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Proceedings Papers

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
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4081978
https://doi.org/10.1190/image2024-4081978.1
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Application of interactive convolutional neural network micro-fracture prediction technology based on prestack depth migration data in deep shale gas reservoirs

Xiaolan Wang, Furong Wu, Junfeng Liu, Dianguang Zang, Xiao Yang, Yangjing Li, Xiaoyan Cheng
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4091022
https://doi.org/10.1190/image2024-4091022.1
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View Paper titled, Application of interactive convolutional neural network micro-fracture prediction technology based on prestack depth migration data in deep shale gas reservoirs
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Enhancing seismic data quality: A machine learning approach to denoising and signal damage reduction

Mark Roberts, Olga Brusova, Leandro Gabioli, Alejandro Valenciano
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4094881
https://doi.org/10.1190/image2024-4094881.1
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View Paper titled, Enhancing seismic data quality: A machine learning approach to denoising and signal damage reduction
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Estimating remanent magnetization of Matachewan and Sudbury mafic dikes in the Abitibi greenstone belt from aeromagnetic data

Skye Hart, Yaoguo Li
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4072718
https://doi.org/10.1190/image2024-4072718.1
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View Paper titled, Estimating remanent magnetization of Matachewan and Sudbury mafic dikes in the Abitibi greenstone belt from aeromagnetic data
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Proceedings Papers

Introducing stochasticity into CNN-based property estimation from angle-stack seismic

Haibin Di, Tao Zhao, Aria Abubakar
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4076489
https://doi.org/10.1190/image2024-4076489.1
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View Paper titled, Introducing stochasticity into CNN-based property estimation from angle-stack seismic
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DiffSim: Denoising diffusion probabilistic models for generative facies geomodeling

Minghui Xu, Suihong Song, Tapan Mukerji
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4081304
https://doi.org/10.1190/image2024-4081304.1
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View Paper titled, DiffSim: Denoising diffusion probabilistic models for generative facies geomodeling
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Proceedings Papers

Massive focal mechanism solutions from deep learning in west Texas

Yangkang Chen, Omar M. Saad, Alexandros Savvaidis, Fangxue Zhang, Yunfeng Chen, Dino Huang, Huijian Li, Farzaneh Aziz Zanjani
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4081476
https://doi.org/10.1190/image2024-4081476.1
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View Paper titled, Massive focal mechanism solutions from deep learning in west Texas
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Proceedings Papers

3D deblending for marine towed-streamer data

Yangkang Chen, Min Zhou, Ray Abma
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4081664
https://doi.org/10.1190/image2024-4081664.1
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Unsupervised frequency space domain deep learning framework for reconstructing 5D seismic data

Gui Chen, Yang Liu, Haoran Zhang, Mi Zhang, Yuhang Sun
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4081840
https://doi.org/10.1190/image2024-4081840.1
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View Paper titled, Unsupervised frequency space domain deep learning framework for reconstructing 5D seismic data
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Using F-score and supervised-mode machine learning algorithms for pore structure prediction from well logs in the Eocene sandstones, Bohai Oilfield, China

Zongbin Liu, Yan Lu, Yang Zheng, Xiaolin Zhu, Xin Zhou
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4082479
https://doi.org/10.1190/image2024-4082479.1
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View Paper titled, Using F-score and supervised-mode machine learning algorithms for pore structure prediction from well logs in the Eocene sandstones, Bohai Oilfield, China
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Proceedings Papers

Improving fault resolution from multiple angle stacks by latent feature analysis with deep learning

Fan Jiang, Konstantin Osypov
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4083103
https://doi.org/10.1190/image2024-4083103.1
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View Paper titled, Improving fault resolution from multiple angle stacks by latent feature analysis with deep learning
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Proceedings Papers

Neural network-based seismic data conditioning: Case study of engineering seismic survey data

Juan Lee, Yongchae Cho
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4086279
https://doi.org/10.1190/image2024-4086279.1
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View Paper titled, Neural network-based seismic data conditioning: Case study of engineering seismic survey data
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Improve automatic migrated gather processing with feature engineering and 4D convolutional neural networks

Wen Pan, Harry Rynja, Ramakrishna Dandu, Zaifeng Liu, Shuzhen Ye, Antonio De Lilla, Jay Chen, Jeremy Vila
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4086530
https://doi.org/10.1190/image2024-4086530.1
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View Paper titled, Improve automatic migrated gather processing with feature engineering and 4D convolutional neural networks
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Semi-supervised ground-roll wave segmentation with noise label via neural network evolution

Yinshuo Li, Wenkai Lu
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4087062
https://doi.org/10.1190/image2024-4087062.1
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View Paper titled, Semi-supervised ground-roll wave segmentation with noise label via neural network evolution
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Proceedings Papers

Advancing autonomous seismic data acquisition with robotic solutions

Ezzedeen Alfataierge, Pavel Golikov, Ahmad Ramdani, Abdulrahman Alshuhail
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4087170
https://doi.org/10.1190/image2024-4087170.1
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Pushing the limit of 5D interpolation using deep learning

Yangkang Chen, Hang Wang, Chao Li, Omar M. Saad
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4087480
https://doi.org/10.1190/image2024-4087480.1
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Proceedings Papers

Attention-based self-calibrated convolution neural network for efficient facies classification

Motaz Alfarraj
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4087583
https://doi.org/10.1190/image2024-4087583.1
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View Paper titled, Attention-based self-calibrated convolution neural network for efficient facies classification
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Proceedings Papers

Backscatter analysis of vehicle-generated noise using symmetric autoencoders

Sanket Bajad, Pawan Bharadwaj
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4087618
https://doi.org/10.1190/image2024-4087618.1
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View Paper titled, Backscatter analysis of vehicle-generated noise using symmetric autoencoders
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Automatic well-log baseline correction via deep learning for rapid screening of potential CO 2 storage sites

Misael M. Morales, Carlos Torres-Verdín, Michael Pyrcz, Murray Christie, Vladimir Rabinovich
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4088064
https://doi.org/10.1190/image2024-4088064.1
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View Paper titled, Automatic well-log baseline correction via deep learning for rapid screening of potential CO 2 storage sites
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Proceedings Papers

JAX acceleration of implicit FWI and field data application

H. V. Nguyen, A. Sekar, K. Wang, T. Zhang, T. Nemeth, U. Albertin, M. Eaid, K. Nihei, E. Wang, K. Innanen
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4089099
https://doi.org/10.1190/image2024-4089099.1
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