Understanding and quantifying uncertainty is crucial for the development of Direct Use Geothermal Systems (DUGS). Subsurface uncertainty remains even in extensively explored geological basins and is related to data, models and spatial properties. In DUGS uncertainty is present on three different levels: a) subsurface characterization, b) development scenarios and c) economic inputs. The data available for DUGS is usually based on previous exploration activities and is often more restricted than for hydrocarbon projects. Due to the lower value of hot water compared to hydrocarbons, the business case of DUGS is more challenging compared to oil and gas projects. This affects the funds available for exploration and additional data acquisition, increasing the uncertainty on the production scenarios and putting the economic viability of some projects at risk.
In this project you will work on determining the properties that are most important for uncertainty quantification and thus enable reliable model predictions and robust decisions in the development of DUGS. An outline of the project goals is as follows:
- Classifying and ranking the impact of subsurface, development and economic inputs on safety, energy generation, lifetime and economic output of DUGS using coupled Thermal-Hydraulic-Mechanical-Economic (THME) models and Distance-Based Global Sensitivity Analysis (DGSA)
- Distinguish and explain how the interplay between convection and conduction behaves across different scales: from laboratory-sample scale to full-field scale models.
- Characterizing and assessing the thermal response of heterogeneous reservoirs with different (N/G) and heterogeneity levels. This will allow the confident use of simplified models when their output matches facies-based or stochastic
Background:
The mechanical behaviour of reservoirs and faults can be influenced by the pressure and temperature changes introduced by geothermal operations. Mechanical stability can be assessed using Mohr-Coulomb theory that considers pressure changes and thermally induced stress changes. The thermal, hydraulic and mechanical interactions and their impact on safety, energy output, lifetime and economic performance require a coupled Thermal-Hydraulic-Mechanical-Economic (THME) model to be fully evaluated.
Geology remains a strong controlling factor for geothermal system performance. Nonetheless, a systematic study of geological sites representative of conduction-dominated settings is not presented in literature.
To reduce the computational load and the parameter space required to quantify uncertainty, a sensitivity study is required. Conventional One-At-a-Time sensitivity is not able to capture the interaction between parameters that is crucial for such a coupled system. Therefore, a Global Sensitivity Analysis (GSA) is needed in order to account for the high dimensionality of the problem. The computation burden of GSA can be overcome by approximating the sensitivity by the distance between the outputs of stochastic models (distance-based global sensitivity analysis)
Understanding the need for detailed facies modelling is important for the predictive capacity of models. To capture the distribution of flow properties in the reservoir and the related uncertainty different methods can be used in increasing level of complexity considering porosity and permeability: averaged homogeneous models, layered homogeneous models, facies-based stochastically generated models and process-based generated models.
Previous studies have shown the importance of net-to-gross (N/G) for DUGS lifetime and recent studies have shown a good agreement in representing heterogeneity with different methods for heterogeneous, high N/G models. However, the different ways for representing heterogeneity have not been systematically studied across a large range of N/G ranges (~15-90%) and heterogeneity levels.
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