1-20 of 81
Neural networks
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Dynamic Response Modeling in Underground Hydrogen Storage Using a Fourier-Integrated Hybrid Neural Framework

Available to Purchase

J. Omeke, S. Misra, A. Retnanto
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24670-MS
https://doi.org/10.2523/IPTC-24670-MS
Add To Cart
View Paper titled, Dynamic Response Modeling in Underground Hydrogen Storage Using a Fourier-Integrated Hybrid Neural Framework
Open the PDF for Dynamic Response Modeling in Underground Hydrogen Storage Using a Fourier-Integrated Hybrid Neural Framework in another window
Add to Citation Manager for Dynamic Response Modeling in Underground Hydrogen Storage Using a Fourier-Integrated Hybrid Neural Framework
Proceedings Papers

Monetising the Forgotten Oil With Machine Learning Assisted Rock Typing In A Giant Brown Field

Available to Purchase

I. M. Gazali, N. Ramly, A. Zakaria, W. Wan Mohamed Zin, B. Nadarajan
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24747-MS
https://doi.org/10.2523/IPTC-24747-MS
Add To Cart
View Paper titled, Monetising the Forgotten Oil With Machine Learning Assisted Rock Typing In A Giant Brown Field
Open the PDF for Monetising the Forgotten Oil With Machine Learning Assisted Rock Typing In A Giant Brown Field in another window
Add to Citation Manager for Monetising the Forgotten Oil With Machine Learning Assisted Rock Typing In A Giant Brown Field
Proceedings Papers

Trapped and Movable CO 2 in Geologic Carbon Storage: Deep-Learning Forecasting and Generalization Study

Available to Purchase

G. Ren, O. Talabi, V. Kumar, S. Misra, U. Odi, A. Silver, A. Gupta
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24804-MS
https://doi.org/10.2523/IPTC-24804-MS
Add To Cart
View Paper titled, Trapped and Movable CO 2 in Geologic Carbon Storage: Deep-Learning Forecasting and Generalization Study
Open the PDF for Trapped and Movable CO 2 in Geologic Carbon Storage: Deep-Learning Forecasting and Generalization Study in another window
Add to Citation Manager for Trapped and Movable CO 2 in Geologic Carbon Storage: Deep-Learning Forecasting and Generalization Study
Proceedings Papers

A New Depth Prediction Technique Based on Particle Swarm Optimization Algorithm with Multiple Main Controlling Factors Constraints

Available to Purchase

Zhimeng Gu, Haojie Liu, Min Gong, Yi Han
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24820-MS
https://doi.org/10.2523/IPTC-24820-MS
Add To Cart
View Paper titled, A New Depth Prediction Technique Based on Particle Swarm Optimization Algorithm with Multiple Main Controlling Factors Constraints
Open the PDF for A New Depth Prediction Technique Based on Particle Swarm Optimization Algorithm with Multiple Main Controlling Factors Constraints in another window
Add to Citation Manager for A New Depth Prediction Technique Based on Particle Swarm Optimization Algorithm with Multiple Main Controlling Factors Constraints
Proceedings Papers

Efficient Surrogate Modeling for Subsurface Flow Simulation Using Multi-Fidelity Data with Physical Constraints

Available to Purchase

Jiawei Cui, Wenyue Sun, Hangyu Li, Shuyang Liu
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24822-MS
https://doi.org/10.2523/IPTC-24822-MS
Add To Cart
View Paper titled, Efficient Surrogate Modeling for Subsurface Flow Simulation Using Multi-Fidelity Data with Physical Constraints
Open the PDF for Efficient Surrogate Modeling for Subsurface Flow Simulation Using Multi-Fidelity Data with Physical Constraints in another window
Add to Citation Manager for Efficient Surrogate Modeling for Subsurface Flow Simulation Using Multi-Fidelity Data with Physical Constraints
Proceedings Papers

Bayesian Neural Network Method for Intelligent Drilling Pattern Discovery using Block Geological Information as Prior Knowledge

Available to Purchase

Zhi Yan, Xianzhi Song, Zhaopeng Zhu, Shijie Xiao, Detao Zhou, Tao Pan, Muchen Liu, Qifeng Li
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24923-MS
https://doi.org/10.2523/IPTC-24923-MS
Add To Cart
View Paper titled, Bayesian Neural Network Method for Intelligent Drilling Pattern Discovery using Block Geological Information as Prior Knowledge
Open the PDF for Bayesian Neural Network Method for Intelligent Drilling Pattern Discovery using Block Geological Information as Prior Knowledge in another window
Add to Citation Manager for Bayesian Neural Network Method for Intelligent Drilling Pattern Discovery using Block Geological Information as Prior Knowledge
Proceedings Papers

Full Borehole Image Data Computation Using GAN Based Model

Available to Purchase

Y. Liu, J. Zhou, J. Zhang, P. Li, Y. Zhou
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24957-EA
https://doi.org/10.2523/IPTC-24957-EA
Add To Cart
View Paper titled, Full Borehole Image Data Computation Using GAN Based Model
Open the PDF for Full Borehole Image Data Computation Using GAN Based Model in another window
Add to Citation Manager for Full Borehole Image Data Computation Using GAN Based Model
Proceedings Papers

Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development

Available to Purchase

Dancheng Zhu, Lian Wang, Jianhua Qu, Liang Zhang, Rui Deng, Feng Jing
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24845-MS
https://doi.org/10.2523/IPTC-24845-MS
Add To Cart
View Paper titled, Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development
Open the PDF for Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development in another window
Add to Citation Manager for Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development
Proceedings Papers

Fine Geological Modeling of Fractured Reservoir in Dual-Medium Buried Hill Based on BP Neural Network and Horizontal Well Parameter Correction

Available to Purchase

Zuobin Lv, Jianbo Chen, Dong Liu, Huan Liu, Jianfang Song, Yuanzhe Lv
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24858-MS
https://doi.org/10.2523/IPTC-24858-MS
Add To Cart
View Paper titled, Fine Geological Modeling of Fractured Reservoir in Dual-Medium Buried Hill Based on BP Neural Network and Horizontal Well Parameter Correction
Open the PDF for Fine Geological Modeling of Fractured Reservoir in Dual-Medium Buried Hill Based on BP Neural Network and Horizontal Well Parameter Correction in another window
Add to Citation Manager for Fine Geological Modeling of Fractured Reservoir in Dual-Medium Buried Hill Based on BP Neural Network and Horizontal Well Parameter Correction
Proceedings Papers

Fast AI Fault Prediction Using Sparsely Interpreted Labels

Available to Purchase

Wei Xiong, Lei Li, Jingbin Cui, Xiaofang Zhang, Lihua Dai, Chen Xu
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24864-EA
https://doi.org/10.2523/IPTC-24864-EA
Add To Cart
View Paper titled, Fast AI Fault Prediction Using Sparsely Interpreted Labels
Open the PDF for Fast AI Fault Prediction Using Sparsely Interpreted Labels in another window
Add to Citation Manager for Fast AI Fault Prediction Using Sparsely Interpreted Labels
Proceedings Papers

Abnormal Events Detection During Drilling Based on Knowledge Embedded Real Time Data Analysis

Available to Purchase

X. Y. Shi, Y. Ji, M. Cui, W. H. Guo, Y. M. Tian, D. Wu, L. Z. Jing, X. Y. Yang
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24870-MS
https://doi.org/10.2523/IPTC-24870-MS
Add To Cart
View Paper titled, Abnormal Events Detection During Drilling Based on Knowledge Embedded Real Time Data Analysis
Open the PDF for Abnormal Events Detection During Drilling Based on Knowledge Embedded Real Time Data Analysis in another window
Add to Citation Manager for Abnormal Events Detection During Drilling Based on Knowledge Embedded Real Time Data Analysis
Proceedings Papers

A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory

Available to Purchase

Z. Lyu, F. Wei, Y. Pan, L. Li, C. Song, G. Song, Z. Zhu, X. Song
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24898-MS
https://doi.org/10.2523/IPTC-24898-MS
Add To Cart
View Paper titled, A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory
Open the PDF for A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory in another window
Add to Citation Manager for A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory
Proceedings Papers

Fluid-Modulus Inversion for Gas Prediction in the Deep-Water Area of Northern South China Sea

Available to Purchase

Leyi Xu, Xumin Liu, Weiwei Zhang
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25013-EA
https://doi.org/10.2523/IPTC-25013-EA
Add To Cart
View Paper titled, Fluid-Modulus Inversion for Gas Prediction in the Deep-Water Area of Northern South China Sea
Open the PDF for Fluid-Modulus Inversion for Gas Prediction in the Deep-Water Area of Northern South China Sea in another window
Add to Citation Manager for Fluid-Modulus Inversion for Gas Prediction in the Deep-Water Area of Northern South China Sea
Proceedings Papers

Enhance the Vertical Resolution of Conventional Well Logs Using Auto-Encoder

Available to Purchase

Juntao Ma, Yansong Huang, Lei Kang, Qing Wang, Lingdan Xia, Yingfei Hu
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25025-EA
https://doi.org/10.2523/IPTC-25025-EA
Add To Cart
View Paper titled, Enhance the Vertical Resolution of Conventional Well Logs Using Auto-Encoder
Open the PDF for Enhance the Vertical Resolution of Conventional Well Logs Using Auto-Encoder in another window
Add to Citation Manager for Enhance the Vertical Resolution of Conventional Well Logs Using Auto-Encoder
Proceedings Papers

Multiplex Visibility Graphs-Based Hybrid Deep Learning Method for Recognizing Pipeline Operation Conditions Using Operating Data

Available to Purchase

L. Zhang, P. Wang, L. Liu, J. Liu, Z. Chen, W. Dong, C. Li, L. Fan
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25065-MS
https://doi.org/10.2523/IPTC-25065-MS
Add To Cart
View Paper titled, Multiplex Visibility Graphs-Based Hybrid Deep Learning Method for Recognizing Pipeline Operation Conditions Using Operating Data
Open the PDF for Multiplex Visibility Graphs-Based Hybrid Deep Learning Method for Recognizing Pipeline Operation Conditions Using Operating Data in another window
Add to Citation Manager for Multiplex Visibility Graphs-Based Hybrid Deep Learning Method for Recognizing Pipeline Operation Conditions Using Operating Data
Proceedings Papers

AI Automation in Civil Infrastructure Asset Management

Available to Purchase

S. Loh, A. Gautam
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25080-MS
https://doi.org/10.2523/IPTC-25080-MS
Add To Cart
View Paper titled, AI Automation in Civil Infrastructure Asset Management
Open the PDF for AI Automation in Civil Infrastructure Asset Management in another window
Add to Citation Manager for AI Automation in Civil Infrastructure Asset Management
Proceedings Papers

Deep Learning Applications for Well Log Correlation

Available to Purchase

J. Fu, R. Li, T. Gao, P. Zhang, C. Wang
Paper presented at the International Petroleum Technology Conference, February 12, 2024
Paper Number: IPTC-24062-MS
https://doi.org/10.2523/IPTC-24062-MS
Add To Cart
View Paper titled, Deep Learning Applications for Well Log Correlation
Open the PDF for Deep Learning Applications for Well Log Correlation in another window
Add to Citation Manager for Deep Learning Applications for Well Log Correlation
Proceedings Papers

Deep-Learning Based LSTM for Production Data Analysis of Hydraulically Fractured Wells

Available to Purchase

Fengyuan Zhang, Minghao Xu, Chao Deng, Wei Zhang, Chuncheng Liu, Zhenhua Rui, Hamid Emami-Meybodi
Paper presented at the International Petroleum Technology Conference, February 12, 2024
Paper Number: IPTC-24126-MS
https://doi.org/10.2523/IPTC-24126-MS
Add To Cart
View Paper titled, Deep-Learning Based LSTM for Production Data Analysis of Hydraulically Fractured Wells
Open the PDF for Deep-Learning Based LSTM for Production Data Analysis of Hydraulically Fractured Wells in another window
Add to Citation Manager for Deep-Learning Based LSTM for Production Data Analysis of Hydraulically Fractured Wells
Proceedings Papers

Deep Learning Real-Time Bit-Wear Model Approves to be Robust and Transferable in Hard Drilling Applications

Available to Purchase

Guodong David Zhan, Abdulwahab Aljohar, Yazeed Qahtani, Xu Huang, Trieu Phat Luu, Ted Furlong, John Bomidi
Paper presented at the International Petroleum Technology Conference, February 12, 2024
Paper Number: IPTC-24135-EA
https://doi.org/10.2523/IPTC-24135-EA
Add To Cart
View Paper titled, Deep Learning Real-Time Bit-Wear Model Approves to be Robust and Transferable in Hard Drilling Applications
Open the PDF for Deep Learning Real-Time Bit-Wear Model Approves to be Robust and Transferable in Hard Drilling Applications in another window
Add to Citation Manager for Deep Learning Real-Time Bit-Wear Model Approves to be Robust and Transferable in Hard Drilling Applications
Proceedings Papers

Development of Two Robust Data-Driven Models Using Machine Learning and Artificial Neural Network Methods to Predict Wells Fluid Rate in a Challenging Offshore Brown Field

Available to Purchase

M. E. Eldessouky, A. M. Darwish, I. I. Mohamed, T. H. Abdelhalem, A. K. Khalil
Paper presented at the International Petroleum Technology Conference, February 12, 2024
Paper Number: IPTC-23669-MS
https://doi.org/10.2523/IPTC-23669-MS
Add To Cart
View Paper titled, Development of Two Robust Data-Driven Models Using Machine Learning and Artificial Neural Network Methods to Predict Wells Fluid Rate in a Challenging Offshore Brown Field
Open the PDF for Development of Two Robust Data-Driven Models Using Machine Learning and Artificial Neural Network Methods to Predict Wells Fluid Rate in a Challenging Offshore Brown Field in another window
Add to Citation Manager for Development of Two Robust Data-Driven Models Using Machine Learning and Artificial Neural Network Methods to Predict Wells Fluid Rate in a Challenging Offshore Brown Field

Product(s) added to cart

Go to Cart Continue Browsing
Close Modal