Welcome to the new Datapages Archives
Datapages has redesigned the Archives with new features. You can search from the home page or browse content from over 40 publishers and societies. Non-subscribers may now view abstracts on all items before purchasing full text. Please continue to send us your feedback at emailaddress.
AAPG Members: Your membership includes full access to the online archive of the AAPG Bulletin. Please login at Members Only. Access to full text from other collections requires a subscription or pay-per-view document purchase.
Welcome to the new Datapages Archives
Search Results > New Search > Revise Search
The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Conditional image prior for uncertainty quantification in full-waveform inversion
Lingyun Yang, Omar M. Saad, Tariq Alkhalifah, Guochen Wu
International Meeting for Applied Geoscience and Energy (IMAGE)
... data. However, FWI results are effected by the limited illumination of the model domain and the quality of that illumination, which is related...
2024
Simultaneous imaging of basement relief and varying susceptibility in deep-learning approach
Zhuo Liu, Yaoguo Li
International Meeting for Applied Geoscience and Energy (IMAGE)
... in the basement rock assuming a 2D model. Particularly, the U-net architecture followed by a fully connected (FC) layer is adopted to map the information...
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
A Physics-Guided Deep Learning Predictive Model for Robust Production Forecasting and Diagnostics in Unconventional Wells
Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Unconventional Resources Technology Conference (URTEC)
... data set and do not offer the opportunity to incorporate domain constraints. In data-driven modeling, a trained model extracts salient features from...
2021
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)
... and then inverse Fourier transform (IFT) was carried out to obtain time domain response after interpolating responses in frequency domain...
2022
Embedding Physical Flow Functions into Deep Learning Predictive Models for Improved Production Forecasting
Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour
Unconventional Resources Technology Conference (URTEC)
...e time-series output (i.e., production rates versus time). Figure 1: Schematic of the Physics-Guided Deep Learning (PGDL) model. With a trained 𝑓...
2022
Deep Earth: Leveraging neural networks for seismic exploration objectives
Tariq Alkhalifah, Claire Birnie, Randy Harsuko, Hanchen Wang, Oleg Ovcharenko
International Meeting for Applied Geoscience and Energy (IMAGE)
... as a classification task in which the model predicts the time sample index of the first-arrival at each o↵set from 376 indices given a shot gather as the input...
2022
Depositional Facies Identification in Wireline Log Patterns Using 1D Convolutional Neural Network (CNN) Deep Learning Algorithms
Galatio Giovani Prabowo, Muhammad Fahmi Ramdani, Abiyyu Daffa Revanzha, Brian Muara Sianturi, Natalia Angel Momongan
Indonesian Petroleum Association
... to use Python, generating dummy data, training data, and model testing. The chosen tool for this research is the Convolutional Neural Network (CNN...
2024
Fracture-cavity carbonate reservoir identification based on channel attention mechanisms
Liuxin Yang, Yongqiang Ma, Guangxiao Deng, Zhen Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... attention mechanisms in a semi-supervised learning framework. The architecture of our inversion model consists of several attention blocks, which combine...
2023
3D Seismic Facies Classification on CPU and GPU HPC Clusters
Sergio Botelho, Vishal Das, Davide Vanzo, Pandu Devarakota, Vinay Rao, Santi Adavani
Unconventional Resources Technology Conference (URTEC)
...; second, neural network design becomes increasingly challenging due to the higher number of parameters in the model and its larger training time. We...
2021
Joint data and physics model driven full-waveform inversion using CMP gathers and well-logging data
Shuliang Wu, Jianhua Geng
International Meeting for Applied Geoscience and Energy (IMAGE)
..., and J. Ma, 2018, Velociy model building with a modified fully convolutional network: 88th Annual International Meeting, SEG, Expanded Abstracts, 2086...
2023
Abstracts: Full Waveform Inversion Using One-way Migration and Well Calibration; #90173 (2015)
Gary F. Margrave, Robert J. Ferguson, and Chad M. Hogan
Search and Discovery.com
... model is proportional to a reverse-time migration of the data residual (the difference between the actual data and data predicted by the model) where...
2015
Convolution model theory-based intelligent AVO inversion method for VTI media
Yuhang Sun, Yang Liu, Hongli Dong
International Meeting for Applied Geoscience and Energy (IMAGE)
... network technology and propose an intelligent seismic AVO inversion method founded on the convolutional model theory. The proposed method formulates...
2023
CGG 3D Surface-Related Multiple Modelling: A Unique Approach, #41590 (2015).
David Le Meur, Antonio Pica, Terje Weisser
Search and Discovery.com
..., and, in general, there is no domain, neither time, depth, nor pre or post migrated, where multiples and primaries can be simplified simultaneously. Conventional...
2015
Stochastic inversion method based on a priori information of compression-sensing divided-frequency waveform indication
Ying Lin, Siyuan Chen, Guangzhi Zhang, Baoli Wang, Minmin Huang
International Meeting for Applied Geoscience and Energy (IMAGE)
... of the proposed method is verified using both marmousi2 model data and field data. combined continuous wavelet transform and convolutional neural...
2023
Implementation of Denoising Diffusion Probability Model for Seismic Interpretation
Fan Jiang, Konstantin Osypov, Julianna Toms
International Meeting for Applied Geoscience and Energy (IMAGE)
...− 𝛼 where 𝜎 = (1 − 𝛼 − 𝜎 𝜖 (𝑥 , 𝑡) + 𝜎 𝜖 )/(1 − 𝛼 ) 1 − 𝛼 /𝛼 U-net model. By scheduling the noise removal process at time t, we can predict...
2023
Integrating Deep Learning and Seismic Data for Mudstone Characterization and SAGD Development in Heterogeneous Reservoirs
Huiwen Pang, Hanqing Wang, Chuan Qin, Jingwei Tian
Unconventional Resources Technology Conference (URTEC)
... calibration to establish spatiotemporally aligned training data; (2) Deep Learning Model Development, employing convolutional neural networks...
2025
Feature Detection for Digital Images Using Machine Learning Algorithms and Image Processing
Xiao Tian, Hugh Daigle, Han Jiang
Unconventional Resources Technology Conference (URTEC)
... is increased greatly. There are 16 weight layers in vgg16 model, including 13 convolutional layers and 3 fully-connected layers. There are 19 weight...
2018
Deep neural networks for 1D impedance inversion
Vladimir Puzyrev, Anton Egorov, Anastasia Pirogova, Chris Elders, Claus Otto
Petroleum Exploration Society of Australia (PESA)
... for multidimensional inversion, where conventional methods inversion methods suffer from large computational cost. At the same time, realistic one-dimensional models...
2019
An Introduction to Deep Learning: Part III
Lasse Amundsen, Hongbo Zhou, Martin Landrø
GEO ExPro Magazine
... computer model that learns to perform classification tasks directly from images. The one that started it all was the 2012 publication ‘ImageNet...
2018
3D CNN for channel identification in seismic volume
Haishan Li, Wuyang Yang, Xiangyang Zhang, Xinjian Wei, Xin Xu
International Meeting for Applied Geoscience and Energy (IMAGE)
... volumes with complex structure using an end-to-end 3D convolutional neural network. To train the network, we automatically generate a training dataset...
2022
Deterministic and Statistical Wavelet Processing
Lee Lu
Southeast Asia Petroleum Exploration Society (SEAPEX)
... with depth, and the convolutional model is no longer strictly valid, although it may be accurate enough provided that we do not analyze too long a time...
1980
A practical approach to automate end-to-end multi-stage iterative source separation with prior framework using machine learning
Rajiv Kumar, Yousif Izzeldin Kamil Amin, Riccardo Giro, Sunil Manikani, Nam Pham, Massimiliano Vassallo, Phillip Bilsby, Tao Zhao
International Meeting for Applied Geoscience and Energy (IMAGE)
... relies on the fact that the seismic signal of interest exhibits higher coherency and is sparse in the transform domain, whereas the interference noise...
2024
Real-time hydraulic fracturing monitoring using deep learning clustering of microseismic data
Chenglong Duan, Lianjie Huang, Michael Gross, Michael Fehler, David Lumley
International Meeting for Applied Geoscience and Energy (IMAGE)
... high-frequency borehole microseismic data for real-time monitoring of fracture growth. Using the output of the UNet, we perform Gaussian mixture model...
2022
Self-supervised learning for seismic swell noise removal
Yuan Zi, Shirui Wang, Pengyu Yuan, Xuqing Wu, Jiefu Chen, Zhu Han
International Meeting for Applied Geoscience and Energy (IMAGE)
... output in shot-gather: (a) Time-domain input: clean seismic data + synthetic swell noise. (b) F-K domain input. (c) Time-domain clean seismic data...
2022