Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems
A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2 -CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data...
Published in: | Computers & Geosciences |
---|---|
Main Authors: | , , |
Language: | unknown |
Published: |
2019
|
Subjects: | |
Online Access: | http://www.osti.gov/servlets/purl/1435086 https://www.osti.gov/biblio/1435086 https://doi.org/10.1016/j.cageo.2017.03.018 |
id |
ftosti:oai:osti.gov:1435086 |
---|---|
record_format |
openpolar |
spelling |
ftosti:oai:osti.gov:1435086 2023-07-30T03:55:36+02:00 Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems Reagan, Matthew T. Moridis, George J. Seim, Katie S. 2019-12-24 application/pdf http://www.osti.gov/servlets/purl/1435086 https://www.osti.gov/biblio/1435086 https://doi.org/10.1016/j.cageo.2017.03.018 unknown http://www.osti.gov/servlets/purl/1435086 https://www.osti.gov/biblio/1435086 https://doi.org/10.1016/j.cageo.2017.03.018 doi:10.1016/j.cageo.2017.03.018 58 GEOSCIENCES 97 MATHEMATICS AND COMPUTING 2019 ftosti https://doi.org/10.1016/j.cageo.2017.03.018 2023-07-11T09:25:34Z A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2 -CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set of fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer. Other/Unknown Material Alaska North Slope north slope Alaska SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Computers & Geosciences 103 191 203 |
institution |
Open Polar |
collection |
SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
58 GEOSCIENCES 97 MATHEMATICS AND COMPUTING |
spellingShingle |
58 GEOSCIENCES 97 MATHEMATICS AND COMPUTING Reagan, Matthew T. Moridis, George J. Seim, Katie S. Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
topic_facet |
58 GEOSCIENCES 97 MATHEMATICS AND COMPUTING |
description |
A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2 -CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set of fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer. |
author |
Reagan, Matthew T. Moridis, George J. Seim, Katie S. |
author_facet |
Reagan, Matthew T. Moridis, George J. Seim, Katie S. |
author_sort |
Reagan, Matthew T. |
title |
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
title_short |
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
title_full |
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
title_fullStr |
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
title_full_unstemmed |
Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems |
title_sort |
fast parametric relationships for the large-scale reservoir simulation of mixed ch 4 -co 2 gas hydrate systems |
publishDate |
2019 |
url |
http://www.osti.gov/servlets/purl/1435086 https://www.osti.gov/biblio/1435086 https://doi.org/10.1016/j.cageo.2017.03.018 |
genre |
Alaska North Slope north slope Alaska |
genre_facet |
Alaska North Slope north slope Alaska |
op_relation |
http://www.osti.gov/servlets/purl/1435086 https://www.osti.gov/biblio/1435086 https://doi.org/10.1016/j.cageo.2017.03.018 doi:10.1016/j.cageo.2017.03.018 |
op_doi |
https://doi.org/10.1016/j.cageo.2017.03.018 |
container_title |
Computers & Geosciences |
container_volume |
103 |
container_start_page |
191 |
op_container_end_page |
203 |
_version_ |
1772819856165437440 |