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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
High-fidelity GPR image super-resolution via deep-supervised machine learning
Kai Gao, Carly M. Donahue, Bradley G. Henderson, Ryan T. Modrak
International Meeting for Applied Geoscience and Energy (IMAGE)
... to achieve high-resolution GPR images in real-time. Our method is based on a supervised attention-based neural network where we train the neural network...
2022
Rock Thin-section Analysis and Mineral Detection Utilizing Deep Learning Approach
Fatick Nath, Sarker Asish, Shaon Sutradhar, Zhiyang Li, Nazmul Shahadat, Happy R. Debi, S M Shamsul Hoque
Unconventional Resources Technology Conference (URTEC)
... of rock thin sections. In a similar objective, Nanjo et al. (2019) implemented convolutional neural network-based model to classify four types of rock...
2023
Predicting Hydrocarbon Production Behavior in Heterogeneous Reservoir Utilizing Deep Learning Models
Fatick Nath, Sarker Asish, Happy R. Debi, Mohammed Omar S Chowdhury, Zackary J. Zamora, Sergio Muñoz
Unconventional Resources Technology Conference (URTEC)
..., the Bi-LSTM model has been examined as a more efficient model in time series data prediction than the LSTM model (Nath et al. 2023a; Nath et al. 2023b...
2023
3D velocity model building based upon hybrid neural network
Herurisa Rusmanugroho, Junxiao Li, M. Daniel Davis Muhammed, Jian Sun
International Meeting for Applied Geoscience and Energy (IMAGE)
... as an image are passed through some convolutional layers to estimate P-velocity model. This network is expected to learn from the features obtained from...
2022
Seismic random noise attenuation via enhanced similarity self-supervised learning
Jiale Wang, Naihao Liu, Yihuai Lou, Jinghuai Gao
International Meeting for Applied Geoscience and Energy (IMAGE)
... the requirement of noise-free labels, we propose an enhanced similarity self-supervised learning (ESSL) model by effectively utilizing the self-similarity...
2022
Lithofacies identification in cores using deep learning segmentation and the role of geoscientists: Turbidite deposits (Gulf of Mexico and North Sea)
Oriol Falivene, Neal C. Auchter, Rafael Pires de Lima, Luuk Kleipool, John G. Solum, Pedram Zarian, Rachel W. Clark, and Irene Espejo
AAPG Bulletin
... and planetary sciences. Acquisition, description, and interpretation of geologic core is fundamental for subsurface characterization. However, it is time...
2022
From Chaos to Caves An Evolution of Seismic Karst Interpretation at the Vorwata Field
Riangguna Eloni, M.R. Husni Sahidu, Ilham Panggeleng, Christopher S. Birt, Ted Manning
Indonesian Petroleum Association
.... These formations have resulted in historical drilling Non-Productive Time (NPT) such as lost circulation, tight hole and stuck pipe. A variety...
2016
Training data versus deep learning architectures in the seismic fault attribute computation
Bo Zhang, Yitao Pu, Zhaohui Xu, Naihao Liu, Shizhen Li, Fangyu Li
International Meeting for Applied Geoscience and Energy (IMAGE)
... all the faults for a sub-seismic volume whose size is 128 (inlines) by 128 (crosslines) by 128 (time samples). However, interpreting a few key inline...
2022
Pushing the limit of 5D interpolation using deep learning
Yangkang Chen, Hang Wang, Chao Li, Omar M. Saad
International Meeting for Applied Geoscience and Energy (IMAGE)
... prepare the initial model in the COP domain instead of the CMP domain is that, in a COP domain with certain offset values, the travel times for adjacent...
2024
The use of FWI in coal exploration
Mehdi Asgharzadeh, Maryam Bahri, Milovan Urosevic
Petroleum Exploration Society of Australia (PESA)
... the time interval t. For a given model m of the subsurface, the forward problem (wave equation) can be solved using numerical methods mod...
2018
Background noise suppression for DAS-VSP data using attention-based deep image prior
Yang Cui, Umair bin Waheed, Yangkang Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
... classical (such as wavelet and curvelet) and dictionary-learning techniques, rely on distinguishing signal components in the transform domain, albeit...
2024
Deep learning-based 3D microseismic event direct location using simultaneous surface and borehole data: An application to the Utah FORGE site
Yuanyuan Yang, Omar M. Saad, Tariq Alkhalifah
International Meeting for Applied Geoscience and Energy (IMAGE)
.... The proposed method has potent compatibility for embracing diverse datasets and a strong ability to model complex dynamics and interactions between...
2024
Machine learning and seismic attributes for prospect identification and risking: An example from offshore Australia
Mohammed Farfour, Douglas Foster
International Meeting for Applied Geoscience and Energy (IMAGE)
... and convert them to Gas chimney probability cube, and to Gamma Ray cube. Next, pre-trained Convolutional Neural Network (CNN) is trained using...
2022
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
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
Artificial intelligence techniques to the interpretation of geophysical measurements
Desmond FitzGerald
Petroleum Exploration Society of Australia (PESA)
... SUMMARY Integration of geology and geophysics thinking requires a common earth model, that accommodates, with errors, all the features from...
2019
Joint 3D inversion of gravity and magnetic data using deep learning neural networks
Nanyu Wei, Dikun Yang, Zhigang Wang, Yao Lu
International Meeting for Applied Geoscience and Energy (IMAGE)
... uses a supervised deep neural network, developed based on fully convolutional networks and further combined with a U-Net architecture. Two multi-model...
2022
Digital Innovation in Subsea Integrity Management
Ricky Thethi, Dharmik Vadel, Mark Haning, Elizabeth Tellier
Australian Petroleum Production & Exploration Association (APPEA) Journal
... (RNN) and convolutional neural network (CNN) based algorithms have been found (Sundararaman et al. 2018) to work well in developing time domain stress...
2020
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
Application of Machine Learning Methods to Assess Progressive Cavity Pumps (PCPs) Performance in Coal Seam Gas (CSG) Wells
Fahd Saghir, M. E. Gonzalez Perdomo, Peter Behrenbruch
Australian Petroleum Production & Exploration Association (APPEA) Journal
...-series data tables directly into a neural network model or (2) by converting time-series data in images. There are three methodologies that describe...
2020
Deep learning velocity model building using an ensemble regression approach
Stuart Farris, Guillaume Barnier, Robert Clapp
International Meeting for Applied Geoscience and Energy (IMAGE)
... framework that uses a convolutional neural network (CNN) to form an ensemble of low wavenumber model predictions which can be integrated to form...
2022
Aiding self-supervised coherent noise suppression by the introduction of signal segmentation using blind-spot networks
Sixiu Liu, Claire Birnie, Tariq Alkhalifah, Andrey Bakulin
International Meeting for Applied Geoscience and Energy (IMAGE)
... al., 2019; Wang and Chen, 2019; Birnie et al., 2021a). A number of NN-based denoising procedures utilise Convolutional Neural Networks (CNNs) to learn...
2022
Accelerating innovation with software abstractions for scalable computational geophysics
Mathias Louboutin, Philipp Witte, Ali Siahkoohi, Gabrio Rizzuti, Ziyi Yin, Rafael Orozco, Felix J. Herrmann
International Meeting for Applied Geoscience and Energy (IMAGE)
... model with a marine acquisition. This RTM was run on a GPU without moving off to the CPU at any time using randomized trace estimation as an extension...
2022
Supervised vs unsupervised deep learning for time-lapse seismic repeatability enforcement
Son Phan, Wenyi Hu, Aria Abubakar
International Meeting for Applied Geoscience and Energy (IMAGE)
... methodology in the medical image domain, in this work, we developed and adapted an unsupervised learning algorithm to time-lapse seismic data analysis...
2024
Augmented Data Management for Subsurface CCUS Data Sets
Rhys Blake, Jess B. Kozman, James Lamb, Lorena Pelegrin
Carbon Capture, Utilization and Storage (CCUS)
... workflows for using artificial and convolutional neural networks to find information in legacy documents that can predict physical properties...
2025