Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models
Includes bibliographical references. 2017 Summer. In this thesis, I revisit the time-lapse gravity data collected to monitor gas-cap water injection at Prudhoe Bay to understand how we can best integrate a field's detailed reservoir simulation data into the gravity inversion for an integrated i...
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ftcolostateunidc:oai:mountainscholar.org:11124/171143 2023-05-15T18:03:37+02:00 Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models Yin, Qian Krahenbuhl, Richard A. Trainor-Guitton, Whitney Benson, Robert D. Maniloff, Peter Li, Yaoguo 2017-07-20T19:38:24Z born digital masters theses application/pdf https://hdl.handle.net/11124/171143 English eng eng Colorado School of Mines. Arthur Lakes Library 2017 - Mines Theses & Dissertations Yin_mines_0052N_11292.pdf T 8308 https://hdl.handle.net/11124/171143 Copyright of the original work is retained by the author. inversion Prudhoe Bay time-lapse gravity monitoring integration reservoir simulation Text 2017 ftcolostateunidc 2021-07-14T20:53:48Z Includes bibliographical references. 2017 Summer. In this thesis, I revisit the time-lapse gravity data collected to monitor gas-cap water injection at Prudhoe Bay to understand how we can best integrate a field's detailed reservoir simulation data into the gravity inversion for an integrated interpretation. For this, I explore two methodologies that can directly incorporate into the inversions a set of time-lapse density models that can be constructed from the reservoir simulation parameters. The first approach is a continuous variable inversion where the reservoir information can be converted into an appropriate reference model to guide both the shape and amplitude of the recovered densities from the water flood. The second is a binary inversion, where the reservoir data are included as background density models to predefine the amplitude of the recovered time-lapse densities, allowing the algorithm to focus on recovering the locations and shape of the expanding water plume. Results for the two methods show that the reservoir data do guide and constrain the gravity inversions to distribution comparable to water movement within the simulation models, and thus provide valuable approaches for integrated monitoring with time-lapse gravity. The results additionally demonstrate deviations from the reservoir simulation models, indicating that either the surface gravity is not sensitive to the subtle changes in saturation in particular regions, or that the reservoir models contain saturation changes that may be too high or too low in areas. Text Prudhoe Bay Digital Collections of Colorado (Colorado State University) |
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Open Polar |
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Digital Collections of Colorado (Colorado State University) |
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ftcolostateunidc |
language |
English |
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inversion Prudhoe Bay time-lapse gravity monitoring integration reservoir simulation |
spellingShingle |
inversion Prudhoe Bay time-lapse gravity monitoring integration reservoir simulation Yin, Qian Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
topic_facet |
inversion Prudhoe Bay time-lapse gravity monitoring integration reservoir simulation |
description |
Includes bibliographical references. 2017 Summer. In this thesis, I revisit the time-lapse gravity data collected to monitor gas-cap water injection at Prudhoe Bay to understand how we can best integrate a field's detailed reservoir simulation data into the gravity inversion for an integrated interpretation. For this, I explore two methodologies that can directly incorporate into the inversions a set of time-lapse density models that can be constructed from the reservoir simulation parameters. The first approach is a continuous variable inversion where the reservoir information can be converted into an appropriate reference model to guide both the shape and amplitude of the recovered densities from the water flood. The second is a binary inversion, where the reservoir data are included as background density models to predefine the amplitude of the recovered time-lapse densities, allowing the algorithm to focus on recovering the locations and shape of the expanding water plume. Results for the two methods show that the reservoir data do guide and constrain the gravity inversions to distribution comparable to water movement within the simulation models, and thus provide valuable approaches for integrated monitoring with time-lapse gravity. The results additionally demonstrate deviations from the reservoir simulation models, indicating that either the surface gravity is not sensitive to the subtle changes in saturation in particular regions, or that the reservoir models contain saturation changes that may be too high or too low in areas. |
author2 |
Krahenbuhl, Richard A. Trainor-Guitton, Whitney Benson, Robert D. Maniloff, Peter Li, Yaoguo |
format |
Text |
author |
Yin, Qian |
author_facet |
Yin, Qian |
author_sort |
Yin, Qian |
title |
Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
title_short |
Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
title_full |
Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
title_fullStr |
Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
title_full_unstemmed |
Time-lapse gravity data at Prudhoe Bay: new understanding through integration with reservoir simulation models |
title_sort |
time-lapse gravity data at prudhoe bay: new understanding through integration with reservoir simulation models |
publisher |
Colorado School of Mines. Arthur Lakes Library |
publishDate |
2017 |
url |
https://hdl.handle.net/11124/171143 |
genre |
Prudhoe Bay |
genre_facet |
Prudhoe Bay |
op_relation |
2017 - Mines Theses & Dissertations Yin_mines_0052N_11292.pdf T 8308 https://hdl.handle.net/11124/171143 |
op_rights |
Copyright of the original work is retained by the author. |
_version_ |
1766174544981131264 |