1887

Abstract

Summary

This paper describes an integrated workflow to characterize the properties and behavior of an enhanced geothermal system (EGS) in four steps, applied to the Utah FORGE dataset. Static modeling is carried out first, including structure modeling, lithology, and rock properties, as well as the construction of a discrete model of natural fractures with a tectonic-based prediction algorithm, from which permeability is derived. The second step is stimulation design, based on reservoir mechanical properties and natural fracture geometry, which allows for forecasting hydraulic fracture propagation and selecting the most effective stimulation strategy. Dynamic heat and fluid flow simulations then calibrate the permeability of the natural and hydraulic fractures, as well as the initial temperature distribution, and forecast heat production performance over 30 years. Finally, the flow simulations are coupled with a geomechanical model to compute stress changes over time and their impact on well integrity and the stability of faults and fractures.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202521224
2025-10-27
2026-01-24
Loading full text...

Full text loading...

References

  1. Gwynn, M. (2018). Utah FORGE: Rock Properties. [Data set]. Geothermal Data Repository. Energy and Geoscience Institute at the University of Utah.
    [Google Scholar]
  2. Khan, A.M., Kresse, O., England, K., McLennan, J., Xing, P., Hobbs, B., and Deville, B. (2024): Integrated Lifecycle Simulation for Utah FORGE: Part I – Fracture Geometry Calibration. GRC Transactions, Volume 48.
    [Google Scholar]
  3. Moore, J., McLennan, J., and Pankow, K. (2020): The Utah Frontier Observatory for Research in Geothermal Energy (FORGE): A Laboratory for Characterizing, Creating and Sustaining Enhanced Geothermal Systems. In: 45th Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, California, February 10–12, SGP-TR-216.
    [Google Scholar]
  4. Mulyani, S., and Aulia, A.B. (2022): Discrete Fracture Network Modelling Based on Natural Fracture Prediction Geomechanic Inversion Process. In: Proceedings, The 8th Indonesia International Geothermal Convention and Exhibition (IIGCE) 2022.
    [Google Scholar]
  5. Mulyani, S., Aulia, A.B., Wisnubroto, B., Widiatmoko, W., Pradana, A., Trikukuh, J.S., and Puspa, M.A. (2023): Comprehensive Study of Geology to Geomechanics for Delineating a Sweet Spot Map in a Geothermal Field. Study Case: Utah FORGE, USA. GRC Transactions, Volume 47.
    [Google Scholar]
/content/papers/10.3997/2214-4609.202521224
Loading
/content/papers/10.3997/2214-4609.202521224
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error