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The AAPG/Datapages Combined Publications Database
Showing 1,956 Results. Searched 195,452 documents.
THE APPLICATION OF ARTIFICIAL NE
Search and Discovery.com
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Geophysical Corner Articles from September 1996 — present, Compiled by Randy Ray
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High Resolution Seismic Data Derived From Prestack Inversion and Machine Learning to Accurately Position Horizontal Wells in the Midland Basin, Texas
Robert Meek, Buzz Davis, Hector Bello
Unconventional Resources Technology Conference (URTEC)
... the data is high enough quality to invert. Stephens et al, 2011, showed how prestack inversion combined with neural networks was able to map out brittle...
2017
ABSTRACT: Flow-Unit Modeling Using Neural Networks, Logs, and Core in a Vuggy Dolomite Reservoir, Dagger Draw Field, New Mexico; #90017 (2003)
Bob Wikan H. Adibrata, Neil F. Hurley
Search and Discovery.com
...ABSTRACT: Flow-Unit Modeling Using Neural Networks, Logs, and Core in a Vuggy Dolomite Reservoir, Dagger Draw Field, New Mexico; #90017 (2003) Bob...
2003
ABSTRACT: Hybridization of artificial neural network and grey relational analysis for the prediction of slope stability
Ashanira Mat Deris, Badariah Solemon
Geological Society of Malaysia (GSM)
... 0.999 ROC value and 99% accuracy, compared to 0.929 and 91% for a single ANN model. Keywords: Statistical machine learning, artificial neural networks...
2021
Abstract: Mining Big Data Using Principal Component Analysis and Using Results to Find Oil and Gas with Neural Analysis of Multiple Seismic Attributes Machine Learning!; #90304 (2017)
Deborah Sacrey
Search and Discovery.com
... recognition process using unsupervised neural networks, and can reveal the natural clustering and patters in the data which often are distinct...
2017
Estimating CO2 saturation and porosity using the double difference approach based invertible neural network
Arnab Dhara, Mrinal K. Sen, Sohini Dasgupta
International Meeting for Applied Geoscience and Energy (IMAGE)
... difference approach. The use of Invertible Neural Networks (INNs) over other network architectures is motivated by the fact that INNs can produce comparable...
2023
Innovative Deep Autoencoder and Machine Learning Algorithms Applied in Production Metering for Sucker-Rod Pumping Wells
Peng Yi, Xiong Chunming, Zhang Jianjun, Zhang Yashun, Gan Qinming, Xu Guojian, Zhang Xishun, Zhao Ruidong, Shi Junfeng, Liu Meng, Wang Cai, Chen Guanhong
Unconventional Resources Technology Conference (URTEC)
.... The machine-learning model contains two neural networks: first, a deep autoencoder to extract the feature representations from all the dynamometer...
2019
Abstract: Integration of Multi Scale Data in Facies Modeling using Neural Network; #90171 (2013)
Khaled Benzaoui and Tom Cox
Search and Discovery.com
... step 3 and the facies probability cubes from step 2. The facies probabilities are used as global probability for the SIS. What is Neural Networks...
2013
Abstract: Integration of Multi Scale Data in Facies Modeling using Neural Network; #90171 (2013)
Khaled Benzaoui and Tom Cox
Search and Discovery.com
... step 3 and the facies probability cubes from step 2. The facies probabilities are used as global probability for the SIS. What is Neural Networks...
2013
High-resolution angle gather tomography with Fourier neural operators
Sean Crawley, Guanghui Huang, Ramzi Djebbi, Jaime Ramos, Nizar Chemingui
International Meeting for Applied Geoscience and Energy (IMAGE)
... global convolutions, efficiently computed with FFTs, rather than local operators typically used by convolution neural networks (CNNs). FNOs...
2023
Inversión Sísmica de un Modelo Teórico Calculado Sobre un Horizonte Sísmico Utilizando Redes Neuronales [PAPER IN SPANISH] Seismic Inversion of a Theoretical Model Calculated on a Seismic Horizon Using Neural Networks
Dario Sergio Cersosimo, Claudia Ravazoli, Garcia Martinez Ramon
Asociación Colombiana de Geólogos y Geofisicos del Petróleo (ACGGP)
... of a Theoretical Model Calculated on a Seismic Horizon Using Neural Networks Dario Sergio Cersosimo, Claudia Ravazoli, Garcia Martinez Ramon INVERSIÓN SÍSMICA...
2004
Application of Common Contour Binning (CCB) and Back Propagation Neural Network (BPNN) for Oil Water Contact Prediction in Carbonate Reservoir (The Case Study at G404 Field)
Wahyu Tri Sutrisno, Septian Prahastudhi, Ayi Syaeful Bahri, Yulia Putri Wulandari
Indonesian Petroleum Association
... processing unit with each input is then used to calculate a sigmoid function output (Saemi, 2007). A sigmoid binary function is used in neural networks...
2013
ABSTRACT: Generating Missing Logs - Techniques and Pitfalls; #90013 (2003)
Michael Holmes, Dominic Holmes, Antony Holmes
Search and Discovery.com
... intervals or entire wells. Neural networks are becoming a fashionable method to fill in missing data, and are powerful. The basic methodology is to train...
2003
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)
.... Introduction Machine Learning and Neural Networks are now commonly used in both the traditional oil and gas industry and in activities related to energy...
2023
Introduction: Field Applications of Intelligent Computing Techniques
P. M. Wong, M. Nikravesh
Journal of Petroleum Geology
..., F., 1999. Challenges direct future of geophysics. The American Oil & Gas Reporter, December, 6 pp. BISHOP, C., 1995. Neural Networks for Pattern...
2001
Fracture Network Characterization of Naturally Fractured Reservoir Using Artificial Neural Network and Fractal Methods
Doddy Abdassah, Sani O. Wahyu
Indonesian Petroleum Association
... Neural Networks, Geomechanics and 3-D Seismic, SPE Paper # 30722, New Mexico. 3. Ershaghi, I., 1996, Naturally Fractured Reservoir: A summer Course...
1998
Abstract: Integrating Well and Seismic Data for Facies Prediction: A Case Study; #90319 (2018)
Rick Leaver, Afrah S. Al-Ajmi, Fatma Al-Otaibi, Ghadna Zeraie, Prabir Kumar Nath, Subratah Bhukta, Bruno De Ribet, Tom Trowbridge, Osamah Al-Bannaw
Search and Discovery.com
... extracted from wells is used to train a first set of neural networks. Soft data taken away from wells is used to stabilize the neural network training...
2018
Enhancing Pre-Stack Seismic Inversion Using Neural Networks for Clastic Reservoir Characterization Simian Field, Offshore Nile Delta, Egypt; #20413 (2018)
Wael Said, Islam A. Mohamed, Ahmed Ali
Search and Discovery.com
...Enhancing Pre-Stack Seismic Inversion Using Neural Networks for Clastic Reservoir Characterization Simian Field, Offshore Nile Delta, Egypt; #20413...
2018
Earthquake Detection and Focal Mechanism Calculation Using Artificial Intelligence
Shane Quimby, Yanwei Zhao, Jie Zhang, GeoTomo
Unconventional Resources Technology Conference (URTEC)
... to propose a novel deep convolutional neural network Focal Mechanism Network (FMNet) for estimating the location, magnitude and source focal mechanisms...
2022
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
... and recurrent neural networks are trained on historical production data to predict future responses. The physics-constrained model is compared...
2021
Coalbed Methane Production Parameter Prediction and Uncertainty Analysis of Coalbed Methane Reservoir with Artificial Neural Networks
Harry Ramadhan Sumardi, Dedy Irawan
Indonesian Petroleum Association
...Coalbed Methane Production Parameter Prediction and Uncertainty Analysis of Coalbed Methane Reservoir with Artificial Neural Networks Harry Ramadhan...
2016
Meta-Attributes: A New Concept for Reservoir Characterization and Seismic Anomaly Detection
Fred Aminzadeh
GCAGS Transactions
... to detect a particular feature. One of the main features of the meta-attribute concept is combining "artificial intelligence" of neural networks...
2003
Abstract: Supporting the Training of Physics Informed Neural Networks for Seismic Inversion Using Provenance;
Renan Souza, Andres Codas, Alberto Nogueira Junior, Joao Almeida, Miguel Quiñones, Leonardo Azevedo, Raphael Thiago, Elton Soares, Marcelo Costalonga Cardoso, Leonardo Martins
Search and Discovery.com
...Abstract: Supporting the Training of Physics Informed Neural Networks for Seismic Inversion Using Provenance; Renan Souza, Andres Codas, Alberto...
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