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The AAPG/Datapages Combined Publications Database
Showing 622 Results. Searched 200,357 documents.
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
Geobody-oriented interpretable velocity fusion modeling in depth domain with seismic facies informed segmentation method
Meng Li, Qingcai Zeng, Hao Shou, Nan Qin, Chunming Wang, Tongsheng Zeng
International Meeting for Applied Geoscience and Energy (IMAGE)
... velocity model. Introduction Ultra-deep reservoirs, complex lithological reservoirs and subtle reservoirs have become key exploration targets...
2023
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
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
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
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
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
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
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
Assessing properties of internal multiples for different geologies
Paul Ras, Mikhail Davydenko, Eric Verschuur
International Meeting for Applied Geoscience and Energy (IMAGE)
... attenuation methods. Introduction When modeling data from a well log it is relatively simple to compute a primary reflection series via the convolutional...
2022
Machine-learning Facilitates Prediction of Geomechanical Properties Directly From SEM Images in Unconventional Plays
Heehwan Yang, Deepak Devegowda, Mark Curtis, Chandra Rai
Unconventional Resources Technology Conference (URTEC)
... non-parametric regression resulting in a unified, easily generalizable model that performs robustly when tested against previously unseen images. Our...
2023
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
ML-based facies classification on acoustic image logs from Brazilian presalt region
Nan You, Yunyue Elita Li, Arthur Cheng
International Meeting for Applied Geoscience and Energy (IMAGE)
... and then choose the one that provides the lowest validation loss after convergence as the optimal DNN model. RESULTS (2) where yk and pk are the label...
2022
Seismic data interpolation via frequency-constrained 3D inception Unet
Yen Sun, Paul Williamson
International Meeting for Applied Geoscience and Energy (IMAGE)
... streamers, in marine acquisitions. We started with a “standard”, 3D convolutional neural network (CNN) architecture: while computationally intense, a 3D...
2022
An integrated workflow of improving the accuracy of first arrivals picking via deep learning
Yitao Pu, Bo Zhang, Chenglin Wei, Yingyu Xu, Hongfei Liu
International Meeting for Applied Geoscience and Energy (IMAGE)
... learning. Firstly, we compute a probability image by applying a model, which is trained using the Historically nested U-Net (HUnet), to the seismic shot...
2022
Post Migration Processing of Seismic Data
Dashuki Mohd.
Geological Society of Malaysia (GSM)
... or multiples. The basis for deconvolution is the convolutional model (Robinson, 1984). In the convolutional model, a seismic trace is viewed...
1994
S-wave velocity prediction using a deep learning scheme and attention mechanism
Gang Feng, Wen-Qin Liu, Zhe Yang, Wei Yang, Jian-Hua Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... several limitations, such as poor model generalization, inadequate exploration of logging curve patterns. In this study, a novel approach based on one...
2024
Time-lapse seismic data shaping with transformer encoder neural networks
Jorge E. Monsegny, Daniel O. Trad, Don C. Lawton
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Alali et al. (2021) use convolutional neural networks to perform this filtering, while Alali et al. (2022) employ recurrent neural networks to shape...
2024
Technical Article: Finding Subtle Traps with Seismic: Interpretative Criteria Clarified
A. Easton Wren
Petroleum Exploration Society of Australia (PESA)
... to what the section should look like. Progressive understanding of the seismic method introduced the concept of the convolutional model: this found...
1986
Self-parametrizing seismic data processing modules: An example on coherent noise suppression
Simone Re, Ran Bachrach, Massimo Clementi, Collin Wilson
International Meeting for Applied Geoscience and Energy (IMAGE)
... separated by means of filtering. In comparison, more sophisticated techniques exploit the physics of surface-wave propagation to model the coherent noise...
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
Innovative Deep Autoencoder and Machine Learning Algorithms Applied in Production Metering for Sucker-Rod Pumping Wells
Peng Yi, Xiong Chunming, Zhang Jianjun, Zhang Yashun, Gan Qinming, Xu Guojian, Zhang Xishun, Zhao Ruidong, Shi Junfeng, Liu Meng, Wang Cai, Chen Guanhong
Unconventional Resources Technology Conference (URTEC)
.... The machine-learning model contains two neural networks: first, a deep autoencoder to extract the feature representations from all the dynamometer...
2019