Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification

Qasem Al-Tashi, Helmi Md Rais, Said Jadid Abdulkadir, Seyedali Mirjalili

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The classification of the hydrocarbon reserve is a significant challenge for both oil and gas producing firms. The factor of reservoir recovery contributes to the proven reservoir growth potential which leads to a good preparation of field development and production. However, the high dimensionality or irrelevant measurements/features of the reservoir data leads to less classification accuracy of the factor reservoir recovery. Therefore, feature selection techniques become a necessity to eliminate the said irrelevant measurements/ features. In this paper, a wrapper-based feature selection method is proposed to select the optimal feature subset. A Binary Grey Wolf Optimization (BGWO) is applied to find the best features/measurements from big reservoir data obtained from U.S.A. oil gas fields. To our knowledge, this is the first time applying the Grey Wolf Optimizer (GWO) as a search technique to search for the most important measurements to achieve high classification accuracy for reservoir recovery factor. The wrapper K-Nearest Neighbors (KNN) classifier is used to evaluate the selected features. In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. The experimental results showed that, the proposed BGWO-KNN significantly outperforms benchmarking methods in terms of feature reduction as well as increasing the classification accuracy. The proposed method shows a great potential for solving the real oil gas problems.

Original languageEnglish
Title of host publication2020 International Conference on Computational Intelligence, ICCI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-216
Number of pages6
ISBN (Electronic)9781728154473
DOIs
Publication statusPublished - 8 Oct 2020
Event2020 International Conference on Computational Intelligence, ICCI 2020 - Bandar Seri Iskandar, Malaysia
Duration: 8 Oct 20209 Oct 2020

Publication series

Name2020 International Conference on Computational Intelligence, ICCI 2020

Conference

Conference2020 International Conference on Computational Intelligence, ICCI 2020
Country/TerritoryMalaysia
CityBandar Seri Iskandar
Period8/10/209/10/20

Keywords

  • classification
  • Feature selection
  • grey wolf optimizer
  • oil gas
  • reservoir

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