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Proceedings Papers

3D Rate of Penetration Prediction for Horizontal Well Planning

Qiuguo Li, Khaqan Khan, Augustine Monyei, Tariq Mahmood
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0078
https://doi.org/10.56952/IGS-2024-0078
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View Paper titled, 3D Rate of Penetration Prediction for Horizontal Well Planning
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Proceedings Papers

A Hybrid Machine Learning Method for Pore Pressure and Wellbore Stability Prediction in a Shale Gas Field at Sichuan Basin

B. Zeng, P. Liu, X. W. Shi, S. J. Liu, W. H. Yue, D. J. Zhang, E. S. Xu, Q. M. Sun, Q. S. Li, T. Yu
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0229
https://doi.org/10.56952/IGS-2024-0229
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View Paper titled, A Hybrid Machine Learning Method for Pore Pressure and Wellbore Stability Prediction in a Shale Gas Field at Sichuan Basin
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Proceedings Papers

Fluid Infiltration vs Hydraulic Fracturing in Weakly Cemented Reservoirs

C. Konstantinou, P. Papanastasiou
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0387
https://doi.org/10.56952/IGS-2024-0387
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View Paper titled, Fluid Infiltration vs Hydraulic Fracturing in Weakly Cemented Reservoirs
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Proceedings Papers

Data-Driven Surrogate Models for Bearing Capacity of Spatially Random Soils

H. C. Nguyen, J. Kowalski, H. Xu, X. He, X. Chen, R. L. Sousa
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0388
https://doi.org/10.56952/IGS-2024-0388
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View Paper titled, Data-Driven Surrogate Models for Bearing Capacity of Spatially Random Soils
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Proceedings Papers

Transfer Learning: A Key Approach to Fault Prediction and Extraction in Deep Learning

Muhammad Khan, Andy Anderson Bery, Syed Sadaqat Ali, Saleh Aldossary
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0423
https://doi.org/10.56952/IGS-2024-0423
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View Paper titled, Transfer Learning: A Key Approach to Fault Prediction and Extraction in Deep Learning
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Proceedings Papers

A Machine Learning-Based Multi-Scale Natural Fracture Characterization Approach Using Seismic Attributes in the Sichuan Basin

Xuefeng Yang, Dongchen Liu, Shaojun Liu, Lieyan Cao, Chongjiu Qu, Xiuyue Shen, Joseph Leines, Chuxi Liu, Wei Yu
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0491
https://doi.org/10.56952/IGS-2024-0491
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View Paper titled, A Machine Learning-Based Multi-Scale Natural Fracture Characterization Approach Using Seismic Attributes in the Sichuan Basin
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Proceedings Papers

AI-Integrated Geology-Engineering Workflow for Hydraulic Fracture Evaluation and Production Prediction

Bo Zeng, Haoyong Huang, Liqing Chen, Chuxi Liu, Wei Yu, Joseph Leines, Jijun Miao
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0504
https://doi.org/10.56952/IGS-2024-0504
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View Paper titled, AI-Integrated Geology-Engineering Workflow for Hydraulic Fracture Evaluation and Production Prediction
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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

Data-Driven Intelligent Optimization Design of Fracturing Stage and Cluster Locations: A Case Study

Xiaodong He, Jie Li, Shengjiang Xu, Shimeng Hu, Mao Sheng, Lijuan Si, Fumin Jiang
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0643
https://doi.org/10.56952/IGS-2024-0643
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View Paper titled, Data-Driven Intelligent Optimization Design of Fracturing Stage and Cluster Locations: A Case Study
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Proceedings Papers

Earthquake Classification Using Resnet 50 Model: A Machine Learning Approach

K. M. Kaushik Mahanta
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0649
https://doi.org/10.56952/IGS-2024-0649
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View Paper titled, Earthquake Classification Using Resnet 50 Model: A Machine Learning Approach
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Proceedings Papers

3D Structural Geomechanics and Machine Learning Based Petrophysical Evaluation of Proven and Mature Oilfield in Upper Indus Basin, Pakistan

Najwa Fayyaz.
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0665
https://doi.org/10.56952/IGS-2024-0665
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View Paper titled, 3D Structural Geomechanics and Machine Learning Based Petrophysical Evaluation of Proven and Mature Oilfield in Upper Indus Basin, Pakistan
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Proceedings Papers

Data-Driven Intelligent Prediction of In-Situ Stress in Horizontal Wells and Its Application in Hydraulic Fracturing Design

Shimeng Hu, Mao Sheng, Fumin Jiang, Xiaodong Ma, Lijuan Si, Shouceng Tian
Paper presented at the International Geomechanics Conference, November 18–20, 2024
Paper Number: ARMA-IGS-2024-0744
https://doi.org/10.56952/IGS-2024-0744
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View Paper titled, Data-Driven Intelligent Prediction of In-Situ Stress in Horizontal Wells and Its Application in Hydraulic Fracturing Design
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Proceedings Papers

Carbonate Formation Pressure Prediction Method Based on Machine Learning

Zhenyu Tao, Honghai Fan, Yuhan Liu, Fei Zhou, Yiwei Chen
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0297
https://doi.org/10.56952/IGS-2023-0297
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View Paper titled, Carbonate Formation Pressure Prediction Method Based on Machine Learning
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Proceedings Papers

A Machine Learning Framework for Quality Assurance and Prediction of Well Trajectory Deviations

H. Khalifa, O. S. Tomomewo, A. Benarbia, A. Dehdouh, B. E. Berrehal
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0230
https://doi.org/10.56952/IGS-2023-0230
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View Paper titled, A Machine Learning Framework for Quality Assurance and Prediction of Well Trajectory Deviations
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Proceedings Papers

Evaluation of Different Tree-Based Machine Learning Approaches for Formation Lithology Classification

Abbas M. Al-Khudafi, Hamzah A. Al-Sharifi, Ghareb M. Hamada, Mohamed A. Bamaga, Abdulrahman A. Kadi, A. A. Al-Gathe
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0026
https://doi.org/10.56952/IGS-2023-0026
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View Paper titled, Evaluation of Different Tree-Based Machine Learning Approaches for Formation Lithology Classification
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Proceedings Papers

Fracture Morphology Evaluation of Surrogate Model for Fast Prediction Using Machine Learning

Zhongyu Hu, Mao Sheng, Zhaoyang Wei, Shouceng Tian, Jun Zhou, Shimeng Hu
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0199
https://doi.org/10.56952/IGS-2023-0199
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View Paper titled, Fracture Morphology Evaluation of Surrogate Model for Fast Prediction Using Machine Learning
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Proceedings Papers

Coupling Fluid Flow and Geomechanical Deformation Using AI & FEM Approaches

Osman Hamid, Tameem Almani, Sulaiman Qannas, Ghalia Alshanbari
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0017
https://doi.org/10.56952/IGS-2023-0017
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View Paper titled, Coupling Fluid Flow and Geomechanical Deformation Using AI & FEM Approaches
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Proceedings Papers

Predicting Rate of Penetration Using the Dual Seq2Seq Model

Tao Pan, Zhen Li, Chengkai Zhang, Xianzhi Song, Lin Zhu, Zhi Yan, Zhaopeng Zhu, Yuan Sun, Pengbo Ni
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0353
https://doi.org/10.56952/IGS-2023-0353
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View Paper titled, Predicting Rate of Penetration Using the Dual Seq2Seq Model
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Proceedings Papers

1D/3D Clustering Techniques of Geomechanical and Reservoir Properties to Overcome Stimulation Challenges

Osman Hamid, Sarah Alamer
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0016
https://doi.org/10.56952/IGS-2023-0016
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View Paper titled, 1D/3D Clustering Techniques of Geomechanical and Reservoir Properties to Overcome Stimulation Challenges
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Proceedings Papers

Predicting Formation Breakdown Pressures for Arbitrary Wellbore Orientation Using Machine Learning Techniques

Tameem Almani, Khaqan Khan
Paper presented at the International Geomechanics Symposium, October 30–November 2, 2023
Paper Number: ARMA-IGS-2023-0079
https://doi.org/10.56952/IGS-2023-0079
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View Paper titled, Predicting Formation Breakdown Pressures for Arbitrary Wellbore Orientation Using Machine Learning Techniques
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