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The AAPG/Datapages Combined Publications Database
Showing 1,954 Results. Searched 195,387 documents.
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).
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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)
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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
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N/A
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
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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)
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2012
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,
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... 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
Feature-based Probabilistic Interpretation of Geobodies from Seismic Amplitudes
J. Caers, B. G. Arpat, C. A. Garcia
AAPG Special Volumes
..., Appleton and Lange, 673 p.Haykin, S., 1999, Neural networks: A comprehensive foundation: Upper Saddle River, New Jersey, Prentice Hall, 842 p.Mallet, J.-L...
2006
ABSTRACT: Inferring Lithofacies from Well Logs by Applying Hybrid Neural Network-Hidden Markov Model Classifiers; #90017 (2003)
Piotr Mirowski, David McCormick
Search and Discovery.com
... Artificial Neural Networks (ANNs) and Hidden Markov Models (HMMs) schemes have proven to be a viable alternative to human interpretation when applied...
2003
Abstract: Evaluation of Hybrid Prediction Models for Accurate Rate of Penetration (ROP) Prediction in Drilling Operations; #91206 (2023)
Abdelhakim Khouissat, Youcefi Mohamed Riad, Ghoulem Ifrene
Search and Discovery.com
... methods, such as artificial neural networks and genetic algorithms, to improve prediction accuracy...
2023
Artificial Intelligence Application on Seismic Data for Automatic First-Break Arrival Picking
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N/A
Abstract: Recognizing facies in the Red River Formation of North Dakota using a Convolutional Neural Network; #90301 (2017)
Stephan H. Nordeng, Ian E. Nordeng, Jeremiah Neubert, Emily G. Sundell
Search and Discovery.com
... and texture. The reason for this new approach is the development of massively intricate algorithms known as Convolutional Neural Networks (CNN) or Deep...
2017
Prediction of Fracture Porosity from Well Log Data by Artificial Neural Network, Case Study: Carbonate Reservoir, DEPOK Field
Okok Wijaya, Pebrian Tunggal P, Ahmat Dafit Hasim, Depta Mahardika, Sungkono, Bagus Jaya S
Indonesian Petroleum Association
... has another parameter called neuron. In the neural network, flow may contain more than one hidden layer (Figure 1). Artificial neural networks...
2015
Geophysics and neural networks: learning from computer vision
Mark Grujic, Liam Webb, Tom Carmichael
Petroleum Exploration Society of Australia (PESA)
...Geophysics and neural networks: learning from computer vision Mark Grujic, Liam Webb, Tom Carmichael Geophysics and neural networks: learning from...
2019
Abstract: A First Attempt to Predict Delta System Dynamic with Artificial Neural Networks, by E. Puhl, O. C. Pedrollo, A. L. O. Borges, and R. D. Maestri; #90090 (2009).
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2009
Chancing Methods to Predict Porosity in a Middle Eastern Carbonate Reservoir from Full-Function Machine-Learning Neural Networks, Seismic Attributes and Inversions
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N/A
Abstract: Grain Segmentation and Region Mask Generation in Digital Rock Images Using Convolutional Neural Networks;
Rengarajan Pelapur, Arash Aghaei, Connor Burt, Bidur Bohara
Search and Discovery.com
...Abstract: Grain Segmentation and Region Mask Generation in Digital Rock Images Using Convolutional Neural Networks; Rengarajan Pelapur, Arash Aghaei...
Unknown
A novel technique for modeling fracture intensity: A case study from the Pinedale anticline in Wyoming
Patrick M. Wong
AAPG Bulletin
...., 1995, Neural networks for pattern recognition: New York, Oxford University Press, 504 p.Boerner, S., D. Gray, A. Zellou, D. Todorovic-Marinic, and G...
2003
ABSTRACT: SEISMIC MULTI-ATTRIBUTE ANALYSIS FOR FLUID SATURATION AND LITHOLOGY DISCRIMINATION IN THE HIBISCUS FIELD, TRINIDAD & TOBAGO
Sierra, J., González, K., Machado, O. and Landa, A, Wong, C., Rojas, G. and Carnevali, B.,
Geological Society of Trinidad & Tobago
... of Trinidad. A post-stack method, supported on model based inversion and neural networks, was followed. The lithology and fluid classification was performed...
2007