Influence of process-based, stochastic and deterministic methods for representing heterogeneity in fluvial geothermal systems. (March 2023)

• Record Type: Journal Article
• Authors: Major, Márton; Daniilidis, Alexandros; Hansen, Thomas Mejer; Khait, Mark; Voskov, Denis
• Is Part Of: Geothermics. Volume 109(2023)
• Publication Date: 2023-03
• Subjects: Heterogeneity -- Process-based -- Stochastic -- Geothermal -- Thermal response -- Directuse; 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.2023.102651
• Languages: English
• ISSNs: 0375-6505

Abstract

Highlights: Comparison of stochastic, process-based and deterministic heterogeneity models. Simple homogeneous and layered models overestimate thermal breakthrough time. Process-based and stochastic models are comparable within the range of ensemble runs. More complex facies than reservoir/non-reservoir yield minor variabilities. Two orders of magnitude time reduction using DARTS on GPU compared to single CPU. Abstract: Focus is on comparing stochastic, process-based and deterministic methods for modelling heterogeneity in hydraulic properties of fluvial geothermal reservoirs. Models are considered a generalized representation of a fluvial sequence in the upper part of the Gassum Formation in northern Denmark. Two ensemble realizations of process-based and stochastic heterogeneity were simulated using the state-of-the-art numerical modelling software, Delft Advanced Research Terra Simulator (DARTS), to assess differences on a statistically relevant sample size. Simulator settings were optimized to achieve two orders of magnitude improvement in simulation time. Our general findings show that the stochastic and process-based methods produce nearly identical results in terms of predicted breakthrough time and production temperature decline for high net-to-gross ratios (N/G). Simple homogenous and layered models overestimate breakthrough and underestimate temperature decline. More complex representation of facies in process-based models show smaller variance in results and stay within the limits of ensemble runs compared to simpler facies representation. Results indicate that a multivariate Gaussian based stochastic representation of heterogeneity provides comparable thermal response to a process-based model in fluvial systems of similar quality.