Stochastic models for flow and transport in heterogeneous porous media
Abstract/Contents
- Abstract
- Modeling flow and transport in porous media is an important part of the decision-making process in managing crucial resources such as underground aquifers and hydrocarbon reservoirs, subsurface disposal of contaminants, and the design of battery systems. The multiscale nature of porous media, the heterogeneity of their properties and the uncertainty of our knowledge of these properties pose significant modeling challenges that have been the focus of extensive research. In this work, four important contributions are made to the modeling of flow and transport in porous systems. First, a non-local formulation is rigorously derived to find the average flow solution in multiscale porous media. Second, the stochastic representation of the flow problem is used for quantifying the flow uncertainty in cases with heterogeneous conductivity fields. An algorithm is proposed for using the Feynman-Kac formulation for one-dimensional elliptic problems with piecewise constant conductivity and various schemes were explored to improve the efficiency of particle tracking algorithms for both stochastic and deterministic flow problems. The third contribution of this work is the introduction of the stencil method, a discrete temporal Markov model for modeling transport in networks representing porous material. The stencil method simplifies the temporal models used to simulate mean transport in porous media. Finally, a fast discrete temporal Markov velocity process is introduced to simulate ensemble transport in highly heterogeneous continuum scale conductivity fields. This is the first stochastic model to simulate dispersion in high-variance conductivity fields for both Gaussian and exponential correlation structures.
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 | Delgoshaie, Amir Hossein |
|---|---|
| Degree supervisor | Tchelepi, Hamdi |
| Thesis advisor | Tchelepi, Hamdi |
| Thesis advisor | Jenny, Patrick |
| Thesis advisor | Tartakovsky, Daniel |
| Degree committee member | Jenny, Patrick |
| Degree committee member | Tartakovsky, Daniel |
| Associated with | Stanford University, Department of Energy Resources Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Amir Hossein Delgoshaie. |
|---|---|
| Note | Submitted to the Department of Energy Resources Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Amir Hossein Delgoshaie
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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