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Proceedings Papers

Using Machine Learning for Geosteering During In-Seam Drilling

Ruizhi Zhong, Ray L. Johnson Jr, Zhongwei Chen
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208298-MS
https://doi.org/10.15530/AP-URTEC-2021-208298
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View Paper titled, Using Machine Learning for Geosteering During In-Seam Drilling
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Proceedings Papers

Gasification Chamber Evolution and Recovery Performance of Underground Coal Gasification in Deep Coal Seam: A Numerical Simulation Study

Bin Zhao, Xiaohu Dong, Liangliang Jiang, Shanshan Chen, Yanpeng Chen, Zhangxin Chen
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208271-MS
https://doi.org/10.15530/AP-URTEC-2021-208271
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View Paper titled, Gasification Chamber Evolution and Recovery Performance of Underground Coal Gasification in Deep Coal Seam: A Numerical Simulation Study
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Proceedings Papers

Application of Physics Informed Neural Networks to Compositional Modelling

Thelma Anizia Ihunde, Olufemi Olorode
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208310-MS
https://doi.org/10.15530/AP-URTEC-2021-208310
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Proceedings Papers

A Machine Learning Approach to Benchmarking: A New Perspective Utilizing Factor Contribution Analysis

Hamed Tabatabaie, Toby Burrough, Camilo Rodriguez Cadena
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208309-MS
https://doi.org/10.15530/AP-URTEC-2021-208309
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View Paper titled, A Machine Learning Approach to Benchmarking: A New Perspective Utilizing Factor Contribution Analysis
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Proceedings Papers

Outlier Detection Techniques Help Us Identify and Remove Outliers in Production Data to Improve Production Forecasting

Himanshu Shekhar Jha, Hafiz Mustafa Ud Din Sheikh, W John Lee
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208384-MS
https://doi.org/10.15530/AP-URTEC-2021-208384
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View Paper titled, Outlier Detection Techniques Help Us Identify and Remove Outliers in Production Data to Improve Production Forecasting
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Proceedings Papers

Combined Application of Unsupervised and Deep Learning in Absolute Open Flow Potential Prediction: A Case Study of the Weiyuan Shale Gas Reservoir

Lian Wang, Yuedong Yao, Kongjie Wang, Caspar Daniel Adenutsi, Guoxiang Zhao
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208348-MS
https://doi.org/10.15530/AP-URTEC-2021-208348
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View Paper titled, Combined Application of Unsupervised and Deep Learning in Absolute Open Flow Potential Prediction: A Case Study of the Weiyuan Shale Gas Reservoir
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Proceedings Papers

Machine Learning Models for Predicting the Rheology of Nanoparticle-Stabilized-CO2-Foam Fracturing Fluid in Reservoir Conditions

Toluwalase Adeola Olukoga, Yin Feng
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208308-MS
https://doi.org/10.15530/AP-URTEC-2021-208308
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View Paper titled, Machine Learning Models for Predicting the Rheology of Nanoparticle-Stabilized-CO2-Foam Fracturing Fluid in Reservoir Conditions
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Proceedings Papers

On Causes of Partial Cement Deficiency at Doglegs and its Impact on Casing Failure; An Integrated Modeling Approach

Hao Yu, Arash Dahi Taleghani, Zhanghua Lian
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208374-MS
https://doi.org/10.15530/AP-URTEC-2021-208374
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View Paper titled, On Causes of Partial Cement Deficiency at Doglegs and its Impact on Casing Failure; An Integrated Modeling Approach
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Proceedings Papers

Dilatancy and the Mean Normal Stress: Unconventional Concepts Needed for Leak Assessment of Tubular Connections

Gang Tao, Malcolm A. Goodman
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208360-MS
https://doi.org/10.15530/AP-URTEC-2021-208360
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View Paper titled, Dilatancy and the Mean Normal Stress: Unconventional Concepts Needed for Leak Assessment of Tubular Connections
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Proceedings Papers

Application of Principal Component Analysis Biplots to Reservoir Characterisation and Classification for Low Permeability Carbonate Reservoirs in the Middle East

Liang Sun, Hang Zhao, Fan Liu, Penghui Su, Kun Liu
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208350-MS
https://doi.org/10.15530/AP-URTEC-2021-208350
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View Paper titled, Application of Principal Component Analysis Biplots to Reservoir Characterisation and Classification for Low Permeability Carbonate Reservoirs in the Middle East
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Proceedings Papers

Real-Time Applications for Geological Operations: Repeatable AI Use Cases

Alfio Malossi, Davide Baldini, Federica Ferrari, Arcangelo Di Palo, Ada Crottini, Chiara Marini, Cesare Ursini
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208367-MS
https://doi.org/10.15530/AP-URTEC-2021-208367
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Proceedings Papers

Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics

Sayed Ameenuddin Irfan, Nadiah Mohd Azli, Firas A. Abdulkareem, Eswaran Padmanabhan
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208313-MS
https://doi.org/10.15530/AP-URTEC-2021-208313
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View Paper titled, Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics
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Proceedings Papers

Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs

Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208394-MS
https://doi.org/10.15530/AP-URTEC-2021-208394
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View Paper titled, Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
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Proceedings Papers

3D Seismic Facies Classification on CPU and GPU HPC Clusters

Sergio Botelho, Vishal Das, Davide Vanzo, Pandu Devarakota, Vinay Rao, Santi Adavani
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 16–18, 2021
Paper Number: URTEC-208344-MS
https://doi.org/10.15530/AP-URTEC-2021-208344
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View Paper titled, 3D Seismic Facies Classification on CPU and GPU HPC Clusters
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Proceedings Papers

Production Forecasting for Shale Gas Well in Transient Flow Using Machine Learning and Decline Curve Analysis

Dongkwon Han, Sunil Kwon, Hanam Son, Janghyun Lee
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198198-MS
https://doi.org/10.15530/AP-URTEC-2019-198198
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View Paper titled, Production Forecasting for Shale Gas Well in Transient Flow Using Machine Learning and Decline Curve Analysis
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Proceedings Papers

Prediction of the Flowing Bottom-Hole Pressure Using Advanced Data Analytics

Mahshid Firouzi, Suren Rathnayake
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198240-MS
https://doi.org/10.15530/AP-URTEC-2019-198240
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Proceedings Papers

Using Machine Learning Methods to Identify Coals from Drilling and Logging-While-Drilling LWD Data

Ruizhi Zhong, Raymond L. Johnson, Zhongwei Chen
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198288-MS
https://doi.org/10.15530/AP-URTEC-2019-198288
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View Paper titled, Using Machine Learning Methods to Identify Coals from Drilling and Logging-While-Drilling LWD Data
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Proceedings Papers

Machine Learning for Progressive Cavity Pump Performance Analysis: A Coal Seam Gas Case Study

Fahd Saghir, M.E. Gonzalez Perdomo, Peter Behrenbruch
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198281-MS
https://doi.org/10.15530/AP-URTEC-2019-198281
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View Paper titled, Machine Learning for Progressive Cavity Pump Performance Analysis: A Coal Seam Gas Case Study
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Proceedings Papers

Smart Midstream Integration For CSG to LNG

Russell Byfield
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198272-MS
https://doi.org/10.15530/AP-URTEC-2019-198272
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Proceedings Papers

Impacting Factors on Horizontal Coal Seam Gas Well Production and Proxy Model Comparison

Qian Wang, Diane Donovan, Thomas Reay, Bevan Thompson, Iain Rodger, Fengde Zhou, Xianbo Su, Emine Sule Yazici
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198251-MS
https://doi.org/10.15530/AP-URTEC-2019-198251
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View Paper titled, Impacting Factors on Horizontal Coal Seam Gas Well Production and Proxy Model Comparison
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