Well Placement Optimization Using a Basic Genetic Search Heuristics Algorithm and a Black Oil Simulator

Onuh, C.Y and Alaigba, David and Rotimi, Oluwatosin J. and Arowolo, Bamidele T. (2017) Well Placement Optimization Using a Basic Genetic Search Heuristics Algorithm and a Black Oil Simulator. Open Journal of Yangtze Gas and Oil, 2. pp. 214-225. ISSN Online: 2473-1900 ISSN Print: 2473-1889

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Abstract

In petroleum reservoir management, the essence of well placement is to develop and maintain reservoir pressure in order to achieve maximum production for economic benefits. Large production can be achieved with the placement of multiple wells but this approach is capital intensive and inefficient for the development of a reservoir. A preferable option is the optimal placement of production and injection wells so as to fully capitalize on the imbedded hydrocarbons at a relatively decreased capital investment. The aim of this study is to use developed algorithm and a black oil simulator to place wells in the zones for optimal recovery in the reservoir. Optimal production was determined out of eight scenarios created from well placement in a hypothetical reservoir (finch reservoir) using a black oil simulator, alongside an algorithm developed with java for determining the best possible locations for well placement, taking into consideration the reservoir permeability, fluid saturation, and pay zone thickness. The results of this study reveal that well placement using the engineering judgment coupled with the application of the algorithm using a black oil simulator results in better production compared to other scenarios which consider the combined effect of algorithm and black oil simulator alone.

Item Type:	Article
Uncontrolled Keywords:	Well Placement, Genetic Algorithm, Reservoir Simulator, Production Analysis, Injection Analysis
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TP Chemical technology
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Mrs Patricia Nwokealisi
Date Deposited:	16 Nov 2017 12:27
Last Modified:	16 Nov 2017 12:27
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/9675

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