Thief Zone Assessment in Sandstone Reservoirs Based on Multi-Layer Weighted Principal Component Analysis

Bin Huang, Rui Xu, Cheng Fu, Ying Wang and Lu Wang
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Bin Huang: College of Petroleum Engineering, Northeast Petroleum University, Daqing 163318, China
Rui Xu: College of Petroleum Engineering, Northeast Petroleum University, Daqing 163318, China
Cheng Fu: College of Petroleum Engineering, Northeast Petroleum University, Daqing 163318, China
Ying Wang: Harold Vance Department of Petroleum Engineering, Texas A&M University, College Station, TX 77843, USA
Lu Wang: China National Petroleum Corporation Exploration and Development Research Institute, Beijing 100083, China

Energies, 2018, vol. 11, issue 5, 1-13

Abstract: Many factors influence the evaluation process of thief zones. The evaluation index contains very complex information. How to quickly obtain effective information is the key to improve the evaluation quality for thief zones. Considering that the correlation and information redundancy among the evaluation indexes will seriously affect the evaluation results for the thief zone, based on the principal component analysis (PCA) method, this paper proposes a multi-layer weighted principal component analysis method (MLWPCA). Firstly, factor analysis is performed on the original data to obtain the plurality subsystems of the evaluation index. Then, a principal component is analyzed through the subsystems of the evaluation index PCA to obtain the principal component score. Finally, the subsystem is weighted by the factor score and the comprehensive thief zone score is obtained by combining the subsystem weight and the subsystem score. A case study on the Daqing oilfield shows the effectiveness of the method, verified by tracer tests when applying the MLWPCA method to evaluate the thief zone. The thief zone of the Daqing oilfield is obviously affected by effective thickness, coefficient of permeability variation and interwell connectivity. At present, there are 10 well developed thief zones and eight medium developed thief zones in Daqing oilfield. The accuracy of this method is 94.44%. Compared with PCA, this method has better pertinence in evaluating thief zones, and is more effective in determining the principle influencing factors.

Keywords: thief zone; multi-layer weighted; principal-component-analysis; tracer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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