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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,685 documents.
Automated metallic pipeline detection using magnetic data and convolutional neural networks
Brett Bernstein, Yaoguo Li, Richard Hammack
International Meeting for Applied Geoscience and Energy (IMAGE)
...Automated metallic pipeline detection using magnetic data and convolutional neural networks Brett Bernstein, Yaoguo Li, Richard Hammack Automated...
2022
Solution for Anomaly Detection in Oil & Gas Well Drilling Sensors Based on Recurrent Neural Networks: A Big Data Approach
María Yamile Orellano, Marilyn Vargas, Julián Benavidez
Unconventional Resources Technology Conference (URTEC)
...Solution for Anomaly Detection in Oil & Gas Well Drilling Sensors Based on Recurrent Neural Networks: A Big Data Approach María Yamile Orellano...
2023
Improving Resolution and Clarity with Neural Networks; #41911 (2016)
Christopher P. Ross
Search and Discovery.com
...Improving Resolution and Clarity with Neural Networks; #41911 (2016) Christopher P. Ross GC Improving Resolution and Clarity with Neural Networks...
2016
Semi-supervised ground-roll wave segmentation with noise label via neural network evolution
Yinshuo Li, Wenkai Lu
International Meeting for Applied Geoscience and Energy (IMAGE)
... achieve better performance than the label. Meanwhile, the co-evolution of neural networks and data is utilized to annotate more data and achieve better...
2024
An Integrated Deep Learning Solution for Petrophysics, Pore Pressure, and Geomechanics Property Prediction
Ehsan Zabihi Naeini, Sam Green, Marianne Rauch-Davies
Unconventional Resources Technology Conference (URTEC)
... and interpreted data to devise solutions which simultaneously integrate wide ranging well bore and wireline logs. We implement three neural networks, all...
2019
Definition of geohazards in exploration 3-D seismic data using attributes and neural-network analysis
Roar Heggland
AAPG Bulletin
.... M., 1999a, Seismic reservoir characterisation using artificial neural networks: 19th Mintrop-Seminar, May 1618, 1999, Mnster, Germany.de Groot, P. F...
2004
Application of Bayesian Optimized Deep Bi-LSTM Neural Networks for Production Forecasting of Gas Wells in Unconventional Shale Gas Reservoirs
Y. Kocoglu, S. Gorell, P. McElroy
Unconventional Resources Technology Conference (URTEC)
...Application of Bayesian Optimized Deep Bi-LSTM Neural Networks for Production Forecasting of Gas Wells in Unconventional Shale Gas Reservoirs Y...
2021
Embedding Physical Flow Functions into Deep Learning Predictive Models for Improved Production Forecasting
Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Unconventional Resources Technology Conference (URTEC)
...; Zobeiry and Humfeld, 2021) use data-driven methods (e.g., neural networks) to explicitly perform physical computations to solve or rather, approximate...
2022
Multilayer perceptron and Bayesian neural network based implicit elastic full-waveform inversion
Tianze Zhang, Jian Sun, Daniel O. Trad, Kristopher A. Innanen
International Meeting for Applied Geoscience and Energy (IMAGE)
... networks: a neural network that generates velocity models, and a recurrent neural network to perform the modeling. The approach is distinct from conventional...
2022
Geological Interpretation Using Pattern Recognition from Self-Organizing Maps and Principal Component Analysis
Search and Discovery.com
N/A
Predicting Facies Distribution Within a Fluvial System in the Subsurface: Triassic of the Central North Sea
Search and Discovery.com
N/A
Reservoir Modeling With Deep Learning
Search and Discovery.com
N/A
ABSTRACT: An iterative method for identifying seismic objects by their texture, orientation and size; #90007 (2002)
Paul Meldahl and Roar Heggland, Bert Bril and Paul de-Groot
Search and Discovery.com
... of semi-automated detection of seismic objects by directive attributes and neural networks: Part II; Interpretation. Annual Meeting. Society...
Unknown
ABSTRACT: Use of Seismic Character for Intelligent Facies Analysis and Reservoir Property Estimation; #90007 (2002)
Fred Aminzadeh, Paul. F. M. de Groot
Search and Discovery.com
... in training the supervised neural networks. The pseudo-well simulator generates stratigraphic columns with the corresponding well logs using a constrained...
2002
ABSTRACT: Statistically-Based Lithofacies Predictions for 3-D Reservoir Modeling: An Example from the Panoma (Council Grove) Field, Hugoton Embayment, Southwest Kansas; #90013 (2003)
Martin K. Dubois, Alan P. Byrnes, Geoffrey C. Bohling, Shane C. Seals, John H. Doveton
Search and Discovery.com
... reservoirs like the Panoma Field, but prediction tools, neural networks and the Excel add-in Kipling.xla, a nonparametric discriminant analysis tool, provide...
2003
Click to view abstract in PDF format
Search and Discovery.com
N/A
Simulating seismic data using generative adversarial networks
Bradley C. Wallet, Eyad Aljishi, Hussain Alfayez
International Meeting for Applied Geoscience and Energy (IMAGE)
...Simulating seismic data using generative adversarial networks Bradley C. Wallet, Eyad Aljishi, Hussain Alfayez Second International Meeting...
2022
A self-attention enhanced encoder-decoder network for seismic data denoising
Stefan Knispel, Jan Walda, Ruediger Zehn, Alexander Bauer, Dirk Gajewski
International Meeting for Applied Geoscience and Energy (IMAGE)
... deep neural networks, can be applied to a large variety of recognition tasks, e.g. the well-known U-Net for detecting cancer cells in biomedical...
2022
Aiding self-supervised coherent noise suppression by the introduction of signal segmentation using blind-spot networks
Sixiu Liu, Claire Birnie, Tariq Alkhalifah, Andrey Bakulin
International Meeting for Applied Geoscience and Energy (IMAGE)
... growth of deep learning procedures, Neural Networks (NNs) have been extensively used to suppress noise in seismic data. Such denoising methods often...
2022
Deep Earth: Leveraging neural networks for seismic exploration objectives
Tariq Alkhalifah, Claire Birnie, Randy Harsuko, Hanchen Wang, Oleg Ovcharenko
International Meeting for Applied Geoscience and Energy (IMAGE)
...Deep Earth: Leveraging neural networks for seismic exploration objectives Tariq Alkhalifah, Claire Birnie, Randy Harsuko, Hanchen Wang, Oleg...
2022
Artificial Neural Networks for Corrosion Rate Prediction in Gas Pipelines
Sumarni, Deden Supriyatman, Kuntjoro Adjie Sidarto, Rochim Suratman, Rinaldy Dasilfa
Indonesian Petroleum Association
...Artificial Neural Networks for Corrosion Rate Prediction in Gas Pipelines Sumarni, Deden Supriyatman, Kuntjoro Adjie Sidarto, Rochim Suratman...
2012
Abstract: Interactive Deep Learning Assisted Seismic Interpretation Technology Applied to Reservoir Characterization: A Case Study From Offshore Santos Basin in Brazil;
Ana Krueger, Bode Omoboya, Paul Endresen, Benjamin Lartigue
Search and Discovery.com
... Convolutional Neural Networks (CNN), the deep neural network acts as an extension of the interpreter to assist in mapping sub-surface geological...
Unknown
Use of Artificial Neural Network Models to Determine Infill Well Locations in a Mature Oil Field
M.I. Arshanda, Y.A. Rachman, E.A. Putra, Y.A. Nagarani
Indonesian Petroleum Association
... locations using Artificial Neural Networks (ANN) with a 44-well data-set. 80% of wells were used for training and the rest was for testing. Two ANN models...
2013
Fast viscoacoustic forward modeling method based on U-net Fourier neural operator
Wenbin Tian, Yang Liu
International Meeting for Applied Geoscience and Energy (IMAGE)
... neural layer, which is visually represented in Figure 2a. The FNO consist of two separate two convolutional neural networks (CNNs): CNNs in the space...
2023
Interpretation of deep neural networks for carbonate thin section classification
Lukas Mosser, George Ghon, Gregor Baechle
International Meeting for Applied Geoscience and Energy (IMAGE)
...Interpretation of deep neural networks for carbonate thin section classification Lukas Mosser, George Ghon, Gregor Baechle Interpretation of Deep...
2022