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Proceedings Papers

Shales: From the Atomic Scale to the Rock-Mass Scale

C. D. Rodriguez-Hernandez, M. Liu, E. Volkova, B. Yan, G. Turkiyyah, J. C. Santamarina
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0959
https://doi.org/10.56952/ARMA-2023-0959
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View Paper titled, Shales: From the Atomic Scale to the Rock-Mass Scale
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Proceedings Papers

Experimental Study of Anisotropic Strength Properties of Shale

Danzhu Zheng, Evren Ozbayoglu, Stefan Miska, Jianguo Zhang
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0128
https://doi.org/10.56952/ARMA-2023-0128
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View Paper titled, Experimental Study of Anisotropic Strength Properties of Shale
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Proceedings Papers

Real-Time Prediction of Formation Pore Pressure Using Hybrid LSTM-BP Model

Xuezhe Yao, Xianzhi Song, Liang Han, Haolin Zhang, Zhaopeng Zhu, Baoyu Li, Rui Zhang
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0130
https://doi.org/10.56952/ARMA-2023-0130
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View Paper titled, Real-Time Prediction of Formation Pore Pressure Using Hybrid LSTM-BP Model
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Proceedings Papers

Linking High Resolution Geomechanical Datasets to Log Scale via Machine Learning

Evan Gragg, Samuel Fluckiger, Shannon Borchardt
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0163
https://doi.org/10.56952/ARMA-2023-0163
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View Paper titled, Linking High Resolution Geomechanical Datasets to Log Scale via Machine Learning
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Proceedings Papers

An Intelligent Prediction Method of Horizontal Well ROP Based on Di-GRU

Tao Pan, Xianzhi Song, Zheng Wang, Zhiyong Yin, Yong Ji, Lin Zhu, Zhijun Pei, Shanlin Ye, Muchen Liu, Zhen Li, Zhaopeng Zhu
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0405
https://doi.org/10.56952/ARMA-2023-0405
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View Paper titled, An Intelligent Prediction Method of Horizontal Well ROP Based on Di-GRU
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Proceedings Papers

A Novel Rock Drillability Characterization and Prediction Method Based on Drilling Big Data and Unsupervised Clustering Algorithm

Zongyu Lu, Zhenxin Jiang, Zhe Wu, Xianzhi Song, Shanlin Ye, Zihao Liu
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0394
https://doi.org/10.56952/ARMA-2023-0394
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View Paper titled, A Novel Rock Drillability Characterization and Prediction Method Based on Drilling Big Data and Unsupervised Clustering Algorithm
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Proceedings Papers

Characterization of a Tight Gas Reservoir Using the Integration of Electrofacies and Fracture Aperture, Ahnet, Algeria

Doina Irofti, Ghoulem E. H. Ifrene, Aimene Aihar, Nassim Bouabdallah, Abdelhakim Khouissat, Safouane Djemai
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0901
https://doi.org/10.56952/ARMA-2023-0901
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View Paper titled, Characterization of a Tight Gas Reservoir Using the Integration of Electrofacies and Fracture Aperture, Ahnet, Algeria
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Proceedings Papers

A New Drill Bit Selection Method Based on Machine Learning and Intelligent Optimization Process

Z. H. Liu, X. Z. Song, S. L. Ye, Z. Y. Yin, Y. Ji, C. K. Zhang, B. D. Ma, Z. P. Zhu, L. Han
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0293
https://doi.org/10.56952/ARMA-2023-0293
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View Paper titled, A New Drill Bit Selection Method Based on Machine Learning and Intelligent Optimization Process
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Proceedings Papers

Drilling Stuck Probability Intelligent Prediction Based on LSTM Considering Local Interpretability

Jianhua Wang, Zhen Guan, Muchen Liu, Xianzhi Song, Zheng Wang
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0326
https://doi.org/10.56952/ARMA-2023-0326
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View Paper titled, Drilling Stuck Probability Intelligent Prediction Based on LSTM Considering Local Interpretability
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Proceedings Papers

Data-Driven Models for Predicting Rate of Penetration Based on Machine Learning Algorithms

Yang Liu, Yang Xi, Xingyun Xiang, Tianshou Ma, Sitong Chen
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0327
https://doi.org/10.56952/ARMA-2023-0327
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View Paper titled, Data-Driven Models for Predicting Rate of Penetration Based on Machine Learning Algorithms
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Proceedings Papers

The Geotechnical Aspects of a Pillar Recovery Project in the DOZ Cave Mine

F. Putra, Hasan R. Meiharriko, J. P. E. Hamman
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0292
https://doi.org/10.56952/ARMA-2023-0292
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View Paper titled, The Geotechnical Aspects of a Pillar Recovery Project in the DOZ Cave Mine
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A Machine Learning Based Proxy Model for the Rapid Prediction of Hydraulic Fractures

Varun Gupta, Alexandros Solomou, Padmanabh Limaye, Gauthier Becker, M. Abinesh, Holger Meier, Dakshina Valiveti, Huafei Sun, Kelvin Amalokwu, Brian Crawford, Ripu Manchanda, Kaustubh Kulkarni
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0315
https://doi.org/10.56952/ARMA-2023-0315
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View Paper titled, A Machine Learning Based Proxy Model for the Rapid Prediction of Hydraulic Fractures
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Proceedings Papers

Fractures Extraction from Core SEM Images Based on Double-Side Inspection and Morphological Completion

Yongdong Fan, Huiwen Pang, Yan Jin, Hui Zhang
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0599
https://doi.org/10.56952/ARMA-2023-0599
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View Paper titled, Fractures Extraction from Core SEM Images Based on Double-Side Inspection and Morphological Completion
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Proceedings Papers

Development of an Expert System for Unplanned Fall of Ground Assessment in Coal Mine Excavation Intersections

A. C. Adoko, N. B. Kaisa
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0585
https://doi.org/10.56952/ARMA-2023-0585
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View Paper titled, Development of an Expert System for Unplanned Fall of Ground Assessment in Coal Mine Excavation Intersections
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Proceedings Papers

Application of Artificial Intelligence in Prediction of Wellbore Stability Using Well Logging and Drilling Data

Juntao Wu, Wei Liu, Hai Lin, Hailong Liu, Chengyong Peng
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0598
https://doi.org/10.56952/ARMA-2023-0598
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View Paper titled, Application of Artificial Intelligence in Prediction of Wellbore Stability Using Well Logging and Drilling Data
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Proceedings Papers

Advance Prediction of Rockmass Conditions During TBM Tunnelling Based on Cost-Sensitive Learning Under Imbalance Dataset

Shaokang Hou, Li Cheng, Yaoru Liu
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0651
https://doi.org/10.56952/ARMA-2023-0651
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View Paper titled, Advance Prediction of Rockmass Conditions During TBM Tunnelling Based on Cost-Sensitive Learning Under Imbalance Dataset
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Proceedings Papers

Effects of Tuning Hyperparameters in Random Forest Regression on Reservoir's Porosity Prediction. Case Study: Volve Oil Field, North Sea

K. Sandunil, Z. Bennour, H. Ben Mahmud, A. Giwelli
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0660
https://doi.org/10.56952/ARMA-2023-0660
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View Paper titled, Effects of Tuning Hyperparameters in Random Forest Regression on Reservoir's Porosity Prediction. Case Study: Volve Oil Field, North Sea
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Proceedings Papers

Experimental Study of Tight Reservoir Rock Failure Process Based on Unsupervised Machine Learning

Shan Wu, Qi Zhao, Hui Yang, Hongkui Ge
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0669
https://doi.org/10.56952/ARMA-2023-0669
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View Paper titled, Experimental Study of Tight Reservoir Rock Failure Process Based on Unsupervised Machine Learning
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Proceedings Papers

Drilling Data Based Approach for Equivalent Circulation Density Prediction While Drilling

Ahmed Abdelaal, Salaheldin Elkatatny, Hany Gamal, Wael Ziadat
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0722
https://doi.org/10.56952/ARMA-2023-0722
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View Paper titled, Drilling Data Based Approach for Equivalent Circulation Density Prediction While Drilling
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Proceedings Papers

An Automated Data-Driven Workflow for Identifying Fractured Horizontal Well Sweet Spots in Shale Reservoirs

Yuxuan Deng, Wendong Wang, Xianfei Du, Yuliang Su, Shibo Sun, Feng Jia, Zhaoqiang Jiang
Paper presented at the 57th U.S. Rock Mechanics/Geomechanics Symposium, June 25–28, 2023
Paper Number: ARMA-2023-0672
https://doi.org/10.56952/ARMA-2023-0672
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View Paper titled, An Automated Data-Driven Workflow for Identifying Fractured Horizontal Well Sweet Spots in Shale Reservoirs
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