Search operators for genetic algorithms applied to well positioning in oil fields
ARTIGO
Inglês
Agradecimentos: This work was supported by the project entitled Methodologies for Oil Field Development and Management through Reservoir Simulations (UNICAMP/PETROBRAS-CENPES/ ANP) and under ANP R&D Commitment to Investments on Research and Development. The authors would like to thank PETROBRAS,...
Agradecimentos: This work was supported by the project entitled Methodologies for Oil Field Development and Management through Reservoir Simulations (UNICAMP/PETROBRAS-CENPES/ ANP) and under ANP R&D Commitment to Investments on Research and Development. The authors would like to thank PETROBRAS, CAPES and Foundation CMG for the financial support and CMG for the software licenses
Abstract: Optimizing production strategies for oil extraction is not a simple task, mainly due to the large number of variables and uncertainties associated with the problem. Metaheuristics are well-known tools that can be easily applied to this type of problem. However, the large amount of...
Abstract: Optimizing production strategies for oil extraction is not a simple task, mainly due to the large number of variables and uncertainties associated with the problem. Metaheuristics are well-known tools that can be easily applied to this type of problem. However, the large amount of objective function evaluations that such tools require to obtain a good solution is a serious drawback in the context of oil production strategy definition (PSD): the evaluation of a production strategy requires the use of oil field simulation software and each simulation can take hours to complete. Thus, in this work a modified version of a steady-state genetic algorithm is proposed, together with specific recombination, mutation and local search operators specifically tailored for the PSD problem, which aim to reduce the computational cost of the optimization process. The developed algorithm was used to optimize the well positions in a production strategy for a synthetic oil reservoir model and the results were compared with those obtained by a classical genetic algorithm and by a commercial optimization tool
COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES
Fechado
DOI: https://doi.org/10.1109/BRACIS.2018.00092
Texto completo: https://ieeexplore.ieee.org/document/8575663
Search operators for genetic algorithms applied to well positioning in oil fields
Search operators for genetic algorithms applied to well positioning in oil fields
Fontes
Proceedings of the 7th Brazilian Conference on Intelligent Systems Piscataway, NJ : Institute of Electrical and Electronics Engineers, 2018. p. 498-503 |