A machine learning-driven stochastic simulation of underground sulfide distribution with multiple constraints

Ji, QY; Han, FL; Qian, W; Guo, Q; Wan, SL

Han, FL (corresponding author), Hohai Univ, Sch Earth Sci & Engn, Nanjing 211000, Peoples R China.; Han, FL (corresponding author), Jiangsu Univ Technol, Sch Comp Engn, Changzhou 213001, Peoples R China.

OPEN GEOSCIENCES, 2021; 13 (1): 807

Abstract

The increase of sulfide (S2-) during the water flooding process has been regarded as an essential and potential risk for oilfield development and safe......

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