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The AAPG/Datapages Combined Publications Database
Showing 635 Results. Searched 201,044 documents.
Seismic inversion with implicit neural representations
Juan Romero, Wolfgang Heidrich, Nick Luiken, Matteo Ravasi
International Meeting for Applied Geoscience and Energy (IMAGE)
... be mathematically represented via the socalled convolutional model (Goupillaud, 1961). This entails the convolution of a source function or wavelet w...
2024
Towards flexible demultiple with deep learning
Mario Fernandez, Norman Ettrich, Matthias Delescluse, Alain Rabaute, Janis Keuper
International Meeting for Applied Geoscience and Energy (IMAGE)
... moveout to be considered multiple reflections in Mi+1 than in Mi . We build the training data through the convolutional model for a large number...
2024
Interactive 3D fault prediction using a weighted 2D-CNN and multidirectional 3D-CNN
Jesse Lomask, Samuel Chambers
International Meeting for Applied Geoscience and Energy (IMAGE)
... using a weighted 2D-CNN and multi-directional 3D-CNN Jesse Lomask* and Samuel Chambers, S&P Global Summary We present an interactive 2D Convolutional...
2022
Leveraging self-supervised deep learning to address cross-talks in multi-parameter inversions
Wenlong Wang, Yulang Wu, Yanfei Wang, George A. McMechan
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Geological structures are typically analyzed using a multiparameter model (MPM). However, current methods such as multi-parameter full waveform...
2024
Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network (Progressive GAN);
Suihong Song, Tapan Mukerji, Jiagen Hou
Search and Discovery.com
...Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network...
Unknown
Improved UCR Development Decision Through Probabilistic Modeling with Convolutional Neural Network
Han Young Park, Yunhui Tan, Baosheng Liang, Yuguang Chen
Unconventional Resources Technology Conference (URTEC)
...Improved UCR Development Decision Through Probabilistic Modeling with Convolutional Neural Network Han Young Park, Yunhui Tan, Baosheng Liang...
2022
Bringing ML models into mainstream applications by enabling cloud platform connections
Rafael Pinto, Ilya Agurov, Roman Emreis, Iurii Koniaev-Gurchenko, Dmitrii Zolotukhin, Viktar Huleu, Evgeny Shulikin, Andrey Derevyanka, Pavel Shashkin, Maksim Krug, Ivan Grechikhin, Anton Petrov, Simon Shaw, Brian Macy, Chengbo Li, Chuck Mosher, Anand Malgi
International Meeting for Applied Geoscience and Energy (IMAGE)
..., the publication comes with a code repository, a trained model, and a license facilitating its incorporation into mainstream applications. However, the vast...
2022
Deep learning-based joint inversion of time-lapse surface gravity and seismic data for monitoring of 3D CO2 plumes
Adrian Celaya, Mauricio Araya-Polo
International Meeting for Applied Geoscience and Energy (IMAGE)
... that measures the difference between the forward response of a given subsurface model and the observed data when the subsurface is directly stimulated...
2024
An Introduction to Deep Learning: Part II
Lasse Amundsen, Hongbo Zhou, Martin Landrø
GEO ExPro Magazine
... often the model fails to predict the correct answer in their top five guesses (the top-5 error rate), in descending order of confidence. ILSVRC 2012...
2017
Abstracts: The Reflectivity Response of Multiple Fractures and its Implications for Azimuthal AVO Inversion; #90173 (2015)
Olivia Collet, Benjamin Roure, Jon Downton
Search and Discovery.com
... studying various rock physics models in order to model the impact of multiple fractures on the elastic parameters of an isotropic medium. Then, we...
2015
High-efficient reflection retrieval from massive ambient noise using a deep-learning workflow
Yinghe Wu, Shulin Pan, Dawei Liu, Yaojie Chen, Qinghui Cui
International Meeting for Applied Geoscience and Energy (IMAGE)
... workflow for quickly retrieving body wave events from massive ambient noise datasets. We feed relevant data to a convolutional autoencoder classifier...
2024
Deep carbonate reservoir characterization with unsupervised machine-learning approaches
Xuanying Zhu, Luanxiao Zhao, Xiangyuan Zhao, Yuchun You, Minghui Xu, Tengfei Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
... (PCA), T-distributed Stochastic Neighbor Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP), and Convolutional Autoencoder (CAE...
2023
Automating the thresholding of multi-stage iterative source separation with priors using machine learning
Nam Pham, Rajiv Kumar, Sunil Manikani, Yousif Izzeldin Kamil Amin, Phillip Bilsby, Massimiliano Vassallo, Tao Zhao
International Meeting for Applied Geoscience and Energy (IMAGE)
... algorithm. A machine learning model is trained with a fraction of data and is then applied to the entire survey. Experimental results on a field dataset...
2024
Abstract: Push the Limits of Seismic Resolution Using Surface Consistent Gabor Deconvolution; #90171 (2013)
Xinxiang Li and Darren P. Schmidt
Search and Discovery.com
... and the time-variant earth wavelet in a nonstationary convolutional trace model, which can be approximately factorized in the Gabor domain...
2013
Estimate near-surface velocity with reversals using deep learning and full-waveform inversion
Yong Ma, Xu Ji, Weiguang He, Tong Fei
International Meeting for Applied Geoscience and Energy (IMAGE)
... inversion, to estimate the near-surface velocity model with reversals. INTRODUCTION An accurate near-surface velocity model is critical for land seismic...
2022
Joint Identification of Lithology and Lithofacies in Core Images Based on Deep Learning
Han Wang, Feifei Gou, Hanqing Wang, Shengjuan Cai
Unconventional Resources Technology Conference (URTEC)
... the lithology identification model. Two lithofacies recognition models are trained for different lithology types. For a core image, the lithology is first...
2025
S/N RATIO AND BANDWIDTH CONSIDERATIONS WHEN UTILIZING SEISMIC DATA IN EXPLORING FOR SUBTLE TRAPS - EXAMPLES FROM THE KNOX PLAY
Edward R. Tegland, Exploration Development, Inc., S. Pikes Peak Dr., Parker, CO Patrick H. Bygott, Exploration Development, Inc., S. Pikes Peak Dr., Parker, CO
Ohio Geological Society
.... Model data created from an Ohio Knox synthetic Seismogram will be used to illustrate what this means to the person...
1999
Boulder prediction for offshore windfarm site evaluation using an interactive 2D CNN and a unique weighting scheme on unmigrated seismic
Samuel Chambers, Jesse Lomask
International Meeting for Applied Geoscience and Energy (IMAGE)
.... This gives the model a basic understanding of what to look for, and how to create the segmented output. The basic convolutional synthetic data was created...
2023
Machine learning applications to seismic structural interpretation: Philosophy, progress, pitfalls, and potential
Kellen L. Gunderson, Zhao Zhang, Barton Payne, Shuxing Cheng, Ziyu Jiang, and Atlas Wang
AAPG Bulletin
... geometric invariance-enforced deep learning based on the Mask region-based convolutional neural network (R-CNN) model. Mask R-CNN is a deep learning model...
2022
4D Finite Difference Forward Modeling within a Redefined Closed-Loop Seismic Reservoir Monitoring Workflow, #41922 (2016).
David Hill, Dominic Lowden, Sonika, Chris Koeninger
Search and Discovery.com
...-field coupled dynamic integrated earth model to surface. From which 3D grids of petro-elastic parameters for a range of reservoir simulations...
2016
Transfer Learning Applied to Seismic Images Classification; #42285 (2018)
Daniel Chevitarese, Daniela Szwarcman, Reinaldo Mozart D. Silva, Emilio Vital Brazil
Search and Discovery.com
... point to adjust model's parameters. A poor initialization may lead to longer training sessions or to the inability of finding a solution. To address...
2018
Abstract: Short-time Wavelet Estimation in the Homomorphic Domain; #90174 (2014)
Roberto H. Herrera and Mirko van der Baan
Search and Discovery.com
... phases in both the wavelet and the reflectivity. Theory The seismic signal is described by the convolutional model (Ulrych, 1971): s(t) = w(t) ⋆ r...
2014
Deep learning-based raster digitization engine
Atul Laxman Katole, Purnaprajna Mangsuli, Omkar Gune, Mohd Saood Shakeel, Abhiman Neelakanteswara, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
... model encountered by the scanned raster images during the digitization process. A semantic segmentation model based on cGAN (Isola et al., 2017...
2022
Deep compressed learning for 3D seismic inversion
Maayan Gelboim, Amir Adler, Yen Sun, Mauricio Araya-Polo
International Meeting for Applied Geoscience and Energy (IMAGE)
... (sorted seismic records) to a 3D velocity model, implemented using a deep convolutional neural network (DCNN). The proposed method provides a solution...
2023
Deep learning seismic full-waveform inversion and transient EM joint inversion for near surface velocity modeling
Daniele Colombo, Ernesto Sandoval-Curiel, Ersan Turkoglu, Weichang Li
International Meeting for Applied Geoscience and Energy (IMAGE)
... of seismic FW and transient EM (TEM) data. Near surface model and data generation A carpet acquisition geometry is used for sources and receivers...
2022