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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Main Author: Yin, Qian
Other Authors: Krahenbuhl, Richard A., Trainor-Guitton, Whitney, Benson, Robert D., Maniloff, Peter, Li, Yaoguo
Format: Text
Language:English
Published: Colorado School of Mines. Arthur Lakes Library 2017
Subjects:
Online Access:https://hdl.handle.net/11124/171143
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record_format openpolar
spelling 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)
institution Open Polar
collection Digital Collections of Colorado (Colorado State University)
op_collection_id ftcolostateunidc
language English
topic 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.
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