Imaging of a fluid injection process using geophysical data — A didactic example
Abstract
In many subsurface industrial applications, fluids are injected into or withdrawn from a geologic formation. It is of practical interest to quantify precisely where, when, and by how much the injected fluid alters the state of the subsurface. Routine geophysical monitoring of such processes attempts to image the way that geophysical properties, such as seismic velocities or electrical conductivity, change through time and space and to then make qualitative inferences as to where the injected fluid has migrated. The more rigorous formulation of the time-lapse geophysical inverse problem forecasts how the subsurface evolves during the course of a fluid-injection application. Using time-lapse geophysical signals as the data to be matched, the model unknowns to be estimated are the multiphysics forward-modeling parameters controlling the fluid-injection process. Properly reproducing the geophysical signature of the flow process, subsequent simulations can predict the fluid migration and alteration in the subsurface. The dynamic nature of fluid-injection processes renders imaging problems more complex than conventional geophysical imaging for static targets. This work intents to clarify the related hydrogeophysical parameter estimation concepts.
- Authors:
-
[1];
[1];
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth & Environmental Sciences
- Finsterle GeoConsulting, Kensington, CA (United States)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division
- OSTI Identifier:
- 1616977
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Geophysics
- Additional Journal Information:
- Journal Volume: 85; Journal Issue: 2; Journal ID: ISSN 0016-8033
- Publisher:
- Society of Exploration Geophysicists
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES
Citation Formats
Commer, Michael, Pride, Steven R., Vasco, Donald W., Finsterle, Stefan, and Kowalsky, Michael B.. Imaging of a fluid injection process using geophysical data — A didactic example. United States: N. p., 2020.
Web. doi:10.1190/GEO2018-0787.1.
Commer, Michael, Pride, Steven R., Vasco, Donald W., Finsterle, Stefan, & Kowalsky, Michael B.. Imaging of a fluid injection process using geophysical data — A didactic example. United States. https://doi.org/10.1190/GEO2018-0787.1
Commer, Michael, Pride, Steven R., Vasco, Donald W., Finsterle, Stefan, and Kowalsky, Michael B.. Sun .
"Imaging of a fluid injection process using geophysical data — A didactic example". United States. https://doi.org/10.1190/GEO2018-0787.1. https://www.osti.gov/servlets/purl/1616977.
@article{osti_1616977,
title = {Imaging of a fluid injection process using geophysical data — A didactic example},
author = {Commer, Michael and Pride, Steven R. and Vasco, Donald W. and Finsterle, Stefan and Kowalsky, Michael B.},
abstractNote = {In many subsurface industrial applications, fluids are injected into or withdrawn from a geologic formation. It is of practical interest to quantify precisely where, when, and by how much the injected fluid alters the state of the subsurface. Routine geophysical monitoring of such processes attempts to image the way that geophysical properties, such as seismic velocities or electrical conductivity, change through time and space and to then make qualitative inferences as to where the injected fluid has migrated. The more rigorous formulation of the time-lapse geophysical inverse problem forecasts how the subsurface evolves during the course of a fluid-injection application. Using time-lapse geophysical signals as the data to be matched, the model unknowns to be estimated are the multiphysics forward-modeling parameters controlling the fluid-injection process. Properly reproducing the geophysical signature of the flow process, subsequent simulations can predict the fluid migration and alteration in the subsurface. The dynamic nature of fluid-injection processes renders imaging problems more complex than conventional geophysical imaging for static targets. This work intents to clarify the related hydrogeophysical parameter estimation concepts.},
doi = {10.1190/GEO2018-0787.1},
journal = {Geophysics},
number = 2,
volume = 85,
place = {United States},
year = {2020},
month = {3}
}
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