Quantifying geological uncertainty and optimizing technoeconomic decisions for geothermal reservoirs
Abstract/Contents
- Abstract
- Globally, 25% percent of greenhouse gas emissions result from electricity generation that is powered by burning fossil fuels. To mitigate climate change due to these emissions, we must increase the electricity portion generated by low-carbon resources, such as geothermal energy. One of the major barriers for geothermal development is financial risk due to geological uncertainty. Production from a geothermal well highly depends on the unknown location of subsurface geological structures, such as faults. Faults are the most important part of geothermal systems because they host the hydrothermal fluids. In geothermal systems, cold rain-water seeps to hot areas in the subsurface and heats up. This hydrothermal fluid then upwells through subsurface faults towards the surface. Geothermal energy developers need to find these faults to: drill wells to intersect these faults, pump out the hot pressurized water and use the water to turn turbines and generate electricity. Yet, characterizing the structure of faults carrying hydrothermal fluids is extremely difficult and uncertain. Traditionally, geoscientists assess the subsurface structure by collecting many different datasets, interpreting the datasets manually, and creating a single model of fault locations. This method, however, is often inaccurate and does not provide any information about geological uncertainty and ensuing financial risk. In this work, we show that geological uncertainty has been a major challenge for developing geothermal systems, specifically enhanced geothermal systems. Using a synthetic case study, we demonstrate that information about geological uncertainty can influence the process of making decisions regarding reservoir management. we then describe a method for generating geologically realistic structural models of geothermal reservoirs that match observed data and apply this stochastic inversion method on real data from the Patua Geothermal Field in Nevada. To conclude, we provide a case study of how geological uncertainty quantified at Patua Geothermal Field can be used to inform the choice of reservoir development actions
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 | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Pollack, Ahinoam |
|---|---|
| Degree supervisor | Mukerji, Tapan, 1965- |
| Thesis advisor | Mukerji, Tapan, 1965- |
| Thesis advisor | Horne, Roland N |
| Thesis advisor | Caers, Jef |
| Degree committee member | Horne, Roland N |
| Degree committee member | Caers, Jef |
| Associated with | Stanford University, Department of Energy Resources Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Ahinoam Pollack |
|---|---|
| Note | Submitted to the Department of Energy Resources Engineering |
| Thesis | Thesis Ph.D. Stanford University 2020 |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Ahinoam Pollack
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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