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Keywords: bayesian inference
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Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3583596
... as observations. The Bayesian inference employs Markov-chain Monte Carlo (McMC) sampling with parallel tempering and principal component diminishing adaption to ensure efficient sampling. The model-parameter uncertainties are quantified through a series of posterior distributions. In the inversion, we adopt new...
Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3583705
... the first application of NF in interpolating (synthetic) seismic data. The statistical measurements retrieved from the network can be used to better characterize the data as it is passed to the post-processing phase. bayesian inference data interpolation reservoir characterization reservoir...
Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3581836
... Uncertainty quantification provides quantitative measures on the reliability of candidate solutions of ill-posed inverse problems. Due to their sequential nature, Monte Carlo sampling methods require large numbers of sampling steps for accurate Bayesian inference and are often computationally...
Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3579316
... classification bayesian inference architecture Facies prediction with Bayesian inference using supervised and semisupervised deep learning Sagar Singh* and Ilya Tsvankin, Colorado School of Mines, and Ehsan Zabihi Naeini, Earth Science Analytics SUMMARY the encoder half of the network compresses the input...
Proceedings Papers

Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3594250
... will be based on unique solver. The Bayesian framework works well in AVO solving the following equation: inversion, which merges multi-formation together to generate posterior distributions of P-wave velocity, S-wave velocity dobs = + (1) and density. In the Bayesian inference, prior distribution, serving...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3415458
... inversion method reflectivity bayesian inference geophysics coefficient reflection coefficient s-impedance equation inversion process synthetic data 2020. Society of Exploration Geophysicists ...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3417560
...: Poster Station 1 Presentation Type: Poster risk management artificial intelligence machine learning risk and uncertainty assessment neural network reservoir simulation inverse problem posterior distribution deep learning automatic horizon reservoir characterization bayesian inference...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3417568
... imaging problems. Presentation Date: Monday, October 12, 2020 Session Start Time: 1:50 PM Presentation Time: 3:55 PM Location: Poster Station 7 Presentation Type: Poster machine learning neural network artificial intelligence reservoir characterization bayesian inference constraint...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3422419
... The Bayesian framework is commonly used to quantify uncertainty in seismic inversion. To perform Bayesian inference, Markov chain Monte Carlo (MCMC) algorithms are regarded as the gold standard technique for sampling from the posterior probability distribution. Consistent MCMC methods have...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3422774
... Uncertainty quantification is an important aspect of time– lapse imaging and is typically done using Bayesian inference. Traditional random– walk sampling methods are slow to converge and they fail to efficiently explore the high dimensional space that must be characterized in time-lapse imaging...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3428211
... reservoir characterization frequency variance bayesian inference wavelet estimation artificial intelligence wavelet estimate slepian function machine learning upstream oil & gas calculation angle stack statistical strength equation individual angle stack ikon science ltd...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3428223
... the cycle-skipping issues. The analogy between objective functions in the deterministic inversion and likelihood functions in Bayesian inversion motivates us to analyze the noise model each objective function accounts for under the Bayesian inference setting. We also show the existence and wellposedness...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3427239
.... Presentation Date: Tuesday, October 13, 2020 Session Start Time: 1:50 PM Presentation Time: 1:50 PM Location: 362C Presentation Type: Oral neural network machine learning reservoir simulation australia dataset ghahramani bayesian inference upstream oil & gas convolutional neural network...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3428389
... of the uncertainties associated with any interpretations and statements based on the seismic data. Bayesian inference solutions provide a framework where these issues can be addressed. However, in its standard formulation and given the size of typical seismic volumes it might result computationally expensive...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3426670
... while exhibiting good parallel scalability for such problems. Presentation Date: Monday, October 12, 2020 Session Start Time: 1:50 PM Presentation Time: 3:05 PM Location: Poster Station 2 Presentation Type: Poster log analysis us government machine learning bayesian inference well logging...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3428150
... characterization bayesian inference machine learning neural network posterior distribution upstream oil & gas full-waveform inversion inverse problem artificial intelligence kullback-leibler divergence geophysics seg international exposition architecture application welling invertible network...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3427560
... learning reservoir simulation bayesian inference model parametrization multimodal distribution model parameter facies artificial intelligence transdimensional ava inversion inverse problem reservoir characterization upstream oil & gas posterior distribution iteration inversion geophysics...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, September 15–20, 2019
Paper Number: SEG-2019-3215174
... posterior distribution upstream oil & gas algorithm seg international exposition neural network constraint seed well accuracy artificial intelligence machine learning probability annual meeting realization well log bayesian inference cnn Brazell , S. , A. Bayeh , I...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, September 15–20, 2019
Paper Number: SEG-2019-3215986
... meeting bayesian inference machine learning metivier tl distance velocity model massachusetts institute artificial intelligence full waveform inversion reservoir characterization geophysics misspecification misfit function full-waveform inversion brossier posterior distribution...
Proceedings Papers

Paper presented at the SEG International Exposition and Annual Meeting, September 15–20, 2019
Paper Number: SEG-2019-3216008
... characterization lanczo algorithm full waveform inversion approximation artificial intelligence standard deviation randomized svd bayesian uncertainty estimation low-rank approximation bayesian inference hessian posterior covariance matrix eigenvalue Bui-Thanh , T. , O. Ghattas...

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