground geological formations for permanent storage. Despite global success in GCS projects, driven by the oil and gas sector, large-scale GCS initiatives are still in their early stages in Brazil. Databases for potential storage sites, including saline aquifers and depleted reservoirs, are in development, as with the regulatory structure. This thesis introduces mathematical models for the systematic selection and ranking of underground CO2 storage sites. The research explores a family of mathematical functionals, each with distinct weighting functions, achieving two main objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions, considering structural traps in caprocks. This methodology is a valuable resource for identifying suitable injection and storage locations. The models were implemented using the Matlab Reservoir Simulation Toolbox (MRST), and a case study using the UNISIM-I-D model for the Namorado Field in the Campos Basin, Brazil, indicates the influence of permeability and porosity as well as sigmoid, exponential or hybrid curves on different interpretations of ideal storage locations, with surpluses that range up to 66% in the best case. The vertical equilibrium model was used to reduce computational cost and Sobol sensitivity analysis to study the individual influence of each parameter. Simulation results corroborate the theoretical analyses. The ultimate objective of the study is to establish a fundamental knowledge base for future GCS projects in Brazil, leveraging legacy well infrastructures.
Silva, J. W. L.; Santos, M. D.; Oliveira, G. P.
Generalized functionals for qualification of geological carbon storage injection sites Journal Article
Em: International Journal of Greenhouse Gas Control, vol. 135, iss. June 2024, 2024, ISSN: 1750-5836.
@article{Silva2024b,
title = {Generalized functionals for qualification of geological carbon storage injection sites},
author = {J.W.L. Silva and M.D. Santos and G.P. Oliveira},
doi = {10.1016/j.ijggc.2024.104167},
issn = {1750-5836},
year = {2024},
date = {2024-06-00},
urldate = {2024-06-00},
journal = {International Journal of Greenhouse Gas Control},
volume = {135},
issue = {June 2024},
publisher = {Elsevier BV},
abstract = {Many nations have pledged to reach carbon neutrality by 2050. Embarking on the decarbonization journey, they posited geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework. The CCUS chain operates to reduce “hard-to-abate” emissions at key sectors by capturing carbon dioxide (CO2), reusing it, transporting it, or disposing of it via injection into underground geological formations for permanent storage. Despite the global success of GCS ventures, mainly driven by the oil and gas industry, GCS initiatives are still in their early stages in several developing countries. In Brazil, for instance, a full setup covering precise storage capacity databases, potential CCUS clusters, national regulatory structure, and auxiliary computer-aided engineering is underway. Intended to push the frontier in the latter subject, this paper introduces mathematical models for qualifying underground CO2 storage sites. Our research explores a family of multivariate functionals endowed with underlying reservoir features and distinct weighting functions, thus envisioning two primary objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions considering structural traps/caprocks settings. Backed by the Matlab Reservoir Simulation Toolbox (MRST) capabilities, the methodology is a subsidiary resource for identifying suitable injection and storage sites. A case study using the UNISIM-I-D model generated dozens of volumetric quality maps that point to unique potential storage sites. Numerical simulation experiments of injection comparing legacy and novel wells reveal storage surpluses improved by up to 50%. The paper seeks to establish foundational knowledge in GCS efficiency for general underground settings. One expects that these outcomes leverage well-repurposing perspectives and stimulate field appraisal actions to scale up GCS projects both in Brazil and worldwide.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Many nations have pledged to reach carbon neutrality by 2050. Embarking on the decarbonization journey, they posited geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework. The CCUS chain operates to reduce “hard-to-abate” emissions at key sectors by capturing carbon dioxide (CO2), reusing it, transporting it, or disposing of it via injection into underground geological formations for permanent storage. Despite the global success of GCS ventures, mainly driven by the oil and gas industry, GCS initiatives are still in their early stages in several developing countries. In Brazil, for instance, a full setup covering precise storage capacity databases, potential CCUS clusters, national regulatory structure, and auxiliary computer-aided engineering is underway. Intended to push the frontier in the latter subject, this paper introduces mathematical models for qualifying underground CO2 storage sites. Our research explores a family of multivariate functionals endowed with underlying reservoir features and distinct weighting functions, thus envisioning two primary objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions considering structural traps/caprocks settings. Backed by the Matlab Reservoir Simulation Toolbox (MRST) capabilities, the methodology is a subsidiary resource for identifying suitable injection and storage sites. A case study using the UNISIM-I-D model generated dozens of volumetric quality maps that point to unique potential storage sites. Numerical simulation experiments of injection comparing legacy and novel wells reveal storage surpluses improved by up to 50%. The paper seeks to establish foundational knowledge in GCS efficiency for general underground settings. One expects that these outcomes leverage well-repurposing perspectives and stimulate field appraisal actions to scale up GCS projects both in Brazil and worldwide.
Tigre, Y. S.; Silva, J. W. L.; Oliveira, G. P.
Classification of Injection Units by Unsupervised Binning Methods for Geological Carbon Storage Workshop
2024.
@workshop{nokey,
title = {Classification of Injection Units by Unsupervised Binning Methods for Geological Carbon Storage},
author = {Y. S. Tigre and J. W. L. Silva and G. P. Oliveira},
year = {2024},
date = {2024-03-26},
abstract = {The oil and gas (O\&G) industry is increasingly committed to balancing the demands of its production chain with climate and environmental issues. Geological Carbon Storage (GCS) technologies will bridge energy transition and CO2 emission reductions worldwide for the next decades [1]. Brazil is under a growing interest in developing adapted workflows for GCS site selection and ranking [2]. In this study, we aim to compare statistical binning methods in determining bin edges for reservoir sites termed "injectivity unit classes" (IUCs) [3]. Through the IUCs, we look for well placement strategies that must balance petrophysical explainability and computational efficiency for numerical simulations of injection. Tests based on direct (sturges, Scott, Friedman-Diaconis, square-root) and indirect (KDE, Bayesian blocks) techniques [4-5] were perfomed over reservoir models similar to Brazilian oilfields. As a result, ideal bandwidths in uniform and non-uniform distributions allowed us to exhibit discrete storage sites and reveal valuable information about rock properties, CO2 injection conditions, and the quality of specific locations. This research expects to develop data-driven tools turned to GCS workflows especially suitable for Brazil.},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
The oil and gas (O&G) industry is increasingly committed to balancing the demands of its production chain with climate and environmental issues. Geological Carbon Storage (GCS) technologies will bridge energy transition and CO2 emission reductions worldwide for the next decades [1]. Brazil is under a growing interest in developing adapted workflows for GCS site selection and ranking [2]. In this study, we aim to compare statistical binning methods in determining bin edges for reservoir sites termed "injectivity unit classes" (IUCs) [3]. Through the IUCs, we look for well placement strategies that must balance petrophysical explainability and computational efficiency for numerical simulations of injection. Tests based on direct (sturges, Scott, Friedman-Diaconis, square-root) and indirect (KDE, Bayesian blocks) techniques [4-5] were perfomed over reservoir models similar to Brazilian oilfields. As a result, ideal bandwidths in uniform and non-uniform distributions allowed us to exhibit discrete storage sites and reveal valuable information about rock properties, CO2 injection conditions, and the quality of specific locations. This research expects to develop data-driven tools turned to GCS workflows especially suitable for Brazil.
Silva, J. W. L.; Santos, M. D.; Oliveira, G. C. P.
Generalized Qualifying Functionals for Geologic Carbon Storage Injection Sites Workshop
2024.
@workshop{silva2024,
title = {Generalized Qualifying Functionals for Geologic Carbon Storage Injection Sites},
author = {J. W. L. Silva and M. D. Santos and G. C. P. Oliveira},
year = {2024},
date = {2024-03-26},
abstract = {Geologic carbon storage (GCS) is a pivotal technology within the broader framework of carbon capture, utilization, and storage (CCUS), which now takes the lead in the energy transition race [1]. The overarching objective of the CCUS initiative is to capture carbon dioxide (CO2) emissions, either recycling them for further use or transporting them via an extensive pipeline network to suitable underground geological formations for permanent storage [2]. Despite the global success of several GCS projects, often driven by the oil and gas sector, full-scale GCS initiatives are relatively nascent in Brazil [3]. Databases of potential storage sites, including saline aquifers and depleted reservoirs, are still under development. This paper aims to introduce mathematical models for the systematic selection and ranking of underground (CO2) storage sites. Our research explores a family of mathematical functionals, each equipped with distinct weighting functions, serving two primary objectives. Firstly, it elucidates the non- linear interactions between rock and fluid properties through quality indicators. Secondly, it assesses geographical regions, considering various structural traps inherent to caprocks. This methodology serves as a valuable resource for identifying suitable injection and storage locations. The models were computationally implemented using the Matlab Reservoir Simulation Toolbox (MRST) software [4], and a case study was conducted using the UNISIM-I-D model, which represents the Namorado Field in the Campos Basin, Brazil [5]. Our findings reveal that the use of certain curves can lead to distinct interpretations of ideal storage sites.},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
Geologic carbon storage (GCS) is a pivotal technology within the broader framework of carbon capture, utilization, and storage (CCUS), which now takes the lead in the energy transition race [1]. The overarching objective of the CCUS initiative is to capture carbon dioxide (CO2) emissions, either recycling them for further use or transporting them via an extensive pipeline network to suitable underground geological formations for permanent storage [2]. Despite the global success of several GCS projects, often driven by the oil and gas sector, full-scale GCS initiatives are relatively nascent in Brazil [3]. Databases of potential storage sites, including saline aquifers and depleted reservoirs, are still under development. This paper aims to introduce mathematical models for the systematic selection and ranking of underground (CO2) storage sites. Our research explores a family of mathematical functionals, each equipped with distinct weighting functions, serving two primary objectives. Firstly, it elucidates the non- linear interactions between rock and fluid properties through quality indicators. Secondly, it assesses geographical regions, considering various structural traps inherent to caprocks. This methodology serves as a valuable resource for identifying suitable injection and storage locations. The models were computationally implemented using the Matlab Reservoir Simulation Toolbox (MRST) software [4], and a case study was conducted using the UNISIM-I-D model, which represents the Namorado Field in the Campos Basin, Brazil [5]. Our findings reveal that the use of certain curves can lead to distinct interpretations of ideal storage sites.
Coutinho, W. P.; Fernandes, C. P. B.; Machado, T. J.; Santos, M. D.; Oliveira, G. C. P.; Omoyemi, P. A.
Mixed-integer programming formulations for the optimisation of directional drilling operations Workshop
2024.
@workshop{coutinho2024,
title = {Mixed-integer programming formulations for the optimisation of directional drilling operations},
author = {W. P. Coutinho and C. P. B. Fernandes and T. J. Machado and M. D. Santos and G. C. P. Oliveira and P. A. Omoyemi
},
year = {2024},
date = {2024-03-26},
abstract = {Over the past decades, directional drilling has continuously advanced to increase hydrocarbon recovery by effectively targeting high-productivity reservoirs. However, existing models often neglect the incorporation of petrophysical attributes that can significantly impact the selection of production targets, such as the reservoir quality indicator. Moreover, many existing approaches primarily focus on heuristic optimisation algorithms. This study introduces a novel application of mixed-integer programming (MIP) for optimizing directional and multi-directional drilling paths for petroleum exploration. By integrating practical considerations such as drift angle constraints, maximum wellbore length and minimum safety distances. We propose MIP formulations for the optimisation of a single path and for the design of multiple paths simultaneously. In addition, a branch-and-cut algorithm is proposed for solving real-world multi-directional instances of challenging sizes. Key to this methodology is the use of maximum closeness centrality within hydraulic flow units to identify optimal reservoir targets. The approach is validated through a case study of the Campos Basin in Brazil, demonstrating that the optimized drilling paths could surpass the basin\'s historical average recovery factor. The results indicate a potential to significantly enhance hydrocarbon recovery, suggesting a promising avenue for future advancements in directional drilling and offshore oil and gas production optimisation.},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
Over the past decades, directional drilling has continuously advanced to increase hydrocarbon recovery by effectively targeting high-productivity reservoirs. However, existing models often neglect the incorporation of petrophysical attributes that can significantly impact the selection of production targets, such as the reservoir quality indicator. Moreover, many existing approaches primarily focus on heuristic optimisation algorithms. This study introduces a novel application of mixed-integer programming (MIP) for optimizing directional and multi-directional drilling paths for petroleum exploration. By integrating practical considerations such as drift angle constraints, maximum wellbore length and minimum safety distances. We propose MIP formulations for the optimisation of a single path and for the design of multiple paths simultaneously. In addition, a branch-and-cut algorithm is proposed for solving real-world multi-directional instances of challenging sizes. Key to this methodology is the use of maximum closeness centrality within hydraulic flow units to identify optimal reservoir targets. The approach is validated through a case study of the Campos Basin in Brazil, demonstrating that the optimized drilling paths could surpass the basin's historical average recovery factor. The results indicate a potential to significantly enhance hydrocarbon recovery, suggesting a promising avenue for future advancements in directional drilling and offshore oil and gas production optimisation.
Almeida, B. R.; Amorim, D. N.; Trajano, A. F.; Oliveira, G. P.
2024.
@workshop{almeida2024,
title = {Geospatial Data Analysis and Onshore Well Infrastructure Opportunity Quantification for CCS Clusters in Brazil},
author = {B. R. Almeida and D. N. Amorim and A. F. Trajano and G. P. Oliveira},
editor = {LITPEG/UFPE},
year = {2024},
date = {2024-03-26},
urldate = {2024-03-26},
abstract = {Carbon capture and storage (CCS) has been recognized as a frontline strategy for decarbonizing the energy and industrial sectors, especially the oil and gas operations [1]. Recent studies indicated that Brazilian sedimentary basins have a remarkable potential for CO2 storage capacity [2]. This competitive advantage can be pivotal to back strategies that curb emissions of hard-to-abate processes. In this study, we have applied geospatial data analysis techniques to identify possible onshore storage spots operating as sinks for CCS hubs and clusters in Brazil. CCS clusters are constructs formed on three pillars: high concentration of emissions, readiness for sharing of infrastructure, and capacity of transport/storage. Hubs are connection elements of the clusters destined to collect and dispose of the CO2 [3,4]. As a starting point, we developed a multivariate metric to quantify the opportunity infrastructure of onshore sites based on legacy wells designated by a status of abandonment. Our proposal combines major CO2 emitters around potential basins, whose selection based on their proximity to stationary CO2 sources and favorable geological conditions, factors that minimize costs associated with transport. This research expects to create geospatial screening maps for economically viable carbon projects.},
keywords = {},
pubstate = {published},
tppubtype = {workshop}
}
Carbon capture and storage (CCS) has been recognized as a frontline strategy for decarbonizing the energy and industrial sectors, especially the oil and gas operations [1]. Recent studies indicated that Brazilian sedimentary basins have a remarkable potential for CO2 storage capacity [2]. This competitive advantage can be pivotal to back strategies that curb emissions of hard-to-abate processes. In this study, we have applied geospatial data analysis techniques to identify possible onshore storage spots operating as sinks for CCS hubs and clusters in Brazil. CCS clusters are constructs formed on three pillars: high concentration of emissions, readiness for sharing of infrastructure, and capacity of transport/storage. Hubs are connection elements of the clusters destined to collect and dispose of the CO2 [3,4]. As a starting point, we developed a multivariate metric to quantify the opportunity infrastructure of onshore sites based on legacy wells designated by a status of abandonment. Our proposal combines major CO2 emitters around potential basins, whose selection based on their proximity to stationary CO2 sources and favorable geological conditions, factors that minimize costs associated with transport. This research expects to create geospatial screening maps for economically viable carbon projects.
Santos, Daniel B. V.; Oliveira, Gustavo P.; Mangiavacchi, Norberto; Valluri, Prashant; Anjos, Gustavo R.
Numerical Investigation of Gas Bubble Interaction in a Circular Cross-Section Channel in Shear Flow Journal Article
Em: Fluids, vol. 9, iss. 2, 2024, ISBN: 2311-5521.
@article{barbedo2024,
title = {Numerical Investigation of Gas Bubble Interaction in a Circular Cross-Section Channel in Shear Flow},
author = {Daniel B. V. Santos and Gustavo P. Oliveira and Norberto Mangiavacchi and Prashant Valluri and Gustavo R. Anjos},
editor = {MDPI Publishing},
doi = {https://doi.org/10.3390/fluids9020032 },
isbn = {2311-5521},
year = {2024},
date = {2024-01-24},
urldate = {2024-01-24},
journal = {Fluids},
volume = {9},
issue = {2},
abstract = {This work’s goal is to numerically investigate the interactions between two gas bubbles in a fluid flow in a circular cross-section channel, both in the presence and in the absence of gravitational forces, with several Reynolds and Weber numbers. The first bubble is placed at the center of the channel, while the second is near the wall. Their positions are set in such a way that a dynamic interaction is expected to occur due to their velocity differences. A finite element numerical tool is utilized to solve the incompressible Navier\textendashStokes equations and simulate two-phase flow using an unfitted mesh to represent the fluid interface, akin to the front-tracking method. The results show that the velocity gradient influences bubble shapes near the wall. Moreover, lower viscosity and surface tension force account for more significant interactions, both in the bubble shape and in the trajectory. In this scenario, it can be observed that one bubble is trapped in the other’s wake, with the proximity possibly allowing the onset of coalescence. The results obtained contribute to a deeper understanding of two-phase inner flows.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This work’s goal is to numerically investigate the interactions between two gas bubbles in a fluid flow in a circular cross-section channel, both in the presence and in the absence of gravitational forces, with several Reynolds and Weber numbers. The first bubble is placed at the center of the channel, while the second is near the wall. Their positions are set in such a way that a dynamic interaction is expected to occur due to their velocity differences. A finite element numerical tool is utilized to solve the incompressible Navier–Stokes equations and simulate two-phase flow using an unfitted mesh to represent the fluid interface, akin to the front-tracking method. The results show that the velocity gradient influences bubble shapes near the wall. Moreover, lower viscosity and surface tension force account for more significant interactions, both in the bubble shape and in the trajectory. In this scenario, it can be observed that one bubble is trapped in the other’s wake, with the proximity possibly allowing the onset of coalescence. The results obtained contribute to a deeper understanding of two-phase inner flows.
2023
Almeida, B. R.; Amorim, D. N.; Trajano, A. F.; Melo, S. A.; Oliveira, G. P.
Índice de Oportunidade de Poços de Petróleo Públicos Brasileiros para Armazenamento de CO2 Working paper
PPGEM/UFPB Seminar 2023, 2023.
@workingpaper{almeida2023,
title = {\'{I}ndice de Oportunidade de Po\c{c}os de Petr\'{o}leo P\'{u}blicos Brasileiros para Armazenamento de CO2},
author = {B. R. Almeida and D. N. Amorim and A. F. Trajano and S. A. Melo and G. P. Oliveira},
year = {2023},
date = {2023-12-14},
urldate = {2023-12-14},
abstract = {A pesquisa destaca a import\^{a}ncia do armazenamento permanente de CO2 em po\c{c}os de petr\'{o}leo brasileiros como estrat\'{e}gia crucial para mitigar as emiss\~{o}es de gases de efeito estufa e avan\c{c}ar rumo a uma economia de baixo carbono. O estudo prop\~{o}e um \'{i}ndice de oportunidade para essa pr\'{a}tica, considerando a complexidade geol\'{o}gica das bacias brasileiras. Ao abordar a urg\^{e}ncia de medidas sustent\'{a}veis diante das mudan\c{c}as clim\'{a}ticas, a pesquisa destaca a ado\c{c}\~{a}o global da captura e armazenamento de carbono (CCS). Explorando o ciclo de vida de po\c{c}os de petr\'{o}leo e a fase de abandono, o estudo ressalta estrat\'{e}gias de desenvolvimento baseadas em registros de po\c{c}os p\'{u}blicos dispon\'{i}veis pelo Banco de Dados de Explora\c{c}\~{a}o e Produ\c{c}\~{a}o (BDEP/ANP). A metodologia utiliza ferramentas Python, GeoPandas e Matplotlib para an\'{a}lise geoespacial de oportunidades futuras tendo por refer\^{e}ncia os anos de 2030 e 2040. Enfatizamos o papel da ind\'{u}stria petrol\'{i}fera na trajet\'{o}ria da descarboniza\c{c}\~{a}o e no aux\'{i}lio \`{a} mitiga\c{c}\~{a}o das emiss\~{o}es de CO2 no pa\'{i}s, bem como destacamos a import\^{a}ncia de estrat\'{e}gias operacionais pr\'{o}-sustentabilidade.},
howpublished = {PPGEM/UFPB Seminar 2023},
keywords = {},
pubstate = {published},
tppubtype = {workingpaper}
}
A pesquisa destaca a importância do armazenamento permanente de CO2 em poços de petróleo brasileiros como estratégia crucial para mitigar as emissões de gases de efeito estufa e avançar rumo a uma economia de baixo carbono. O estudo propõe um índice de oportunidade para essa prática, considerando a complexidade geológica das bacias brasileiras. Ao abordar a urgência de medidas sustentáveis diante das mudanças climáticas, a pesquisa destaca a adoção global da captura e armazenamento de carbono (CCS). Explorando o ciclo de vida de poços de petróleo e a fase de abandono, o estudo ressalta estratégias de desenvolvimento baseadas em registros de poços públicos disponíveis pelo Banco de Dados de Exploração e Produção (BDEP/ANP). A metodologia utiliza ferramentas Python, GeoPandas e Matplotlib para análise geoespacial de oportunidades futuras tendo por referência os anos de 2030 e 2040. Enfatizamos o papel da indústria petrolífera na trajetória da descarbonização e no auxílio à mitigação das emissões de CO2 no país, bem como destacamos a importância de estratégias operacionais pró-sustentabilidade.
Marcussi, B. A.; Martins, A. C.; Lucena, R. M.; Mangiavacchi, N.
Convective Patterns in Hele-Shaw Flows Driven by Density Gradients and Chemical Composition Changes Proceedings Article
Em: Annals of the 27th International Congress of Mechanical Engineering, Brazilian Society of Mechanical Sciences and Engineering, Florianópolis, Brazil, 2023.
@inproceedings{marcussi2023cobem,
title = {Convective Patterns in Hele-Shaw Flows Driven by Density Gradients and Chemical Composition Changes},
author = {B. A. Marcussi and A. C. Martins and R. M. Lucena and N. Mangiavacchi},
year = {2023},
date = {2023-12-08},
booktitle = {Annals of the 27th International Congress of Mechanical Engineering},
publisher = {Brazilian Society of Mechanical Sciences and Engineering},
address = {Florian\'{o}polis, Brazil},
abstract = {The phenomenon of fluid displacement in porous media is of great practical interest for a variety of geophysical and environmental applications, such as Carbon Capture and Storage (CCS), oil recovery, water contamination, and granular flows, however studying this phenomenon in situ is extremely challenging. During displacement, convective flow patterns known as fingering have been observed and studied using the Hele-Shaw cell, an experimental device which replicates the porous media flow conditions found in nature, and may be used as a benchmarking tool for theoretical models and numerical simulations of fluid flow patterns against experimental data. The fluid flow behaviour in porous media can be explained by applying Darcy’s law, provided that the solute hydrodynamic dispersion effect in the cell is taken into account. Therefore, this study involved the assembly of a Hele-Shaw cell to investigate the formation of flow patterns with fingering instability in density-driven flows in porous media generated by changes in chemical composition of the fluid medium. The cell consisted of two rectangular plates separated by seals and enclosing impermeable boundaries and an adjustable uniform gap with the upper boundary left open, where concentration gradients were generated and resulted in density gradients. Following an initial diffusive phase, the layer of heavy mixture thickened and developed instability, leading to the formation of finger-like structures and the flow evolution was recorded using a camera while the Hele-Shaw cell was illuminated from the backside with an array of LED lamps. The problem was characterised by three dimensionless parameters which determined the flow regime between the plates. The average finger tip flow velocity during the experiments was calculated and estimates derived from the Hele-Shaw equation were obtained. Furthermore, the concentration field and its derivative with respect to the width dimension of the cell were determined and yielded fluid vorticity. Thus, the stream function was determined by solving a Poisson equation and, finally, the velocity components in both the vertical and horizontal directions were computed and the derivative of concentration with respect to time was obtained. The average value of the integral concentration boundary layer thickness was also calculated. Thus, this study utilised a Hele-Shaw cell to replicate the two-dimensional fluid flow behaviour in porous media, providing valuable insights into the dynamic structures of gravity-driven porous media flows.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The phenomenon of fluid displacement in porous media is of great practical interest for a variety of geophysical and environmental applications, such as Carbon Capture and Storage (CCS), oil recovery, water contamination, and granular flows, however studying this phenomenon in situ is extremely challenging. During displacement, convective flow patterns known as fingering have been observed and studied using the Hele-Shaw cell, an experimental device which replicates the porous media flow conditions found in nature, and may be used as a benchmarking tool for theoretical models and numerical simulations of fluid flow patterns against experimental data. The fluid flow behaviour in porous media can be explained by applying Darcy’s law, provided that the solute hydrodynamic dispersion effect in the cell is taken into account. Therefore, this study involved the assembly of a Hele-Shaw cell to investigate the formation of flow patterns with fingering instability in density-driven flows in porous media generated by changes in chemical composition of the fluid medium. The cell consisted of two rectangular plates separated by seals and enclosing impermeable boundaries and an adjustable uniform gap with the upper boundary left open, where concentration gradients were generated and resulted in density gradients. Following an initial diffusive phase, the layer of heavy mixture thickened and developed instability, leading to the formation of finger-like structures and the flow evolution was recorded using a camera while the Hele-Shaw cell was illuminated from the backside with an array of LED lamps. The problem was characterised by three dimensionless parameters which determined the flow regime between the plates. The average finger tip flow velocity during the experiments was calculated and estimates derived from the Hele-Shaw equation were obtained. Furthermore, the concentration field and its derivative with respect to the width dimension of the cell were determined and yielded fluid vorticity. Thus, the stream function was determined by solving a Poisson equation and, finally, the velocity components in both the vertical and horizontal directions were computed and the derivative of concentration with respect to time was obtained. The average value of the integral concentration boundary layer thickness was also calculated. Thus, this study utilised a Hele-Shaw cell to replicate the two-dimensional fluid flow behaviour in porous media, providing valuable insights into the dynamic structures of gravity-driven porous media flows.
Silva, J. W. L.; Santos, M. D.; Oliveira, G. P.
Distance-to-Trap Weighting Functions for Selection and Ranking of CO2 Storage Sites Proceedings Article
Em: Annals of the 27th International Congress of Mechanical Engineering, Brazilian Society of Mechanical Sciences and Engineering, Florianópolis, Brazil, 2023.
@inproceedings{silva2023cobem,
title = {Distance-to-Trap Weighting Functions for Selection and Ranking of CO2 Storage Sites},
author = {J. W. L. Silva and M. D. Santos and G.P. Oliveira},
year = {2023},
date = {2023-12-08},
booktitle = {Annals of the 27th International Congress of Mechanical Engineering},
publisher = {Brazilian Society of Mechanical Sciences and Engineering},
address = {Florian\'{o}polis, Brazil},
abstract = {Several countries are boldly committed to reaching a carbon neutrality scenario by 2050. Geologic carbon storage (GCS) is a bridging technology under the broader carbon capture, utilization, and storage (CCUS) scope that now spearheads the Net Zero race. The goal of the CCUS chain is to capture the carbon dioxide (CO2) dispersed into the atmosphere, recycle it for further usage, or transport it to suitable locations through a pipeline network, and finally inject it into deep geological formations for permanent storage. Regardless of numerous GCS projects that have succeeded around the globe mainly fostered by the oil and gas industry, the reality of full-scale GCS projects still is very young in Brazil. So far, there is only one CCUS operational project in the country, currently located in Santos Basin and totally devoted to enhanced oil recovery. The database of storage, injectivity, and containment mechanisms of CO2 in potential storage sites, like saline aquifers and depleted reservoirs, is also limited. This paper intends to present a few mathematical models for qualifying potential underground CO2 storage sites. We studied a group of functionals endowed with distinct weighting functions with two main objectives. First, to explain the nonlinear relationship of rock and fluid properties through rock quality estimates. Second, to grade field regions taking into account multiple structural traps featured by caprocks. The method works as a suggestive resource for convenient injection and storage loci. We implemented the models computationally through the Matlab Reservoir Simulation Toolbox (MRST) software and organized a case study over the UNISIM-I-D model, a representation of the Namorado Field (Campos Basin, Brazil). Preliminary results show that, decaying exponential, logistic or hybrid functions can lead to different storage sites, locations for injection wells, and storage surpluses. In contrast to the injection performance of in-field legacy wells, our approach reaches modest gains. The ultimate purpose of this study is to provide a knowledge base for future GCS projects in Brazil.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Several countries are boldly committed to reaching a carbon neutrality scenario by 2050. Geologic carbon storage (GCS) is a bridging technology under the broader carbon capture, utilization, and storage (CCUS) scope that now spearheads the Net Zero race. The goal of the CCUS chain is to capture the carbon dioxide (CO2) dispersed into the atmosphere, recycle it for further usage, or transport it to suitable locations through a pipeline network, and finally inject it into deep geological formations for permanent storage. Regardless of numerous GCS projects that have succeeded around the globe mainly fostered by the oil and gas industry, the reality of full-scale GCS projects still is very young in Brazil. So far, there is only one CCUS operational project in the country, currently located in Santos Basin and totally devoted to enhanced oil recovery. The database of storage, injectivity, and containment mechanisms of CO2 in potential storage sites, like saline aquifers and depleted reservoirs, is also limited. This paper intends to present a few mathematical models for qualifying potential underground CO2 storage sites. We studied a group of functionals endowed with distinct weighting functions with two main objectives. First, to explain the nonlinear relationship of rock and fluid properties through rock quality estimates. Second, to grade field regions taking into account multiple structural traps featured by caprocks. The method works as a suggestive resource for convenient injection and storage loci. We implemented the models computationally through the Matlab Reservoir Simulation Toolbox (MRST) software and organized a case study over the UNISIM-I-D model, a representation of the Namorado Field (Campos Basin, Brazil). Preliminary results show that, decaying exponential, logistic or hybrid functions can lead to different storage sites, locations for injection wells, and storage surpluses. In contrast to the injection performance of in-field legacy wells, our approach reaches modest gains. The ultimate purpose of this study is to provide a knowledge base for future GCS projects in Brazil.
Silva, J. W. L.; Oliveira, G. P.
Generalized Functionals for Qualification of Geologic Carbon Storage Sites Apresentação
26.09.2023.
@misc{jwlsilva2023mrstsymposium,
title = {Generalized Functionals for Qualification of Geologic Carbon Storage Sites},
author = {J.W.L. Silva and G.P. Oliveira},
editor = {SINTEF Digital},
year = {2023},
date = {2023-09-26},
urldate = {2023-09-26},
booktitle = {MRST Symposium 2023},
keywords = {},
pubstate = {published},
tppubtype = {presentation}
}
Tosta, Mateus; Oliveira, Gustavo P.; Wang, Bin; Chen, Zhiming; Liao, Qinzhuo
APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models Journal Article
Em: Advances in Geo-Energy Research, vol. 8, não 3, pp. 206-210, 2023.
@article{tosta2023,
title = {APyCE: A Python module for parsing and visualizing 3D reservoir digital twin models},
author = {Mateus Tosta and Gustavo P. Oliveira and Bin Wang and Zhiming Chen and Qinzhuo Liao},
doi = {10.46690/ager.2023.06.07},
year = {2023},
date = {2023-06-01},
urldate = {2023-06-01},
journal = {Advances in Geo-Energy Research},
volume = {8},
number = {3},
pages = {206-210},
abstract = {Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular open-source visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Engineers, geoscientists, and analysts can benefit from fast, easy, and real-time immersive 3D visualization to enhance their understanding and collaboration in a virtual 3D world. However, converting 3D reservoir data formats between different software programs and open-source standards can be challenging due to the complexity of programming and discrepancies in internal data structures. This paper introduces an open-source Python implementation focused on parsing industry reservoir data formats into a popular open-source visualization data format, Visual Toolkit files. Using object-oriented programming, a simple workflow was developed to export corner-point grids to Visual Toolkit-hexahedron structures. To demonstrate the utility of the software, standard raw input files of reservoir models are processed and visualized using Paraview. This tool aims to accelerate the digital transformation of the oil and gas industry in terms of 3D digital content generation and collaboration.
2022
Silva, J. W. L.; Tigre, Y. S.; Santos, M. D.; Mirzaei-Paiaman, A.; Oliveira, G. C. P.
Analysis of Injectivity Functionals Based on Static and Dynamic Parameters for CO2 Storage Projects Proceedings Article
Em: Anais do XXV Encontro Nacional de Modelagem Computacional (XXV ENMC), 2022, ISBN: 978-85-5722-474-2, (https://even3.blob.core.windows.net/anais/543218.pdf).
@inproceedings{jwlsilva2022,
title = {Analysis of Injectivity Functionals Based on Static and Dynamic Parameters for CO2 Storage Projects},
author = {J. W. L. Silva and Y. S. Tigre and M. D. Santos and A. Mirzaei-Paiaman and G. C. P. Oliveira},
url = {https://even3.blob.core.windows.net/anais/543218.pdf},
isbn = {978-85-5722-474-2},
year = {2022},
date = {2022-12-21},
urldate = {2022-12-21},
booktitle = {Anais do XXV Encontro Nacional de Modelagem Computacional (XXV ENMC)},
note = {https://even3.blob.core.windows.net/anais/543218.pdf},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Lucena, R. M.; Pontes, J.; Wit, A. De; Anjos, G. R.; Mangiavacchi, N.
Linear stability analysis and nonlinear simulations of convective dissolution in an inclined porous layer between impermeable surfaces Journal Article
Em: Chaos, vol. 32, não 11, 2022, ISSN: 1089-7682.
@article{Lucena2022,
title = {Linear stability analysis and nonlinear simulations of convective dissolution in an inclined porous layer between impermeable surfaces},
author = {R. M. Lucena and J. Pontes and A. De Wit and G. R. Anjos and N. Mangiavacchi},
doi = {10.1063/5.0089326},
issn = {1089-7682},
year = {2022},
date = {2022-11-01},
urldate = {2022-11-01},
journal = {Chaos},
volume = {32},
number = {11},
publisher = {AIP Publishing},
abstract = {\<jats:p\>Convective dissolution can occur in porous media when a given solute dissolves in a host layer from above and increases the density of the host solution. Buoyancy-driven fingering can then develop, which increases the transfer flux of the solute. We investigate here numerically the properties of this convective dissolution when the porous host layer is inclined by an angle θ relative to the horizontal direction. We consider an incompressible flow in porous media governed by Darcy’s law, driven by density gradients associated with the concentration of the dissolving solute. The model problem focuses on the case of a very long (infinite) tilted porous layer limited by two parallel impermeable surfaces. A linear stability analysis and nonlinear simulations are performed using the Boussinesq approximation. A vorticity-stream function formulation is adopted to solve the two-dimensional hydrodynamic field through the finite element method. We find that the inclination of the interface decreases the growth rate of the instability and the range of unstable wavenumbers, delaying or even suppressing the onset of the fingering instability. Moreover, it introduces a drift velocity on the perturbations, which is characterized here in both the linear stability analysis and the nonlinear simulations.\</jats:p\>},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
<jats:p>Convective dissolution can occur in porous media when a given solute dissolves in a host layer from above and increases the density of the host solution. Buoyancy-driven fingering can then develop, which increases the transfer flux of the solute. We investigate here numerically the properties of this convective dissolution when the porous host layer is inclined by an angle θ relative to the horizontal direction. We consider an incompressible flow in porous media governed by Darcy’s law, driven by density gradients associated with the concentration of the dissolving solute. The model problem focuses on the case of a very long (infinite) tilted porous layer limited by two parallel impermeable surfaces. A linear stability analysis and nonlinear simulations are performed using the Boussinesq approximation. A vorticity-stream function formulation is adopted to solve the two-dimensional hydrodynamic field through the finite element method. We find that the inclination of the interface decreases the growth rate of the instability and the range of unstable wavenumbers, delaying or even suppressing the onset of the fingering instability. Moreover, it introduces a drift velocity on the perturbations, which is characterized here in both the linear stability analysis and the nonlinear simulations.</jats:p>