Autor(es)

Brum, Artur ; Coelho, Guilherme ; Santos, Antonio Alberto ; Schiozer, Denis Jose

• Tipo de documento: Artigo Científico
• Fonte: COMPUTATIONAL GEOSCIENCES; v. 29, n. 1, p. 17-pg., 2025-02-01.

Resumo

Optimizing well placement is one of the primary challenges in oil field development. The number and positions of wells must be carefully considered, as it is directly related to the infrastructure cost and the profits over the field's life cycle. In this paper, we propose three estimation of distribution algorithms to optimize well placement with the objective of maximizing the net present value. The methods are guided by an elite set of solutions and are able to obtain multiple local optima in a single run. We also present an auxiliary regression model to preemptively discard candidate solutions with poor performance prediction, thus avoiding running computationally expensive simulations for unpromising candidates. The model is trained with the data obtained during the search process and does not require previous training. Our algorithms yielded a significant improvement compared to a state-of-the-art reference method from the literature, as evidenced by computational experiments with two benchmarks. (AU)

• Processo FAPESP: 17/15736-3 - Centro de Pesquisa em Engenharia em Reservatórios e Gerenciamento de Produção de Petróleo
• Beneficiário: Denis José Schiozer
• Modalidade de apoio: Auxílio à Pesquisa - Programa Centros de Pesquisa Aplicada
• Processo FAPESP: 20/14710-3 - Desenvolvimento de Meta-heurísticas para Otimização de Estratégias de Produção para Campos de Petróleo
• Beneficiário: Artur Ferreira Brum
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado