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Uncertainty Evaluation Method and Application of Reservoir Lithofacies Proportion under the Condition of Few Wells
Author(s) -
Shaohua Li,
Chuan Du,
Daowu Huang,
Dongping Duan,
Fang Ding,
Siyu Yu,
Xin Huang
Publication year - 2022
Publication title -
lithosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.737
H-Index - 43
eISSN - 1941-8264
pISSN - 1947-4253
DOI - 10.2113/2022/1305201
Subject(s) - geology , quantile , range (aeronautics) , sampling (signal processing) , natural gas field , distribution (mathematics) , statistics , mathematics , natural gas , mathematical analysis , materials science , chemistry , organic chemistry , filter (signal processing) , computer science , composite material , computer vision
The proportion of different lithofacies is essential to determine the net-gross ratio, which directly affects the calculation of oil and gas reserves. Under the condition of few wells, the reliability of different lithofacies proportions obtained using well data is poor because it is difficult to estimate the uncertainty variation range of different lithofacies proportions. The present study overcomes this problem using an uncertainty evaluation method for reservoir lithofacies proportion. First, different lithofacies proportions of the reservoir are determined using the well and seismic data and are considered as the most likely estimated. Based on the lithofacies proportion, the lithofacies models of the study area are developed. Second, uniform and random methods are applied to sample the lithofacies models, and then, the probability distribution functions of different lithofacies proportions are derived. Third, the three levels of lithofacies proportions in the study area are calculated using the method of quantile and discretization of the probability distribution. Finally, we take M gas field as a sample and compare the test results of the fixed and random well structures. The results show that the sampling results of the fixed well structure model significantly deviate under the influence of the extension direction of the channel and well pattern distribution. Therefore, it is suggested to use random well structure to determine the uncertainty distribution range of lithofacies proportion.

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