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The AAPG/Datapages Combined Publications Database
Showing 622 Results. Searched 200,357 documents.
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
Incorporating Artificial Intelligence into Traditional Exploration Workflows in the Cooper-Eromanga Basin, South Australia
H. M. Garcia, W. G. "Woody" Leel Jr., M. Riehle, P. Szafian
International Meeting for Applied Geoscience and Energy (IMAGE)
... a detail geological model at the seismic resolution. This was complemented with the structural information from the AI. Combining all the information...
2021
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
Refining our understanding of the subsurface geology using deep learning techniques
Salma Alsinan, Philippe Nivlet, Hamad Alghenaim
International Meeting for Applied Geoscience and Energy (IMAGE)
... Alghenaim, Unconventional Resources, Saudi Aramco Summary This work addresses the question surrounding the importance of the geological model used...
2022
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
Effectiveness of dip-in DAS observations for low-frequency strain and microseismic analysis: The CanDiD experiment
David W. Eaton, Yuanyuan Ma, Chaoyi Wang, Kelly MacDougall
International Meeting for Applied Geoscience and Energy (IMAGE)
...: Arrival-time picking method, based on classification using machine learning. learning approach. For event detection, we developed a convolutional neural...
2022
Imaging and fold comparison of mirror reverse time migration vs. interferometric imaging for VSP data
Liwei Cheng, James Simmons, Ali Tura
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Mirror migration and interferometric imaging utilize free-surface multiples to extend the subsurface illumination. We design a 2-D synthetic model...
2022
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
What Broke? Microseismic analysis using seismic derived rock properties and structural attributes in the Eagle Ford play
Robert Meek, Bailo Suliman, Robert Hull, Hector Bello, Doug Portis
Unconventional Resources Technology Conference (URTEC)
... regression analysis technique. Rock properties and structural attributes are combined with an ellipsoid stimulation model around the well bore...
2013
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
Joint inversion of magnetotelluric and seismic travel time data with intelligent interpretation of geophysical models
Hongyu Zhou, Rui Guo, Maokun Li, Fan Yang, Shengheng Xu, Zuzhi Hu, Deqiang Tao
International Meeting for Applied Geoscience and Energy (IMAGE)
... models and seismic post-stack data. In the joint inversion, the output of the IntNet is used as the reference model to constrain the searching space...
2022
Strong Foundations, Deep Integration, Infinite Possibilities
James Lowell, Peter Szafian, Nicola Tessen
GEO ExPro Magazine
... years and is effective for building a conceptual model of the geology and QC’ing the individual faults and overall interpretation whilst picking...
2019
Amplitude enhancement of far-offset refractions via machine learning
Lurun Su, Han Wang, Jie Zhang
International Meeting for Applied Geoscience and Energy (IMAGE)
... refractions using a physical model. Such methods are time-consuming, especially for 3D applications. In this study, we apply a machine learning method...
2022
Deep learning to maximize the value of fast-track 4D seismic processing
Arnab Dhara, Haron Abdel-Raziq, Denis Kiyashchenko, Asiya Kudarova, Janaki Vamaraju, Albena Mateeva, Pandu Devarakota, Kanglin Wang, Jorge Lopez
International Meeting for Applied Geoscience and Energy (IMAGE)
... signals requires beating the noise, which may increase the timeline further. This paper leverages deep convolutional neural networks (CNN) to reduce...
2022
Explainable machine learning for hydrocarbon prospect risking
Ahmad Mustafa, Ghassan AlRegib
International Meeting for Applied Geoscience and Energy (IMAGE)
... limited thus far owing to a lack of transparency in the way complicated, black box models generate decisions. We demonstrate how LIME—a model-agnostic...
2022
OpenFWI 2.0: Benchmark Datasets for Elastic Full-waveform Inversion
Shihang Feng, Hanchen Wang, Chengyuan Deng, Yinan Feng, Min Zhu, Peng Jin, Yinpeng Chen, Youzuo Lin
International Meeting for Applied Geoscience and Energy (IMAGE)
... into the inversion significantly expands the model space and introduces increased degrees of freedom, resulting in even more pronounced nonlinearity (Operto et...
2023
GeoStreamer X Delivers Near-Field Multi-Azimuth Dataset for Accurate Lead Characterisation, South Viking Graben, Norway
Cyrille Reiser, Eric Mueller, PGS
GEO ExPro Magazine
... summarised below: • Comprehensive demultiple sequence addressing the short and long period multiples integrating 3D convolutional and wave equation...
2021
A deep learning workflow for petro-mechanical facies predictions in unconventionals
Noah R. Vento, Enru Liu, Mary Johns
International Meeting for Applied Geoscience and Energy (IMAGE)
... extracted from 23 well locations across the survey and used as inputs to the proposed DL model. Due to poor S/N ratio and the presence of residual...
2023
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 Data Compression by Variational Autoencoder With Hyperprior
Shirui Wang, Wenyi Hu, Aria Abubakar, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
..., end-to-end approach. Our experimental analyses demonstrate the efficacy of the introduced compression model on both pre-migration and post-migration...
2023
Fast viscoacoustic forward modeling method based on U-net Fourier neural operator
Wenbin Tian, Yang Liu
International Meeting for Applied Geoscience and Energy (IMAGE)
... constraint method. The first method aims to model instances of PDEs (Smith et al., 2020). This method exhibits a simple structure. However, its solution...
2023
Estimating subsurface geostatistical parameters from surface-based GPR reflection data using a deep-learning approach
Yu Liu, James Irving, Klaus Holliger
International Meeting for Applied Geoscience and Energy (IMAGE)
... task in a highly efficient manner. The proposed approach uses a convolutional neural network (CNN), which is trained on a vast database...
2023
Deep learning based microearthquake location prediction at Newberry EGS using physics-informed synthetic dataset
Zi Xian Leong, Tieyuan Zhu
International Meeting for Applied Geoscience and Energy (IMAGE)
...-velocity model to simulate physicsinformed synthetic MEQ events and corresponding acoustic waveforms. We introduce a deep learning-based method namely...
2023
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
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