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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Implementation of Denoising Diffusion Probability Model for Seismic Interpretation
Fan Jiang, Konstantin Osypov, Julianna Toms
International Meeting for Applied Geoscience and Energy (IMAGE)
...Implementation of Denoising Diffusion Probability Model for Seismic Interpretation Fan Jiang, Konstantin Osypov, Julianna Toms Implementation...
2023
Seismic sparse time-frequency representation via GAN-based unsupervised learning
Youbo Lei, Yang Yang, Naihao Liu, Shengtao Wei, Jinghuai Gao, Xiudi Jiang
International Meeting for Applied Geoscience and Energy (IMAGE)
... the optimization problem. However, STFR is often based on a mathematical model designed with the domain knowledge. Moreover, it suffers from the expensive...
2022
Facies-constrained elastic full-waveform inversion for tilted orthorhombic media
Ashish Kumar, Ilya Tsvankin
International Meeting for Applied Geoscience and Energy (IMAGE)
... convolutional neural networks to mitigate the influence of tradeoffs and increase the spatial resolution of FWI. The developed CNN generates a facies model...
2024
Deep Learning Models for Methane Emissions Identification and Quantification
Ismot Jahan, Mohamed Mehana, Bulbul Ahmmed, Javier E. Santos, Dan O’Malley, Hari Viswanathan
Unconventional Resources Technology Conference (URTEC)
... to prepare the data for the machine learning model. In this section, we will outline the preprocessing and Convolutional Neural Network (CNN) model...
2023
Interactive channel interpretation using deep learning
Hao Zhang, Peimin Zhu, Zhiying Liao, Zewei Li, Dianyong Ruan
International Meeting for Applied Geoscience and Energy (IMAGE)
..., it is difficult to extract channels completely. With the development of machine learning technology, convolutional neural network (CNN) is widely...
2022
Deep water OBN multiple prediction from local reflectivity in the Stolt domain
Cesar Ricardez
International Meeting for Applied Geoscience and Energy (IMAGE)
... of multiple attenuation techniques. Many techniques exist for mitigating multiples in OBN surveys. Among these methods are convolutional techniques...
2024
Estimating CO2 saturation and porosity using the double difference approach based invertible neural network
Arnab Dhara, Mrinal K. Sen, Sohini Dasgupta
International Meeting for Applied Geoscience and Energy (IMAGE)
... posterior pdfs of model parameters to those obtained using Markov Chain Monte Carlo methods at significantly less computational time. We use two...
2023
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)
... – 211. Mohd Razak S, Jafarpour B. (2020a) Convolutional neural networks (CNN) for feature-based model calibration under uncertain geologic scenarios...
2021
How Machine Learning is Helping Seismic Structural Interpreters in The Age of Big Data
Çağil Karakaş, James Kiely
GEO ExPro Magazine
... is a very time-consuming task, often leading to a simplified fault model, a geology-driven, machine-learning workflow can significantly improve...
2021
Abstract: Fault System Delineation Driven by New Technology in Tazhong Karsted Carbonate Reservoirs; #91204 (2023)
Yanming Tong, Xingliang Deng, Chuan Wu, Shiti Cui, Pin Yang, Chunguang Shen, Gaige Wang, Jiangyong Wu, Chenqing Tan
Search and Discovery.com
... the technology of an “end-to-end convolutional neural network (CNN)” to efficiently detect faults from 3D seismic images. In this machine learning...
2023
Application of Deep Learning for Methane Emissions Quantification and Uncertainty Reduction from Spectrometer Images
Ismot Jahan, Mohamed Mehana, Hari Viswanathan
Unconventional Resources Technology Conference (URTEC)
... oil and gas fields in the fields of Texas, California and New Mexico. Methods: We trained a convolutional neural network (CNN) using Large Eddy...
2024
A case study of generating synthetic seismic from simulation to validate reservoir models
Dhananjay Kumar, Jing Zhang, Robert Chrisman, Nayyer Islam, Matt Le Good
International Meeting for Applied Geoscience and Energy (IMAGE)
... a velocity model. Once the elastic model is in the time domain, we used the convolutional method to simulate synthetic seismic. The seismic response (EEI10...
2022
Seismic Forward Modeling of Semberah Fluvio-Deltaic Reservoir
Adi Widyantoro, Wahyu Dwijo Santoso
Indonesian Petroleum Association
... modeling at each UKM wells to understand lithology and fluid effects over amplitude variations, 3) conceptual 2D convolutional model to understand boundary...
2021
Application of Artificial Intelligence for Depositional Facies Recognition - Permian Basin
Randall Miller, Skip Rhodes, Deepak Khosla, Fernando Nino
Unconventional Resources Technology Conference (URTEC)
... in the Permian Basin. Training sets of core facies were selected by a sedimentologist. A model was built using a convolutional neural network...
2019
Accelerate Well Correlation with Deep Learning; #42429 (2019)
Bo Zhang, Yuming Liu, Xinmao Zhou, Zhaohui Xu
Search and Discovery.com
... patterns (such as upward fining and coarsening) in neighboring wells and links them using a conscious or subconscious stratigraphic sequence model...
2019
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
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
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
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
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
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