Results 91 to 100 of about 232 (137)

Causes and Controlling Factors of Overpressure Systems in the Qingshankou Formation: Insights for Unconventional Oil and Gas Exploration

Overpressure systems in the Qingshankou Formation of the Gulong Sag have a significant impact on unconventional shale oil accumulation, but their distribution and genesis are unknown.
Xiuli Fu, Guoshuai Bai, Fangju Chen, Shuangfang Lu, Suo Wang, Jie Li, Mengxia Li, Qiang Zheng   +7 more
core   +1 more source

Lithofacies Characteristics of the Lower Cretaceous Qing 1 Member in the Heiyupao Depression, Northern Binbei Area of the Songliao Basin

Strategic breakthroughs have been made in the exploration and evaluation of Gulong shale oil in the Songliao Basin. However, the Heiyupao Depression, located near the Gulong Depression, hosts a thick section of the Qingshankou Formation shale that has ...
Xun Ge, Wangpeng Li, Xuntao Yu, Jiapeng Yuan, Yali Liu, Pei Li, Pengfei Liu, Xiaotong Ge, Botao Huang, Haiguang Wu   +9 more
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A new method for quantitative evaluation of shale laminae using electrical image logging

Shale oil reservoirs are generally characterized by complex mineral compositions, rapid lithofacies changes, and thin laminae. Explorations have confirmed that the type and density of shale laminae significantly influence reservoir quality, highlighting ...
Weilin Yan, Hongliang Wu, Kewen Wang, Zhou Feng, Chaoliu Li, Han Tian, Jiandong Zheng   +6 more
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A LithoScanner logging data processing method and application applicable to shale oil formation

Lithology identification is crucial for understanding the characteristics of reservoirs, optimizing development plans, and enhancing development efficiency.
Zhen Lin Wang, Lei Zhao, Xiao Xuan Chen, Peng Liu, Xuan Hu, Wang Wang Yang, Jing Su   +6 more
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Prediction of Total Organic Carbon Content in Shale Based on PCA-PSO-XGBoost

Total organic carbon (TOC) content is an important parameter for evaluating the abundance of organic matter in, and the hydrocarbon production capacity, of shale. Currently, no prediction method is applicable to all geological conditions, so exploring an
Jinyou Zhang, Yingjie Meng, Tingting Li, Lu Tang, Chengwu Xu, Tianyong Liu   +5 more
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Differential reservoir formation mechanisms of shale oil reservoirs in the Qingshankou Formation, Cretaceous system, Songliao Basin. [PDF]

Sci Rep
Qi Y, Chengwu X, Tingting L, Shiguo S, Chuanhao L, Mengying W, Yunheng Z, Xiaoxuan L.   +7 more
europepmc   +1 more source

Origin and Evolution of Clay Mineral and Its Impact on Shale Oil Enrichment: Insight from Qingshankou Formation, Songliao Basin, NE China. [PDF]

ACS Omega
Kang Y, Liu K, Zhu R, Zhang S, Wu S, Zhang J, Liu C.   +6 more
europepmc   +1 more source

Transfer learning for well logging formation evaluation using similarity weights

Machine learning has been widely applied in well logging formation evaluation studies. However, several challenges negatively impacted the generalization capabilities of machine learning models in practical implementations, such as the mismatch of data ...
Rongbo Shao, Jun Zhou, Binsen Xu, Peng Liu, Hongliang Wu, Zhou Feng, Weizhong Li, Han Tian, Lizhi Xiao   +8 more
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Microscopic oil occurrence in high-maturity lacustrine shales: Qingshankou Formation, Gulong Sag, Songliao Basin

Petroleum Science, 2023
Jing-Ya Zhang, Ru-Kai Zhu, Song-Tao Wu, Xiao-Hua Jiang, Chang Liu, Yi Cai, Su-Rong Zhang, Tian-Shu Zhang   +7 more
openaire   +1 more source

Research and Application on Automatic Stratigraphic Sequence Division and Comparison Method Based on Integrated Prediction Error Filter Analysis

The effectiveness of the integrated prediction error filter analysis (INPEFA) technique, which reveals the stratigraphic sequence structure with trend and turning points information by highlighting the cyclic features in the logging curves, is verified ...
NING Weifeng, LIN Yaoqiang, WANG Hao, LIU Yingming, WANG Caizhi, WEI Xingyun, JIANG Qingchun   +6 more
core   +1 more source