Statistically reliable petrophysical properties of potential reservoir rocks for geothermal energy use and their relation to lithostratigraphy and rock composition: The NE Rhenish Massif and the Lower Rhine Embayment (Germany)

Jorand, R.; Clauser, Christoph; Marquart, Gabriele; Pechnig, Renate

doi:10.1016/j.geothermics.2014.08.008

Cited by 41 publications

(26 citation statements)

References 25 publications

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“…For example, the higher the SiO 2 content in the rock, the greater the thermal conductivity and thermal diffusion coefficient, and the smaller the specific heat capacity. It can be seen from Figure 4 that there is a positive correlation between SiO 2 content and thermal conductivity and thermal diffusivity in the blastopsammitic rock, slate, quartz sandstone and siltstone, which have SiO 2 as the main mineral component, and a negative correlation with specific heat capacity, consistent with previous work [21].…”

Section: Influence Of Mineral Components On Rock Thermophysical Propesupporting

confidence: 89%

Analysis of the Thermophysical Properties and Influencing Factors of Various Rock Types From the Guizhou Province

Song

Jiang

Peiwen³

2018

E3S Web Conf.

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A series of analyses have been carried out on a number of rock types from the Guizhou Province to investigate their thermophysical properties. A total of 433 samples from 14 types of rock were collected, tested and analyzed. It was found that in this province, the average thermal conductivity of the samples ranged between 1.516±0.264 and 5.066±0.521 W/(m·K), the average specific heat capacity varied from 0.272±0.042 to 0.603±0.096 kJ/(kg·°C), and the average thermal diffusion coefficients were from 0.752±0.331 to 2.854±0.368 MJ/(m3·K). The older rocks always had higher thermal conductivity and thermal diffusion. Thermal conductivity and thermal diffusion of rocks are positively correlated with the mineral content of high thermal conductivity species, but the situation for the specific heat capacity is the opposite. With increasing mineral particle size, the thermal conductivity and thermal diffusion coefficient also increase, but the relationship with specific heat capacity is not obvious. The thermal conductivity and thermal diffusion coefficient of rocks increases under water saturated conditions compared to dry conditions, but the specific heat capacity decreases.

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Section: Influence Of Mineral Components On Rock Thermophysical Propesupporting

confidence: 89%

Analysis of the Thermophysical Properties and Influencing Factors of Various Rock Types From the Guizhou Province

Song

Jiang

Peiwen³

2018

E3S Web Conf.

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“…8a suggests that porosities of < 5% no longer have a significant impact on λ b values. Our results do not only confirm that at low porosities, existing porosity models become insignificant (Jorand et al 2015), but also that in case of water saturation, porosity models are generally object of large errors and not suitable for the prediction of λ b under water-saturated conditions to be expected in the subsurface.…”

Section: Correlation Of λ B With φ Valuessupporting

confidence: 64%

“…This is mostly related to the scarcity of quantitative mineralogical composition data, which are needed to identify the specific impact of single mineral phases on λ m . Studies that examined the methodological aspect of the λ m determination indicate a fluctuation of the absolute λ m value when different types of fluid are present in the pore space, but only included a few measurements of sandstones (e.g., Clauser and Huenges 1995;Jorand et al 2015).…”

Section: Existing and New Empirical Models For Bulk Thermal Conductivmentioning

confidence: 99%

“…Although new techniques such as the optical scanning method (Popov et al 1999) allow rapid measurements of λ b , the generation of statistically reliable datasets covering large stratigraphic sections is very time-consuming and might require multi-year studies (c.f., Clauser et al 2007Clauser et al , 2009Fuchs and Föster 2010;Bär 2012;Jorand et al 2015;Fuchs and Balling 2016). Especially in the case of sandstones, the alternative use of textbookderived mean values for thermal modeling is not sufficient for accurate temperature predictions.…”

Section: Introductionmentioning

confidence: 99%

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Pore-fluid-dependent controls of matrix and bulk thermal conductivity of mineralogically heterogeneous sandstones

Kämmlein

Stollhofen

2019

Geotherm Energy

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For a variety of geothermal engineering applications, the only indirectly determinable matrix thermal conductivity (λ m) is frequently used to convert the measured bulk rock thermal conductivity (λ b) of air-saturated sandstones to water-saturated conditions. However, the necessary assumption that the absolute value of λ m remains constant irrespective of the pore fluid present turns out to be not valid in practice and the explicit control factors on λ m have not been demonstrated yet for different pore fluids. A pore fluid-controlled change in the λ m value also questions the transferability of empirical proxy models for the estimation of water-saturated λ b when they were calibrated on air-saturated samples. This study applies a multiple regression analysis to quantitative mineralogical composition data and porosity (Φ) to identify the controls of the λ m for different types of pore fluids (water-vs. air-saturation). In addition, the differences in the calculated λ m values resulting from different calculation methods or input data (theoretical geometric mean model or mineralogical composition data) are examined. We further test the suitability of different sandstone properties as potential proxies for the estimation of the λ b , with respect to the pore fluid type. Differences in the absolute value of λ m of sandstones from different measurement conditions (air-or water-saturated) are most probably related to the formation of authigenic kaolinite in the pore space, originating from the alteration of alkali feldspar. In addition, the thermal properties of the rock matrix are mainly controlled by the volume fractions of the high thermally conductive mineral fractions quartz and dolomite. Empirical models that have solely Φ or P-wave velocity (v p) as variables are not suitable for the prediction of water-saturated λ b of sandstones. Instead, quantitative mineralogical data of high thermally conductive mineral phases such as quartz and dolomite have to be included. The easily measureable v p is proposed as a promising proxy for both pore fluid types tested: combined with the total quartz volume/porosity ratio for air-saturated sandstones, and combined with the quartz plus dolomite volume fractions for water-saturated sandstones.

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“…Units. The thickness distribution of the main geological units (Figure 3) illustrates that the permeable Cenozoic sediments 3 Geofluids Marl, sand, and clay [32] 0.18 [16,[33][34][35][36] 7E − 14 [13,16,29,33,35,37] 860 [38] 1.3 [39] 1.0 [34] 2585 [24] Dogger/Lias/Keuper Clay, marlstone, limestone, and sandstone [39,40] 0.04 [37] 4E − 16 [35,37] 800 [34,41] 2.6 [39] 1.6 [34] 2667 [24] Pre [33,39] 1.0 [34] 2780 [24] UC: Mid-German Crystalline High Granitoids [33,44] 0.01 [34] 3E − 18 [37] 755 [33] 2.4 [33] 1.8 [45] 2717 [24] UC: Saxothuringian Slate, granitoids [46,47] 0.01 [34] 3E − 18 [37] 900 [34] 2.5 [48] 2.5 [47] 2747 [24] UC: Moldanubian Gneiss, gra...…”

Section: Configuration and Physical Properties Of The Geologicalmentioning

confidence: 99%

Influence of the Main Border Faults on the 3D Hydraulic Field of the Central Upper Rhine Graben

et al. 2019

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The Upper Rhine Graben (URG) is an active rift with a high geothermal potential. Despite being a well-studied area, the three-dimensional interaction of the main controlling factors of the thermal and hydraulic regime is still not fully understood. Therefore, we have used a data-based 3D structural model of the lithological configuration of the central URG for some conceptual numerical experiments of 3D coupled simulations of fluid and heat transport. To assess the influence of the main faults bordering the graben on the hydraulic and the deep thermal field, we carried out a sensitivity analysis on fault width and permeability. Depending on the assigned width and permeability of the main border faults, fluid velocity and temperatures are affected only in the direct proximity of the respective border faults. Hence, the hydraulic characteristics of these major faults do not significantly influence the graben-wide groundwater flow patterns. Instead, the different scenarios tested provide a consistent image of the main characteristics of fluid and heat transport as they have in common: (1) a topography-driven basin-wide fluid flow perpendicular to the rift axis from the graben shoulders to the rift center, (2) a N/NE-directed flow parallel to the rift axis in the center of the rift and, (3) a pronounced upflow of hot fluids along the rift central axis, where the streams from both sides of the rift merge. This upflow axis is predicted to occur predominantly in the center of the URG (northern and southern model area) and shifted towards the eastern boundary fault (central model area).

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Statistically reliable petrophysical properties of potential reservoir rocks for geothermal energy use and their relation to lithostratigraphy and rock composition: The NE Rhenish Massif and the Lower Rhine Embayment (Germany)

Cited by 41 publications

References 25 publications

Analysis of the Thermophysical Properties and Influencing Factors of Various Rock Types From the Guizhou Province

Analysis of the Thermophysical Properties and Influencing Factors of Various Rock Types From the Guizhou Province

Pore-fluid-dependent controls of matrix and bulk thermal conductivity of mineralogically heterogeneous sandstones

Influence of the Main Border Faults on the 3D Hydraulic Field of the Central Upper Rhine Graben

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