Data assimilation for a geological process model using the ensemble Kalman filter
We consider the problem of conditioning a geological process‐based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we frame this as a Bayesian inverse problem, and propose to characterise the poste...
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Online Access: | http://hdl.handle.net/11250/2493745 https://doi.org/10.1111/bre.12273 |
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ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2493745 2023-05-15T17:40:14+02:00 Data assimilation for a geological process model using the ensemble Kalman filter Skauvold, Jacob Eidsvik, Jo 2017 http://hdl.handle.net/11250/2493745 https://doi.org/10.1111/bre.12273 eng eng Wiley Norges forskningsråd: 234001 urn:issn:0950-091X http://hdl.handle.net/11250/2493745 https://doi.org/10.1111/bre.12273 cristin:1543850 Basin Research Journal article 2017 ftntnutrondheimi https://doi.org/10.1111/bre.12273 2019-09-17T06:53:49Z We consider the problem of conditioning a geological process‐based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we frame this as a Bayesian inverse problem, and propose to characterise the posterior probability distribution of the geological quantities of interest by using a variant of the ensemble Kalman filter, an estimation method which linearly and sequentially conditions realisations of the system state to data. A test case involving synthetic data is used to assess the performance of the proposed estimation method, and to compare it with similar approaches. We further apply the method to a more realistic test case, involving real well data from the Colville foreland basin, North Slope, Alaska. submittedVersion This is the pre-peer reviewed version of the following article: [Data assimilation for a geological process model using the ensemble Kalman filter], which has been published in final form at [https://onlinelibrary.wiley.com/doi/abs/10.1111/bre.12273]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. Article in Journal/Newspaper north slope Alaska NTNU Open Archive (Norwegian University of Science and Technology) Basin Research 30 4 730 745 |
institution |
Open Polar |
collection |
NTNU Open Archive (Norwegian University of Science and Technology) |
op_collection_id |
ftntnutrondheimi |
language |
English |
description |
We consider the problem of conditioning a geological process‐based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we frame this as a Bayesian inverse problem, and propose to characterise the posterior probability distribution of the geological quantities of interest by using a variant of the ensemble Kalman filter, an estimation method which linearly and sequentially conditions realisations of the system state to data. A test case involving synthetic data is used to assess the performance of the proposed estimation method, and to compare it with similar approaches. We further apply the method to a more realistic test case, involving real well data from the Colville foreland basin, North Slope, Alaska. submittedVersion This is the pre-peer reviewed version of the following article: [Data assimilation for a geological process model using the ensemble Kalman filter], which has been published in final form at [https://onlinelibrary.wiley.com/doi/abs/10.1111/bre.12273]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. |
format |
Article in Journal/Newspaper |
author |
Skauvold, Jacob Eidsvik, Jo |
spellingShingle |
Skauvold, Jacob Eidsvik, Jo Data assimilation for a geological process model using the ensemble Kalman filter |
author_facet |
Skauvold, Jacob Eidsvik, Jo |
author_sort |
Skauvold, Jacob |
title |
Data assimilation for a geological process model using the ensemble Kalman filter |
title_short |
Data assimilation for a geological process model using the ensemble Kalman filter |
title_full |
Data assimilation for a geological process model using the ensemble Kalman filter |
title_fullStr |
Data assimilation for a geological process model using the ensemble Kalman filter |
title_full_unstemmed |
Data assimilation for a geological process model using the ensemble Kalman filter |
title_sort |
data assimilation for a geological process model using the ensemble kalman filter |
publisher |
Wiley |
publishDate |
2017 |
url |
http://hdl.handle.net/11250/2493745 https://doi.org/10.1111/bre.12273 |
genre |
north slope Alaska |
genre_facet |
north slope Alaska |
op_source |
Basin Research |
op_relation |
Norges forskningsråd: 234001 urn:issn:0950-091X http://hdl.handle.net/11250/2493745 https://doi.org/10.1111/bre.12273 cristin:1543850 |
op_doi |
https://doi.org/10.1111/bre.12273 |
container_title |
Basin Research |
container_volume |
30 |
container_issue |
4 |
container_start_page |
730 |
op_container_end_page |
745 |
_version_ |
1766141115208040448 |