Abstract
Abstract. The Waiwera aquifer hosts a structurally complex geothermal groundwater system, where a localized thermal anomaly feeds the thermal reservoir. The temperature anomaly is formed by the mixing of waters from three different sources: fresh cold groundwater, cold seawater and warm geothermal water. The stratified reservoir rock has been tilted, folded, faulted, and fractured by tectonic movement, providing the pathways for the groundwater. Characterization of such systems is challenging, due to the resulting complex hydraulic and thermal conditions which cannot be represented by a continuous porous matrix. By using discrete fracture network models (DFNs) the discrete aquifer features can be modelled, and the main geological structures can be identified. A major limitation of this modelling approach is that the results are strongly dependent on the parametrization of the chosen initial solution. Classic inversion techniques require to define the number of fractures before any interpretation is done. In this research we apply the transdimensional DFN inversion methodology that overcome this limitation by keeping fracture numbers flexible and gives a good estimation on fracture locations. This stochastic inversion method uses the reversible-jump Markov chain Monte Carlo algorithm and was originally developed for tomographic experiments. In contrast to such applications, this study is limited to the use of steady-state borehole temperature profiles – with significantly less data. This is mitigated by using a strongly simplified DFN model of the reservoir, constructed according to available geological information. We present a synthetic example to prove the viability of the concept, then use the algorithm on field observations for the first time. The fit of the reconstructed temperature fields cannot compete yet with complex three-dimensional continuum models, but indicate areas of the aquifer where fracturing plays a big role. This could not be resolved before with continuum modelling. It is for the first time that the transdimensional DFN inversion was used on field data and on borehole temperature logs as input.
Highlights
Aquifer systems in fractured rocks can be modelled by using either continuum or discrete models
Continuum models substitute the fractured rock with an equivalent porous media (Day-Lewis et al, 2000; Hao et al, 2008; Illman et al, 2009; Illman and Neuman, 2003; Sahimi, 2011; Vesselinov et al, 2001; Zha et al, 2015)
Fractures could only be inserted to specific discrete points along the existing Discrete fracture network models (DFNs)
Summary
Aquifer systems in fractured rocks can be modelled by using either continuum or discrete models. Continuum models substitute the fractured rock with an equivalent porous media (Day-Lewis et al, 2000; Hao et al, 2008; Illman et al, 2009; Illman and Neuman, 2003; Sahimi, 2011; Vesselinov et al, 2001; Zha et al, 2015) These methods often fail to model the exact location of the fractures due to their strong averaging behavior and they are considered most suited to problems with high fracture density (Long et al, 1982). Discrete fracture network models (DFNs) are more realistic representations of the fractured media, where fractures and the rock matrix are modelled separately (Dorn et al, 2013; Jang et al, 2008; Neuman, 2005; Niven and Deutsch, 2012). The use of DFN models for inversion purposes is not as straightforward as classic equivalent porous medium models
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