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The AAPG/Datapages Combined Publications Database
Showing 622 Results. Searched 200,357 documents.
Abstract: Unsupervised Segmentation of Rock MicroCT Scans Using Deep Learning;
Fernando Bordignon, Giovanni Formighieri, Eduardo Burgel, Bruno Rodrigues
Search and Discovery.com
... of DNNs when working with images are the Convolutional Neural Networks (CNN), usually employed in conjunction with supervised training, which needs...
Unknown
Application of interactive convolutional neural network micro-fracture prediction technology based on prestack depth migration data in deep shale gas reservoirs
Xiaolan Wang, Furong Wu, Junfeng Liu, Dianguang Zang, Xiao Yang, Yangjing Li, Xiaoyan Cheng
International Meeting for Applied Geoscience and Energy (IMAGE)
... Neural Prediction Technology Network (CNN) Fracture Convolutional neural networks are a type of deep learning model specifically designed...
2024
Attention-based self-calibrated convolution neural network for efficient facies classification
Motaz Alfarraj
International Meeting for Applied Geoscience and Energy (IMAGE)
... and production operations. Deep convolutional neural networks have been widely used for seismic interpretation tasks including detection, classification...
2024
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
Seismic simulations of experimental strata
Lincoln Pratson, Wences Gouveia
AAPG Bulletin
... of the resulting seismic section. Convolutional Model The convolutional seismic model convolves a seismic wavelet with a time series of reflection...
2002
MACHINE LEARNING UTILIZATION FOR ENHANCED SUCKER ROD PUMP DYNACARD RECOGNITION
Fadhila Tanjungsari, Hilman Lazuardi, Bonni Ariwibowo, Indra Sukmana, and Candra Kurniawan
Indonesian Petroleum Association
...% testing datasets, and 10% validation datasets. Different machine learning algorithms were evaluated, and it is found that the top performing model...
2025
APPLICATION OF MACHINE LEARNING IN COORDINATION NUMBER ESTIMATION FOR RESERVOIR ROCK EXTRACTION
Dinanti Syafirani Zahra, Maharani Arisandy, Shafa Maura Fidela, Aldenia Alexandra, and Irwan Ary Dharmawan
Indonesian Petroleum Association
..., relying on experimental data or manual image analysis. This study explores a machine learning approach using a custom- developed Convolutional Neural...
2025
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
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
Abstract: A Deep Learning Saturation Imaging Framework to Optimize Reservoir Contact While Drilling; #91204 (2023)
Abdallah AlShehri, Klemens Katterbauer, Ali AlYouesf
Search and Discovery.com
... framework for the optimization of hydrocarbon contact while drilling. The framework utilizes a deep learning convolutional imaging framework in order...
2023
-- no title --
user1
Search and Discovery.com
... and optimization in seismic interpretation workflow. The existing workflow for seismic interpretation using Convolutional Neural Network (CNN) relies...
Unknown
3D real-time imaging for electromagnetic fracturing monitoring based on deep learning
Zhigang Wang, Yao Lu, Ying Hu, Yinchu Li, Ke Wang, Dikun Yang
International Meeting for Applied Geoscience and Energy (IMAGE)
... an improved supervised deep fully convolutional network (FCN) to learn the relationship between surface electromagnetic data patterns...
2022
Automated velocity model building using Fourier neural operators
Guanghui Huang, Sean Crawley, Ramzi Djebbi, Jaime Ramos-Martinez, Nizar Chemingui
International Meeting for Applied Geoscience and Energy (IMAGE)
.../10.3997/2214-4609.202112777. Wang, W., F. Yang, and J. Ma, 2018, Velocity model building with a modified fully convolutional network: 88th Annual International Meeting...
2023
Application of transfer learning and multi-scale feature fusion in intelligent suppression of seismic random noise
Xin Xu, Wuyang Yang, Xinjian Wei, Haishan Li, Nang Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Key Laboratory of lnternet of Things,CNPC Summary Denoising Convolutional Neural Networks (DnCNN), a data-driven learning algorithm, has been widely...
2024
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
Seismic image-to-image translation using a conditional GAN with Bayesian inference
Xiaolei Song, Muhong Zhou, Petr Jilek, Rodney Johnston, Sean Cardinez, Kareem Vincent
International Meeting for Applied Geoscience and Energy (IMAGE)
... uncertainties. We take a similar approach by adopting two convolutional Bayesian layers as the network output layers to capture the model...
2022
A self-attention enhanced encoder-decoder network for seismic data denoising
Stefan Knispel, Jan Walda, Ruediger Zehn, Alexander Bauer, Dirk Gajewski
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutions (Bello et al., 2019), where attentional feature maps are generated and concatenated to the convolutional feature maps. This does not replace...
2022
An integrated machine learning-based fault classification workflow
Jie Qi, Carolan Laudon, Kurt Marfurt
International Meeting for Applied Geoscience and Energy (IMAGE)
... on the human interpreter. We first compute a 3D fault probability volume from pre-conditioned seismic amplitude data using a 3D convolutional neural network...
2022
Anti-aliasing seismic data interpolation by dip-informed self-supervised learning
Shirui Wang, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... an event of angle α is marked. (b) A traditional (3 × 3) convolutional kernel. (c) A deformed (3 × 3) convolutional kernel offset along the event...
2023
A simultaneous denoising and event picking approach using supervised machine learning
Salman Abbasi, Motaz Alfarraj, Dmitry Borisov, Vikram Jayaram, Iftekhar Alam, Bakhtawer Sarosh
International Meeting for Applied Geoscience and Energy (IMAGE)
... problems (i.e., denoising and event detection) using a single network. A convolutional neural network is used to capture the high frequency times series...
2023
A Siamese network-based full-wave inversion: Application on real data
Omar M. Saad, Randy Harsuko, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
... two identical Convolutional Neural Networks (CNNs) with shared weights to ensure consistent feature extraction from observed and simulated data...
2024
CNN for image super-resolution of airborne magnetic data in Ontario, Canada
Rafael Pires de Lima
International Meeting for Applied Geoscience and Energy (IMAGE)
... the two first convolutional blocks of a VGG model (Liu and Deng, 2015) pretrained on ImageNet (Russakovsky et al., 2015). RESULTS AND DISCUSSION We begin...
2024
Time-lapse matching of OBN seismic data using 2D convolutional neural networks
Ramon C. F. Araújo, Gilberto Corso, Samuel Xavier-de-Souza, João M. de Araújo, Tiago Barros
International Meeting for Applied Geoscience and Energy (IMAGE)
...Time-lapse matching of OBN seismic data using 2D convolutional neural networks Ramon C. F. Araújo, Gilberto Corso, Samuel Xavier-de-Souza, João M. de...
2024
Feasibility Study Methodology for Fracture Analysis Studies Using Seismic Azimuthal Amplitude Variation: Application in Southern Mexico
Alexis Ferrer Balas, Nahum Campos, Jesus Garcia Hernandez
GCAGS Transactions
... be provided by a geometrical feasibility study, followed by convolutional modeling and azimuthal amplitude vs. offset (or angle) analysis (often abbreviated...
2011