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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

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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

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

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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

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

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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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View Paper titled, Real-Time Applications for Geological Operations: Repeatable AI Use Cases
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Proceedings Papers

Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs

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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

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

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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

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

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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

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

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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

Using Machine Learning for Geosteering During In-Seam Drilling

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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

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

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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

Application of Physics Informed Neural Networks to Compositional Modelling

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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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View Paper titled, Application of Physics Informed Neural Networks to Compositional Modelling
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Proceedings Papers

3D Seismic Facies Classification on CPU and GPU HPC Clusters

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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

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

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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

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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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

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

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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

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

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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

Monitoring Socio-Economic Changes in Small Towns Affected by Large Scale CSG-LNG Development

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Katherine Witt, Jonathan Simpson
Paper presented at the SPE/AAPG/SEG Asia Pacific Unconventional Resources Technology Conference, November 18–19, 2019
Paper Number: URTEC-198314-MS
https://doi.org/10.15530/AP-URTEC-2019-198314
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View Paper titled, Monitoring Socio-Economic Changes in Small Towns Affected by Large Scale CSG-LNG Development
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Proceedings Papers

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

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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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View Paper titled, Prediction of the Flowing Bottom-Hole Pressure Using Advanced Data Analytics
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Proceedings Papers

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

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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

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

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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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Proceedings Papers

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

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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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