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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,673 documents.
Permeability Estimation Using a Neural Network: A Case Study from the Roberts Unit, Wasson Field, Yoakum County, Texas
Debra A. Osborne
West Texas Geological Society
... an alternative method for determining reservoir permeability. Neural networks estimate permeability by learning the relationships between many reservoir...
1992
Case Study of a Cadomin Gas Reservoir (Leland) in the Deep Basin: From Deterministic Inversion to Neural Network Analysis, #10732 (2015).
Carmen Dumitrescu, Fred Mayer
Search and Discovery.com
... neural networks to establish the nonlinear relationships between seismic attributes and reservoir properties at well locations, 3. validate results...
2015
An Introduction to Deep Learning: Part II
Lasse Amundsen, Hongbo Zhou, Martin Landrø
GEO ExPro Magazine
... on. With these computing breakthroughs, neural networks were revisited, and they could be made huge. ImageNet Large Scale Visual Recognition...
2017
Kronecker neural networks for the win: Overcoming spectral bias for PINN-based wavefield computation
Umair bin Waheed
International Meeting for Applied Geoscience and Energy (IMAGE)
...Kronecker neural networks for the win: Overcoming spectral bias for PINN-based wavefield computation Umair bin Waheed Kronecker neural networks...
2022
ABSTRACT: Resistivity Modeling and Neural Network Synthetics—Powerful New Exploration and Development Tools
Steven M. Goolsby, Jeff S. Arbogast
Kansas Geological Society
... solution for multiwell applications. If porosity and permeability information is inaccurate, incomplete, or simply not available, neural networks can...
1999
Abstract: Deep Learning Inversion on Seismic Cubes; #91204 (2023)
Aleksandr Koriagin, Alexey Kozhevin, Stepan Goriachev, Roman Khudorozhkov
Search and Discovery.com
... to the latter, the existing literature describes how neural networks can be used for inversion on small patches of traces/seismic slides. In this work we...
2023
Generating Missing Logs -- Techniques and Pitfalls, by Michael Holmes, Dominic Holmes, and Antony Holmes, #40107 (2003).
Search and Discovery.com
2003
Convolution neural networks fault interpretation in the Brazilian presalt
Hugo Garcia, Edimar Perico, Ana Moliterno, Alexandre Kolisnyk, Michael Lowsby
International Meeting for Applied Geoscience and Energy (IMAGE)
...Convolution neural networks fault interpretation in the Brazilian presalt Hugo Garcia, Edimar Perico, Ana Moliterno, Alexandre Kolisnyk, Michael...
2024
Abstract: Analysis of Fault Seals Using Complex Seismic Trace Attributes Calibrated to Artificial Neural Networks, by M. L. Shoemaker, C. Walker, and B. Brennan; #90090 (2009).
Search and Discovery.com
2009
Abstract: Risk Reduction through Neural Networks Chimney Analysis: Frontier Exploration in East African Rift Basin, by Baranova, Valentina; Mustaqeem, Azer; Karaja, Francis; Mburu, Danson; #90163 (2013)
Search and Discovery.com
2013
Application of Seismic Stratigraphy, Artificial Neural Networks and 3D Seismic Geomorphology to Improve Reservoir Understanding of Lower Goru Sequence in Central Indus Basin, Pakistan
Search and Discovery.com
N/A
Transfer learning seismic and GPR diffraction separation with a convolutional neural network
Alexander Bauer, Jan Walda, Dirk Gajewski
International Meeting for Applied Geoscience and Energy (IMAGE)
... application. Numerous applications in the recent past have proven that neural networks can be a powerful tool for subsurface data analysis...
2022
ABSTRACT: Neural Network Analyses of Seismic Attributes and Facies at the Stratton Field, South Texas, by Shawn M. Len and Wayne D. Pennington; #90906(2001)
Search and Discovery.com
2001
Abstract: Seismic Attribute Analysis and the use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional Reservoirs; #90227 (2015)
Deborah Sacrey
Search and Discovery.com
...Abstract: Seismic Attribute Analysis and the use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional...
2015
Abstract: Seismic Attribute Analysis and the Use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional Reservoirs; #90239 (2015)
Deborah Sacrey
Search and Discovery.com
...Abstract: Seismic Attribute Analysis and the Use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional...
2015
Abstract: Seismic Attribute Analysis and the Use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional Reservoirs; #90245 (2016)
Deborah Sacrey
Search and Discovery.com
...Abstract: Seismic Attribute Analysis and the Use of Unsupervised Neural Networks and Principal Component Analysis in Unconventional and Conventional...
2016
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
... prospect development tool. This presentation introduces a method based on an association of neural networks to resolve reservoir facies heterogeneity...
2021
Integrating Probabilistic Neural Networks and Generalized Boosted Regression Modelling for Lithofacies Classifications and Formation Permeability Estimation
Search and Discovery.com
N/A
Neural Network Application on Selection of the Best Correlation of Multiphase Flow in Pipes
Riko Abdillah, Tutuka Ariadji
Indonesian Petroleum Association
..., Mizutani, Eiji, 1997. Neuro-Fuzzy and Soft Computing, New Jersey. Lawrence, J., 1994. Introduction to Neural Networks, California Scientific...
2003
ABSTRACT: Determining Lithofacies and Quantitative Mineralogy of Sedimentary Rocks from Bulk Elemental Geochemistry: A Neural Network Approach, by Smith, Christopher N.; Assous, Said; #90142 (2012)
Search and Discovery.com
2012
Increasing signal-to-noise ratio of borehole image logs using convolutional neural networks
Mustafa A. Al Ibrahim, Mokhles M. Mezghani
International Meeting for Applied Geoscience and Energy (IMAGE)
...Increasing signal-to-noise ratio of borehole image logs using convolutional neural networks Mustafa A. Al Ibrahim, Mokhles M. Mezghani Increasing...
2022
Porosity Prediction Using Multiattribute Transforms and Probabilistic Neural Networks Analysis from Limestone Formation in BSJ Gas Field, Central Sulawesi, Indonesia
Ikawati Basri, Sabrianto Aswad, Suryana, Ikhsan Novryan Priatama
Indonesian Petroleum Association
...Porosity Prediction Using Multiattribute Transforms and Probabilistic Neural Networks Analysis from Limestone Formation in BSJ Gas Field, Central...
2018
Porosity and Permeability Estimation using Neural Network Approach from Well Log Data, #41276 (2014)
Akhilesh K. Verma, Burns A. Cheadle, Aurobinda Routray, William K. Mohanty, Lalu Mansinha,
Search and Discovery.com
... of Electrical Engineering, Indian Institute of Technology, Kharagpur, India 2 Abstract In recent years, artificial intelligence techniques, and neural networks...
2014
Demystifying Data-Driven Neural Networks for Multivariate Production Analysis
Ayush Rastogi, Karn Agarwal, Ely Lolon, Mike Mayerhofer, Oladapo Oduba
Unconventional Resources Technology Conference (URTEC)
...Demystifying Data-Driven Neural Networks for Multivariate Production Analysis Ayush Rastogi, Karn Agarwal, Ely Lolon, Mike Mayerhofer, Oladapo Oduba...
2019
Improve automatic migrated gather processing with feature engineering and 4D convolutional neural networks
Wen Pan, Harry Rynja, Ramakrishna Dandu, Zaifeng Liu, Shuzhen Ye, Antonio De Lilla, Jay Chen, Jeremy Vila
International Meeting for Applied Geoscience and Energy (IMAGE)
...Improve automatic migrated gather processing with feature engineering and 4D convolutional neural networks Wen Pan, Harry Rynja, Ramakrishna Dandu...
2024