Quantification of factors affecting fault sealing by using machine learning: Shuangtaizi fault anticline, southern margin of the Liaohe Western Depression, Northeastern China-Reference-Cited by-同舟云学术

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

Published:2024-10 Issue: Volume:168 Page:106999
ISSN:0264-8172
Container-title:Marine and Petroleum Geology
language:en
Short-container-title:Marine and Petroleum Geology

Author:

Fu Xiaofei,Jiang Mingming^ORCID,Hu Zhiming,Jin Yejun,Meng Lingdong,Du Ruishan,Liu Qi

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference48 articles.

1. Petrophysical study of faults in sandstone using petrographic image analysis and X-ray computerized tomography;Antonellini;Pure and Appl. Geophys. PAGEOPH.,1994

2. Size-dependent comminution, tectonic mixing, and sealing behavior of a “structurally oversimplified” fault zone in poorly lithified sands: evidence for a coseismic rupture?;Balsamo;Geol. Soc. Am. Bull.,2011

3. Constraints from fault roughness on the scale-dependent strength of rocks;Brodsky;Geology,2016

4. Overpressure in moderately deep to deep strata in the Lengjia-Leijia area，western Liaohe Depression，Bohai Bay Basin：Origin and effects on hydrocarbon accumulation;Chen;Oil Gas Geol.,2024

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