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Dr. Paromita Deb

1. price of the year 2022

Resource Assessment and Performance Predictions in Unconventional Geothermal Reservoirs

Institute for Applied Geophysics and Geothermal Energy, RWTH Aachen University

© Paromita DebDr. Paromita Deb (1. Preis): "Resource Assessment and Performance Predictions in Unconventional Geothermal Reservoirs", Institute for Applied Geophysics and Geothermal Energy, RWTH Aachen University
Copyright: Paromita Deb

Description of the work:

Human-induced climate change is a major crisis threatening the stability of our ecosystem. Meanwhile global energy consumption continues to rise, increasing the need for more renewable energy options. Geothermal energy, extracted from the earth’s natural heat is a proven source of sustainable and clean energy. Its exploitation and growth have however, been stagnant in the last decades primarily due to following reasons: (i) financial risks related to high capital expenditure associated with drilling and completions of geothermal wells, (ii) geothermal energy for power production has been limited to only conventional hydrothermal systems (i.e., areas characterized by naturally high heat flow and permeable rocks, such as Italy, Turkey, Philippines, Indonesia, to name a few); and (iii) geological risks related to uncertain subsurface structure and properties. In my work, I explore two unconventional geothermal technologies, which have the potential to tackle the above challenges and expedite geothermal growth for a widespread, economic, and sustainable exploitation of this natural energy source.
One of the biggest factors that determine the economic feasibility of geothermal projects is the cost associated with drilling and completion of geothermal wells, which can account for almost 30 % - 60 % of the total capital investment. This increases the cost of electricity generation from geothermal sources as compared to fossil sources. To make geothermal energy cost-effective, it is therefore, essential to target higher temperatures to increase the overall productivity of the wells. This is achievable by either drilling very deep or targeting shallower hot spots.
For this reason, Super-Hot Geothermal Systems (SHGS) have gained interest in the last decades because of their very high temperature (> 374 °C) resources. These are usually found in active volcanic areas, characterized by young and shallow magmatic intrusions in the crust. Exploitation of this resource is estimated to potentially increase the productivity of each geothermal well by ten times, thereby justifying the drilling costs. However, one of the major challenges for exploring this type of resource is associated with the limited knowledge of the geometry and structure of the underlying magmatic system, which is decisive for selecting the right drilling location.
My study aims at integrating this heterogeneous knowledge from different domains to generate more reliable assessments of geothermal resources, thus reducing the risk related to selection of wrong drilling locations. In my innovative approach, the characteristics of the underlying magmatic heat sources are in fact, constrained from geochemistry, petrology, and surface geology. The workflow was developed within the case study of an active volcanic field in Mexico, which hosts a super-hot geothermal system. Rather than assuming a static heat source in the form of a large magma chamber, the developed conceptual model considers the temporal and spatial evolution of multiple magmatic heat sources, active at different depths in the crust at different instants of time. This comprehensive modeling approach allowed to quantify the relative contribution of different magmatic events towards the final and current temperature of the geothermal field. While previous studies failed at explaining the observed thermal anomalies, my approach provides a good explanation, thereby providing a more accurate assessment of the locations of exploitable superhot resources at shallow depths for future geothermal wells.
In a separate case study, I also investigated the influence of uncertain thermophysical parameters in geothermal potential estimation of a greenfield through statistical methods. The financial risks in geothermal projects are enhanced because of the uncertainty associated with the quality of the geothermal resources, which is determined by the subsurface temperature and the hydraulic properties of the reservoir. Inaccurate assessment of resource quality directly affects the engineering considerations for powerplant size and design. In the examined case study, the improvement in the predictions of temperature and hence exploitable power potential were found to be ten-fold. This directly translates to a more accurate financial analysis and reliable feasibility studies.
Another unconventional geothermal technology studied in this work is the Enhanced Geothermal Systems (EGS). EGS involves creating fluid pathways within the hot rock mass by activating existing, or creating new fracture networks, a process also referred to as “stimulation”. This process enables creating artificial heat exchangers in the subsurface and can potentially be implemented worldwide without any pre-requisite for specific geological characteristics of the subsurface. However, in the past decade, one of the main concerns related to EGS has been the risk of induced seismicity, which occur when the stress equilibrium of subsurface rocks is disturbed by fluid injections. A critical pre-requisite for designing a safe and efficient EGS is to accurately predict the thermal, hydraulic and mechanical processes related to fracture growth and propagation in the subsurface. To this end, it is indispensable to verify and improve the predictions of numerical simulators by comparing their results with experimental observations. With this objective in mind, we designed controlled laboratory-scale stimulation experiments in granite rocks, which are generally the target rocks for EGS. Through series of high-quality reproducible experiments, I recorded the rock response to stimulation and generated benchmark datasets.
In the next step, I brought together specialists from six research groups from Germany, Australia, and Switzerland, in the joint effort of testing the capabilities of six numerical simulators commonly used for designing field-scale EGS experiments. This work resulted in a very positive impact for the involved groups because the verification of this class of simulators against laboratory-scale observations is an essential and critical step for their confident application in the field. Furthermore, the huge amount of data acquired during the experiments was entirely made available to the international research community in open access, promoting the idea of open science to reduce the knowledge gap amongst researchers and at the same time foster the creation of cooperative problem-solving approaches.
Safe and efficient utilization of the enormous geothermal power potential is only possible if the associated risks can be quantified and reduced. My thesis promotes methods that can be implemented to reduce risks in exploration, production and development of unconventional geothermal systems. The results presented here are not only significant for geothermal scientists and engineers to reduce financial, geological and environmental risks of geothermal projects, but also for policy makers, corporate sectors and social scientists involved in making critical decisions regarding environment, investments and public engagement respectively.