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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,685 documents.
2010
Deep learning software accelerators for full-waveform inversion
Sergio Botelho, Souvik Mukherjee, Vinay Rao, Santi Adavani
International Meeting for Applied Geoscience and Energy (IMAGE)
... is the use of (deep) neural networks, which have proven to be capable of learning complex non-linear relationships between the velocity model...
2022
Data-embedded physics-informed neural network for electromagnetic wave propagation simulation: Potentials and challenges
Yawei Su, Wenyi Hu, Jiefu Chen, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
... domain with a small amount of training data, yielding more accurate results than the pure data-driven neural networks. Despite the recognized...
2024
Seismic imaging profile noise suppression based on self supervised deep learning: a case study in the Yellow Sea
Qiang Xu
International Meeting for Applied Geoscience and Energy (IMAGE)
... it. When using Convolutional Neural Networks for denoising, each input data point is passed through a series of stacked convolutional layers, pooling...
2024
Abstract: Porosity and Permeability Prediction of Zechstein-2-Carbonates From 3D Seismic Data, by H. Trappe, P. Krajewski, and S. Aust; #90956 (1995).
Search and Discovery.com
1995
Abstract: Different Approaches to Shear Wave Prediction, by O.H. Afif, M. Ahmed, and H.H. Soepriatna,#90188 (2014)
Search and Discovery.com
2014
Deep Learning Used in Permeability Prediction of Channel Sand Bodies With Strong Heterogeneity
Search and Discovery.com
N/A
ABSTRACT: Using Advanced Seismic Attribute Analysis to Reduce Risk in Frontier Exploration - West Newfoundland Offshore; #90108 (2010)
Azer Mustaqeem and Valentina V. Baranova
Search and Discovery.com
... a formation triggers the dolomitization process, we used seismic attributes and neural networks to identify areas with karst morphology...
2010
Abstract: AI- Assisted Palynological Analysis Using an Expert-Trained Convolutional Neural Network: A Case Study form the Jurassic in the North Sea; #91204 (2023)
Rader Abdul Fattah, Merijn de Bakker, Alexander Houben, Roel Verreussel, Robert Williams
Search and Discovery.com
... for classification and localization of polynomorphs. A SSD is a supervised machine learning algorithm based on convolutional neural networks. Once trained...
2023
Regional Data Analysis to Determine Production Trends Using a Fuzzy Expert Exploration Tool
Robert S. Balch, William W. Weiss, Shaochang Wo, Darren M. Hart
West Texas Geological Society
... is proposed for oil exploration. This tool relies on a digital data base, and computer maps generated by neural networks using “fuzzy” logic. Fuzzy logic...
2000
Extended Abstract: Fresh Outlook in Numerical Methods for Geodynamics
Gabriele Morra
GCAGS Transactions
... Data Analytics and Geodynamic Modeling will merge, with the help of Artificial Intelligence. Recent efforts have shown how machine learning, neural...
2020
Abstract: Extracting Formation Properties from Hydraulically Induced Microseisms, Seismic Attributes, and Impedance Inversion; #90240 (2015)
Xavier Refunjol
Search and Discovery.com
... for a more successful development. Regional rock property analysis can be used to identify hydrocarbon-bearing zones using seismic inversion, and neural...
2015
Abstract: Using Seismic Attributes to Predict Reservoir Properties-Potential Risks
Cynthia T. Kalkomey
Houston Geological Society Bulletin
..., depletion strategy, or gas and water injection operations. All of the prediction methods-regression, geostatistics, and neural networks-require...
1999
ABSTRACT: Manual and Automatic Seismic Facies Analysis on SISMAGE{TM} Workstation, by M. Morice, N. Keskes, and F. Jeanjean; #91021 (2010)
Search and Discovery.com
2010
Abstract: Predicting Biofacies Distributions Using a Sequence Stratigraphic Model and Artificial Intelligence Methods, by Tao Zhang and Roy E. Plotnick; #90914(2000)
Search and Discovery.com
2000
ABSTRACT: Meta attributes: A new concept for reservoir characterization and seismic anomaly detection; #90021 (2003)
FRED AMINZADEH
Search and Discovery.com
... a particular feature. One of the main features of the meta-attribute concept is combining “artificial intelligence” of neural networks with the “natural...
2003
Abstract: What is Deep Learning? - And a Bit More; #90304 (2017)
Kamal Hami-Eddine
Search and Discovery.com
... will understand how neural network perform. The transition from neural networks to deep learning will then be a simple step. All these techniques will be introduced...
2017
Abstract: Challenges and Opportunities for Advancing Reservoir Simulation with AI; #91213 (2025)
Ahmed H. Elsheikh
Search and Discovery.com
... reservoir simulation technologies. Recent breakthroughs in deep neural networks and neural operators have demonstrated remarkable capabilities...
2025
Seismic Classification
Search and Discovery.com
N/A
Enhancing seismic image resolution using Brownian diffusion bridge model
Bingbing Sun, Abdulmoshen M. Ali, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... enhancement. Machine learning-based techniques, particularly those using convolutional neural networks (CNNs), aim to predict high-resolution images...
2024
Physics-informed full-waveform inversion using learned wavefield solutions
Xinquan Huang, Tariq Alkhalifah, Fu Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... modeling, offering the potential for instantaneous inference. Physics-Informed Neural Networks (PINNs), as one of the neural PDE solvers...
2024
A robust approach for shear log predictions using deep learning on big data sets from a carbonate reservoir for integrated reservoir characterization projects
Aun Al Ghaithi
International Meeting for Applied Geoscience and Energy (IMAGE)
... a big well log dataset from a field containing 100s of wells. Artificial Neural Networks (ANNs) consist of an input layer, hidden layers and an output...
2022
Broader Spectrum Seismic after Seismic Inversion via Neural Network Solutions: Its Contribution to Seismic Interpretation
Luis Vernengo, Juan A. Tavella, Maximiliano Garcia Torrejon
Unconventional Resources Technology Conference (URTEC)
... networks (CNN). b. Direct neural network prediction with synthetic seismic as target (MAR and DNN). Throughout this work several tests are mentioned...
2023