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.
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BibTeX (Download)
@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}
}