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The AAPG/Datapages Combined Publications Database
Showing 2,441 Results. Searched 200,616 documents.
A Bi-Directional Long Short-Term Memory Neural Network for Geologic-Facies Classification
Search and Discovery.com
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Application of Machine Learning and Deep Learning for Complex Fault Network Characterizationon the North Slope, Alaska
Search and Discovery.com
N/A
Abstract: Reservoir Characterization Using Converted-Wave Seismic Data: Case Study from Lower Cretaceous McMurray Formation, Athabasca Oil Sands; #90224 (2015)
Carmen C. Dumitrescu, Glenn Larson, Fred Mayer, and Draga Talinga
Search and Discovery.com
... to image the reservoir heterogeneity. These workflows include petrophysical analysis, joint PP-PS inversion and neural network analysis. Three...
2015
Organically-Rich Sweet Spot Determination in Utica Shale; #42137 (2017)
Satinder Chopra, Ritesh Kumar Sharma, Hossein Nemati, James Keay
Search and Discovery.com
... of density from prestack simultaneous impedance inversion, neural network approach was followed to compute density using seismic data...
2017
Characterizing Connectivity of Multiscale Pore Structure in Unconventional Reservoirs by the Complex Network Theory
Bin Zhao, Yanjun Shang, Lu Jin, Bao Jia
Unconventional Resources Technology Conference (URTEC)
... covering a wide range of pore sizes [25-28]. The artificial neural network model was also established based on the parameters of pores and throats...
2017
Deep-learning-based downhole tool electromagnetic telemetry noise attenuation and source separation
Carlos Urdaneta, Arnaud Jarrot, Shirui Wang, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... an improved source transformer in the separation layer that makes use of recurrent neural networks to learn the order of information in speech sequences...
2022
A data-feature-policy solution for multiscale geological-geophysical intelligent reservoir characterization
Wenhao Zheng, Fei Tian, Qingyun Di, Jiangyun Zhang, Hui Zhou, Wang Zhang, Zhongxing Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... Lorenz 96 chaotic system using machinelearning methods: Reservoir computing, artificial neural network, and long short-term memory network: Nonlinear...
2022
Recursive DIP for seismic random noise attenuation
Yun Zhang, Benfeng Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... method requires a large amount of training data. Convolutional Neural Networks (CNN) has strong prior characterization ability and profound...
2022
Sedimentological and Petrophysical Characterization of the Eocene Mirador Formation, Cupiagua Field, Llanos Basin, Colombia
C.A. Amaya, A. Ortiz, M. Martinez, N. Yepes
Asociación Colombiana de Geólogos y Geofisicos del Petróleo (ACGGP)
... enables petrophysical behavior to have a geological sense and be therefore more predictable. Petrophysical characterization and neural networks make...
2006
Unsupervised Learning Applied to Hydraulic Flow Unit Identification Based on Wireline Formation Pressure Data; #42260 (2018)
Jose Victor Contreras
Search and Discovery.com
... preservation in Self-Organizing Maps: Proceeding of International Conference on Neural Networks (ICNN), p. 294-299. Roy et al., 2013, Active learning...
2018
Time Lapse Seismic and Neural Network Evaluation of an Alberta Thermal Heavy Oil Prospect
Eric Andersen
Search and Discovery.com
...Time Lapse Seismic and Neural Network Evaluation of an Alberta Thermal Heavy Oil Prospect Eric Andersen Time Lapse Seismic and Neural Network...
Unknown
Time Lapse Seismic and Neural Network Evaluation of an Alberta Thermal Heavy Oil Prospect
Eric Andersen
Search and Discovery.com
...Time Lapse Seismic and Neural Network Evaluation of an Alberta Thermal Heavy Oil Prospect Eric Andersen Time Lapse Seismic and Neural Network...
Unknown
Abstract: Identification of Potential Lacustrine Stratigraphic Intervals in the Woodford Shale, Oklahoma, Using Multi-Attribute 3D Seismic Displays and a Supervised Neural Network; #90309 (2017)
Emilio J. Torres, Roger M. Slatt, Kurt J. Marfurt, Lennon E. Infante, Luis A. Castillo
Search and Discovery.com
... and a Supervised Neural Network; #90309 (2017) Emilio J. Torres, Roger M. Slatt, Kurt J. Marfurt, Lennon E. Infante, Luis A. Castillo AAPG Datapages...
2017
Abstract: Identification of Potential Lacustrine/Embayment Stratigraphic Intervals in the Woodford Shale, Oklahoma, Using Multi-Attribute 3-D Seismic Displays and a Supervised Probabilistic Neural Network; #90321 (2018)
Emilio Torres Parada
Search and Discovery.com
... Displays and a Supervised Probabilistic Neural Network; #90321 (2018) Emilio Torres Parada Identification of Potential Lacustrine/Embayment...
2018
Abstract: Total Organic Carbon Content Prediction From Well Logs via Artificial Neural Network Models;
Yunlai Yang, Zhenzhu Wan, Pan Luo, Abid Bhullar
Search and Discovery.com
...Abstract: Total Organic Carbon Content Prediction From Well Logs via Artificial Neural Network Models; Yunlai Yang, Zhenzhu Wan, Pan Luo, Abid...
Unknown
Evaluating Gas Production Performances in Marcellus Using Data Mining Technologies
Qiumei Zhou, Robert Dilmore, Andrew Kleit, John Yilin Wang
Unconventional Resources Technology Conference (URTEC)
..., and that weighting value will change during the self-learning processes of neural networks. Once the neural network is trained well, it is possible...
2014
A deep learning workflow for petro-mechanical facies predictions in unconventionals
Noah R. Vento, Enru Liu, Mary Johns
International Meeting for Applied Geoscience and Energy (IMAGE)
... is a subset of machine learning using neural networks, to characterize facies using an unconventional dataset. A 1D U-Net is trained to predict PMFs...
2023
Predicting S-wave sonic logs using machine learning with conventional logs for the Delaware Basin, Texas
Jaewook Lee, Yangkang Chen, Robin Dommisse, Alexandros Savvaidis, Guo-chin Dino Huang
International Meeting for Applied Geoscience and Energy (IMAGE)
... supervised ML models, including regression trees, support vector machines, kernels, ensembles, and neural networks, and determine the best ML prediction...
2023
Massive focal mechanism solutions from deep learning in west Texas
Yangkang Chen, Omar M. Saad, Alexandros Savvaidis, Fangxue Zhang, Yunfeng Chen, Dino Huang, Huijian Li, Farzaneh Aziz Zanjani
International Meeting for Applied Geoscience and Energy (IMAGE)
... within a neural network model so that when applied to a challenging case, the pre-trained model can extract the key features from the input data...
2024
Carbonate reservoir characterization and fluid identification using electrical imaging logging in the Pre-Caspian Basin
Xining Li, Xiaodong Cheng, Jiapeng Wu, Hulin Niu, Shengbin Zhang, Yonggui Li, Yuanqi Yang
International Meeting for Applied Geoscience and Energy (IMAGE)
... and conventional well logs based on artificial neural networks in the CambroOrdovician reservoir of Mesdar oil field. Amartey et al. (2017) applied an integrating...
2024
A hybrid framework of physical constraints and sequence learning for production forecasting with application in the Weirong shale gas field, China
Ji Chang, Han Wang, Hanqing Wang, Yujie Zhou, Jin Meng, Yitian Xiao
International Meeting for Applied Geoscience and Energy (IMAGE)
... can assist traditional methods to improve the accuracy of production forecasting. As a special autoregressive model, recurrent neural network (RNN...
2024
Encoding the subsurface in 3D with seismic
Ben Lasscock, Altay Sansal, Alejandro Valenciano
International Meeting for Applied Geoscience and Energy (IMAGE)
...., S. Poche, S. Kainkaryam, A. Valenciano, and A. Sharma, 2021, An innovative strategy for seismic swell noise removal using deep neural networks: First...
2024
Unsupervised machine learning for seismic facies classification using a 3D grid approach
David Manzano, Edgar Galvan, Dan Ferdinand Fernandez
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutional neural networks (CNNs) to directly apply to 3D seismic volumes, providing better spatial awareness and automatic feature extraction based...
2024
Geophysics in gold hydrogen exploration
Mengli Zhang, Yaoguo Li
International Meeting for Applied Geoscience and Energy (IMAGE)
...., and A. Abubakar, 2022, Estimating subsurface properties using a semisupervised neural network approach: Geophysics, 87, no. 1, IM1–IM10, doi: doi: https://doi.org...
2024
Development of a Machine-Learning-Based Workflow for Well Completion Optimization in Permian Basin
Leizheng (Kevin) Wang, Julia Gale, Alexander Y. Sun
Unconventional Resources Technology Conference (URTEC)
... Resources Technology Conference: 23. Rastogi, A., K. Agarwal, et al. (2019). Demystifying Data-Driven Neural Networks for Multivariate Production...
2020