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The AAPG/Datapages Combined Publications Database
Showing 624 Results. Searched 200,691 documents.
Automatic well-log baseline correction via deep learning for rapid screening of potential CO2 storage sites
Misael M. Morales, Carlos Torres-Verdín, Michael Pyrcz, Murray Christie, Vladimir Rabinovich
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutional U-Net model to estimate the baselinecorrected SP log from the raw SP log and a set of collocated predictor features based on feature engineering...
2024
The Perfect Frac Stage, Whats the Value?
Craig Cipolla, Ankush Singh, Mark McClure, Michael McKimmy, John Lassek
Unconventional Resources Technology Conference (URTEC)
..., and Alfred Hill. "Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional...
2024
Deep learning to predict subsurface properties from injected CO2 plume bodies using time-lapse seismic shot gathers
Son Phan, Wenyi Hu, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
... between the depth domain property contrast and the time domain seismic response to CO2 injection and plume body migration using a fully processed baseline...
2022
Multi-information intelligent decision process for first-break picking
Fei Luo, Lanlan Yan
International Meeting for Applied Geoscience and Energy (IMAGE)
... analysis. Recently, several authors have employed convolutional neural networks as classifiers to determine the presence of a first arrival signal...
2024
Microsoft Word - image2023_final (10).docx
J0381057
International Meeting for Applied Geoscience and Energy (IMAGE)
...., 2020). Neural networks, as the backbone of deep learning, are usually composed of convolutional layers that are designed to be trained on large datasets...
Unknown
Physics-Assisted Transfer Learning for Production Prediction in Unconventional Reservoirs
J. Cornelio, S. Mohd Razak, A. Jahandideh, Y. Cho, H-H. Liu, R. Vaidya, B. Jafarpour
Unconventional Resources Technology Conference (URTEC)
.... Society of Petroleum Engineers. Mohd Razak S, Jafarpour B. (2020a) Convolutional neural networks (CNN) for feature-based model calibration under uncertain...
2021
Detailed petroleum system insights using deep learning: A case study from the Scarborough Gas Field, offshore Australia
Scotty Salamoff, Julian Chenin, Benjamin Lartigue, Nguyen Phan, Paul Endresen
International Meeting for Applied Geoscience and Energy (IMAGE)
... to B) the interactive deep learning method for handling patches. The deep learning architecture presented is based on a Convolutional Neural Network...
2022
Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition
Keyla Gonzalez, Eduardo Gildin, Richard L. Gibson Jr.
Unconventional Resources Technology Conference (URTEC)
... of data is achieved. In this research, we implement a high-order SVD (HOSVD) model reduction method for denoising and compressing microseismic...
2021
Combined P and S Waves Survey for Hydrocarbon Exploration
Basuki Puspoputro
Indonesian Petroleum Association
... velocity analysis and the convolutional model: IHRDC, Boston. Sheriff, R.E., 1984, Encyclopedic dictionary of exploration geophysics, 2nd edition...
1990
CMP domain near-surface velocity model building based on deep learning
Yihao Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
...CMP domain near-surface velocity model building based on deep learning Yihao Wang CMP domain near-surface velocity model building based on deep...
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
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
Sub-seafloor reflectivity estimation by upgoing wavefield deconvolution
Hassan Masoomzadeh, Tim Seher, M. A. H. Zuberi
International Meeting for Applied Geoscience and Energy (IMAGE)
... in shallow water settings. The first practical obstacle is that node data sampling in the space domain is usually quite sparse. The second concern...
2023
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
Abstract: Azimuthal Fourier Coefficient Elastic Inversion; #90174 (2014)
Benjamin Roure and Jon Downton
Search and Discovery.com
... and the real data expressed as follows: Misfit R *W data i , j 2 (1) i, j The modeled data is calculated using a convolutional model where...
2014
Physics-Constrained Deep Learning for Production Forecast in Tight Reservoirs
Nguyen T. Le, Roman J. Shor, Zhuoheng Chen
Unconventional Resources Technology Conference (URTEC)
.... The above limitation necessitates the incorporation of domain knowledge into deep learning model. First, to investigate whether it is possible for deep...
2021
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)
... with the Cartesian coordinate planes. The model size with a 7.5 m spacing is [Nx , Ny , Nz ] = 2563 . We inject a Ricker wavelet with a peak frequency of 20...
2022
Joint inversion of multi-height gravity and vertical gradient via physics-informed neural network
Yinshuo Li, Wenkai Lu, Cao Song
International Meeting for Applied Geoscience and Energy (IMAGE)
...]. The inversion model is based on convolutional layers. Since the 3D convolution neural network is computationally heavy, this abstract proposed to reduce...
2024
Transfer Learning with Recurrent Neural Networks for Long-term Production Forecasting in Unconventional Reservoirs
Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Unconventional Resources Technology Conference (URTEC)
... practical use. In this paper, a deep recurrent neural network (RNN) model is developed for robust long-term production forecasting in unconventional...
2021
Using deep learning for automatic detection and segmentation of carbonate microtextures
Claire Birnie, Viswasanthi Chandra
International Meeting for Applied Geoscience and Energy (IMAGE)
... on Microsoft’s Common Objects in COntext (COCO) dataset. The resulting model accurately detects and separates a number of crystals observed within...
2022
Applying Machine Learning Technologies in the Niobrara Formation, DJ Basin, to Quickly Produce an Integrated Structural and Stratigraphic Seismic Classification Volume Calibrated to Wells
Carolan Laudon, Jie Qi, Yin-Kai Wang
Unconventional Resources Technology Conference (URTEC)
... Detection Methodology Seismic amplitude is the basis for machine learning fault detection which uses deep learning Convolutional Neural Networks (CNNs...
2022
Efficient subsurface carbon storage modeling with Fourier neural operator
Suraj Pawar, Pandu Devarakota, Faruk O. Alpak, Jeroen Snippe, Detlef Hohl
International Meeting for Applied Geoscience and Energy (IMAGE)
... accurately model the complex interplay of buoyancy, viscous, and capillary forces for large subsurface CO2 containers over long forecast periods. However...
2023
Use of Machine Learning to Estimate Sonic Data for Seismic Well Ties; #42471 (2019)
Thanapong Ketmalee
Search and Discovery.com
... Computed Convolutional Model Filter DT Casing Bad hole condition Spike RC * Wavelet Synthetic Seismogram AI Comparison Scenarios Actual DT ML...
2019
Volumetric Calculations Using 3D Seismic Calibrated Against Porosity Logs - Pretty Hill Formation Reservoirs, Onshore Otway Basin
P. J. Boult, J. Donley
Petroleum Exploration Society of Australia (PESA)
... be considered an extension of the conventional post-stack inversion process. The latter method uses a convolutional model, which is based on an extracted...
2001
High-resolution seismic detection of shallow natural gas beneath Hutchinson, Kansas
Susan E. Nissen, W. Lynn Watney, Jianghai Xia
Environmental Geosciences (DEG)
...-frequency reflections are artifacts of the overlying gas, which cannot be accurately reproduced with the simple convolutional model used to create...
2004