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Proceedings Papers

NMR Logging Data Processing Using Deep Learning

Gang Luo, Sihui Luo, Lizhi Xiao, Martin J. Blunt, Branko Bijeljic, Guangzhi Liao, Rongbo Shao
Publisher: Society of Petrophysicists and Well-Log Analysts
Paper presented at the SPWLA 64th Annual Logging Symposium, June 10–14, 2023
Paper Number: SPWLA-2023-0026
https://doi.org/10.30632/SPWLA-2023-0026
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Proceedings Papers

A New Workflow for Estimating Reservoir Properties with Gradient Boosting Model and Joint Inversion Using MWD Measurements

Hyungjoo Lee, Alexander Mitkus, Andrew Pare, Kenneth McCarthy, Marc Willerth, Paul Reynerson, Tannor Ziehm, Timothy Gee
Publisher: Society of Petrophysicists and Well-Log Analysts
Paper presented at the SPWLA 64th Annual Logging Symposium, June 10–14, 2023
Paper Number: SPWLA-2023-0044
https://doi.org/10.30632/SPWLA-2023-0044
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View Paper titled, A New Workflow for Estimating Reservoir Properties with Gradient Boosting Model and Joint Inversion Using MWD Measurements
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Proceedings Papers

Strata-Constrained GWLSTM Network for Logging Lithology Prediction

Jianjun Li, Haotian Lv, Haining Zhang, Hui Li, Baohai Wu
Publisher: Society of Petrophysicists and Well-Log Analysts
Paper presented at the SPWLA 64th Annual Logging Symposium, June 10–14, 2023
Paper Number: SPWLA-2023-0076
https://doi.org/10.30632/SPWLA-2023-0076
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View Paper titled, Strata-Constrained GWLSTM Network for Logging Lithology Prediction
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Proceedings Papers

Best Practices in Automatic Permeability Estimation: Machine-Learning Methods vs. Conventional Petrophysical Models

Oriyomi Raheem, Wen Pan, Carlos Torres-Verdín, Misael M. Morales
Publisher: Society of Petrophysicists and Well-Log Analysts
Paper presented at the SPWLA 64th Annual Logging Symposium, June 10–14, 2023
Paper Number: SPWLA-2023-0084
https://doi.org/10.30632/SPWLA-2023-0084
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View Paper titled, Best Practices in Automatic Permeability Estimation: Machine-Learning Methods vs. Conventional Petrophysical Models
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Proceedings Papers

AI Guided Interpretation: Automated Quality Assessment for Depth-Matched Images

Kristina Prokopetc, Alexis He, Salma Benslimane, Josselin Kherroubi, Nadege Bize-Forest
Publisher: Society of Petrophysicists and Well-Log Analysts
Paper presented at the SPWLA 64th Annual Logging Symposium, June 10–14, 2023
Paper Number: SPWLA-2023-0087
https://doi.org/10.30632/SPWLA-2023-0087
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View Paper titled, AI Guided Interpretation: Automated Quality Assessment for Depth-Matched Images
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Proceedings Papers

Estimation of Matrix Properties from Geochemical Spectroscopy Logs Using Machine Learning

Vasileios-Marios Gkortsas, Paul Craddock, Jeffrey Miles, Harish Datir, Lalitha Venkataramanan
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0103
https://doi.org/10.30632/SPWLA-2022-0103
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View Paper titled, Estimation of Matrix Properties from Geochemical Spectroscopy Logs Using Machine Learning
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Proceedings Papers

Embedding Artificial Intelligence on LWD Images for Automated Drilling Optimization

A. Escobar, J. Kherroubi, D. Quesada, N. Bize-Forest, C. Shrivastava, M. Tarrius, E. Padin
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0106
https://doi.org/10.30632/SPWLA-2022-0106
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View Paper titled, Embedding Artificial Intelligence on LWD Images for Automated Drilling Optimization
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Proceedings Papers

Sequential Multi-Realization Probabilistic Interpretation of Well Logs and Geological Prediction by a Deep-Learning Method

Sergey Alyaev, Adrian Ambrus, Nazanin Jahani, Ahmed H. Elsheikh
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0112
https://doi.org/10.30632/SPWLA-2022-0112
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View Paper titled, Sequential Multi-Realization Probabilistic Interpretation of Well Logs and Geological Prediction by a Deep-Learning Method
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Proceedings Papers

Multi-Level Reservoir Identification with Logs Based on Machine Learning

Gang Luo, Lizhi Xiao, Guangzhi Liao, Sihui Luo, Rongbo Shao, Jun Zhou, Guojun Li, Shengluan Hou, Jiewen Wu
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0114
https://doi.org/10.30632/SPWLA-2022-0114
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View Paper titled, Multi-Level Reservoir Identification with Logs Based on Machine Learning
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Proceedings Papers

Automatic Fracture Segmentation and Detection from Image Logging Using Mask R-CNN

Yubo Liu, Guangzhi Liao, Lizhi Xiao, Zhen Liang, Jiawei Zhang, Xinyu Zhang, Zhe Zhang, Jun Zhou, Guojun Li
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0115
https://doi.org/10.30632/SPWLA-2022-0115
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View Paper titled, Automatic Fracture Segmentation and Detection from Image Logging Using Mask R-CNN
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Proceedings Papers

Impact of Missing Data on Petrophysical Regression-Based Machine Learning Model Performance

Andrew McDonald
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0125
https://doi.org/10.30632/SPWLA-2022-0125
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View Paper titled, Impact of Missing Data on Petrophysical Regression-Based Machine Learning Model Performance
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Proceedings Papers

A Comparative Study for Machine-Learning-Based Methods for Log Prediction

Vanessa Simoes, Hiren Maniar, Tao Zhao, Aria Abubakar, Ridvan Akkurt
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0067
https://doi.org/10.30632/SPWLA-2022-0067
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View Paper titled, A Comparative Study for Machine-Learning-Based Methods for Log Prediction
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Proceedings Papers

Machine Learning for Determining Remaining Oil Saturation Based on C/O Spectral Logging in Multilayer String Cased Well

Fei Qiu, Feng Zhang, Zhiyuan Liu, Guiping Xiao, Qunwei Fang
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0082
https://doi.org/10.30632/SPWLA-2022-0082
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View Paper titled, Machine Learning for Determining Remaining Oil Saturation Based on C/O Spectral Logging in Multilayer String Cased Well
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Proceedings Papers

Automated Corrosion Analysis with Prior Domain Knowledge-Informed Neural Networks

Salma Benslimane, Josselin Kherroubi, Kamaljeet Singh, Jean-Luc Le Calvez, Thomas Berard, Mikhail Lemarenko
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0097
https://doi.org/10.30632/SPWLA-2022-0097
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View Paper titled, Automated Corrosion Analysis with Prior Domain Knowledge-Informed Neural Networks
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Proceedings Papers

Best Image: Deep Learning for Saliency Estimation Using Expert Rankings

Pontus Loviken, Nadege Bize-Forest, Daniel Quesada, Fatma Mahfoudh, Josselin Kherroubi
Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0098
https://doi.org/10.30632/SPWLA-2022-0098
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View Paper titled, Best Image: Deep Learning for Saliency Estimation Using Expert Rankings
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Proceedings Papers

Deep Dielectric-Based Water Saturation in Freshwater and Mixed Salinity Environments

Ping Zhang, Wael Abdallah, Gong Li Wang, Shouxiang Mark Ma
Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0033
https://doi.org/10.30632/SPWLA-2021-0033
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View Paper titled, Deep Dielectric-Based Water Saturation in Freshwater and Mixed Salinity Environments
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Proceedings Papers

Data Quality Considerations for Petrophysical Machine Learning Models

Andrew McDonald
Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0036
https://doi.org/10.30632/SPWLA-2021-0036
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View Paper titled, Data Quality Considerations for Petrophysical Machine Learning Models
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Proceedings Papers

A Deep-Learning Approach for Lithological Classification Using 3D Whole Core CT-Scan Images

Kurdistan Chawshin, Carl Fredrik Berg, Damiano Varagnolo, Olivier Lopez
Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0029
https://doi.org/10.30632/SPWLA-2021-0029
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View Paper titled, A Deep-Learning Approach for Lithological Classification Using 3D Whole Core CT-Scan Images
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Proceedings Papers

Deep-Learning-Based Automated Sedimentary Geometry Characterization from Borehole Images

Marie Lefranc, Zikri Bayraktar, Morten Kristensen, Hedi Driss, Isabelle Le Nir, Philippe Marza, Josselin Kherroubi
Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0082
https://doi.org/10.30632/SPWLA-2021-0082
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View Paper titled, Deep-Learning-Based Automated Sedimentary Geometry Characterization from Borehole Images
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Proceedings Papers

Enhanced Mineral Quantification and Uncertainty Analysis from Downhole Spectroscopy Logs Using Variational Autoencoders

Paul Craddock, Prakhar Srivastava, Harish Datir, David Rose, Tong Zhou, Laurent Mosse, Lalitha Venkataramanan
Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0069
https://doi.org/10.30632/SPWLA-2021-0069
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View Paper titled, Enhanced Mineral Quantification and Uncertainty Analysis from Downhole Spectroscopy Logs Using Variational Autoencoders
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