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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,756 documents.
Abstract: Deepwater Hydrocarbon Development in the New Millennium, by G. J. Bergman and W. R. Landrum; #90923 (1999)
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1999
Abstract: Mineralogical Characterization of the Upper Devonian Duvernay Formation of Alberta, Western Canada Sedimentary Basin; #90224 (2015)
Julia M. McMillan, Levi J. Knapp, and Nicholas B. Harris
Search and Discovery.com
... Geophysical Wireline Logs and Artificial Neural Networks.” Petroleum Geoscience 10.2 (2004): 141–151. pg.geoscienceworld.org.login.ezproxy.library.ualberta.ca....
2015
AAPG Decision Based Integrated Reservoir Modeling GTW; - Abstracts, #91213 (2025).
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2025
Description of Productive Intervals Using Shear Wave Velocity in Southwest Iran
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N/A
Noise suppression and compressive sensing recovery with seismic-adapted DnCNN within RED
Nasser Kazemi
International Meeting for Applied Geoscience and Energy (IMAGE)
..., applying natural-images-learned feedforward denoising convolutional neural networks (DnCNN) operator on seismic data does not provide satisfactory...
2024
Abstract: Oil Sands Reservoir Characterization A Case Study at Nexen/Opti Long Lake, by Laurie Weston Bellman; #90075 (2008)
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2008
Abstract: Attribute-Assisted Stratigraphic Interpretation; #90172 (2014)
Fred M. Peterson
Search and Discovery.com
... complexity to the interpretation problem; though mentally comparing and contrasting more than three maps at once is a challenge for me! Neural Networks offer...
2014
Oil Sands Reservoir Characterization: A Case Study at Nexen/Opti Long Lake, by Laurie Weston Bellman, #40276 (2008).
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2008
Waveform Classification Proves Itself a Valuable Tool, by Satinder Chopra; #41024 (2012).
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2012
Injection Pattern Design to Maximize the Efficiency of Carbon Dioxide Injection for Sequestration Purposes in Brine Formations; #80334 (2013)
Qian Sun and Turgay Ertekin
Search and Discovery.com
... in Figure 3. These two artificial neural networks are validated through internal blind tests. These tests show error margins of around 10%, which...
2013
Eliminating the Influence of Caprock Thickness on Anomaly Intensities in Geochemical Surface Survey in the South Slope of the Dongying Depression in East China; #41304 (2014)
Liuping Zhang, Zhenli Wang, and Yingquan Zhao
Search and Discovery.com
... years, we focused on these problems and established a series of methods by using statistics, fractal geometry, wavelet analysis, and artificial neural...
2014
Estimating Reservoir Oil Volume and its Likelihood from 3C-3D Seismic Data, Well Logs, and Geostatistics; #41305 (2014)
Robert R. Stewart and Henrique A. Fraquelli
Search and Discovery.com
... a sand-shale distribution as well as a time-to-depth conversion from the various seismic and well log data. Linear multiregression and neural networks...
2014
Accelerate Well Correlation with Deep Learning; #42429 (2019)
Bo Zhang, Yuming Liu, Xinmao Zhou, Zhaohui Xu
Search and Discovery.com
... geostatistical inversion. Conclusions Convolutional neural networks have been used to identify objects for self-driving cars as well as faults and salt domes...
2019
Label-defect tolerance ability of deep learning inversion networks and its applications
Yang Ping, Xu Hunqun, Liu Di, Tao Chunfeng, Wang Chengxiang, Yue Changqing
International Meeting for Applied Geoscience and Energy (IMAGE)
...Label-defect tolerance ability of deep learning inversion networks and its applications Yang Ping, Xu Hunqun, Liu Di, Tao Chunfeng, Wang Chengxiang...
2023
Diagnosing Fracture-Wellbore Connectivity Using Chemical Tracer Flowback Data
Ashish Kumar, Mukul M. Sharma
Unconventional Resources Technology Conference (URTEC)
... length and permeability were lumped to define an effective connected fracture length, a parameter which correlates with production. Neural network based...
2018
Machine Learning and Artificial Intelligence Provides Wolfcamp Completion Design Insight
R. Shelley, H. Melcher, O. Oduba
Unconventional Resources Technology Conference (URTEC)
... neural networks are useful for this task and in addition they can exhibit remarkable properties of self-organization. An illustration of a type...
2021
Introducing stochasticity into CNN-based property estimation from angle-stack seismic
Haibin Di, Tao Zhao, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
..., H., and A. Abubakar, 2023, Estimating elastic properties from angle-stack seismic data via deep neural networks: 84th Annual International Conference...
2024
Enhancing full-waveform inversion with a deep-learning approximated inverse Hessian: A field data application
Mustafa Alfarhan, Matteo Ravasi, Fuqiang Chen, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... to enhance the update vector at each FWI iteration. We exploit neural networks’ adaptability through transfer learning, given the gradual iterationto...
2024
Optimized transparent boundary conditions for wave propagation
G. Roncoroni, B. Arntsen, E. Forte, M. Pipan
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Aigbavboa, 2018, A comparative analysis of gradient descent-based optimization algorithms on convolutional neural networks: 2018 International Conference...
2024
Bi-directional LSTM-based non-causal deconvolution
G. Roncoroni, I. Deiana, E. Forte, M. Pipan
International Meeting for Applied Geoscience and Energy (IMAGE)
... events (Menanno & Mazzotti, 2011). Additionally, the integration of neural networks in deconvolution processes has attracted more and more attention...
2024
Predicting Rock Properties of Hydrocarbon Reservoirs from Bulk Elemental Geochemistry; #40988 (2012)
Christopher N. Smith, Said Assous, Hamed Chok, and Henrik Friis
Search and Discovery.com
... studies, in shoreline clastic environments. The strength of the predictive capabilities of the neural networks is that detailed facies models...
2012
Solimões Basin onshore Brazil volcanic intrusions characterization using an interactive, data-centric deep leaning approach
Ana Krueger, Scotty Salamoff
International Meeting for Applied Geoscience and Energy (IMAGE)
... deep learning methodology that leverages neural networks to predict volcanics in the study area. Figure 1 Location map modified from ANP Geomaps...
2024
Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential
Kellen L. Gunderson, Zhao Zhang, Barton Payne, Shuxing Cheng, Ziyu Jiang, and Atlas Wang
AAPG Bulletin
...’s ability to continually improve with more data. Most of the current research in the discipline is focused on using convolutional neural networks...
2022
ABSTRACT: Vertical Hydrocarbon Migration at the Nigerian Continental Slope: Applications of Seismic Mapping Techniques; #90013 (2003)
ROAR HEGGLAND
Search and Discovery.com
... seismic data using neural networks (Heggland et al., 2000, Meldahl et al., 2001). This method has successfully been applied in different areas to reveal...
2003
Development and Application of a Real-Time Drilling State Classification Algorithm with Machine Learning
Yuxing Ben, Chris James, Dingzhou Cao
Unconventional Resources Technology Conference (URTEC)
.... Cardiologist-level arrhythmia detection with convolutional neural networks. https://arxiv.org/abs/1707.01836. Veres, G. and Sabeur Z. 2015. Date analytics...
2019