Oil well characterization and artificial gas lift optimization using neural networks combined with genetic algorithm

Monyei, Chukwuka; Adewumi, Aderemi O.; Obolo, Michael O.

Abstract

This paper examines the characterization of six oil wells and the allocation of gas considering limited and unlimited case scenario. Artificial gas lift involves injecting high-pressured gas from the surface into the producing fluid column through one or more subsurface valves set at predetermined depths. This improves recovery by reducing the bottom-hole pressure at which wells become uneconomical and are thus abandoned. This paper presents a successive application of modified artificial neural network (MANN) combined with a mild intrusive genetic algorithm (MIGA) to the oil well characteristics with promising results. This method helps to prevent the overallocation of gas to wells for recovery purposes while also maximizing oil production by ensuring that computed allocation configuration ensures maximum economic accrual. Results obtained show marked improvements in the allocation especially in terms of economic returns. © 2014 Chukwuka G. Monyei et al.

Citation

Monyei, C., Adewumi, A. O., & Obolo, M. O. (2014). Oil well characterization and artificial gas lift optimization using neural networks combined with genetic algorithm. Discrete Dynamics in Nature and Society, 2014, 289239. https://doi.org/10.1155/2014/289239

• Journal Article Type: Article
• Acceptance Date: Apr 8, 2014
• Publication Date: Jan 1, 2014
• Deposit Date: Dec 20, 2018
• Publicly Available Date: Dec 20, 2018
• Journal: Discrete Dynamics in Nature and Society
• Print ISSN: 1026-0226
• Electronic ISSN: 1607-887X
• Publisher: Hindawi
• Peer Reviewed: Peer Reviewed
• Volume: 2014
• Pages: 289239
• DOI: https://doi.org/10.1155/2014/289239
• Public URL: https://uwe-repository.worktribe.com/output/817468
• Publisher URL: https://doi.org/10.1155/2014/289239