Skip Nav Destination
Close Modal
Update search
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
- Paper Number
NARROW
Format
Subjects
Article Type
Date
Availability
1-13 of 13
Keywords: posterior
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 27–September 1, 2023
Paper Number: SEG-2023-3910056
... We use the Hamiltonian Monte Carlo (HMC) algorithm to estimate the posterior probability distribution of a number of earthquake source parameters. This distribution describes the probability of these parameters attaining a specific set of values. The efficiency of the HMC algorithm, however, can...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3750132
... a framework that considerably mitigates the aforementioned challenges of expensive physics and complex posteriors. The proposed framework exploits the low-dimensionality provided by deep generative priors, and approximates the posterior using deep mixture models via variational inference. The efficacy of our...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3584203
... UQ in geophysical inverse problems. optimization problem engineering reservoir characterization structural geology artificial intelligence upstream oil & gas posterior practical bayesian inversion representation applied geoscience salt body exploration geophysicist 10 machine...
Proceedings Papers
Andrea Scarinci, Youssef Marzouk, Chen Gu, Michael Fehler, Umair bin Waheed, Sanlinn Kaka, Ben M. Dia
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, September 26–October 1, 2021
Paper Number: SEG-2021-3594806
... layered-medium models derived from vertical profiles of velocity at single locations in the 3D model. A consistent Bayesian update is established to integrate the aforementioned distance with FWI. Through an appropriate scoring system, we show that, on average, TL distances produce posterior distributions...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3428223
... of their corresponding posterior measures. In particular, the theorem shows that theWasserstein-type likelihood offers better stability with respect to the noise in the recorded data. Together with an application of the level-set prior, we demonstrate by numerical examples the successful reconstruction from Bayesian...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3422534
... to construct 2D migration images. A machine learning approach is used to calculate the posterior probabilities needed for the value of imperfect information. Our 2D numerical experiments compare images created from both sparsely space (80m), two-component geophone sampling to high spatial resolution (1 m...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the SEG International Exposition and Annual Meeting, October 11–16, 2020
Paper Number: SEG-2020-3426204
... to synthetic datasets and show that we converge towards an accurate posterior distribution. BEL1D (Bayesian Evidential Learning 1D imaging) has This will be performed by comparing our results with a state- recently been introduced as a viable option for the stochastic of-the-art McMC algorithm: DREAM (Vrugt...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2016 SEG International Exposition and Annual Meeting, October 16–21, 2016
Paper Number: SEG-2016-13875371
... the uncertainty of the fault plane solution. The posterior distribution is effectively calculated by sampling from the posterior distribution of the event location, and performing a moment-tensor inversion using individual samples. The uncertainty in the reconstructed moment tensor depends on the receiver...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2015 SEG Annual Meeting, October 18–23, 2015
Paper Number: SEG-2015-5733829
... surveillance voi imperfect conductance bin geothermal reservoir reservoir characterization production control clay cap production monitoring geothermal field data geothermal resource interpretation information management information analysis artificial intelligence posterior new drilling...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2013 SEG Annual Meeting, September 22–27, 2013
Paper Number: SEG-2013-1059
... Summary I present a new scheme for solving the general stochastic inverse problem. The main pillars of the technique are hierarchical parameterizations of the model domain, posterior misfit approximation (and prediction), re-sampling of the predicted posterior, and a posterior model...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2010 SEG Annual Meeting, October 17–22, 2010
Paper Number: SEG-2010-3882
... Summary We outline a general nonlinear inverse uncertainty estimation method that allows for the comprehensive search of model posterior space while maintaining computational efficiencies similar to deterministic inversions. Integral to this method is the combination of a parameter reduction...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2007 SEG Annual Meeting, September 23–28, 2007
Paper Number: SEG-2007-1918
... the posterior distribution by a Metropolis-Hastings algorithm, see e.g. Tjelmeland and Eidsvik (2005), but here we only focus on the maximum a posteriori solution. MODEL The parametrization we are using for the reflection coefficients is in P-wave and S-wave impedance and density. Stovas and Ursin (2003...
Proceedings Papers
Publisher: Society of Exploration Geophysicists
Paper presented at the 2007 SEG Annual Meeting, September 23–28, 2007
Paper Number: SEG-2007-1883
... SUMMARY It is superior to formulate an inverse problem in a Bayesian framework and fully solve it by stochastically constructing the posterior probability density function or PPD surface using MCMC (Monte Carlo Markov Chain) algorithms. The estimated PPD can also be used to compute several...