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The AAPG/Datapages Combined Publications Database
Showing 621 Results. Searched 200,293 documents.
Interpretation of deep neural networks for carbonate thin section classification
Lukas Mosser, George Ghon, Gregor Baechle
International Meeting for Applied Geoscience and Energy (IMAGE)
... and Duarte, 2021; Patel and Chatterjee, 2016; Pe˜ a et al., 2019). n Interpretation of carbonate rock types is time-consuming and requires expert domain...
2022
ABSTRACT: Quantitative Integration of 4D Seismic for Field Development; #90007 (2002)
Garnham, Gail Riekie, Malu Jensen, Liz Pointing
Search and Discovery.com
..., a dedicated time-lapse monitoring survey was acquired and, in 2000, a further 4D survey was acquired. Forward Convolutional Models of 4D Signature Forward...
Unknown
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)
... conditions. Synthetic 3D acoustic time-domain data are generated via finite difference and the obtained 3D seismic dataset is decomposed through...
2022
Seismic interpolation based on quadratic denoising neural network
Yuhan Sui, Xiaojing Wang, Jianwei Ma
International Meeting for Applied Geoscience and Energy (IMAGE)
.... Recently, a deep learning-based method is developed to achieve seismic interpolation by integrating the well-trained denoising convolutional neural...
2024
Abstract: Machine Learning Assisted Fracture Characterization with Borehole Image Logs in Geothermal Wells; #91204 (2023)
Chicheng Xu
Search and Discovery.com
... from multiple sources of data, we build a convolutional neural network model and train it with the labeled results from borehole image log. The model...
2023
Coloured Seismic Inversion, a Simple, Fast and Cost Effective Way of Inverting Seismic Data: Examples from Clastic and Carbonate Reservoirs, Indonesia
Keith Maynard, Paulus Allo, Phill Houghton
Indonesian Petroleum Association
... response. Figure 4. Operator design process. The assumption is made that the seismic data is zero phase, so that a convolutional operator in the time...
2003
Bridging the gap: Deep learning on seismic field data with synthetic training for building Gulf of Mexico velocity models
Stuart Farris, Robert Clapp
International Meeting for Applied Geoscience and Energy (IMAGE)
... Clapp, Stanford University SUMMARY This study employs Convolutional Neural Networks (CNNs) to predict low-wavenumber seismic velocity models to serve...
2023
Sparse time-frequency representation based on Unet with domain adaptation
Yuxin Zhang, Naihao Liu, Yang Yang, Zhiguo Wang, Jinghuai Gao, Xiudi Jiang
International Meeting for Applied Geoscience and Energy (IMAGE)
... propose the sparse time-frequency representation (STFR) based on Unet with domain adaptation (STFR-UDA) model for solving these issues. First, we...
2022
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
Deep learning Laplace-Fourier full-waveform inversion with virtual supershot gathers
Lei Fu, Daniele Colombo, Weichang Li, Ernesto Sandoval-Curiel, Ersan Turkoglu
International Meeting for Applied Geoscience and Energy (IMAGE)
...equally spaced sources and receivers at 100 m and 25 m respectively, covering the whole extension of the model that measures 6.0 km × 2.0 km. Time...
2022
Deep learning-based Vz-noise attenuation for OBS data
Jing Sun, Arash Jafargandomi, Julian Holden
International Meeting for Applied Geoscience and Energy (IMAGE)
... component is its coherency in the common-receiver domain and incoherency in the commonshot domain. There have been a range of noise attenuation...
2023
Towards Universal Production Forecasting via Adversarial Transfer Learning and Transformer with Application in the Shengli Oilfield, China
Ji Chang, Jin Meng, Dongwei Zhang, Tianrui Ye, Han Wang, Yitian Xiao
Unconventional Resources Technology Conference (URTEC)
... and as the optional control covariates (such as choke size and stroke length). We aim to make -time step ahead forecasts via deep learning model...
2024
High-resolution seismic reservoir monitoring with multitask and transfer learning
Ahmed M. Ahmed, Ilya Tsvankin, Yanhua Liu
International Meeting for Applied Geoscience and Energy (IMAGE)
... for various encoder-decoder configurations helps evaluate the model’s efficiency. As expected, the time increases with the number of encoders...
2024
Generative modeling for inverse problems
Rami Nammour
International Meeting for Applied Geoscience and Energy (IMAGE)
... of the model (the domain) of the IP renders global optimization methods feasible, circumventing nonconvexity. The decimation of the data (the range) of the IP...
2022
Predicting horizons for salt body models using machine learning from neighboring seismic surveys: A case study from the northern Gulf of Mexico
Andrew Reisdorf, Dan Ferdinand Fernandez, Hugo Enrique Munoz Cuenca, Ryan King, David Manzano, Gavin Menzel-Jones
International Meeting for Applied Geoscience and Energy (IMAGE)
... regions with little to no upfront interpretation. This decreases the turnaround time for seismic interpretations and allows for more model...
2022
Deep learning based automatic marker separation
Atul Laxman Katole, Aria Abubakar, Edo Hoekstra, Srikanth Ryali, Tao Zhao
International Meeting for Applied Geoscience and Energy (IMAGE)
... entirely dispenses with convolutional and recurrence-based approaches, and instead rely on the attention mechanism to model the sequential nature...
2023
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
..., i.e. Radon domain signal and resolution enhancement, Time-domain amplitude balancing and Frequency-domain lowfrequency balancing. From the raw...
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
Convolutional neural networks as an aid to biostratigraphy and micropaleontology: a test on late Paleozoic microfossils
Rafael Pires De Lima, Katie F. Welch, James E. Barrick, Kurt J. Marfurt, Roger Burkhalter, Murphy Cassel, Gerilyn S. Soreghan
PALAIOS
... and the input data to train the convolutional kernel weights. Cross Entropy Loss.—A measure of the difference between the model’s predictions are from...
2020
Transfer learning for cement evaluation: An image classification approach using VDL time series
Amirhossein Abdollahian, Hua Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
.... These examples could range from images and text to audio, signals, or even tabular data, depending on the original domain of the model. When this model is applied...
2024
Detect Oil Spill in Offshore Facility Using Convolutional Neural Network and Transfer Learning
Dharmawan Raharjo, Muhamad Solehudin
Indonesian Petroleum Association
...Detect Oil Spill in Offshore Facility Using Convolutional Neural Network and Transfer Learning Dharmawan Raharjo, Muhamad Solehudin This paper has...
2021
SaltCrawler: AI solution for accelerating velocity model building
Engin Alkan, Yihua Cai, Pandu Devarakota, Apurva Gala, John Kimbro, Dean Knott, Gislain Madiba, Jeff Moore
International Meeting for Applied Geoscience and Energy (IMAGE)
... to our velocity model building workflows and deployed and has demonstrated cycle time reduction in several exploration and development interpretation...
2022
Optimized transparent boundary conditions for wave propagation
G. Roncoroni, B. Arntsen, E. Forte, M. Pipan
International Meeting for Applied Geoscience and Energy (IMAGE)
... within a 1D velocity model, we ensure the absence of boundary reflections within the region of interest of the extended domain (see Figure 2), thereby...
2024
GAN-based priors for Bayesian inference of subsurface geology at large scale
Kevin B. Daly, Tuan A. Tran, Brent D. Wheelock, Grant J. Seastream
International Meeting for Applied Geoscience and Energy (IMAGE)
... knowledge within a Generative Adversarial Network (GAN; Goodfellow et al., 2014), a generative machine-learning (ML) model with fast sampling-time...
2024
Automated metallic pipeline detection using magnetic data and convolutional neural networks
Brett Bernstein, Yaoguo Li, Richard Hammack
International Meeting for Applied Geoscience and Energy (IMAGE)
...Automated metallic pipeline detection using magnetic data and convolutional neural networks Brett Bernstein, Yaoguo Li, Richard Hammack Automated...
2022