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Proceedings Papers

Machine Learning-Based Prediction of Natural Fractures and Vugs in Carbonate Reservoir

Huiwen Pang, Hanqing Wang, Yan Jin, Jingwei Tian
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0506
https://doi.org/10.56952/IGS-2024-0506
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View Paper titled, Machine Learning-Based Prediction of Natural Fractures and Vugs in Carbonate Reservoir
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Proceedings Papers

Automatic low-order weak faults detection from carbonate reservoir based on deep learning and ant tracking

Han Wang, Xingwei Wu, Hanqing Wang, Jin Meng, Ji Chang, Tianrui Ye, Yujie Zhou, Dongwei Zhang, Yitian Xiao
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4089465
https://doi.org/10.1190/image2024-4089465.1
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View Paper titled, Automatic low-order weak faults detection from carbonate reservoir based on deep learning and ant tracking
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Proceedings Papers

A hybrid framework of physical constraints and sequence learning for production forecasting with application in the Weirong shale gas field, China

Ji Chang, Han Wang, Hanqing Wang, Yujie Zhou, Jin Meng, Yitian Xiao
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4097293
https://doi.org/10.1190/image2024-4097293.1
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View Paper titled, A hybrid framework of physical constraints and sequence learning for production forecasting with application in the Weirong shale gas field, China
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Proceedings Papers

Data-Driven Rock Mechanics Parameter Calculation Through the Integration of EPBP and OSDU: A Case Study

Hanqing Wang, Meng Han, Xiaobin Zhang, Xiaomei Kang, Zhimin Bai, Jin Meng, Dongwei Zhang, Yujie Zhou, Tianrui Ye, Ji Chang, Han Wang, Yitian Xiao, Xudong Sun
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1189
https://doi.org/10.56952/ARMA-2024-1189
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View Paper titled, Data-Driven Rock Mechanics Parameter Calculation Through the Integration of EPBP and OSDU: A Case Study
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Proceedings Papers

A Machine-Learning-Based Workflow for Drilling Risk Prediction of Wellbore Instability and Trajectory Optimization in Ultra-Deep Formation

Hanqing Wang, Ruxin Zhang, Ziyan Deng, Jin Meng, Han Wang, Yujie Zhou, Fan Yang, Ji Chang, Yitian Xiao, Huiwen Pang
Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, June 17–19, 2024
Paper Number: URTEC-4034008-MS
https://doi.org/10.15530/urtec-2024-4034008
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View Paper titled, A Machine-Learning-Based Workflow for Drilling Risk Prediction of Wellbore Instability and Trajectory Optimization in Ultra-Deep Formation
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Proceedings Papers

Prediction of Safe Mud Window Based on Seismic Data in Carbonate Formation

Huiwen Pang, Hanqing Wang, Yan Jin
Paper presented at the 15th ISRM Congress, October 9–14, 2023
Paper Number: ISRM-15CONGRESS-2023-367
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View Paper titled, Prediction of Safe Mud Window Based on Seismic Data in Carbonate Formation
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Proceedings Papers

Prediction of Mud Loss Type Based on Seismic Data Using Machine Learning

Huiwen Pang, Hanqing Wang, Yan Jin, Yunhu Lu, Yongdong Fan
Paper presented at the 56th U.S. Rock Mechanics/Geomechanics Symposium, June 26–29, 2022
Paper Number: ARMA-2022-0485
https://doi.org/10.56952/ARMA-2022-0485
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View Paper titled, Prediction of Mud Loss Type Based on Seismic Data Using Machine Learning
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Proceedings Papers

Segmentation Methods for X-Ray Computer Tomography Images of Oil Sands

Huiwen Pang, Yan Jin, Jingnan Dong, Yanfang Gao, Hanqing Wang, Zhenyu Wang
Paper presented at the 5th ISRM Young Scholars' Symposium on Rock Mechanics and International Symposium on Rock Engineering for Innovative Future, December 1–4, 2019
Paper Number: ISRM-YSRM-2019-166
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View Paper titled, Segmentation Methods for X-Ray Computer Tomography Images of Oil Sands
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Proceedings Papers

An Extended Finite Element Method for Hydro-Mechanically Coupled Analysis of Mud Loss in Naturally Fractured Formations

Yang Xia, Yan Jin, Zhao Huang, Yunhu Lu, Hanqing Wang
Paper presented at the 53rd U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2019
Paper Number: ARMA-2019-0395
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View Paper titled, An Extended Finite Element Method for Hydro-Mechanically Coupled Analysis of Mud Loss in Naturally Fractured Formations
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Proceedings Papers

Study on Intelligent Prediction for Risk Level of Lost Circulation While Drilling Based on Machine Learning

Zejun Li, Mian Chen, Yan Jin, Yunhu Lu, Hanqing Wang, Zhi Geng, Shiming Wei
Paper presented at the 52nd U.S. Rock Mechanics/Geomechanics Symposium, June 17–20, 2018
Paper Number: ARMA-2018-105
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View Paper titled, Study on Intelligent Prediction for Risk Level of Lost Circulation While Drilling Based on Machine Learning
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