Modeling study of deep direct use geothermal on the West Virginia university campus-morgantown, WV. (September 2020)

• Record Type: Journal Article
• Authors: Zhang, Yingqi; Garapati, Nagasree; Doughty, Christine; Jeanne, Pierre
• Is Part Of: Geothermics. Volume 87(2020)
• Publication Date: 2020-09
• Subjects: Deep Direct-use geothermal -- Numerical simulations -- Prediction uncertainty -- Heterogeneity; Hydrogeology -- Periodicals; Geothermal resources -- Periodicals; Énergie géothermique -- Périodiques; GEOTHERMAL ENGINEERING; GEOTHERMAL ENERGY; GEOTHERMAL EXPLORATION; Geothermal resources; Hydrogeology; Periodicals; Electronic journals; 621.44
• DOI: 10.1016/j.geothermics.2020.101848
• Languages: English
• ISSNs: 0375-6505

Abstract

Highlights: The heat exchange between fracture and matrix is dominated by the matrix volume. Reservoir heterogeneity has a large impact on injection overpressure and thermal breakthrough curves. Horizontal well scenario is a more robust design especially for a heterogeneous field. Key parameters to reduce prediction uncertainty are correlation length, average permeability and porosity. Abstract: To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use (DDU) system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. As a result, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided only the single permeability model is needed; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the prediction, therefore, heterogeneity is included in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis will be used for further economic studies.