Techno-economic uncertainty quantification and robust design optimization of hydrothermal and CO2-based geothermal systems


Project Description

The viability and sustainability of geothermal energy development are subject to several reservoir (subsurface) and economic parameter uncertainties. Determining the optimal operational parameters of the geothermal system, in the presence of uncertainty, require hundreds, if not thousands, of permutations of the different uncertain or naturally variable reservoir, operational and economic parameters for any specific hydrothermal system. The key task of this project is to quantify reservoir and economic uncertainties and to examine their effects on the techno-economic performance of the hydrothermal doublet system. What are the ranges of permissible reservoir conditions (parameters) to render a geothermal system economically viable? What are the trade-offs between these parameters? What are the ‘acceptable uncertainties’ and the ‘optimized values’ for a geothermal-energy producer in the economic decision-making? These kinds of questions will be addressed in this project, by means of scanning the related parameter-space via a very large number of numerical simulations, to then derive first-order ‘reduced model metrics’ that help to derive simplified decision-making quantities. In this study, we will develop a novel generalized non-dimensional expression of power generation over time to characterize the optimal operational parameters for various combinations of the reservoir parameters, and to determine which combination of the parameters depletes the reservoir heat the fastest. This methodology will further be applied to evaluate and compare the performance of geothermal systems that use in-situ brine or (sequestered) CO2 as the heat-extraction fluid, with emphasis on Saudi Arabia’s geological and economic conditions. Finite element/volume simulators such as TOUGH2/3, DARTS, or CMG, and wellbore-power system models will be used to conduct comprehensive simulations and to stochastically assess the system’s power and lifetime based on a range of available subsurface parameters (e.g., depth, thickness, permeability, porosity, permeability anisotropy), operational parameters (e.g., flow rate, injection temperature, well spacing) and economic parameters (e.g., drilling cost, heat cost, electricity cost, etc.). The candidate must have the willingness to learn basic geoscience and reservoir engineering concepts. Affinity with programming (preferably MATLAB/Python) and Paraview or related visualization tools is an advantage.
Program - Earth Science and Engineering
Division - Physical Sciences and Engineering
Faculty Lab Link -
Center Affiliation - Ali I. Al-Naimi Petroleum Engineering Research Center
Field of Study - Earth Science and Engineering - Geothermal energy and Co2 utilization and geological storage

About the

Paul Martin Mai

Professor, Earth Science and Engineering

Paul Martin Mai
Research Interests
  • Multi-scale earthquake phenomena: from data-driven experimental studies to HPC-enabled forward simulations
  • Physics-based ground-motion simulations for seismic & tsunami hazard applications
  • Seismic waves in inhomogeneous media: scattering simulations and imaging Earth structure 
  • Engineering seismology, seismic hazard assessment, and coupled natural hazards (tsunamis, landslides)
  • Geothermal energy for Saudi Arabia: low-enthalpy geothermal energy system in Red Sea rift basins

Desired Project Deliverables

The intern will (i) carry out a literature study to compile a range of relevant subsurface inputs, (ii) build a parameterizable 3D reservoir model for the simulation of the geothermal system, (iii) develop an economic model for geothermal energy development in Saudi Arabia and, (iv) perform numerical simulations for optimization and uncertainty quantification of hydrothermal and CO2-based geothermal systems.