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The AAPG/Datapages Combined Publications Database
Showing 2,442 Results. Searched 200,693 documents.
Abstract: Machine Learning Algorithms for Predicting Liquid Loading in Gas Wells; #91206 (2023)
Nassim Bouabdallah, Abdeldjalil Latrach, Adesina Fadairo, Aimene Aihar
Search and Discovery.com
..., XGBoost, and Neural Networks, to predict whether the well is loaded or unloaded. We then compared the predictions of the machine learning algorithms...
2023
-- no title --
user1
Search and Discovery.com
... by utilizing Convolutional Neural Networks(CNNs) and Wavelet-based approaches. This ensures a clear interpretation of subsurface characteristics for a better...
Unknown
Abstract: Next-Gen Geological Modeling Driven by Machine Learning; #91213 (2025)
Manish Kumar Singh
Search and Discovery.com
... focuses on seismic interpretation using convolutional neural networks. Manually interpreted seismic lines serve as training data, allowing the model...
2025
Data Mining Techniques for Segmentation Analysis of Seismic Data, by Daniel R.S. Moraes, Rogério P. Espíndola, Márcia K. Karam, Alexandre G. Evsukoff, and Nelson F. F. Ebecken; #90052 (2006)
Search and Discovery.com
2006
Integrating Seismic Multi-Attribute Classification and Forward Stratigraphic Modeling in Mid- Cretaceous Carbonate Sequences, Arabian Gulf, Offshore Iran
Search and Discovery.com
N/A
Use of Information Technologies to Address Reservoir Compartments in the Permian Gas Fields of Southwest Kansas, by Timothy R. Carr, Martin K. Dubois, Alan P. Byrnes, #90030 (2004)
Search and Discovery.com
2004
Intelligent Seismic Inversion; From Surface Seismic to Well Logs via VSP. Artun, Emre, Mohaghegh, Shahab D., Toro, Jaime, Wilson, Tom, and Sanchez, Alejandro #90044 (2005).
Search and Discovery.com
2005
Estimation of lithologies and depositional facies from wire-line logs
M. M. Saggaf, Ed L. Nebrija
AAPG Bulletin
... of identifying facies from well logs through the use of neural networks that perform vector quantization of input data by competitive learning. The method...
2000
Deep learning cross-basin identification of TOC-rich zones in shale formations
Adewale Amosu, Yuefeng Sun
International Meeting for Applied Geoscience and Energy (IMAGE)
... and single-layer artificial neural networks (ANN), have been used to predict TOC from well logs (Tan et al., 2015; Rui et al., 2019; Amosu et al...
2022
Seismic image-to-image translation using a conditional GAN with Bayesian inference
Xiaolei Song, Muhong Zhou, Petr Jilek, Rodney Johnston, Sean Cardinez, Kareem Vincent
International Meeting for Applied Geoscience and Energy (IMAGE)
... problems. Our framework is a composition of two neural networks trained in a joint fashion as follows: A generator G that makes the input (X) -output (Y...
2022
NLP applications in the oil and natural gas industry
Prashanth Pillai, Srikanth Ryali, Hiren Maniar, Purnaprajna Mangsuli, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
.../10.1162/neco.1997.9.8 .1735. Krizhevsky, A., I. Sutskever, and G.E. Hinton, 2012, ImageNet classification with deep convolutional neural networks: Communications...
2022
Deep learning in salt interpretation from R&D to deployment: Challenges and lessons learned
Pandu Devarakota, Apurva Gala, Zhenggang Li, Engin Alkan, Yihua Cai, John Kimbro, Dean Knott, Jeff Moore, Gislain Madiba
International Meeting for Applied Geoscience and Energy (IMAGE)
... 5% in test set. We have employed the standard encoder-decoder convolutional neural networks (CNNs) as a baseline architecture to train the models...
2022
Effects of Early-Time Production Data on Machine-Learning-Assisted Long-Term Production Forecasting
Mohammad H. Elkady, Siddharth Misra, Veena T. Kumar, Uchenna Odi, Andrew Silver
Unconventional Resources Technology Conference (URTEC)
..., the utilization of deep neural networks to capture complex relationships, and considerations such as data quality, overfitting prevention...
2024
A Way of TOC Characterization on Barnett and Woodford Shale; #80429 (2014)
Sumit Verma, Kurt Marfurt
Search and Discovery.com
... in the Barnett shale: Supervised probabilistic neural networks vs. unsupervised multi-attribute Kohonen SOM, 82nd Annual International Meeting, SEG...
2014
PWD-PINN: Slope-assisted seismic interpolation with physics-informed neural networks
Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
...PWD-PINN: Slope-assisted seismic interpolation with physics-informed neural networks Francesco Brandolin, Matteo Ravasi, Tariq Alkhalifah PWD-PINN...
2022
3D surface-consistent residual statics estimation by deep learning
Han Wang, Jie Zhang
International Meeting for Applied Geoscience and Energy (IMAGE)
... required in the stack power could be a serious computational burden. We develop a 3D residual statics method using deep neural networks to derive...
2022
Fluid and Petrophysical Prediction in the Elastic Impedance Domain Using Neural Network Technique; #41066 (2012)
M. Hermana, M. Najmi, Z.Z.T. Harith, and C.W. Sum
Search and Discovery.com
... logic and neural networks for determining the in-situ stress profile of hydrocarbon reservoirs. In this study, neural network will be used to predict...
2012
Understanding Attributes and Their Use in the Application of Neural Analysis Case Histories Both Conventional and Unconventional, #41473 (2014).
Deborah Sacrey, Rocky Roden
Search and Discovery.com
... volume Neural networks address the Big Data problem Neurons classifying data in 3 dimensions Amplitude Spec. Decomp. Curvature Dip Azimuth...
2014
Shale Gas Sweet Spot Identification using Quantitative Seismic Interpretation (QSI) and Neural Network in Krishna-Godavari Basin, India
Soumen Deshmukh, Shrey Omer, P. S. Tomor, Harilal
Unconventional Resources Technology Conference (URTEC)
... is shown in Figure 2. Figure 2. Workflow adopted for pre-stack inversion Neural networks form a broad category of computer algorithms that solve...
2020
Estimate near-surface velocity with reversals using deep learning and full-waveform inversion
Yong Ma, Xu Ji, Weiguang He, Tong Fei
International Meeting for Applied Geoscience and Energy (IMAGE)
...., 2018; Geng et al., 2022). It usually relies on convolutional neural networks (CNNs) and synthetic training data sets to learn complex and often...
2022
Prediction and Analysis of Geomechanical Properties using Deep Learning: A Permian Basin Case Study
Fatick Nath, Karina Murillo, Sarker Monojit Asish, Deepak Ganta, Valeria Limon, Edgardo Aguirre, Gabriel Aguirre, Happy R. Debi, Jose L. Perez, Cesar Netro, Flavio Borjas
Unconventional Resources Technology Conference (URTEC)
... of the geomechanical properties for the Permian Basin using ML and deep neural networks. The highest performance for a single well prediction using...
2022
Use of Seismic Geomorphology to Re-define Mature Fields: Application of Spectral Decomposition and Neural Networks to 3D Examples from Canada and Colombia; #41215 (2013)
Azer Mustaqeem and Valentina Baranova
Search and Discovery.com
...Use of Seismic Geomorphology to Re-define Mature Fields: Application of Spectral Decomposition and Neural Networks to 3D Examples from Canada...
2013
Probabilistic seismic interpolation with the implicit prior of a deep denoiser
Matteo Ravasi
International Meeting for Applied Geoscience and Energy (IMAGE)
... of Monte-Carlo Markov Chain methods. We present a flexible approach to probabilistic sampling that leverages the ability of denoising neural networks...
2023
Self-organizing mapping neural network analysis on seismic-sedimentary facies
Tianyun Wang, Yuan Li, Xiaoping Sun, Pei Ke, Tao Li, Hongxiao Ning, Wei Liu, Xiaofeng Han
International Meeting for Applied Geoscience and Energy (IMAGE)
..., and M. I. Marhoon, 2003, Seismic facies classification and identification by competritive neural networks: Geophysics, 68, 1984–1999, doi: https...
2022
Spatial statistical analysis and geomodelling of banana holes using point patterns and generative adversarial networks
Rayan Kanfar, Charles Breithaupt, Tapan Mukerji
International Meeting for Applied Geoscience and Energy (IMAGE)
...Spatial statistical analysis and geomodelling of banana holes using point patterns and generative adversarial networks Rayan Kanfar, Charles...
2023