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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Seismic resolution enhancement with self-supervised learning
Shijun Cheng, Tariq Alkhalifah, Haoran Zhang
International Meeting for Applied Geoscience and Energy (IMAGE)
... et al. (2023) incorporated the convolutional model into the loss function in a self-supervised manner to constrain the network’s predicted outcomes...
2024
CMP domain near-surface velocity model building based on deep learning
Yihao Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... model building method from raw seismic shot gathers by using a fully convolutional neural network (FCN). Feng et al. (2020) apply physically realistic...
2022
A flexible and versatile joint inversion framework using deep learning
Yanyan Hu, Jiefu Chen, Xuqing Wu, Yueqin Huang
International Meeting for Applied Geoscience and Energy (IMAGE)
... and prospects. Unlike conventional end-to-end networks that map directly from the data domain to the model domain, this DLE framework is designed...
2022
VSP Guided Reprocessing and Inversion of Surface Seismic Data
R. Gir, Dominique Pajot, Serge Des Ligneris
Southeast Asia Petroleum Exploration Society (SEAPEX)
... seismic data is known as the “convolutional model of the seismogram”. This model states that after proper data processing, the final seismic data has...
1988
A novel deep learning-assisted reservoir fracture delineation with conditional generative adversarial networks
Ardiansyah Koeshidayatullah, Ivan Ferreira
International Meeting for Applied Geoscience and Energy (IMAGE)
...) model being chosen to test the abilities of image domain-translation in geoscientific tasks. This architecture uses a U-Net Ronneberger et al. (2015...
2022
Abstract: Integrating Geologic and Geophysical Data in Geostatistical Inversion; #90187 (2014)
John V. Pendrel
Search and Discovery.com
... constraints are applied simultaneously The seismic and reservoir properties are related through a predictive rock physics model The facies definitions...
2014
Improving fault resolution from multiple angle stacks by latent feature analysis with deep learning
Fan Jiang, Konstantin Osypov
International Meeting for Applied Geoscience and Energy (IMAGE)
... the ultimate "best-of-all" output. In this abstract, we use the convolutional network to analyze each predicted fault in latent space and then combine...
2024
Deep learning approach for denoising and resolution enhancement of poststack seismic data
Ruslan Malikov, Tatyana Yusubova, Izat Shahsenov
International Meeting for Applied Geoscience and Energy (IMAGE)
... structure. To mimic real geological structures, folding, and tilting are added by vertically shifting the initial model. The fault complexes are added...
2024
An application of FWI with progressive transfer learning
Shirui Wang, Jinjun Liu, Yuchen Jin, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
..., University of Houston Summary The lack of low-frequency data components has been a major obstacle in FWI applications for velocity model building...
2022
Estimating soil strength using ultra high-resolution seismic and geological unit
Donglin Zhu, Ge Jin, Yi Shen, Xuefeng Shang, Shuang Hu, Jinbo Chen, Vanessa Goh
International Meeting for Applied Geoscience and Energy (IMAGE)
... soil assessment for foundation design, due to their high foundation costs and complex integration into marine environments. We propose a convolutional...
2024
Transfer learning seismic and GPR diffraction separation with a convolutional neural network
Alexander Bauer, Jan Walda, Dirk Gajewski
International Meeting for Applied Geoscience and Energy (IMAGE)
...Transfer learning seismic and GPR diffraction separation with a convolutional neural network Alexander Bauer, Jan Walda, Dirk Gajewski Transfer...
2022
Fluid distribution modeling impact on estimating CO2 saturation in Cranfield: A capillary pressure equilibrium approach with invertible neural networks
Sohini Dasgupta, Arnab Dhara, Mrinal K. Sen
International Meeting for Applied Geoscience and Energy (IMAGE)
... inversion strategy which uses a capillary pressure based rock physics model with invertible neural networks (INNs) to estimate CO2 saturation...
2024
AVA attribute estimation from misaligned seismic gathers using U-Net
Ammar Ghanim, Ricard Durall, Norman Ettrich
International Meeting for Applied Geoscience and Energy (IMAGE)
... are mainly caused by inaccuracies in the velocity model used during migration. Aligning these reflections in seismic normal moveout (NMO) corrected...
2024
Machine learning-based residual moveout picking
Farhad Bazargani, Wenjun Zhang, Anu Chandran, Zaifeng Liu, Harry Rynja
International Meeting for Applied Geoscience and Energy (IMAGE)
... in the migration velocity model. Accurate and efficient RMO picking is the key to the success of tomographic velocity model building workflows. Conventional RMO...
2022
Reliability estimation of the prediction results by 1D deep learning ATEM inversion using maximum depth of investigation
Hyeonwoo Kang, Minkyu Bang, Soon Jee Seol, Joongmoo Byun
International Meeting for Applied Geoscience and Energy (IMAGE)
... neural network is overlaid on the predicted resistivities by the trained ConvNeXt model to provide the guideline of the prediction reliability...
2022
A deep learning-based inverse Hessian for full-waveform inversion
Mustafa Alfarhan, Matteo Ravasi, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... the entire seismic waveform data at once to construct a high resolution subsurface model. The data misfit between the modeled data, obtained from...
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)
... assist in characterizing the subsurface. By adopting the stationary convolution model, seismic reflectivity inversion is posed as a multichannel deblurring...
2022
Abstracts: Full Waveform Inversion Using One-way Migration and Well Calibration; #90173 (2015)
Gary F. Margrave, Robert J. Ferguson, and Chad M. Hogan
Search and Discovery.com
... model is proportional to a reverse-time migration of the data residual (the difference between the actual data and data predicted by the model) where...
2015
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
Research and application of Intelligent high resolution processing method based on ISTA-Net
Huahui Zeng, Qin Su, Sanyi Yuan, Lide Wang, Yanwu Xu, Huijie Meng, Deying Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... of these methods in mathematical form and numerical test. Yuan et al. (2021) established a connection between traditional model-driven high-resolution processing...
2024
Jointly data and model driven pre-stack inversion of elastic and anisotropy parameters in HTI media
Xin Zhang, Jianhua Geng
International Meeting for Applied Geoscience and Energy (IMAGE)
...Jointly data and model driven pre-stack inversion of elastic and anisotropy parameters in HTI media Xin Zhang, Jianhua Geng Jointly data and model...
2024
Towards Universal Production Forecasting via Adversarial Transfer Learning and Transformer with Application in the Shengli Oilfield, China
Ji Chang, Jin Meng, Dongwei Zhang, Tianrui Ye, Han Wang, Yitian Xiao
Unconventional Resources Technology Conference (URTEC)
... an adversarial transfer-assisted transformer model, which utilizes advanced transfer learning techniques to achieve more accurate and universally...
2024
Lithology and Fluid Seismic Determination for the Acae Area, Puerto Colon Oil Field, Colombia
F. H. Gómez, J. P. Castagna
Asociación Colombiana de Geólogos y Geofisicos del Petróleo (ACGGP)
... of matching model reflectivity from well logs to that contained in the seismic data; * Attribute analysis to predict petrophysical properties from seismic...
2004
An immersed absorbing boundary condition for scalar wavefield modeling under topography
KeJi Chen, Hanming Chen, Hui Zhou
International Meeting for Applied Geoscience and Energy (IMAGE)
... of electromagnetic waves. Roden and Gedney (2000) developed a convolutional PML (CPML) that was later introduced to seismic modeling by Komatitsch...
2022
Micro transient EM for seismic sand corrections through physics-coupled deep learning
Daniele Colombo, Ersan Turkoglu, Ernesto Sandoval-Curiel, Javier Giraldo-Buitrago
International Meeting for Applied Geoscience and Energy (IMAGE)
.... data-driven approaches (e.g., tomography), at exploration seismic acquisition specifications, are inadequate to reliably model the extremely low sand...
2022