Petroleum Science >2022, lssue 4: - DOI: https://doi.org/10.1016/j.petsci.2022.03.001.
A novel method of quantitative evaluation and comprehensive classification of low permeability-tight oil reservoirs: A case study of Jidong Open Access
文章信息
作者:Dong-Liang Jiang, Hao Chen, Jian-Peng Xing, Lin Shang, Qun-Hui Wang, Yan-Chun Sun, Yao Zhao, Jian Cui, Ian Duncan
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引用方式:Dong-Liang Jiang, Hao Chen, Jian-Peng Xing, Lin Shang, Qun-Hui Wang, Yan-Chun Sun, Yao Zhao, Jian Cui, Ian Duncan, A novel method of quantitative evaluation and comprehensive classification of low permeability-tight oil reservoirs: A case study of Jidong Oilfield, China, Petroleum Science, Volume 19, Issue 4, 2022, Pages 1527-1541, https://doi.org/10.1016/j.petsci.2022.03.001.
文章摘要
Abstract: The classification of low permeability-tight reservoirs is the premise of development. The deep reservoir of Shahejie 3 member contains rich low permeability-tight reserves, but the strong heterogeneity and complex micro pore structure make the main controlling factors subjective and the classification boundaries unclear. Therefore, a new indicator considering the interaction between fluid and rock named Threshold Flow Zone Indicator (TFZI) is proposed, it can be used as the main sequence of correlation analysis to screen the main controlling factors, and the clustering algorithm is optimized combined with probability distribution to determine the classification boundaries. The sorting coefficient, main throat radius, movable fluid saturation and displacement pressure are screened as the representative parameters for the following four key aspects: rock composition, microstructure, flow capacity and the interaction between rock and fluid. Compared with the traditional probability distribution and clustering algorithm, the boundary of the optimized clustering algorithm proposed in this paper is more accurate. The classification results are consistent with sedimentary facies, oil levels and oil production intensity. This method provides an important basis for the development of low permeability-tight reservoirs.
关键词
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Keywords: Low permeability-tight reservoir; Classification boundary; Correlation analysis; Probability distribution; Clustering algorithm