Itasca Consulting Group, Inc. — Department of Energy SBIR Phase I: 12a
Itasca Consulting Group, Inc. — SBIR Phase I award from Department of Energy.
- Amount
- $149,504
- Agency
- Department of Energy
- Program / Phase
- SBIR · Phase I
- Topic
- 12a
- Solicitation
- DE-FOA-0001619
- NAICS
- —
- Place of performance
- MN
- Period
- 2017-06-12 → 2018-03-11
Description
This project will develop an efficient and unique numerical modeling tool for engineering an Enhanced Geothermal System (EGS) that incorporates both the capability of modeling thermo-hydro-mechanical processes and explicitly representing realistic discrete fracture networks with thousands of fractures. Through transformative science and technology solutions and by improving predictive analysis, design, and optimization of EGS reservoirs, this project will be a big step forward in the core mission of the Office of Energy Efficiency and Renewable Energy to bring down the cost of EGS energy to 6 c/KWh. Economically viable EGS will directly impact the effort of Department of Energy to reach security in the energy supply but also achieving environmental and economic security. The EGS reservoirs typically involve hard rocks with a pre-existing discrete fracture network with low in-situ permeability. Therefore, they need to be stimulated to increase permeability in a sufficiently large volume of the reservoir and to maintain economical flow and temperature. Field observations of a number of EGS experiments indicate that, despite stimulation efforts, fluid tends to localize in a few channels, which leads to a relatively quick decrease in the produced temperature. Historically, continuum models have been used for predictive assessment of the EGS. However, they have failed to produce accurate results because they are incapable of capturing localization effects of deformation and flow. Numerical methods that incorporate fractures explicitly and consider heterogeneity in the fracture properties have been shown capable of more realistic assessments of EGS and can potentially address the most challenging issues with the EGS, i.e., prediction and assessment of reservoir response, including effects rising from uncertainties in field measurements. The proposed work will build on existing expertise developed by Itasca. 3DEC is a state-of-the art commercial software developed by Itasca for numerical modeling of deformation, flow, and coupled hydro-mechanical processes in fractured rock masses. It is based on the Distinct Element Method, a computational technique pioneered by Itasca. We propose to extend functionality of 3DEC software to model coupled thermo-hydro- mechanical processes in 3D fractured reservoirs. In Phase 1, capabilities for modeling the physics of heat transfer by advection and convection along the fractures will be developed. Computational algorithms will be adapted to modify the model discretization (i.e., meshing) based on the requirements of capturing the important temperature gradients for heat conduction perpendicular to the surface of fractures. Because this problem involves physical processes occurring at significantly different time scales, a hybrid implicit/explicit time integration technique will be developed. Functional tests will be performed on amended codes to demonstrate that the implementation is fit for purpose. The code will be verified using available laboratory and simplified field data. In Phase 2, the code enhancements for large-scale problems will be implemented, including direct implementation of some of the developed functions into the 3DEC engine and capabilities for parallel processing to reduce solution time. At the end of Phase II, the full functionality of the software will be tested for large-scale field data, and subsequently it will be available for predictive analysis, evaluating sensitivity to different parameters and the effect of uncertainty, mitigating induced seismicity risks, and optimizing design. Without DOE funding, there is little chance that Itasca could internally fund this project, because implementing such complex models and verification, including verification against field data requires a significant amount of resources that is beyond the current financial capabilities of our small business.