Geothermal reservoir characterization: a ... - Wiley Online Library

doi: 10.1111/j.1365-3121.2011.01048.x

Geothermal reservoir characterization: a thermofacies concept Ingo Sass and Annette E. Go¨tz Geothermal Science and Technology, Institute of Applied Geosciences, TU Darmstadt, Schnittspahnstr. 9, D-64287 Darmstadt, Germany

ABSTRACT The thermofacies concept is based on new measurements of about 11 000 plug samples drilled from sedimentary rocks and investigated at TU Darmstadt from 2007 to 2011. Some hundred representative thin sections were analysed for facies interpretation. The thermofacies concept was developed for low and mid enthalpy geothermal systems linked to graben settings and deep sedimentary basins located in Central Europe. The understanding of the spatio-temporal development of

Introduction Permeability and thermal conductivity belong to the key parameters in geothermal reservoir characterization (Tester et al., 2005, 2006). In previous publications and databases, the number of investigations where both key parameters were measured on the same sample is very low. Clauser and Huenges (1995) presented ternary diagrams on the thermal conductivity of the major rock types. Yet, thermophysical properties and facies-controlled parameters were not investigated with respect to their dependence. The scientific motivation for this study arises from the fact that these parameters should be determined in one coherent approach. A new geothermal facies concept, where geothermal parameters are dependent on facies, may represent such a coherent approach. In early stage exploration when geo-data do not exist, yet the geothermal potential needs to be defined, outcrop analogue studies enable the determination and correlation of thermophysical rock properties. If these studies include a detailed facies analysis, the geothermal exploration concept becomes more precise and descriptive.

Correspondence: Ingo Sass, Geothermal Science and Technology, Institute of Applied Geosciences, TU Darmstadt, Schnittspahnstr. 9, D-64287 Darmstadt, Germany. Tel.: +49 6151 162871; fax: +49 6151 166539; e-mail: sass@geo. tu-darmstadt.de 142

sedimentary facies within a specific geothermal exploration area may contribute to establish integrated structural 3D reservoir models. Thus, thermofacies – the facies dependence of geothermal parameters – become a key feature for reservoir prognosis, reservoir stimulation and efficient reservoir utilization.

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From the engineering point of view, geothermal facies concepts serve to distinguish between petrothermal and hydrothermal systems (Ku¨hn, 2004; Huenges, 2010). Outcrop analogue studies may offer cost-effective opportunities to gain data to be transferred to geothermal systems at greater depths and higher temperatures. In Central Europe, the future geothermal utilization will depend on exploration of comparatively deep reservoirs, which may be characterized as low-to-mid enthalpy resources (discussed in Dickson and Fanelli, 2003). At the early stage of a project, characterization of a reservoir is difficult because survey data are lacking. In these reservoirs, investigation drillings are extremely costly due to the great depths of 3000–5000 m and deeper. It is recommended to design exploration wells for a possible later use as production or injection wells. This makes sufficient reservoir property prognosis necessary based on quantitative data sets. Facies concepts have to be integrated by outcrop analogue studies to obtain a threedimensional image of the system, as well as measured thermophysical formation properties. Therefore, a statistically relevant number of outcrop analogue data are required. The approach to use data from outcrop samples requires furthermore the prediction of the effect of reservoir pressure, temperature and natural fracture fabric on permeability and thermal conductivity. This study introduces the conceptual framework to predict reservoir characteristics based on facies distri-

bution. Data from ongoing field and laboratory studies are introduced to test whether a 3D prognosis of facies can be used as a reliable method to explore geothermal reservoir properties of the deep subsurface. Early in a geothermal project design, the following key questions dealing with the burial, thermal and tectonic history, and recent state of a rock formation shall be answered: 1 What is the expected reservoir permeability? 2 What are the values of thermal conductivity and other thermophysical rock parameters? 3 What is the impact of a distinct stress field and local tectonics on the double porosity? 4 What are the status and effect of hydrothermal alteration? 5 Are karst phenomena predictable for the reservoir rock? Here, we address the key questions concerning (1) reservoir permeability and (2) thermal conductivity, whereas (3) double porosity (Barenblatt et al., 1960; Streltsova, 1976; Moench, 1984; S¸en, 1988, 2002; Kruseman and De Ridder, 1991), (4) hydrothermal alteration (Browne, 1978) and (5) karstification (Smith and Davies, 2006; Esteban et al., 2009; Goldscheider et al., 2011) are matters of investigations, which may be based on the thermofacies concept as introduced in this study.

Materials and methods Cores drilled from outcrops with a field sampling rig and core samples 2012 Blackwell Publishing Ltd

I. Sass and A. E. Go¨tz • Thermofacies concept

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............................................................................................................................................................. obtained from groundwater exploration wells (100–800 m TVD) cover representative clastic and carbonate successions of Central Europe. They represent potential geothermal reservoir formations in low-to-mid enthalpy settings, e.g. the Upper Rhine Graben (Muschelkalk, south-western Germany), the Southern Permian Basin (Rotliegend, northern Poland and Germany), the Molasse Basin (Jurassic, southern Germany), the Vienna Basin (Triassic, Austria) and the Pannonian Basin (Triassic and Tertiary, Hungary). Figure 1 shows the sampled locations in Central Europe and the stratigraphic position. Table 1 refers to the depositional settings of the sampled series. Permeability, thermal conductivity, porosity and density were obtained from about 11 000 measurements. Facies determination is based on microscopic analysis of some hundred representative polished slabs and thin sections. As the bulk rock permeability (total permeability of the pore space, fractures and karst volume) and the bulk thermal conductivity have to be quantified on stochastically validated

Table 1 Depositional settings and sedimentary facies of the sampled series in Central Europe. Depositional environment

Sedimentary facies

Lacustrine Fluvial ⁄ Alluvial

Siltstones Sandstones ⁄ Conglomerates

Coastal-Deltaic

Sandstones

Shallow Marine

Grainstones Mud-Grainstones

Deep Marine

Reefal Limestones Lagoonal Dolomite Mud-Grainstones Reefal Limestones Claystones

matrix data obtained from laboratory measurements (Ba¨r et al., 2011) and compiled with structural and karst data (field and site measurements), it is reasonable to investigate matrix-related thermophysical rock properties in a first step. Recent research on optical scanning shows that thermal conductivity should be

Samples Rotliegend (Permian), Saar Nahe Basin (Germany) Rotliegend (Permian), Saar Nahe Basin (Germany) Lower Triassic, Odenwald Mts (Germany) Upper Triassic, Mecsek Mts (Hungary) Tertiary, Buda Mts (Hungary) Upper Triassic, Mecsek Mts (Hungary Lower Jurassic, Mecsek Mts (Hungary) Lower Jurassic, Tatra Mts (Poland, Slovakia) Tertiary, Buda Mts (Hungary) Middle Triassic, Germanic Basin (The Netherlands, Germany, Switzerland, Poland) Upper Triassic, Northern Calcareous Alps (Austria) Upper Triassic, Transdanubian Range (Hungary) Upper Triassic, Tatra Mts (Poland, Slovakia) Upper Jurassic, Swabian ⁄ Franconian Alb (Germany) Tertiary, Buda Mts (Hungary)

measured on oven-dried samples to achieve the required reproducibility of results. Depending on the lithology, the measurement error may be significantly reduced. Furthermore, a large number of samples and a good consistency of the optical scanning data are required. Using these data in reservoir prognosis requires calculations. For sedimentary rocks, the thermal conductivity may be corrected for saturated conditions after Eq. (1). 1n kr ¼ knf km ;

ð1Þ

where kr is the thermal conductivity of the reservoir [W (mÆK))1]; kf, thermal conductivity of the fluid [W (mÆK))1]; and km, thermal conductivity of the matrix [W (mÆK))1]. Somerton (1992) published the empirical Eq. (2) to calculate thermal effects on the measured thermal conductivity of the matrix (km, k20) under burial conditions. This is just one example for upscaling of lab data to match reservoir conditions, kðT Þ¼k20 103 ðT 293Þ ðk20 1:38Þ h i 0:25k20 þ1:28 k0:64 k20 1:8103 T 20

Fig. 1 Location map and stratigraphic position of the sampled sedimentary series. 2012 Blackwell Publishing Ltd

where T is the reservoir temperature (K). The disadvantage of conventional permeability measurements is that the well-known standard methods allow only determining the bulk sample permeability of a drill core specimen, etc., resulting in a wide variation in permeability data. 143

Thermofacies concept • I. Sass and A. E. Go¨tz


............................................................................................................................................................. The concept applied here correlates point-like permeability data with linear (resp. quasi-punctual) thermal conductivity data. For this purpose, a gas-pressure permeameter and a mini-permeameter are combined and used for measurements of plug samples drilled from outcrop and wellbore core samples (Mielke et al., 2010). The principle of the permeability measurement is shown in Fig. 2. Popov et al. (1999) introduced the method of optical scanning to determine the thermal conductivity of rock samples. The present study refers to more than 11 000 thermal conductivity measurements carried out at the TU Darmstadt laboratory HydroThermikum, applying the method of Popov. Figure 3 shows the operation principle of an optical thermal scanning device.

The accuracy of the optical scanning and gas-pressure measurements was part of internal laboratory test series at TU Darmstadt. The measuring error does not exceed 3%. The error of the permeability measurements is dependent on the order of magnitude of the permeability (Ba¨r et al., 2011). The total error increases from 5% above K = 1 · 10)13 m2 to about 400% at K = 1 · 10)18 m2. Considering the purpose of this approach and alternative measurement in low permeable rock, it is satisfactory just to be within an order of magnitude. Permeability and thermal conductivity have to be measured at the same point of a sample. This is important to identify the facies-related impact on the parameters. Permeability data obtained from water flow based Darcy

Fig. 2 Scheme of the gas-pressure permeability measurement. The permeameter utilizes pressured differential air flow through a core sample. Permeability is calculated by incorporating the injection pressure pi, the mass flow rate Mi and the ambient atmospheric pressure pa (Goggin et al., 1988).

experiments result in mean values for the entire sample or core, which is insufficient to correlate thermal conductivity with permeability, i.e. such data would not be applicable on the thermofacies concept. Upscaling is not considered in this approach, because related effects need to be identified from local burial conditions, tectonic stresses, and hydrothermal reservoir alteration.

Thermophysical rock properties Heat capacity, thermal diffusivity and thermal conductivity are connected through the Debye-Equation (Eq. 3) qr ¼

k ; cr a

where qr is the density of the reservoir rock (kg m)3); cr, specific heat capacity of the reservoir rock [WÆs (kgÆK))1]; k, thermal conductivity [W (mÆK))1]; a, thermal diffusivity (temperature conductivity) (m2 s)1). This approach indicates one simple fact: thermophysical rock properties are density controlled. Density itself is strongly dependent on the facies of sedimentary rocks (carbonates, siliciclastics, as well as volcaniclastics). First steps of reservoir investigation include the determination of the theoretical geothermal potential following Eq. (3). Heat in place is calculated from geometric data of the target formation, the temperature prognosis and the heat capacity of the distinct reservoir rocks. The Federal German Geothermal Potential Study (Jung et al., 2002) applied Eq. (4) to determine the heat in place. The application of a thermofacies approach takes place in early exploration stages when detailed reservoir information on porosity, fluid properties, secondary porosity, stress field and tectonization, etc. is not available. Equation (4) leads to an appropriate estimation of the heat in place value at this point of geothermal investigations. On the other hand, Bundschuh and Sua´rez Arriaga (2010) introduced different more complex approaches. Eth ¼ cr qr V ðTr Ts Þ;

Fig. 3 Scheme of the optical scanning method to determine the thermal conductivity of a rock sample with respect to a reference with a known conductivity. 144

ð3Þ

ð4Þ

where Eth is the heat in place (WÆs); cr, specific heat capacity of the reservoir rock [WÆs (kgÆK))1]; qr, density of the reservoir rock (kg m)3); V, volume of

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............................................................................................................................................................. the reservoir (m3); Tr, undisturbed temperature of the reservoir rock (K); Ts, temperature at the ground surface (K). The next step in such initial geothermal investigations is to assess the extractability of heat. Therefore, permeability and porosity correlation and evaluation are important tools in reservoir engineering to extend the initial reservoir property prognosis. Precise and reproducible measurements are indispensible. However, the correlation between porosity and permeability is in many cases complex, depending on many other rock properties, such as pore size, connectivity of pores, tortuosity, etc. (Vosteen et al., 2003). With respect to sedimentary facies, distinct lithotypes have to be catalogued and paralleled with poroperm data. Integrating lithofacies types into physical rock properties helps to indentify correlations.

Thermophysical rock properties and sedimentary facies Selected rock types of different depositional environments and different

stratigraphic ages (Fig. 1, Table 1) were measured. The data are plotted in the permeability-thermal conductivity diagram as shown in Fig. 4. The large number of samples and the accurate measurements indicate a strong correlation between facies, representing depositional conditions, and thermophysical rock properties. Fine-grained pelagic claystones show the lowest values of permeability and thermal conductivity in comparison with sedimentary rocks of other depositional settings. They are characterized by a high content of inner crystalline water, which leads to a low thermal conductivity. Coastal and terrestrial sandstones and conglomerates represent deposits with the highest permeability and thermal conductivity because they show the highest effective porosity (high permeability) and high quartz contents (high thermal conductivity). In addition, silica cements lead to the highest thermal conductivity values within this group. Provided the dependency of facies and thermophysical properties is correct, geothermal reservoir types can be correlated with facies types as shown

in Fig. 5. Natural geothermal systems are here defined as hydrothermal and petrothermal. With respect to crossover hydraulic behaviour like transition from laminar to turbulent flow patterns, the term transitional systems seems to be appropriate. Enhanced (or engineered) geothermal systems (EGS) operate with man-made permeability improvement (Tester et al., 2005; Huenges, 2010) such as hydraulic fracturing. The aim is to use thermal water as a heat carrier because the conductive heat transfer in petrothermal systems (naturally nearly impermeable with very limited availability of natural thermal water) excludes the economic utilization. Enhancement of a reservoir is necessary in most hydrothermal systems as well as in all petrothermal systems for economic and technical reasons. Typically, hydrothermal systems have a level of permeability where natural un-forced convection may take place if the thermal gradients are large enough (Sass and Go¨tz, 2010). Enhancement of such type of a reservoir leads to rock formation permeabilities, which allow mostly

Fig. 4 Thermophysical properties (error bars not plotted) of sedimentary reservoir rocks (examples from Palaeozoic, Mesozoic and Cenozoic series of Central Europe; Sass and Go¨tz, 2008; To¨ro¨k et al., 2008; Sass and Go¨tz, 2010; Ba¨r et al., 2010; Go¨tz and Lenhardt, 2011; Homuth et al., 2011) with correlation to a general geothermal system characterization depending on the major heat transfer mechanism (convective vs. conductive).


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Fig. 5 Conceptual thermofacies approach: carbonate, clastic and magmatic rocks in relation to hydrothermal, transitional and petrothermal systems. The database of magmatic rocks is taken from unpublished TU Darmstadt research reports to demonstrate the conceptual framework.

laminar fluid flow under all operational conditions. If one applies the concept of the Darcy-modified Raleigh number on the range of transition from un-forced convection to hydraulic gradient-driven convection, one will find critical permeabilities at about 10)13 to 10)14 m2 characteristic of medium-to-fine-grained sediments, e.g. dolomites and fluvial sandstones (Fig. 4). That is the most feasible range for starting reservoir stimulation (EGS) at comparatively high permeabilities (Sass and Go¨tz, 2011).

Implications for geothermal exploration The here presented data (facies, permeability, thermal conductivity) allow us to propose a thermofacies concept as shown in Fig. 5. The reservoir characteristics are strongly influenced by the facies type and thus define the type of geothermal system (hydrothermal, petrothermal, enhanced ⁄ engineered). Ultimately, the reservoir characteristics might influence the course of geothermal field development and applied technology. In the new approach, facies concepts are applied as an exploration method producing conservative results because secondary porosities, karstification and distinct stress fields will mostly lead to higher reservoir capacities. Thus, thermofacies may become an additional key feature for reservoir prognosis, reservoir stimulation and efficient reservoir utilization. Ongoing investigations include magmatic rocks to characterize mineral parageneses, their alteration patterns and their thermophysical reservoir properties. First results indicate that the degree of alteration of magmatic rocks seems to have similar impor146

tance as distinct sedimentary facies types of siliciclastic and carbonate rocks.

Acknowledgements We kindly acknowledge discussions with Yuri Popov, Academy of Science Moscow and Andre´ Strasser, University of Fribourg. We thank Ernst Huenges, Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences for encouraging us to publish the thermofacies concept. Robert M. Priebs reviewed the English text. The constructive remarks of two anonymous reviewers greatly improved the manuscript.

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