3D Analysis of Geothermal Fluid Flow Favorability; Brady’s, Nevada, USA

Abstract

Geothermal circulation requires heat, permeability and fluids. Fracture permeability along discrete fault zones provides the pathways for fluid convection. Within individual faults, however, fluid flow zones can have variable character, size, and spatial distribution, representing a significant challenge to exploration and evaluation of geothermal resources. A comprehensive and validated methodology for quantitatively identifying the character, extent, and location of most likely fluid upflow zones within a resource area does not exist. Here, we present a methodology for evaluating favorability for geothermal fluid flow in 3D, an application of this technique to the Brady’s geothermal system, Nevada, USA, and a preliminary evaluation of the results based on data from the production field. A variety of data types, including 2D seismic reflection data, downhole lithologic data, and geologic map data are integrated in 3D space in order to develop a 3D geologic model of the Brady’s geothermal system. From this geologic model, the stress state of modeled faults, the density of fault intersections, and the inferred fluid flow characteristics of the various stratigraphic intervals are evaluated as proxies for permeability and geothermal fluid flow. Integration of these results with temperature data reveals locations within the geothermal field where the collocation of probable fracture permeability and high temperatures indicates a high likelihood for hosting geothermal fluid circulation. These results are consistent with the locations of injection, production, and non-productive wells within the Brady’s field. Validation of these results with data from the well field suggests that these techniques do indeed shed light on specific details of the fluid flow systematics in geothermal systems. Though Brady’s is a relatively data-rich system, this methodology can be adapted and applied to exploration and resource assessment not only in mature production fields, but also in blind, greenfield and otherwise data-poor geothermal areas.