Fracture characterization in geothermal reservoirs using time-lapse electric potential data
Abstract/Contents
- Abstract
- The configuration of fractures in a geothermal reservoir is central to the performance of the system. The interconnected fractures control the heat and mass transport in the reservoir and if the fluid reaches production wells before it is fully heated, unfavorable effects on energy production may result due to decreasing fluid enthalpies. Consequently, inappropriate placing of injection or production wells can lead to premature thermal breakthrough. Thus, fracture characterization in geothermal reservoirs is an important task in order to design the recovery strategy appropriately and increase the overall efficiency of the power production. This is true both in naturally fractured geothermal systems as well as in Enhanced Geothermal Systems (EGS) with man-made fractures produced by hydraulic stimulation. In this study, the aim was to estimate fracture connectivity in geothermal reservoirs using a conductive fluid injection and an inversion of time-lapse electric potential data. Discrete fracture networks were modeled and a flow simulator was used first to simulate the flow of a conductive tracer through the reservoirs. Then, the simulator was applied to solve the electric fields at each time step by utilizing the analogy between Ohm's law and Darcy's law. The electric potential difference between well-pairs drops as a conductive fluid fills fracture paths from the injector towards the producer. Therefore, the time-lapse electric potential data can be representative of the connectivity of the fracture network. Flow and electric simulations were performed on models of various fracture networks and inverse modeling was used to match reservoir models to other fracture networks in a library of networks by comparing the time-histories of the electric potential. Two fracture characterization indices were investigated for describing the character of the fractured reservoirs; the fractional connected area and the spatial fractal dimension. In most cases, the electrical potential approach was used successfully to estimate both the fractional connected area of the reservoirs and the spatial fractal dimension. The locations of the linked fracture sets were also predicted correctly. Next, the electric method was compared to using only the simple tracer return curves at the producers in the inverse analysis. The study showed that the fracture characterization indices were estimated somewhat better using the electric approach. The locations of connected areas in the predicted network were also in many cases incorrect when only the tracer return curves were used. The use of the electric approach to predict thermal return was investigated and compared to using just the simple tracer return curves. The electric approach predicted the thermal return curves relatively accurately. However, in some cases the tracer return gave a better estimation of the thermal behavior. The electric measurements are affected by both the time it takes for the conductive tracer to reach the production well, as well as the overall location of the connected areas. When only the tracer return curves are used in the inverse analysis, only the concentration of tracer at the producer is measured but there is a good correlation between the tracer breakthrough time and the thermal breakthrough times. Thus, the tracer return curves can predict the thermal return accurately but the overall location of fractures might not be predicted correctly. The electric data and the tracer return data were also used together in an inverse analysis to predict the thermal returns. The results were in some cases somewhat better than using only the tracer return curves or only the electric data. A different injection scheme was also tested for both approaches. The electric data characterized the overall fracture network better than the tracer return curves so when the well pattern was changed from what was used during the tracer and electric measurements, the electric approach predicted the new thermal return better. In addition, the thermal return was predicted considerably better using the electric approach when measurements over a shorter period of time were used in the inverse analysis. In addition to characterizing the fracture distribution better, the electric approach can give information about the conductive fluid flowing through the fracture network even before it has reached the production wells.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Magnúsdóttir, Lilja |
|---|---|
| Associated with | Stanford University, Department of Energy Resources Engineering. |
| Primary advisor | Horne, Roland N |
| Thesis advisor | Horne, Roland N |
| Thesis advisor | Mavko, Gary, 1949- |
| Thesis advisor | Tchelepi, Hamdi |
| Advisor | Mavko, Gary, 1949- |
| Advisor | Tchelepi, Hamdi |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Lilja Magnúsdóttir. |
|---|---|
| Note | Submitted to the Department of Energy Resources Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2013. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Lilja Magnusdottir
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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