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A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys

Reservoir simulations for subsurface processes play an important role in successful deployment of geoscience applications such as geothermal energy extraction and geo-storage of fluids. These simulations provide time-lapse dynamics of the coupled poromechanical processes within the reservoir and its...

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Autores principales: van IJsseldijk, Johno, Hajibeygi, Hadi, Wapenaar, Kees
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444811/
https://www.ncbi.nlm.nih.gov/pubmed/37607979
http://dx.doi.org/10.1038/s41598-023-40548-0
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author van IJsseldijk, Johno
Hajibeygi, Hadi
Wapenaar, Kees
author_facet van IJsseldijk, Johno
Hajibeygi, Hadi
Wapenaar, Kees
author_sort van IJsseldijk, Johno
collection PubMed
description Reservoir simulations for subsurface processes play an important role in successful deployment of geoscience applications such as geothermal energy extraction and geo-storage of fluids. These simulations provide time-lapse dynamics of the coupled poromechanical processes within the reservoir and its over-, under-, and side-burden environments. For more reliable operations, it is crucial to connect these reservoir simulation results with the seismic surveys (i.e., observation data). However, despite being crucial, such integration is challenging due to the fact that the reservoir dynamics alters the seismic parameters. In this work, a coupled reservoir simulation and time-lapse seismic methodology is developed for multiphase flow operations in subsurface reservoirs. To this end, a poromechanical simulator is designed for multiphase flow and connected to a forward seismic modeller. This simulator is then used to assess a novel methodology of seismic monitoring by isolating the reservoir signal from the entire reflection response. This methodology is shown to be able to track the development of the fluid front over time, even in the presence of a highly reflective overburden with strong time-lapse variations. These results suggest that the proposed methodology can contribute to a better understanding of fluid flow in the subsurface. Ultimately, this will lead to improved monitoring of reservoirs for underground energy storage or production.
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spelling pubmed-104448112023-08-24 A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys van IJsseldijk, Johno Hajibeygi, Hadi Wapenaar, Kees Sci Rep Article Reservoir simulations for subsurface processes play an important role in successful deployment of geoscience applications such as geothermal energy extraction and geo-storage of fluids. These simulations provide time-lapse dynamics of the coupled poromechanical processes within the reservoir and its over-, under-, and side-burden environments. For more reliable operations, it is crucial to connect these reservoir simulation results with the seismic surveys (i.e., observation data). However, despite being crucial, such integration is challenging due to the fact that the reservoir dynamics alters the seismic parameters. In this work, a coupled reservoir simulation and time-lapse seismic methodology is developed for multiphase flow operations in subsurface reservoirs. To this end, a poromechanical simulator is designed for multiphase flow and connected to a forward seismic modeller. This simulator is then used to assess a novel methodology of seismic monitoring by isolating the reservoir signal from the entire reflection response. This methodology is shown to be able to track the development of the fluid front over time, even in the presence of a highly reflective overburden with strong time-lapse variations. These results suggest that the proposed methodology can contribute to a better understanding of fluid flow in the subsurface. Ultimately, this will lead to improved monitoring of reservoirs for underground energy storage or production. Nature Publishing Group UK 2023-08-22 /pmc/articles/PMC10444811/ /pubmed/37607979 http://dx.doi.org/10.1038/s41598-023-40548-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
van IJsseldijk, Johno
Hajibeygi, Hadi
Wapenaar, Kees
A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title_full A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title_fullStr A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title_full_unstemmed A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title_short A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
title_sort framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444811/
https://www.ncbi.nlm.nih.gov/pubmed/37607979
http://dx.doi.org/10.1038/s41598-023-40548-0
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