Advancing utilization of positron emission tomography for quantifying fluid transport and CO₂ trapping in geologic porous media

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Abstract/Contents

Abstract
Accurate observations and descriptions of the role of heterogeneity on water and CO2 transport and immobilization in porous and fractured geologic media are important for understanding and modeling multiphase conditions present in geologic carbon storage reservoirs. The growth in in-situ imaging has lead to remarkable advancements in understanding and quantification of this complex fluid transport behavior. Despite these advancements, commonly used imaging and experimental methods such as clinical computed tomography, micro computed tomography, nuclear magnetic resonance, and optical imaged micromodels each have limitations. Each modality faces individual challenges with observing fluid advection, dispersion, and diffusion, in 3D geologic porous media. In this work, micro-positron emission tomography (micro-PET), in combination with other imaging methods, is utilized to study a number of challenging transport problems in earth science.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2018; ©2018
Publication date 2018; 2018
Issuance monographic
Language English

Creators/Contributors

Author Zahasky, Christopher James
Degree supervisor Benson, Sally
Thesis advisor Benson, Sally
Thesis advisor Horne, Roland N
Thesis advisor Kovscek, Anthony R. (Anthony Robert)
Degree committee member Horne, Roland N
Degree committee member Kovscek, Anthony R. (Anthony Robert)
Associated with Stanford University, Department of Energy Resources Engineering.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Christopher James Zahasky.
Note Submitted to the Department of Energy Resources Engineering.
Thesis Thesis Ph.D. Stanford University 2018.
Location electronic resource

Access conditions

Copyright
© 2018 by Christopher Zahasky
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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