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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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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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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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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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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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Feature template based nonlinear time difference correction for first break automatic picking

Chao Ning, Huazhong Wang, Bo Feng, Chengliang Wu
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4100627
https://doi.org/10.1190/image2024-4100627.1
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Automating the thresholding of multi-stage iterative source separation with priors using machine learning

Nam Pham, Rajiv Kumar, Sunil Manikani, Yousif Izzeldin Kamil Amin, Phillip Bilsby, Massimiliano Vassallo, Tao Zhao
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4100817
https://doi.org/10.1190/image2024-4100817.1
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View Paper titled, Automating the thresholding of multi-stage iterative source separation with priors using machine learning
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Proceedings Papers

Guided strategies for improving machine learning models applied to geophysical problems

Satyan Singh, Konstantin Osypov, Graham Baines, Mark Willis
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101010
https://doi.org/10.1190/image2024-4101010.1
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Nano-enhanced drilling fluids: Effects of MgO and ZnO nanoparticles on rheological properties and ANN modeling for predictive analysis

Moamen Gasser, Taha Yehia, Hossam Ebaid, Nathan Meehan, Omar Mahmoud
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101073
https://doi.org/10.1190/image2024-4101073.1
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View Paper titled, Nano-enhanced drilling fluids: Effects of MgO and ZnO nanoparticles on rheological properties and ANN modeling for predictive analysis
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Evaluation of AI-enhanced processing for automated passive seismic detection and location

Aaron Booterbaugh, Evgeny Naumov
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101278
https://doi.org/10.1190/image2024-4101278.1
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View Paper titled, Evaluation of AI-enhanced processing for automated passive seismic detection and location
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Efficient Bayesian full-waveform inversion using a deep convolutional autoencoder prior

Shuhua Hu, Mrinal K Sen, Zeyu Zhao, Abdelrahman Elmeliegy, Shuo Zhang
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101311
https://doi.org/10.1190/image2024-4101311.1
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View Paper titled, Efficient Bayesian full-waveform inversion using a deep convolutional autoencoder prior
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From well logs to 3D models: A case study of automated stratigraphic correlation in the Midland Basin

Keyla Gonzalez, Zoltan Sylvester, Alejandro Valenciano, Ben Lasscock
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101544
https://doi.org/10.1190/image2024-4101544.1
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Machine learning and explainable AI for predicting missing well log data with uncertainty analysis: A case study in the Norwegian North Sea

Sushil Acharya, Karl Fabian
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101553
https://doi.org/10.1190/image2024-4101553.1
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View Paper titled, Machine learning and explainable AI for predicting missing well log data with uncertainty analysis: A case study in the Norwegian North Sea
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ZTEM natural field EM-magnetic case study and mineral targeting results over the Huckleberry Cu-Mo Porphyry project, northwestern British Columbia

Jean M. Legault, Karl Kwan, Derek Saxton, Jim Miller-Tait
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101601
https://doi.org/10.1190/image2024-4101601.1
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View Paper titled, ZTEM natural field EM-magnetic case study and mineral targeting results over the Huckleberry Cu-Mo Porphyry project, northwestern British Columbia
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Proceedings Papers

Is the human-in-the-loop necessary to accurately apply large language models for enterprise decision-making?

Amit Juneja, Mahir Morshed, John Harvill, Mark Hasegawa-Johnson, Henri Blondelle
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101715
https://doi.org/10.1190/image2024-4101715.1
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Proceedings Papers

Generating high-quality labels for deep learning CO 2 monitoring using local orthogonalization

Shuang Gao, Sergey Fomel, Yangkang Chen
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4101934
https://doi.org/10.1190/image2024-4101934.1
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View Paper titled, Generating high-quality labels for deep learning CO 2 monitoring using local orthogonalization
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Proceedings Papers

Bayesian uncertainty quantification for reservoir parameter changes estimated from time-lapse machine learning

Jinsong Chen, Chang Li, Lei Wei, Anusha Sekar, Maisha Amaru
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4089869
https://doi.org/10.1190/image2024-4089869.1
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View Paper titled, Bayesian uncertainty quantification for reservoir parameter changes estimated from time-lapse machine learning
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Proceedings Papers

Conditional image prior for uncertainty quantification in full-waveform inversion

Lingyun Yang, Omar M. Saad, Tariq Alkhalifah, Guochen Wu
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4090025
https://doi.org/10.1190/image2024-4090025.1
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View Paper titled, Conditional image prior for uncertainty quantification in full-waveform inversion
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Enhancing seismic delineation of obscured geologic architectural elements in a deepwater channel complex through multi-attribute analysis: A study from the Taranaki Basin

April Moreno-Ward, Heather Bedle, Alexandro Vera-Arroyo
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4090516
https://doi.org/10.1190/image2024-4090516.1
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View Paper titled, Enhancing seismic delineation of obscured geologic architectural elements in a deepwater channel complex through multi-attribute analysis: A study from the Taranaki Basin
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Proceedings Papers

Refraction multiple attenuation by pattern-based machine learning with a case study

Chunming Wang, Xiaohong Chen, Yongsheng Wang, Christof Stork, Sissy Theisen, Seann Day, Junru Jiao, Grace Yan, Xianhuai Zhu
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 26–29, 2024
Paper Number: SEG-2024-4091349
https://doi.org/10.1190/image2024-4091349.1
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View Paper titled, Refraction multiple attenuation by pattern-based machine learning with a case study
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