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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Deep learning-based Vz-noise attenuation for OBS data
Jing Sun, Arash Jafargandomi, Julian Holden
International Meeting for Applied Geoscience and Energy (IMAGE)
... component is its coherency in the common-receiver domain and incoherency in the commonshot domain. There have been a range of noise attenuation...
2023
Seismic reflectivity inversion via a regularized deep image prior
Hongling Chen, Mauricio D. Sacchi, Jinghuai Gao
International Meeting for Applied Geoscience and Energy (IMAGE)
... deconvolution with frequency-domain constraints: Geophysics, 59, 938– 945, doi: https://doi.org/10.1190/1.1443653. Shi, Y., X. Wu, and S. Fomel, 2020...
2022
Abstract: Kirchhoff Imaging with Adaptive Greens Functions for Compensation for Dispersion, Attenuation, and Velocity Imprecision; #90187 (2014)
Andrew V. Barrett
Search and Discovery.com
... frequencies appear to propagate at the velocity of the asymptotic high frequency. If we know the attenuation constant ‘Q’, and if the model for attenuation...
2014
Abstract: Grain Segmentation and Region Mask Generation in Digital Rock Images Using Convolutional Neural Networks;
Rengarajan Pelapur, Arash Aghaei, Connor Burt, Bidur Bohara
Search and Discovery.com
... neural networks. This model is trained on a database of rock models generated using a 3D process-based modeling technique. Convolutional Neural Network...
Unknown
Deep learning based automatic marker separation
Atul Laxman Katole, Aria Abubakar, Edo Hoekstra, Srikanth Ryali, Tao Zhao
International Meeting for Applied Geoscience and Energy (IMAGE)
... entirely dispenses with convolutional and recurrence-based approaches, and instead rely on the attention mechanism to model the sequential nature...
2023
Predicting horizons for salt body models using machine learning from neighboring seismic surveys: A case study from the northern Gulf of Mexico
Andrew Reisdorf, Dan Ferdinand Fernandez, Hugo Enrique Munoz Cuenca, Ryan King, David Manzano, Gavin Menzel-Jones
International Meeting for Applied Geoscience and Energy (IMAGE)
... and manual effort are required to provide horizons that are input into the earth model building process. The quality of these horizons determines...
2022
Pyseis: A high-performance, user-friendly Python package for GPU-accelerated seismic modeling and subsurface imaging
Stuart Farris, Guillaume Barnier, Ettore Biondi, Robert Clapp
International Meeting for Applied Geoscience and Energy (IMAGE)
... NVIDIA V100 GPU. In these tests, we kept the number of time steps constant while varying the size of the model domain, a realistic scenario where high...
2023
Seismic inversion with dictionary learning using unsupervised machine learning
Debajeet Barman, Mrinal K. Sen
International Meeting for Applied Geoscience and Energy (IMAGE)
... (ML) has recently gained immense popularity in almost every field. This popularity is attributed to the invention of the Convolutional Neural Network...
2022
Abstract: AI- Assisted Palynological Analysis Using an Expert-Trained Convolutional Neural Network: A Case Study form the Jurassic in the North Sea; #91204 (2023)
Rader Abdul Fattah, Merijn de Bakker, Alexander Houben, Roel Verreussel, Robert Williams
Search and Discovery.com
...Abstract: AI- Assisted Palynological Analysis Using an Expert-Trained Convolutional Neural Network: A Case Study form the Jurassic in the North Sea...
2023
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
Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential
Kellen L. Gunderson, Zhao Zhang, Barton Payne, Shuxing Cheng, Ziyu Jiang, and Atlas Wang
AAPG Bulletin
... geometric invariance-enforced deep learning based on the Mask region-based convolutional neural network (R-CNN) model. Mask R-CNN is a deep learning model...
2022
Seismic image resolution enhancement with limited-well datasets using deep learning
Son Phan, Haibin Di, Wenyi Hu, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Lee, M. W., 1986, Spectral whitening in the frequency domain: USGS, 86–108. Li, J., X. Wu, and Z. Hu, 2021, Deep learning for simultaneous seismic...
2024
Implementation of Seismic Data Quality Characterisation Using Supervised Deep Learning
Joshua Thorp, Krista Davies, Julien Bluteau, Peter Hoiles
Australian Petroleum Production & Exploration Association (APPEA) Journal
... convolutional autoencoders. Geophysics 83, A39–A43. doi:10.1190/geo2017-0524.1 Tishchenko, I. (2016). Different methods of QC the low frequency content...
2020
Extending Engine Change Out Respective to Running Hours Using Data Driven Using One Dimension (1-D) Convolutional Neural Network Algorithm
Subhan Malik, Harry Poetra Soedarsono
Indonesian Petroleum Association
...Extending Engine Change Out Respective to Running Hours Using Data Driven Using One Dimension (1-D) Convolutional Neural Network Algorithm Subhan...
2024
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)
... measurement from the DAS VSP data can help to detect injected CO2 at the FRS. Attenuation model and measurement In the frequency domain, the non-stationary...
2022
Marchenko focusing using convolutional neural networks
Mert S. R. Kiraz, Roel Snieder
International Meeting for Applied Geoscience and Energy (IMAGE)
...Marchenko focusing using convolutional neural networks Mert S. R. Kiraz, Roel Snieder Marchenko focusing using convolutional neural networks Mert...
2022
The impact of the synthetic seismic data generation method on automated AI-based horizon interpretation
F. Vizeu, J. Zambrini, A. Canning
International Meeting for Applied Geoscience and Energy (IMAGE)
... by using the convolutional model with full control of the synthetic wavelet, and add noise to it. To convert the 2D data into 3D we use a technique...
2023
Abstract: Automated Fault Detection from 3-D Seismic Using Artificial Intelligence Practical Application and Examples from the Gulf of Mexico and North Slope Alaska;
Andrew Pomroy, Zachary Wolfe
Search and Discovery.com
... in the realm of seismic attributes given its well established strengths in image pattern analysis and recognition. With this in mind, a Convolutional...
Unknown
Abstract: New Approach to Finite-Difference Memory Variables by Using Lagrangian Mechanics; #90187 (2014)
Wubing Deng and Igor Morozov
Search and Discovery.com
... J (Pa.s) k Figure 1. Dissipation factor as a function of frequency for a GSLS model with five Maxwell bodies. k J (MPa) 1000 15 15 15 15 15...
2014
SaltCrawler: AI solution for accelerating velocity model building
Engin Alkan, Yihua Cai, Pandu Devarakota, Apurva Gala, John Kimbro, Dean Knott, Gislain Madiba, Jeff Moore
International Meeting for Applied Geoscience and Energy (IMAGE)
... have recently increased in seismic imaging and velocity model building. We have seen many publications in this domain (Shi 2019, Zeng 2019, Kaul 2021...
2022
High-resolution prestack seismic inversion of reservoir parameters using an arch network
Ting Chen, Yaojun Wang, Yuan Yuan, Gang Yu, Guangmin Hu
International Meeting for Applied Geoscience and Energy (IMAGE)
... to be normalized at the beginning, and then 2 wells are used to construct the initial low-frequency model for the conventional pre-stack inversion. The initial...
2022
Abstract: Machine Learning and Deep Learning in Oil and Gas Industry: A Review Ofapplications, Opportunities and Challenges; #91204 (2023)
Tejas Balasaheb Sabale, Syed Aaquib Hussain, Mohd Zuhair, Mohammad Saud Afzal, Arnab Ghosh
Search and Discovery.com
... algorithms to predict the outcome correctly [17]. The model is initialized with control parameters and then the input data is fed into the model...
2023
Interbed Multiple Suppression in Carbonate Sequences
Gabriel Gil
Unconventional Resources Technology Conference (URTEC)
... transform. The presented workflow shows a model-based approach to predict and suppress the presence of interbed multiples from migrated pre-stack data...
2025
Abstract: Can Q Explain Observations Made from a VSP?, by Hamish Wilson, Scott W. Peters, and Robert W. Wiley; #90105 (2010)
Search and Discovery.com
2010
Deep Learning for Quantitative Hydraulic Fracture Profiling from Fiber Optic Measurements
Weichang Li, Han Lu, Yuchen Jin, Frode Hveding
Unconventional Resources Technology Conference (URTEC)
... to the synced pump data independently; and II) a convolutional LSTM (long short-term memory) sequence learning model maps time segments...
2021