An Overview of Evolutionary Computing for Interpretation in the Oil and Gas Industry

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2016

Autores

Lopes, RL (Autor) Outra; Jahromi, HN (Autor) Outra; Jorge, AM (Autor) FCUP

Ata de Conferência Internacional

Título: ACM International Conference Proceeding Series

Páginas: 110-114

9th International C* Conference on Computer Science and Software Engineering, C3S2E 2016

20 July 2016 through 22 July 2016

Indexação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00K-S91

DOI: 10.1145/2948992.2949006

Abstract (EN): The Oil and Gas Exploration & Production (E&P) field deals with high-dimensional heterogeneous data, collected at different stages of the E&P activities from various sources. Over the years different soft-computing algorithms have been proposed for data-driven oil and gas applications. The most popular by far are Artificial Neural Networks, but there are applications of Fuzzy Logic systems, Support Vector Machines, and Evolutionary Algorithms (EAs) as well. This article provides an overview of the applications of EAs in the oil and gas E&P industry. The relevant literature is reviewed and categorised, showing an increasing interest amongst the geoscience community. © 2016 ACM.

Idioma: Inglês

Tipo (Avaliação Docente): Científica