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The AAPG/Datapages Combined Publications Database
Showing 55,891 Results. Searched 195,354 documents.
Application of Machine Learning to Facies Classification of Carbonate Core Images
Sharinia Kanagandran
Southeast Asia Petroleum Exploration Society (SEAPEX)
...Application of Machine Learning to Facies Classification of Carbonate Core Images Sharinia Kanagandran 2019 36 In recent years, the use of machine...
2019
ABSTRACT: Application of Novel Machine Learning Algorithms for Facies Classification; #90115 (2010)
Olivier Malinur and Cyril U. Edem
Search and Discovery.com
...ABSTRACT: Application of Novel Machine Learning Algorithms for Facies Classification; #90115 (2010) Olivier Malinur and Cyril U. Edem Application...
2010
ABSTRACT: Integrated Machine Learning Unsupervised Log Facies and Seismic Facies Workflows to delineate stratigraphic traps for field developments
Stanley Wharton
Geological Society of Trinidad & Tobago
...ABSTRACT: Integrated Machine Learning Unsupervised Log Facies and Seismic Facies Workflows to delineate stratigraphic traps for field developments...
2022
Abstract: FaciesNet: Machine Learning Applications for Facies Classification in Well Logs;
Chayawan Jaikla, Pandu Devarakota, Neal Auchter, Mohamed Sidahmed, Irene Espejo
Search and Discovery.com
... data-driven machine learning algorithms using well logs alone to classify facies by solving multiclass classification problem. Classifying facies...
Unknown
Machine learning facies identifications applied to the Late Devonian Duvernay Formation, Western Canadian Sedimentary Basin
Search and Discovery.com
N/A
Facies Classification Based on Well Logs by Using an Convolutional Neural Network
Search and Discovery.com
N/A
Minimizing Geothermal Exploration Costs Using Machine Learning As A Tool To Drive Deep Geothermal Exploration
Search and Discovery.com
N/A
Abstract: Frequency-Based Facies Recognition Using Unsupervised Machine Learning; #91204 (2023)
Thamer Almahamidh, Sihai Zhang
Search and Discovery.com
...Abstract: Frequency-Based Facies Recognition Using Unsupervised Machine Learning; #91204 (2023) Thamer Almahamidh, Sihai Zhang Frequency-Based Facies...
2023
Reservoir Insights Enabled by Machine Learning Technology: A Supervised Machine Learning Method for Probabilistic Rock Type Prediction; #42465 (2021)
Bruno de Ribet, Gerardo Gonzalez
Search and Discovery.com
... Emerson Agenda Introduction Critical Aspects of Reservoir Characterization Benefits of Machine Learning Rock Type Classification Case Study Conclusion...
2021
Machine-Learning Assisted Reservoir Property Prediction: A Case Study From the Triassic Snadd and Kobbe Formations, Norwegian Barents Sea
Search and Discovery.com
N/A
Paleokarst Reservoir Seismic Facies Classification Using Frequency Spectral Decomposition, Machine Learning and Electrofacies Constrained Approach
Search and Discovery.com
N/A
Geological Facies Prediction Using Computed Tomography in a Machine Learning and Deep Learning Environment
Uchenna Odi, Thomas Nguyen
Unconventional Resources Technology Conference (URTEC)
... for statistical feature detection in whole-core CT volumes. Facies classification, using machine learning, of wireline datasets has recently received a lot...
2018
Abstract: Seismic Attribute Optimization for Deep-Water Facies Classification in SOM Analysis;
Karelia La Marca Molina, Heather Bedle
Search and Discovery.com
... to investigate the impact of a user-controlled selection of attributes to perform SOM for facies classification versus a machine- derived result. Using...
Unknown
A Bi-Directional Long Short-Term Memory Neural Network for Geologic-Facies Classification
Search and Discovery.com
N/A
Evaluation of Machine Learning Methods for Automatic Facies Classification As a Tool for Determining Sandstone and Limestone Reservoir
Irvan Rahadian Putra, M. Irsyad Hibatullah, Christopher Salim, Firman Syaifuddin
Indonesian Petroleum Association
... of lithology facies from well log data is one of them. Using the machine learning concept, lithofacies classification activities using well logs can be done...
2019
Towards a Basin-Scale Lithofacies Model - An Integrated Machine Learning Approach Using Well Logs and Core for the Permian Basin
Search and Discovery.com
N/A
The Value of Integrating Machine Learning for Enhanced Understanding of Petroleum Systems
Search and Discovery.com
N/A
Abstract: Automated Data Driven 3D Facies Modelling for Reservoir Simulation using Machine Learning Algorithms; #91204 (2023)
Salma Alsinan, Hamad Alghenaim
Search and Discovery.com
...Abstract: Automated Data Driven 3D Facies Modelling for Reservoir Simulation using Machine Learning Algorithms; #91204 (2023) Salma Alsinan, Hamad...
2023
Wireline Log Data Conditioning to Improve Machine Learning Based Facies Identification Across the Well
Search and Discovery.com
N/A
Application of Artificial Intelligence for Depositional Facies Recognition - Permian Basin
Randall Miller, Skip Rhodes, Deepak Khosla, Fernando Nino
Unconventional Resources Technology Conference (URTEC)
...-guided machine learning has been used to classify depositional facies from core photographs of the Wolfcamp, Bone Spring and Spraberry formations...
2019
Facies classification with different machine learning algorithm An efficient artificial intelligence technique for improved classification
Partha Pratim Mandal, Reza Rezaee
Petroleum Exploration Society of Australia (PESA)
...Facies classification with different machine learning algorithm An efficient artificial intelligence technique for improved classification Partha...
2019
Abstract: A Novel Approach Combining Machine Learning & Classical Modeling Techniques to Characterize The Clastic Reservoirs In the Northern Area of Greater Burgan Field; #91204 (2023)
Reham Al-Houti, Jean-Michel Filak
Search and Discovery.com
... Generating geological models by using different methods where machine learning is combined with classical modelling techniques, has already been established...
2023
Abstract: Potential Applications of Deep Learning to Geosciences; #90306 (2017)
Pedro Mario Cruz e Silva
Search and Discovery.com
... revolution. Deep Learning (DL) is the Machine Learning (ML) technique enabling breakthroughs in several industrial, business, and scientific workflows...
2017
Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential
Kellen L. Gunderson, Zhao Zhang, Barton Payne, Shuxing Cheng, Ziyu Jiang, and Atlas Wang
AAPG Bulletin
... or effective stress. Because of this, considerable effort has gone into improving the subsurface interpretation of salt bodies using machine learning approaches...
2022