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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,693 documents.
Supervised Learning Applied to Rock Type Classification in Sandstone Based on Wireline Formation Pressure Data; #42539 (2020)
Jose Victor Contreras
Search and Discovery.com
... Forests, and Artificial Neural networks. Capacity, Overfitting, and Underfitting The main challenge in machine learning is to create a model that make...
2020
Comparison of Machine Learning and Statistical Predictive Models for Production Time Series Forecasting in Tight Oil Reservoirs
Hamid Rahmanifard, Ian Gates, Abdolmohsen Shabib-Asl
Unconventional Resources Technology Conference (URTEC)
... of six modern ML networks, including Multilayer Perceptrons (MLP), Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Convolutional Neural...
2022
Lithofacies identification in cores using deep learning segmentation and the role of geoscientists: Turbidite deposits (Gulf of Mexico and North Sea)
Oriol Falivene, Neal C. Auchter, Rafael Pires de Lima, Luuk Kleipool, John G. Solum, Pedram Zarian, Rachel W. Clark, and Irene Espejo
AAPG Bulletin
... of convolutional neural networks (CNNs) using semantic segmentation architectures to automate the identification of common lithofacies from core images. Images...
2022
Abstract: Technology Integration for Reservoir Characterisation and Optimized Well Planning at Larut Field Offshore Malay Basin (Poster 11)
Melanie J. Ryan, Christopher E. Harris
Geological Society of Malaysia (GSM)
... as the thickness of these reservoirs is below seismic resolution. In order to extract more information from the 3-D seismic data, neural networks...
2003
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
.... - Application of a horizon-based 3D seismic facies Unsupervised classification technique using neural networks for noise reduction and seismic facies...
2022
Application of Machine Learning to Facies Classification of Carbonate Core Images
Sharinia Kanagandran
Southeast Asia Petroleum Exploration Society (SEAPEX)
... learning techniques. The study evaluated two commonly used machine learning algorithms, Random Forest (RF) and Convolutional Neural Networks (CNNs...
2019
Abstract: Using Unsupervised Classification of Seismic Trace Shape to Create Facies Maps: Examples from the Australian North West Shelf
Jim Dirstein
Petroleum Exploration Society of Australia (PESA)
... to change from interpreter to interpreter. Using neural networks, the unsupervised class ificat ion of an interva l in a 3D survey can rapidly map...
2001
ABSTRACT: Reservoir Characterization in Bao and Ma Oil Fields, Kailu Basin, by Feng Shen, Jinliang Zing, Zhiyun Lai; #91020 (1995).
Search and Discovery.com
1995
ABSTRACT: Incorporating Geologic and Data Uncertainties Into Hugoton Field Pore Volume Estimates, by Kvk Prasad, Terri M. Olson, and Steve D. Boughton; #91019 (1996)
Search and Discovery.com
1996
ABSTRACT: Mudstone (Shale!) Permeability: A Key Unknown in Basin Modelling, by A. O. Aplin, Y. Yang, S. R. Larter, D. N. Dewhurst, and J.-P. Sarda; #91021 (2010)
Search and Discovery.com
2010
Abstract: Petrographic Analysis of Carbonate "End Member" Samples, by F. Anselmetti, G. Eberli, and S. Luthi; #90942 (1997).
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1997
Quantitative Characterization of Carbonate Pore Systems by Digital Image Analysis
Flavio S. Anselmetti, Stefan Luthi, and Gregor P. Eberli
AAPG Bulletin
... neural networks, permeability appears to be mainly controlled by the macropore shape in high-permeability samples, and by the amount of intrinsic...
1998
Abstract: Endicott Field: Revitalizing a Mature Field with New Technology, by M. K. Westergaard, M. A. Vandergon, and C. Sullivan; #90008 (2002).
Search and Discovery.com
2002
Abstract: Permeability Prediction in Marine-Eolian Sediments Using Multivariate Analysis and Nonparametric Regression, by Yumei Li; #90033 (2004)
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2004
Abstract: Using Field Data to Demonstrate the Importance and Pitfalls of Flow-Unit Interpretation for Reservoir Description and Modeling, by Anne-Kristine Stolz and Ramona M. Graves; #90039 (2005)
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2005
Abstract: Detecting Fault Related Hydrocarbon Migration Pathways in Seismic Data: Implications for Fault Seal, Pressure, and Charge Prediction, by David L. Connolly and Friso Brouwer; #90085 (2008)
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2008
Abstract: Applying Modern Petrophysical Techniques to Vintage E-log's, Kettleman Hills North Dome Field, CA, by Jason B.Robbins and Jonathan P. Lange; #90076 (2008)
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2008
Abstract: Data Mining Well Completion Data for the Dakota Formation, San Juan Basin, New Mexico, by R. Balch and A. K. Iduri; #90092 (2009)
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2009
Abstract: Understanding Complex Lower Mannville Deposits in the Western Canadian Sedimentary Basin by Integrating Geological and Geophysical Data, by S. Sarzalejo and B. S. Hart; #90090 (2009).
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2009
Abstract: Image Petrophysics - A New Approach to Reservoir Characterization, by Manfred Frass and Nicholas Harvey; #90105 (2010)
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2010
Abstract: Fast, Fully Probabilistic, Nonlinear Inversion of Seismic Attributes for Petrophysical Parameters, by Andrew Curtis, Mohammad Shahraeeni, and Gabriel Chao; #120034 (2012)
Search and Discovery.com
2012
Abstract: Seismic Attribute Applications for Interpreters; #90171 (2013)
Satinder Chopra and Kurt J. Marfurt
Search and Discovery.com
... of these classes of attributes can be quantitatively correlated to well control using multivariate analysis, geostatistics, or neural networks. Seismic...
2013
Identifying the Sedimentary Facies Through Analysis of Seismic Facies in Non-Marine Sedimentary Basin: A Case Study From the Offshore Bohai Bay Basin, East China
Search and Discovery.com
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Seismic Analysis of Total Organic Carbon (TOC) Distribution in the Woodford Shale, Oklahoma, USA
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N/A