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The AAPG/Datapages Combined Publications Database
Showing 57,453 Results. Searched 200,293 documents.
A Deep Learning Workflow for Integrated Geological, Petrophysical, and Geomechanical Interpretation
Vanessa Simoes, Atul Katole, Bhuvaneswari Sankaranarayanan, Tao Zhao, Aria Abubakar
Unconventional Resources Technology Conference (URTEC)
.... These differences in sampling rates should be identified, and possibly reduced, during the data exploration before using the data as input for machine learning...
2024
Seismic Facies Segmentation Using Deep Learning; #42286 (2018)
Daniel Chevitarese, Daniela Szwarcman, Reinaldo Mozart D. Silva, Emilio Vital Brazil
Search and Discovery.com
...Seismic Facies Segmentation Using Deep Learning; #42286 (2018) Daniel Chevitarese, Daniela Szwarcman, Reinaldo Mozart D. Silva, Emilio Vital Brazil...
2018
Facies and Rock Type Prediction in a Heterogenous Environment Shale Oil, An Argentina Case Study
Bruno de Ribet, Maximiliano Garcia Torrejon, Luis Vernengo, Juan Moirano
Unconventional Resources Technology Conference (URTEC)
... by anyone other than the author without the written consent of LA URTeC is prohibited. Abstract The strength of Machine Learning-based technology is its...
2023
Application of Data Analytics for Production Optimization in Unconventional Reservoirs: A Critical Review
Srikanta Mishra, Luan Lin
Unconventional Resources Technology Conference (URTEC)
... CJ, 1984. Classification and Regression trees. Monterey, CA: Wadsworth and Brooks/Cole; 1984. 6. Breiman, L. 2001. Random forests, Machine Learning...
2017
Abstract: Machine Learning Predicted S-Sonic Log and Facies Driven Modelling: A Seismic Reservoir Characterization Approach; #91204 (2023)
Shraddha Chatterjee, Santan Kumar, Felipe Melo, Veronica Perez, ChungShen Lee
Search and Discovery.com
...Abstract: Machine Learning Predicted S-Sonic Log and Facies Driven Modelling: A Seismic Reservoir Characterization Approach; #91204 (2023) Shraddha...
2023
An Approach in Caving Recognition by An Integrated Model of Computer Vision and Machine Learning for Any Drilling Environment, #42374 (2019).
Carlos A. Izurieta, Luis A. Rocha, Dan Sui,
Search and Discovery.com
.... This process is done automatically by the algorithm. Selected References Bestagini, P., V. Lipari, and S. Tubaro, 2017, A Machine Learning Approach to Facies...
2019
A NN Supported Seismic Workflow to Create New Exploration Concepts Offshore Bahrain
Search and Discovery.com
N/A
3D seismic image-to-image translation
Xiaolei Song, Muhong Zhou, Lifeng Wang, Rodney Johnston
International Meeting for Applied Geoscience and Energy (IMAGE)
... based on machine learning, using two 3D input datasets of different characteristics and spatial extent. We would like to share our experience of training...
2023
Synthetic Well Logs from Virtual Outcrops: a Database-Driven Approach; #42597 (2025)
G. Bello, J. Howell, A. Hartley, N. Naumann, J. H. Pugsley, K. Aliyuda
Search and Discovery.com
... that integrates machine learning, geodata-science and geostatistics to generates synthetic well logs from architectural-interpretations of virtual outcrops...
2025
Using machine learning to predict total organic content case study: Canning Basin, Western Australia
Russell Menezes
Petroleum Exploration Society of Australia (PESA)
...Using machine learning to predict total organic content case study: Canning Basin, Western Australia Russell Menezes Using machine learning...
2019
CO2 injectivity and storage potential of the Arbuckle Group using supervised machine learning and seismic-constrained reservoir modeling and simulation, Wellington Field, Kansas
Abidin B. Caf, David Lubo-Robles, Matthew J. Pranter, Heather Bedle, Kurt J. Marfurt, Zulfiquar A. Reza
International Meeting for Applied Geoscience and Energy (IMAGE)
...CO2 injectivity and storage potential of the Arbuckle Group using supervised machine learning and seismic-constrained reservoir modeling...
2022
Artificial Intelligence Integration for Optimal Reservoir Data Analysis and Pattern Recognition
Dr. Leon Hamilton, Dr. Marianne Rauch
Unconventional Resources Technology Conference (URTEC)
..., L. Villaseñor-Pineda, C.A. Reyes-Garcia, & O. Mendoza-Montoya (eds). Biosignal processing and classification using computational learning...
2024
Some Machine Learning Applications in Seismic Interpretation; #42270 (2018)
Satinder Chopra, David Lubo-Robles, Kurt J. Marfurt
Search and Discovery.com
...Some Machine Learning Applications in Seismic Interpretation; #42270 (2018) Satinder Chopra, David Lubo-Robles, Kurt J. Marfurt GC Some Machine...
2018
Abstract: Close-the-Loop Log Property Modeling Using Semi-Unsupervised Learning as a Proxy for Facies Classification;
Sher Didi-Ooi, Andrew Derenthal, Michael Pyrcz, Christian Noll
Search and Discovery.com
...Abstract: Close-the-Loop Log Property Modeling Using Semi-Unsupervised Learning as a Proxy for Facies Classification; Sher Didi-Ooi, Andrew Derenthal...
Unknown
Anisotropic Reservoir Characterization Based on Support Vector Machine Technique
Search and Discovery.com
...Anisotropic Reservoir Characterization Based on Support Vector Machine Technique Anisotropic Reservoir Characterization Based on Support Vector...
2013
Seismic Quantitative Analysis for Physical-Based Deep Learning: The Teapot Dome and Niobrara Shale Examples
Nicolas Martin, Maria Donati
Unconventional Resources Technology Conference (URTEC)
... and validation performance for fracture density classification (MATLAB Statistics and Machine Learning Toolbox™) 11 URTeC 2900 The results of applying...
2020
Harnessing AI and Computer Vision for Efficient Geothermal Field Exploration and Prospect Evaluation
Moamen Gasser, Danny Rehg, Marcus Oesterberg, Nathan Meehan
Unconventional Resources Technology Conference (URTEC)
.... and Fawcett, T., 2001. Robust classification for imprecise environments. Machine learning, 42, pp.203-231. Richards, M. & Blackwell, D.D., 2002...
2025
Integrating Geostatistical Modeling with Machine Learning for Production Forecast in Shale Reservoirs: Case Study from Eagle Ford
Alexander Bakay, Jef Caers, Tapan Mukerji, Yan Dong, Arnulfo Briceno, Devery Neumann
Unconventional Resources Technology Conference (URTEC)
.... We account for local effects by using cokriging to merge total production from nearby wells with the production from machine learning-based...
2019
Optimizing Completions Strategies Using Low-Cost Data Learning
Antoine Jacques, Clement Daguet-Schott, Anthony Billat, Benoit Brouard
Unconventional Resources Technology Conference (URTEC)
... relations based on only two wells usually is proscribed. Instead, machine-learning models should be deployed to find relations between facies...
2022
Attention-based self-calibrated convolution neural network for efficient facies classification
Motaz Alfarraj
International Meeting for Applied Geoscience and Energy (IMAGE)
... Association of Petroleum Geologists REFERENCES Alaudah, Y., P. Michalowicz, M. Alfarraj, and G. AlRegib, 2019, A machine-learning benchmark for facies...
2024
Do We Really Need Deep Learning? A Study on Play Identification using SEM Images
Hanyan Zhang, Max T. Kasumov, Deepak Devegowda, Mark E. Curtis
Unconventional Resources Technology Conference (URTEC)
... to identify vuggy facies using borehole-resistivity images from a well in the Arbuckle Group in Kansas. Core image classification is also another...
2021
Seismic Facies Segmentation Using Deep Learning
Search and Discovery.com
N/A
Combining machine learning and geostatistics for scenario models of the Handil Oilfield
Aditya Suardiputra, Julfree Slanturi, Andar Trianto, Colin Daly, Joko Sosiawan Trikukuh
International Meeting for Applied Geoscience and Energy (IMAGE)
... facies codes and zones is very time consuming and is the reason that PHM wanted to investigate the machine learning approach. However, any potential new...
2022
Depositional Facies Identification in Wireline Log Patterns Using 1D Convolutional Neural Network (CNN) Deep Learning Algorithms
Galatio Giovani Prabowo, Muhammad Fahmi Ramdani, Abiyyu Daffa Revanzha, Brian Muara Sianturi, Natalia Angel Momongan
Indonesian Petroleum Association
...Depositional Facies Identification in Wireline Log Patterns Using 1D Convolutional Neural Network (CNN) Deep Learning Algorithms Galatio Giovani...
2024
Abstract: Integrated Reservoir Characterisation with Three Dimensional Modeling in Thin Bed Low Resistivity Natural Gas Exploration
Yen Jun Lim, Shyh Zung Lo
Geological Society of Malaysia (GSM)
... neural network facies classification, machine learning well correlation, and automated fault interpretation. With the final geological model produced from...
2017