What micro earthquakes tell us about geothermal reservoirs?
Development of models for fluid flow migration in the sub-surface for the Geothermal field site United Downs
In deep enhanced geothermal systems (EGS) fluid circulation mainly occurs along natural faults and/or fracture networks. Experience in developing and circulating geothermal reservoirs in crystalline rock e.g. at Rosemanowes/UK , Soultz-sous-Forêts/France and Cooper Basin/Australia suggests that natural fracture systems control fluid flow and that artificial fractures are relatively unimportant (Willis-Richards 1995, Dorbath et al., 2009; Baisch et al., 2010; 2015). Percolation through these networks is a function of fracture density, orientation, connectivity, aperture, petrophysics, and in situ stress. However, evaluating the production capacity of fractured basement reservoirs in terms of reservoir extent, flow directions and flow rates remains a challenging task.
We compiled structural and numerical models of the subsurface based on available information on the local geologic-tectonic settings at the United down field site. The knowledge about subsurface conditions continuously improves in the course of project development. To account for uncertainties of subsurface conditions, a framework is developed where a suite of alternative subsurface models covers the range of parameter uncertainties. Prognoses of the reservoir performance and induced seismicity response are made for the entire set of competing models. As new information becomes available, the number of subsurface models decreases and the range of forecasts narrows. A single, calibrated fluid flow model will be developed and validated within the next step of the project.
The workflow of this research project is schematically depicted in the following figure.
Figure 1: Schematic workflow. Prior to calibration, competing fluid flow models result in a forecast range which narrows in the course of project development
Key parameters for characterizing a geothermal reservoir are the hydraulic reservoir properties and the associated spatio-temporal hydraulic pressure distribution during operations (testing, stimulation and production). Reservoir models typically rely on a limited number of pressure measurements at wellbore locations, whereas hydraulic pressure away from wells is a modelled parameter and inherently ambiguous (e.g. Horne, 1995). To improve our understanding of in situ reservoir pressure, a new methodology has been developed. The so-called Seismo-Hydraulic-Pressure Mapping (SHPM) uses induced earthquakes as ‘in situ pressure gauges’ and reveals the spatio-temporal evolution of hydraulic reservoir pressure during geothermal operations.
The approach is based on fracture patches slipping repeatedly during fluid injection operations. Sequences of repeated slip bear the information of stress-strength conditions being in exact equilibrium at the time of seismic activation. The co-seismic stress changes associated with each individual slip can be deduced from seismogram recordings. stress deficit, becomes a known parameter. We resolve to what extend pore pressure compensates the stress deficit while explicitly accounting for inter-earthquake stress interferences.
Therefore, the amount of additional stress required to re-activate the fracture, the
We demonstrate the performance of the proposed methodology using a data set of seismicity induced during hydraulic stimulation of a geothermal reservoir in the Cooper Basin, Australia (figure 4). spatio-temporal evolution of in situ pressure is resolved over the entire reservoir. Despite some data scattering, we observe the following: (i) the maximum pore pressure is obtained near the injection well and tends to decrease with distance from the well; (ii) the magnitude of pore pressure is consistent with the injection pressure; (iii) the temporal evolution of pressure increase generally follows the signature of the injection pressure; (iv) the delay of the pressure signal increases with distance from the injection well; (v) the reservoir is dominated by (previously unknown) pressure channels. The latter observation is crucial for the development strategy of a geothermal reservoir in order to reach economic scale.
The developed SHPM methodology and the fluid flow models can significantly contribute to the understanding of deep geothermal reservoirs and their safe and sustainable management.
Figure 2: Spatial distribution of fluid pressure inferred from repeated slip in map view. Overpressures are shown at 4 different times during the Habanero#4 stimulation and are stated in Megapascals according to the gray map which issaturated at 25 MPa. The star denotes the location of the well Habanero 4. Contour line denotes main region of seismic activity as outlined by the hypocenter distribution. Arrow indicates North direction. See textfordetails
Authors: Pia Carstens, Stefan Baisch, Christopher Koch