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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Application of Artificial Intelligence for Depositional Facies Recognition - Permian Basin
Randall Miller, Skip Rhodes, Deepak Khosla, Fernando Nino
Unconventional Resources Technology Conference (URTEC)
... in the Permian Basin. Training sets of core facies were selected by a sedimentologist. A model was built using a convolutional neural network...
2019
Deep learning-based joint inversion of time-lapse surface gravity and seismic data for monitoring of 3D CO2 plumes
Adrian Celaya, Mauricio Araya-Polo
International Meeting for Applied Geoscience and Energy (IMAGE)
...s more memory and time during training. Our joint inversion model takes roughly 45s per epoch on 4 A100 GPUs with a batch size of 8. In contrast, D...
2024
Deep Learning Models for Methane Emissions Identification and Quantification
Ismot Jahan, Mohamed Mehana, Bulbul Ahmmed, Javier E. Santos, Dan O’Malley, Hari Viswanathan
Unconventional Resources Technology Conference (URTEC)
... in Jongaramrungruang et al., 2021; where details about the model parameterization and initialization can be found. The plume shape varies with time...
2023
Improving pre-stack inter-trace variation extraction with a self-supervised learning approach
Yifeng Fei, Xin He, Bangli Zou, Jiandong Liang, Dajun Li
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Notable examples include utilizing a geological and geophysical model-driven convolutional neural network (CNN) for the extraction of elastic parameter...
2024
Application of Deep Learning for Methane Emissions Quantification and Uncertainty Reduction from Spectrometer Images
Ismot Jahan, Mohamed Mehana, Hari Viswanathan
Unconventional Resources Technology Conference (URTEC)
... oil and gas fields in the fields of Texas, California and New Mexico. Methods: We trained a convolutional neural network (CNN) using Large Eddy...
2024
Comparison of Seismic Reconvolution and Gabor Deconvolution in Improving Seismic Images to Detect Local Fluid Trapping
Madaniya Oktariena, Wahyu Triyoso
Indonesian Petroleum Association
.... The convolutional model is constructed using the Gabor Transform of a non-stationary seismic to estimate Gabor Transform of the reflectivity. While...
2016
Integrating U-net with full-waveform inversion for an efficient salt body construction
Abdullah Alaliand, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
..., T., 2016, Full-model wavenumber inversion: An emphasis on the appropriate wavenumber continuation: Geophysics, 81, no. 3, R89–R98, doi: https...
2022
Interactive channel interpretation using deep learning
Hao Zhang, Peimin Zhu, Zhiying Liao, Zewei Li, Dianyong Ruan
International Meeting for Applied Geoscience and Energy (IMAGE)
..., it is difficult to extract channels completely. With the development of machine learning technology, convolutional neural network (CNN) is widely...
2022
Facies-constrained elastic full-waveform inversion for tilted orthorhombic media
Ashish Kumar, Ilya Tsvankin
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutional neural networks to mitigate the influence of tradeoffs and increase the spatial resolution of FWI. The developed CNN generates a facies model...
2024
Inference of Induced Fracture Geometries Using Fiber-Optic Distributed Strain Sensing in Hydraulic Fracture Test Site 2
Stephen Bourne, Kees Hindriks, Alexei A. Savitski, Gustavo A. Ugueto, Magdalena Wojtaszek
Unconventional Resources Technology Conference (URTEC)
...al fracture apertures. Conclusions The convolutional model provides a rapid method for simulating the time-depth distribution of fiber strains or strain rates i...
2021
Abstract: Seismic Characterization of Complex Salt Dome Structures using Machine Learning; #91204 (2023)
Osama Alsalmi, Saleh Dossary, Gino Ananos
Search and Discovery.com
.... Convolutional Neural Networks (CNNs) gained popularity in image segmentation tasks. In this study, a machine learning model based on U-Net architecture is used...
2023
-- no title --
user1
Search and Discovery.com
... and optimization in seismic interpretation workflow. The existing workflow for seismic interpretation using Convolutional Neural Network (CNN) relies...
Unknown
Velocity continuation with Fourier neural operators for accelerated uncertainty quantification
Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
International Meeting for Applied Geoscience and Energy (IMAGE)
... be started as the same time as the background model posterior sampling phase, using the already collected posterior samples as training data. In the next...
2022
Transformer-based deep learning model for accurate rate of penetration prediction in drilling
Carlos Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... vary over time. To overcome these challenges, this study introduces a novel approach utilizing a transformer-based deep learning model, which is well...
2023
Abstract: Seismic Fault Detection by Denoising Diffusion Probabilistic Model; #91204 (2023)
Bingbing Sun, Ali Abdulmohsen, Nasher AlBinHassan
Search and Discovery.com
...Abstract: Seismic Fault Detection by Denoising Diffusion Probabilistic Model; #91204 (2023) Bingbing Sun, Ali Abdulmohsen, Nasher AlBinHassan Seismic...
2023
GAN based data enhancement for first arrival picking on both onshore and offshore seismic data
Ding Jicai, Wei Yanwen, Wang Yichuan, Sun Wenbo, Wang Jianhua
International Meeting for Applied Geoscience and Energy (IMAGE)
... be studied from three perspectives: data, models, and algorithms (Wang et al., 2020; Ding et al., 2024). Among the three perspectives of data, model...
2024
The Hybrid Theory-Guided Data Science-Based Method: Unlocking the Full Potential of Seismic Reservoirs Characterization
Rino Saputra, Akash Mathur, Awal Mandong
Indonesian Petroleum Association
... model. 5. Synthetic angle gathers are then generated for each pseudo-well using a convolutional model in which the P-wave reflection coefficients...
2023
Hierarchical machine learning workflow for conditional and multiscale deep-water reservoir modeling
Wen Pan, Honggeun Jo, Javier E. Santos, Carlos Torres-Verdín, and Michael J. Pyrcz
AAPG Bulletin
... a stratigraphic time difference T, is the averaged sedimentation rate, and A is the lateral area of a model. The leading coefficient a and CI κ...
2022
An Introduction to Deep Learning: Part II
Lasse Amundsen, Hongbo Zhou, Martin Landrø
GEO ExPro Magazine
... often the model fails to predict the correct answer in their top five guesses (the top-5 error rate), in descending order of confidence. ILSVRC 2012...
2017
Using Machine Learning to Automate FDI Analysis
Reid Thompson, Lance Legel, Thomas Hanlon
Unconventional Resources Technology Conference (URTEC)
... is an automated stage detection model. The core of the stage detection model is a onedimensional deep convolutional U-net neural network with residual layers...
2024
GPU-based 3D anisotropic elastic modeling using mimetic finite differences
Harpreet Singh, Jeffrey Shragge, Ilya Tsvankin, Fatmir Hoxha
International Meeting for Applied Geoscience and Energy (IMAGE)
...., and B. Tapley, 2017, Solving the tensorial 3D acoustic wave equation: A mimetic finite-difference time-domain approach: Geophysics, 82, no. 4, T183...
2022
Boulder prediction for offshore windfarm site evaluation using an interactive 2D CNN and a unique weighting scheme on unmigrated seismic
Samuel Chambers, Jesse Lomask
International Meeting for Applied Geoscience and Energy (IMAGE)
.... This gives the model a basic understanding of what to look for, and how to create the segmented output. The basic convolutional synthetic data was created...
2023
MACHINE LEARNING UTILIZATION FOR ENHANCED SUCKER ROD PUMP DYNACARD RECOGNITION
Fadhila Tanjungsari, Hilman Lazuardi, Bonni Ariwibowo, Indra Sukmana, and Candra Kurniawan
Indonesian Petroleum Association
...% testing datasets, and 10% validation datasets. Different machine learning algorithms were evaluated, and it is found that the top performing model...
2025
Complete detection of small earthquakes uncovers intricate relation between injection and seismicity
Yangkang Chen, Alexandros Savvaidis, Omar M. Saad, Daniel Siervo, Dino Huang, Yunfeng Chen, Iason Grigoratos, Sergey Fomel, Caroline Breton
International Meeting for Applied Geoscience and Energy (IMAGE)
... earthquake compact convolutional transformer (EQCCT) for training a model to pick the P- and S-wave from 3-C earthquake waveforms in Texas (Hassani et...
2024
Improving Depth Prediction Accuracy of Quantified Drilling Hazards
W. Scott Leaney, William H. Borland
Geological Society of Malaysia (GSM)
... problem without a forward problem, and the forward problem underlying seismic trace inversion is the convolutional model. A processed seismic trace...
1996