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Proceedings Papers

Advancing Online Verification and Validation in Complex Multi-Providers Drilling Automation Systems

R. Mihai, M. Edwards, J. de Wardt, S. Dharmaselvan, J. Carney
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220774-MS
https://doi.org/10.2118/220774-MS
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Proceedings Papers

Improving Reliability of Seismic Stratigraphy Prediction: Integration of Uncertainty Quantification in Attention Mechanism Neural Network

C. T. Ang, A. H. Elsheikh
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220708-MS
https://doi.org/10.2118/220708-MS
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View Paper titled, Improving Reliability of Seismic Stratigraphy Prediction: Integration of Uncertainty Quantification in Attention Mechanism Neural Network
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Proceedings Papers

Gas Flow Rate Estimation with Artificial Intelligence: Bridging Reality Through Computer Vision and Machine Learning

V. Santhalingam, A. Abinader, V. Vesselinov, D. Krishna
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220903-MS
https://doi.org/10.2118/220903-MS
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View Paper titled, Gas Flow Rate Estimation with Artificial Intelligence: Bridging Reality Through Computer Vision and Machine Learning
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Proceedings Papers

Real-Time Artificial Intelligence-Enhanced Machine Learning Technique for Accurate Drilling Parameter Prediction and Optimization

Behzad Elahifar
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220914-MS
https://doi.org/10.2118/220914-MS
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View Paper titled, Real-Time Artificial Intelligence-Enhanced Machine Learning Technique for Accurate Drilling Parameter Prediction and Optimization
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Proceedings Papers

Two-Step Process to Quantify Effects of Geological and Completion Parameters on Unconventional Well Performance

M. Kelkar, A. Itteyra
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220966-MS
https://doi.org/10.2118/220966-MS
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View Paper titled, Two-Step Process to Quantify Effects of Geological and Completion Parameters on Unconventional Well Performance
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Proceedings Papers

Field Application of Image Analysis Models to Measure the Drill Cuttings Recovery Rate

Shekhar Gosavi, John Gilroy, Francois Ruel, Calvin Holt
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220985-MS
https://doi.org/10.2118/220985-MS
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Proceedings Papers

Transfer Learning in Subsurface Flow Surrogate Model with Physics-Guided Neural Network

H. B. Cheng, J. H. Qiao, Y. C. Wei, S. C. Li, P. Zeng, H. B. Yu
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220978-MS
https://doi.org/10.2118/220978-MS
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Proceedings Papers

Demonstration of Seamless Interoperability for Automatic Drilling Management in a Multi-Vendor Context

E. Cayeux, B. Daireaux, K. K. Olsen, K. Antosz, M. Dahle Johansen, H. S. Næsgaard, L. Hoarau
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220987-MS
https://doi.org/10.2118/220987-MS
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View Paper titled, Demonstration of Seamless Interoperability for Automatic Drilling Management in a Multi-Vendor Context
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Proceedings Papers

Refined Diffusion Posterior Sampling for Seismic Denoising and Interpolation

Tung Nguyen, Tung Pham, Minh Nguyen, Tuan Nguyen
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221000-MS
https://doi.org/10.2118/221000-MS
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View Paper titled, Refined Diffusion Posterior Sampling for Seismic Denoising and Interpolation
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Proceedings Papers

Estimating Rock Typing in Uncored Wells Using Machine Learning Techniques for Brazilian Pre-Salt Carbonate Reservoir

Mohammad Saad Allahham, Vinicius Eduardo Botechia, Alessandra Davólio, Denis José Schiozer
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220992-MS
https://doi.org/10.2118/220992-MS
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View Paper titled, Estimating Rock Typing in Uncored Wells Using Machine Learning Techniques for Brazilian Pre-Salt Carbonate Reservoir
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Proceedings Papers

Inertial Effect of Drill Pipe Friction Trend and Early Warning of Stuck Pipe

Muchen Liu, Xianzhi Song, Zhaopeng Zhu, Gensheng Li, Hao Xiao, Li Fu, Tao Pan, Xintong Li, Yanlong Yang
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220991-MS
https://doi.org/10.2118/220991-MS
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View Paper titled, Inertial Effect of Drill Pipe Friction Trend and Early Warning of Stuck Pipe
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Proceedings Papers

Video-Powered AI Solutions for Active Monitoring and Safety Improvement in Offshore Environments: The BRAM Offshore and Altave Case

Wilson Augusto Borges Leal Neto, José Henrique Mouallem Gonçalves, Marco Duplan
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221026-MS
https://doi.org/10.2118/221026-MS
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View Paper titled, Video-Powered AI Solutions for Active Monitoring and Safety Improvement in Offshore Environments: The BRAM Offshore and Altave Case
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Proceedings Papers

Leveraging Large Language Models for Cost Management and Supply Chain Optimization

Maryam Shahini, Carina Yu Wang, Marc A. Roeder, Sanjay Pethe, Sarah W. Coffman, Preston Howard, Bo Hu, Hannah N. Wasserman, Joshua Arnwine
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221022-MS
https://doi.org/10.2118/221022-MS
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View Paper titled, Leveraging Large Language Models for Cost Management and Supply Chain Optimization
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Proceedings Papers

Hyperspectral Image Segmentation of Methane Plumes Using Large Machine Learning Model

Yuan Zi, Jiefu Chen, Xuqing Wu, Lei Fan, Zhu Han
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221013-MS
https://doi.org/10.2118/221013-MS
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View Paper titled, Hyperspectral Image Segmentation of Methane Plumes Using Large Machine Learning Model
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Proceedings Papers

Enhancing Reservoir Model History Matching with AI Surrogate and Ensemble Iterative Algorithms

Khaled J. Hammad, Ali A. Al-Turki, Sharizan B. Sudirman, Zaid A. Sawlan
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221028-MS
https://doi.org/10.2118/221028-MS
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View Paper titled, Enhancing Reservoir Model History Matching with AI Surrogate and Ensemble Iterative Algorithms
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Proceedings Papers

ConGANergy: A Framework for Engineering Data Augmentation with Application to Solid Particle Erosion

Jun Zhang, Yijie Li, Weiping Pei, Siamack Shirazi
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220954-MS
https://doi.org/10.2118/220954-MS
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View Paper titled, ConGANergy: A Framework for Engineering Data Augmentation with Application to Solid Particle Erosion
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Proceedings Papers

Developing a Novel Machine Learning-Based Petrophysical Rock Typing (PRT) Classification: Applied on Heterogenous Carbonate Reservoirs

Mohammed A. Abbas, Watheq J. Al-Mudhafar, Ahmed Alsubaih, Ali Al-Maliki, Ali Al-Sukaini
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220964-MS
https://doi.org/10.2118/220964-MS
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View Paper titled, Developing a Novel Machine Learning-Based Petrophysical Rock Typing (PRT) Classification: Applied on Heterogenous Carbonate Reservoirs
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Proceedings Papers

Chasing Remaining Potential in Mature East Nile Delta Development Blocks Using Machine Learning

I. Yahia, M. M. Abdelrahman, S. Mohammed, M. Abd El-Gwad
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221058-MS
https://doi.org/10.2118/221058-MS
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View Paper titled, Chasing Remaining Potential in Mature East Nile Delta Development Blocks Using Machine Learning
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Proceedings Papers

Physics Informed Machine Learning for Reservoir Connectivity Identification and Production Forecastingfor CO2-EOR

Masahiro Nagao, Akhil Datta-Gupta
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221057-MS
https://doi.org/10.2118/221057-MS
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View Paper titled, Physics Informed Machine Learning for Reservoir Connectivity Identification and Production Forecastingfor CO2-EOR
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Proceedings Papers

Transfer Learning for Variable Well Locations and Permeability Distributions in Physics-Aware Deep Learning Reservoir Simulation Proxy Models

G. Kompantsev
Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-223505-STU
https://doi.org/10.2118/223505-STU
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View Paper titled, Transfer Learning for Variable Well Locations and Permeability Distributions in Physics-Aware Deep Learning Reservoir Simulation Proxy Models
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