Quantification of factors affecting fault sealing by using machine learning: Shuangtaizi fault anticline, southern margin of the Liaohe Western Depression, Northeastern China

Xiaofei Fu(State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation), Qi Liu(China National Petroleum Corporation (China)), Mingming Jiang(Peking University), Zhiming Hu(Sinopec (China)), Ruishan Du(Northeast Petroleum University), Lingdong Meng(Innovation Team (China)), Yejun Jin(Northeast Petroleum University)
Marine and Petroleum Geology
July 17, 2024
10.1016/j.marpetgeo.2024.106999
Cited by 6

Related Papers

Lithofacies and depositional setting of a highly prospective lacustrine shale oil succession from the Upper Cretaceous Qingshankou Formation in the Gulong sag, northern Songliao Basin, northeast China
|AAPG Bulletin|2019|383
Synthesis of Group VIII Magnetic Transition-Metal-Doped Monolayer MoSe<sub>2</sub>
|ACS Nano|2022|91
Risking fault reactivation induced by gas injection into depleted reservoirs based on the heterogeneity of geomechanical properties of fault zones
|Petroleum Geoscience|2016|45
Multi-scale characterization and control factors of bedding-parallel fractures in continental shale reservoirs: Insights from the Qingshankou Formation, Songliao Basin, China
|Marine and Petroleum Geology|2025|30
Prediction model and real-time diagnostics of hydraulic fracturing pressure for highly deviated wells in deep oil and gas reservoirs
|Scientific Reports|2025|25