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The AAPG/Datapages Combined Publications Database
Showing 324 Results. Searched 195,452 documents.
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)
...), the difference in frequency between the well log and seismic data is handled by using a convolutional operator and assuming that each sample of the target log...
2004
Demultiple for Wide-Tow Broadband Acquisition in a Shallow Water Environment: A Case Study from the NW Shelf, Australia
Mike Hartley, Shuo Ji, Alex Browne
Petroleum Exploration Society of Australia (PESA)
... in shallow water, especially for outer cables. Rcvr depth(m) Shot: channel Frequency(Hz) Time (sec) Model base water-layer demultiple predicts...
2016
Abstract: Seismic Characterization of Complex Salt Dome Structures using Machine Learning; #91204 (2023)
Osama Alsalmi, Saleh Dossary, Gino Ananos
Search and Discovery.com
.... Convolutional Neural Networks (CNNs) gained popularity in image segmentation tasks. In this study, a machine learning model based on U-Net architecture is used...
2023
Do We Really Need Deep Learning? A Study on Play Identification using SEM Images
Hanyan Zhang, Max T. Kasumov, Deepak Devegowda, Mark E. Curtis
Unconventional Resources Technology Conference (URTEC)
... classification. For all image resolutions considered, surprisingly, the simplest and shallowest one-convolutional layer model performs remarkably well...
2021
Using Second-Order Adjoint State Methods in GPUS to Quantify Resolution on Full Waveform Inversions, #42034 (2017).
Sergio Abreo, Ana Ramirez, Oscar Mauricio Reyes Torres
Search and Discovery.com
... Inversion (FWI) allows quantifying resolution of the velocity model obtained. Although there are different ways to compute approximations of the Hessian...
2017
Deterministic and Statistical Wavelet Processing
Lee Lu
Southeast Asia Petroleum Exploration Society (SEAPEX)
... on the convolutional model for a seismic trace: it is assumed that an observed trace, x, is the convolution of an “effective wavelet”, w, with an “effective reflectivity...
1980
Deep convolutional neural networks for generating grain-size logs from core photographs
Thomas T. Tran, Tobias H. D. Payenberg, Feng X. Jian, Scott Cole, and Ishtar Barranco
AAPG Bulletin
...Deep convolutional neural networks for generating grain-size logs from core photographs Thomas T. Tran, Tobias H. D. Payenberg, Feng X. Jian, Scott...
2022
Abstract: Seismic Fault Detection by Denoising Diffusion Probabilistic Model; #91204 (2023)
Bingbing Sun, Ali Abdulmohsen, Nasher AlBinHassan
Search and Discovery.com
...Abstract: Seismic Fault Detection by Denoising Diffusion Probabilistic Model; #91204 (2023) Bingbing Sun, Ali Abdulmohsen, Nasher AlBinHassan Seismic...
2023
Abstract: Fast and Accurate Impedance Inversion by Well-Log Calibration; #90171 (2013)
Igor B. Morozov and Jinfeng Ma
Search and Discovery.com
...) the convolutional equation; 2) time-depth constraints from the seismic data, 3) background low-frequency model from the logs or seismic/geological interpretation...
2013
Prestack Seismic Data Inversion for Shale Gas Reservoir Characterization in China
Gang Yu, Yusheng Zhang, Ximing Wang, Xing Liang, Uwe Strecker, Maggie Smith
Unconventional Resources Technology Conference (URTEC)
... model along with interpreted horizons for structural control. The seismic velocity field provides low frequency impedance trends away from the well...
2016
Dual constrained reservoir modeling with geological factors and seismic attributes for exploration stage
Hongmei Luo, Yiran Xing, Changjiang Wang, Zhijing Zhang
International Meeting for Applied Geoscience and Energy (IMAGE)
... model as the covariate to realize the geostatistical modeling in the exploration stage. Consequently, the reliability and effectiveness of the modeling...
2023
U-net based primary alignment
Ricard Durall, Ammar Ghanim, Norman Ettrich
International Meeting for Applied Geoscience and Energy (IMAGE)
... processing workflows. Misalignments are mainly caused by inaccuracies in the velocity model. Traditional approaches to event flattening typically involve...
2023
Abstract: Utilizing Seismic Attributes for Machine Assisted Fault Detection and Extraction; #91204 (2023)
Muhammad Khan, Yasir Bashir, Saleh Dossary, Syed Ali
Search and Discovery.com
... labelled data as transfer learning to update the foundation Convolutional Neural Network (CNN) model that was initially trained on synthetic data...
2023
ABSTRACT: Seismic Heterogeneity Cubes and Corresponding Equiprobable Simulations; #90013 (2003)
Matthias Imhof, William Kempner
Search and Discovery.com
... attributes. Instead, model statistics with only six parameters are fitted to the raw statistics. These six parameters include three orthogonal...
2003
Abstract: A Transfer Learning Approach to Rock Property Estimation Workflows;
Ahmad Mustafa, Motaz Alfarraj, Ghassan Alregib
Search and Discovery.com
.... This results in vertical discontinuities in the computed property volumes using such a model, since it becomes sensitive to lateral changes...
Unknown
A deep learning-based inverse Hessian for full-waveform inversion
Mustafa Alfarhan, Matteo Ravasi, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
.... A smoothed version of this model is used as starting guess for FWI. A wavelet with a peak frequency of 5 Hz is utilized to perform the modeling of 25 shots...
2023
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
Methods of estimating wavelet stationarity, stabilizing non-stationarity, and evaluating its impact on inversion: A synthetic example using SEAM II Barrett unconventional model
Jesse Buckner, Michael Fry, Joe Zuech, Peter Harris, Bill Shea
International Meeting for Applied Geoscience and Energy (IMAGE)
... is simulated across a continuous 3D convolutional synthetic seismic volume, derived from the earth model of the SEAM II Barrett dataset. Multiple...
2023
Novel application of machine learning assisted fault interpretation to delineate earthquake risk from saltwater disposal in the Midland Basin
Niven Shumaker, Mohammed Afia
International Meeting for Applied Geoscience and Energy (IMAGE)
... seismic survey using a 3D convolutional neural for edge pixels in a 2D data array. Lines that pass through network (Abubakar et al. 2022). Fault points...
2023
Earthquake Detection and Focal Mechanism Calculation Using Artificial Intelligence
Shane Quimby, Yanwei Zhao, Jie Zhang, GeoTomo
Unconventional Resources Technology Conference (URTEC)
... network (FCN). FCNs are supervised deep learning networks based on convolutional layers, without being fully connected. This necessitates fewer model...
2022
Rock-physics based time-lapse inversion in Delivery4D: synthetic feasibility study for CO2CRC Otway Project
Stanislav Glubokokvskikh, James Gunning, Tess Dance, Roman Pevzner, Dmitry Popik, Christian Proud
Petroleum Exploration Society of Australia (PESA)
... seismic AVO-inversion based on convolutional model of seismic trace. A subsurface model consists of 1D ‘layered cakes’, inverted independently...
2018
Prestack Seismic Data Inversion for Shale Gas Reservoir Characterization in China; #41829 (2016)
Gang Yu, Yusheng Zhang, Uwe Strecker, Maggie Smith
Search and Discovery.com
... connected to well information through well-tie and wavelet extraction. Well data is also used in the low frequency model along with interpreted horizons...
2016
Transfer Learning Applied to Seismic Images Classification
Search and Discovery.com
N/A
Abstract: CO2 Distribution Prediction Using Machine Learning Based Proxy Model in Geological Carbon Sequestration;
Zhi Zhong, Alexander Sun
Search and Discovery.com
... knowledge and assumptions on input data distributions. In particular, our cDC-GAN model is designed to learn cross-domain mappings between high...
Unknown
Revolutionizing seismic data compression: Unlocking the power of stable diffusion neural networks
Ayrat Abdullin, Umair Bin Waheed, Naveed Iqbal
International Meeting for Applied Geoscience and Energy (IMAGE)
... principal component analysis (DPCA). By leveraging a mixture model to represent the statistics of seismic traces and computing global principal components...
2023