Abstract
Understanding fractures and fracture networks is essential for the investigation and use of subsurface reservoirs. The aim is to predict the fractures and the fracture network when there is no direct access to subsurface images available. This article presents a universal workflow to numerically compute a discrete fracture network by combining the 1D scanline survey method, processed with the newly written SkaPy script, together with the multiple point statistic method (MPS). This workflow is applied to a potential geothermal site in Mexico called Acoculco. We use Las Minas outcrops and quarries as surface analogues for the Acoculco reservoir, as Las Minas and Acoculco are both formed by the influence of a plutonic intrusion into the Jurassic–Cretaceous carbonate sequence of the Sierra Madre Oriental in the Trans-Mexican volcanic belt (TMVB). The intrusion is associated with contact metamorphism and metasomatic phenomena, providing the basis for the mining activities at Las Minas. The results obtained using this workflow demonstrate the feasibility of the approach, which presents a solution combining the efficiency of data processing and an interpretation-driven approach to build realistic discrete fracture networks. This workflow can be used in the process of estimating the permeability of a fracture controlled reservoir, with using only scanline surveys data as input. This is essential in the process of evaluating the feasibility to develop an enhanced geothermal system.
Highlights
The use of the subsurface and the exploitation of subsurface resources require prior knowledge of fluid flow through fracture networks, in low permeability rocks
To overcome this potential problem, we developed a workflow to numerically compute a discrete fracture network based on the combination of the scanline survey method performed at single outcrops, processed with the newly written SkaPy script, together with the Multiple Point Statistic method (MPS) (e.g. Liu et al, 2002; Chugunova et al, 2017) proposed by (Bruna et al, 2019)
Acoculco within the regional geological context The method we developed creates discrete fracture networks (DFNs), where the main input are scanline datasets measured at outcrops near the Acoculco test site
Summary
The use of the subsurface and the exploitation of subsurface resources require prior knowledge of fluid flow through fracture networks, in low permeability rocks. The question we address here is how to predict the fractures and the fracture network of an area when there is no large scale information available, for example from seismic data or aerial images (Unmanned Aerial Vehicle - UAV, or drone) To overcome this potential problem, we developed a workflow to numerically compute a discrete fracture network based on the combination of the scanline survey method performed at single outcrops, processed with the newly written SkaPy script, together with the Multiple Point Statistic method (MPS) The development of EGS requires stimulation treatments of the reservoir to enable or increase the flow rate of the geothermal fluid for the extraction of heat from high temperature and initially low permeability rocks, In EGS, the production and injection wells are hydraulically connected by increasing the rock permeability (Tester et al, 2006), which for a fractured tight reservoir corresponds to stimulating the pre-existing natural fractures and using them as fluid pathways and heat exchangers
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