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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Hydraulic fracture-hit detection system using low-frequency DAS data
Xiaoyu Zhu, Ge Jin, Richard Hammack
International Meeting for Applied Geoscience and Energy (IMAGE)
... detection convolutional neural network to detect fracture hits in real-time, as trained on synthetic datasets and successfully transferred to field data...
2022
Marchenko redatuming and seismic interferometry based internal multiple prediction for salt structures
Zhiwei Gu, Jianhua Geng, Ru-Shan Wu
International Meeting for Applied Geoscience and Energy (IMAGE)
... of the background velocity model, the recorded data can be accurately redatumed to a target area by solving coupled Marchenko equations. Then, an image without...
2023
Background noise suppression for DAS-VSP data using attention-based deep image prior
Yang Cui, Umair bin Waheed, Yangkang Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... recovery in DAS data. Yang et al. (2023a) proposed a fully convolutional framework for extracting hidden signals and attenuating diverse noise in DAS data...
2024
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
Integrating U-net into full-waveform inversion for salt body building: A challenging case
Sixiu Liu, Abdullah Alali, Shijun Cheng, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... Alkhalifah, KAUST SUMMARY Full-waveform inversion (FWI) applied to regions with large salt bodies often fails without a good initial model, long offsets...
2024
Drilling and Completion Anomaly Detection in Daily Reports by Deep Learning and Natural Language Processing Techniques
Hongbao Zhang, Yijin Zeng, Hongzhi Bao, Lulu Liao, Jian Song, Zaifu Huang, Xinjin Chen, Zhifa Wang, Yang Xu, Xin Jin
Unconventional Resources Technology Conference (URTEC)
...”, “grapple” and “bumper”, which are all fishing related tools, that means the model has learned the semantics of words. Convolutional neural network (CNN...
2020
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
Demultiple of High Resolution P-Cable Data in the Norwegian Barents Sea An Iterative Approach
A.J. Hardwick, S. Jansen, B. Kjolhamar
Petroleum Exploration Society of Australia (PESA)
... applied to remove range available. Convolutional,two stages, multiple prediction itself stage, particularly in shallow water. For model and (e) a PRE...
2017
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
Acoustic and Elastic Modeling of Seismic Time-Lapse Data from the Sleipner CO2 Storage Operation
R. J. Arts, M. Trani, R. A. Chadwick, O. Eiken, S. Dortland, L. G. H. van der Meer
AAPG Special Volumes
... (being essentially one-dimensional), which enables many model scenarios to be investigated. Acoustic seismic modeling of stacked migrated data has...
2009
Applying deep learning for identifying bioturbation from core photographs
Eric Timmer, Calla Knudson, and Murray Gingras
AAPG Bulletin
... to the convolutional layers to reduce model overfitting (Srivastava et al., 2014). Overfitting occurs when the neural network memorizes the data set...
2021
Abstract: Recovering Low Frequencies for Impedance Inversion by Frequency Domain Deconvolution; #90224 (2015)
Sina Esmaeili and Gary Frank
Search and Discovery.com
... reflectivity. We start by reintroducing the convolutional model for normal incident seismograms and then show how reflectivity can be estimated...
2015
CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Using Distributed Pressure and Temperature Measurements at the Illinois Basin-Decatur Carbon Sequestration Project
Takuto Sakai, Masahiro Nagao, Chin Hsiang Chan, Akhil Datta-Gupta
Carbon Capture, Utilization and Storage (CCUS)
... by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir. In the proposed...
2024
Automated Data and ML Pipelines to Accelerate Subsurface Digitalization
Raj Kannan, Vikas Jain
Unconventional Resources Technology Conference (URTEC)
... the ML craft and providing first principal guard-rails. An MLOps pipeline can manage model versions and continuously deliver qualified ML models...
2023
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
Statistical Analysis of Estimated Ultimate Recovery: Comparing Machine Learning and Traditional DCA Methods in the Eagle Ford and Bakken
Palash Panja, Carlos Vega-Ortiz, Milind Deo, Brian McPherson, Rasoul Sorkhabi
Unconventional Resources Technology Conference (URTEC)
...) (Yan et al., 2021), the Temporal Convolutional Network (TCN) (Lea et al., 2016), and the transformer model (Vaswani et al., 2017). The efficacy of LSTMs...
2024
Augmented Data Management for Subsurface CCUS Data Sets
Rhys Blake, Jess B. Kozman, James Lamb, Lorena Pelegrin
Carbon Capture, Utilization and Storage (CCUS)
... workflows for using artificial and convolutional neural networks to find information in legacy documents that can predict physical properties...
2025
Estimation of anisotropic parameters from semblance picking using dynamic programming
Hong Liang, Houzhu (James) Zhang, Dongliang Zhang, Hongwei Liu, Xu Ji
International Meeting for Applied Geoscience and Energy (IMAGE)
... and anisotropic parameters from the semblance panels. We apply the automatic model building workflow to synthetic and field data examples to demonstrate...
2022
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
Facies-induced bias in machine learning-enhanced seismic lithology (inversion)
Hongliu Zeng, Bo Zhang, Mariana Olariu
International Meeting for Applied Geoscience and Energy (IMAGE)
... tests on the subject. A geologically realistic model is used to quantitively demonstrate the methods to reduce the bias. A field-data test...
2022
A robust approach for shear log predictions using deep learning on big data sets from a carbonate reservoir for integrated reservoir characterization projects
Aun Al Ghaithi
International Meeting for Applied Geoscience and Energy (IMAGE)
... reservoir. The trained model was then used to predict shear logs in wells drilled previously without acquired shear log data. Deep learning provided added...
2022
Seismic fault proximity to production
Jesse Lomask, Toby Burrough, Allison Gilmore, Michael Pyrcz
International Meeting for Applied Geoscience and Energy (IMAGE)
... learning can be utilized to learn and model the relationships between well performance, proximity to faults and the various associated fault attributes...
2022
Finding the reservoir in an intensely scattered wavefield: A case study from the Central Sichuan Basin, China
John Coffin, Mengmeng Zhang, Panos Doulgeris, Peter Haffinger, Angie Kelsay, Jinsong Li
International Meeting for Applied Geoscience and Energy (IMAGE)
... an elastic modelling scheme including interbed multiples and multiple mode conversions for the well-tie. A linear convolutional model results in perfectly...
2022
Efficient and accurate velocity building from Gramian-constrained multiphysics reflection and transmission data
Jide Nosakare Ogunbo
International Meeting for Applied Geoscience and Energy (IMAGE)
..., the use of the convolutional model (Buland and Omre, 2003), by the z-transform, is readily more practical than the seismic operator for either...
2022
Automated fault surfaces extraction from 3D fault imaging volume
Nam Nguyen, Alejandro Jaramillo
International Meeting for Applied Geoscience and Energy (IMAGE)
... be integrated into a geological model for identification of hydrocarbon bearing formations, improving structural trapping definition, and preventing drilling...
2022