| Keywords |
thermal breakthrough forecasting, temperature, nanoparticle, tracer, EGS, DNA, thermochromic, inverse problem |
| Abstract |
Nanoparticle tracers are being investigated as a potential tool to measure temperature distributions in geothermal reservoirs. If the temperature distributions could be measured more precisely, this would greatly enhance the power and accuracy of thermal breakthrough forecasting, which would in turn inform reservoir engineering and field management decisions. Work toward two distinct but parallel objectives are described here. The first is to rank the informativity of various tracer candidates using modeling. The second is to develop temperature sensitive tracers experimentally, such that they would be capable of characterizing fracture properties and temperature distribution. The design of temperature-sensitive tracers is built around the design of the temperature sensing mechanism. In other words, the mechanism by which temperature is measured and the form and resolution of the resulting data, or response, have a profound impact on how informative that tracer can be about thermal breakthrough. Therefore, it is important to model the responses of candidate tracers in the context of an inverse problem to determine their relative informativity. In order to quantify tracer informativity for the simplified case in which the reservoir consists of a single parallel-plate fracture, one-dimensional analytical models were used to calculate the responses of four tracer types: conservative solute tracer, dye-releasing nanotracer, threshold nanoreactor, and temperature-time tracer (TTT). The solute tracer and TTT represent the lower and upper bounds on informativity, respectively, and the other two are tracer candidates currently being investigated. Inverse modeling was performed in which the data was fit by adjusting fracture width and half-aperture (with a fixed, known length) to obtain an ensemble of 1000 solutions for each tracer. This analysis was repeated for various operation times, threshold temperatures, and levels of noise in the data, in order to identify strengths and weaknesses associated with each particular type of tracer. Finally, thermal breakthrough curves were calculated for each solution found. All tracers were found to perform very well, with small ranges of uncertainty for both thermal breakthrough forecasting and fracture property estimation. This was because the problem was highly constrained in its definition. In a more realistic inverse problem, the uncertainty would be larger, as one would not be able to say that the reservoir consists of a single fracture of a given length. However, this simple model was used to determine if there were any noticeable differences between the inverse problems for each tracer on the most basic level. If any had not performed well for such a simple, constrained problem, then it would have certainly failed in a more complex case. For more realistic reservoir models consisting of complex fracture networks, it is expected that all three temperature-sensitive tracers will outperform conservative solute tracers because their responses contain information about the temperature distribution. The experimental objective is to develop methods for acquiring reservoir temperature data within the formation and to correlate such information with fracture connectivity and geometry. Existing reservoir-characterization tools allow temperature to be measured only at the wellbore. Temperature-sensitive nanosensors will enable in-situ measurements within the reservoir. Such detailed temperature information enhances the ability to infer reservoir and fracture properties and inform reservoir engineering decisions. Toward the development of nanosensors, both experimental work and theoretical modeling were performed. Experiments were performed to evaluate several potential nanosensor candidates for their temperature-sensitivity and to investigate particle mobility through porous and fractured media. In a parallel effort, modeling was performed to evaluate how temperature information provided by different sensing mechanisms could be used in the context of an inverse problem, with the goal of ranking the usefulness of the data provided by potential nanosensor candidates. Temperature sensing mechanisms of potential candidates were investigated. Temperature-sensitive particles investigated in this study include the irreversible thermochromic, dye-attached silica and silica-protected DNA particles. A combined heat and flow test confirmed the temperature-sensitivity of the irreversible thermochromic particles by observing the color change. A detectable change in the fluorescent emission spectrum of the dye-attached silica particles upon heating was observed. The processing and detection of silica-encapsulated DNA particles with hydrofluoric acid chemistry was tested. A protocol to release the DNA by dissolving the silica layer without completely destroying the DNA was established. The silica-encapsulated DNA particles were flowed through a porous medium at high temperature. Some dissolution of silica particles was observed, leading to a reduction in their size. This research showed that synthesizing particles to respond to a specific reservoir property such as temperature is feasible. Using particles to measure reservoir properties is advantageous because particles can be transported to areas in the reservoir that would not be accessible by other means and therefore provide measurements deep within the formation. |