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The AAPG/Datapages Combined Publications Database
Showing 23,346 Results. Searched 200,619 documents.
Machine-learning Facilitates Prediction of Geomechanical Properties Directly From SEM Images in Unconventional Plays
Heehwan Yang, Deepak Devegowda, Mark Curtis, Chandra Rai
Unconventional Resources Technology Conference (URTEC)
... non-parametric regression resulting in a unified, easily generalizable model that performs robustly when tested against previously unseen images. Our...
2023
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
... patterns emerges in different time frames. In this paper, the ability of a purely data driven deep learning model to handle non-stationary production...
2021
Introduction to Deep Learning: Part I
Hongbo Zhou, Lasse Amundsen, Martin Landrø
GEO ExPro Magazine
... of some objective or loss function on a training set of examples. Loss functions express the misfit between the predictions of the model being...
2017
Estimation of anisotropic parameters from semblance picking using dynamic programming
Hong Liang, Houzhu (James) Zhang, Dongliang Zhang, Hongwei Liu, Xu Ji
International Meeting for Applied Geoscience and Energy (IMAGE)
... and anisotropic parameters from the semblance panels. We apply the automatic model building workflow to synthetic and field data examples to demonstrate...
2022
Applying deep learning for identifying bioturbation from core photographs
Eric Timmer, Calla Knudson, and Murray Gingras
AAPG Bulletin
... to the convolutional layers to reduce model overfitting (Srivastava et al., 2014). Overfitting occurs when the neural network memorizes the data set...
2021
Modeling Distributed Fiber Optic Sensor Signals Using Computational Rock Mechanics
Christopher S. Sherman, Robert J. Mellors, Joseph P. Morris, Frederick J. Ryerson
Unconventional Resources Technology Conference (URTEC)
... with the 3D thermo-hydro-mechanical (THM) code GEOS. GEOS is a flexible and well-validated code designed to model subsurface fractures. It has been used...
2018
Fracture Diagnostics in Naturally Fractured Formations: An Efficient Geomechanical Microseismic Inversion Model
Meng Cao, Mukul M. Sharma
Unconventional Resources Technology Conference (URTEC)
...Fracture Diagnostics in Naturally Fractured Formations: An Efficient Geomechanical Microseismic Inversion Model Meng Cao, Mukul M. Sharma URTeC...
2022
Bi-directional LSTM-based non-causal deconvolution
G. Roncoroni, I. Deiana, E. Forte, M. Pipan
International Meeting for Applied Geoscience and Energy (IMAGE)
...). To generate the training dataset, we used a modified convolutional model defined as: where tracei and traceo represent the input and the reference output...
2024
Marchenko redatuming and seismic interferometry based internal multiple prediction for salt structures
Zhiwei Gu, Jianhua Geng, Ru-Shan Wu
International Meeting for Applied Geoscience and Energy (IMAGE)
... of the background velocity model, the recorded data can be accurately redatumed to a target area by solving coupled Marchenko equations. Then, an image without...
2023
Deep learning Laplace-Fourier full-waveform inversion with virtual supershot gathers
Lei Fu, Daniele Colombo, Weichang Li, Ernesto Sandoval-Curiel, Ersan Turkoglu
International Meeting for Applied Geoscience and Energy (IMAGE)
... the velocity model from seismic data organized in the virtual super gathers (VSG) in the Laplace-Fourier domain by deep learning network (DNN). The proposed new...
2022
Time-lapse attenuation variations during CO2 injection using DAS VSP data from the CaMI Field Research Station, Alberta, Canada
Yichuan Wang, Donald C. Lawton
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutional model for seismic reflection signal is A(t, f ) = S ( f ) R (t, f ) F (t, f ) G (t ) , (1) where A(t, f) is the time-frequency variant...
2022
Abstract: Color Correction for Gabor Deconvolution and Nonstationary Phase Rotation; #90171 (2013)
Peng Cheng and Gary F. Margrave
Search and Discovery.com
... deconvolution is based on a nonstationary convolution model of the seismic trace. Margrave (1998) presented a nonstationary convolutional model, which...
2013
Abstract: Color Correction for Gabor Deconvolution and Nonstationary Phase Rotation; #90171 (2013)
Peng Cheng and Gary F. Margrave
Search and Discovery.com
... deconvolution is based on a nonstationary convolution model of the seismic trace. Margrave (1998) presented a nonstationary convolutional model, which...
2013
Generating high-quality labels for deep learning CO2 monitoring using local orthogonalization
Shuang Gao, Sergey Fomel, Yangkang Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... label generation. We implement a modified 3D U-Net deep learning model to interpret the seismic attributes associated with CO2 injections for complex...
2024
Generating geophysical models from text for constructing the dataset of learning-based MT inversion
Yutong Li, Hongyu Zhou, Rui Guo, Maokun Li, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
... of text embedding is the bag-of-words model, where each extracted key point is quantized into one of the visual words, and each image is represented...
2023
An AI approach to using magnetic gradient tensor analysis for quick depth and property estimation
David A. Pratt, K. Blair McKenzie, Anthony S. White
Petroleum Exploration Society of Australia (PESA)
... and improve geological model style selection in the AI system. Pratt, D.A., McKenzie, K.B., White, A.S., Foss, C.A., Shamin, A. and Shi, Z., 2001 A user...
2019
Source location using physics-informed neural networks with hard constraints
Xinquan Huang, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... allows for direct image extraction of the subsurface using inverse Fourier transform. Numerical tests on the Overthrust model demonstrate...
2022
Abstract: Fast and Accurate Impedance Inversion by Well-Log Calibration; #90171 (2013)
Igor B. Morozov and Jinfeng Ma
Search and Discovery.com
...) the convolutional equation; 2) time-depth constraints from the seismic data, 3) background low-frequency model from the logs or seismic/geological interpretation...
2013
Enhancing Lithology Classification through a Deep Learning Framework
P. Zhang, T. Gao, R. Li
Unconventional Resources Technology Conference (URTEC)
..., more data typically improves model accuracy but also increases costs, this research optimizes the utility of existing and common logs. To leverage...
2025
Machine-Learning Driven Prediction of Geological Marker Signatures
Shashin Sharan, Kaustubh Shrivastava, Per Irgens, Tatjana Scherschel
Unconventional Resources Technology Conference (URTEC)
... to predict markers. The procedure involves three steps: data conditioning, feature extraction, and model training. Initially, log data is preprocessed...
2025
Abstracts: Revisiting Homomorphic Wavelet Estimation and Phase Unwrapping; #90173 (2015)
Roberto H. Herrera and Mirko van der Baan
Search and Discovery.com
... given as a convolution between the propagating wavelet and the reflectivity series of the earth and normally it is assumed that a white noise is added...
2015
Abstract: Structural evolution and deformation of the Caledonian Highlands, New Brunswick: a preliminary model
Adrian F. Park, Andrew C. Parmenter, Sandra M. Barr, Chris E. White, Peter H. Reynolds
Atlantic Geology
..., New Brunswick: a preliminary model Adrian F. Park 1 , Andrew C. Parmenter 1 , Sandra M. Barr 2 , Chris E. White 3 , and Peter H. Reynolds 4 1...
2009
Fault MLReal: A fault delineation study for the Decatur CO2 field data using neural network predicted passive seismic locations
Hanchen Wang, Yinpeng Chen, Tariq Alkhalifah, Youzuo Lin
International Meeting for Applied Geoscience and Energy (IMAGE)
... for mitigating climate change by reducing greenhouse gas emissions, particularly CO2, from industrial and energy-related sources (White et al., 2016...
2023
Abstract: Innovative QCs for More Effective 4D Processing; #90187 (2014)
Cyril Saint Andre, Benoit Blanco, Christian Hubans, and Benoit Paternoster
Search and Discovery.com
... problem in the framework of the 1D convolutional model. This attribute and the following developments were initially detailed by Cantillo (2012) [3...
2014
Abstract: Deterministic Marine Deghosting: Tutorial and Recent Advances; #90224 (2015)
Mike J. Perz and Hassan Masoomzadeh
Search and Discovery.com
... violates the convolutional model that forms the cornerstone of the derivation of our deterministic deghosting operator, and would lead to unacceptable...
2015