Implications of heterogeneous fracture distribution on reservoir quality; an analogue from the Torridon Group sandstone, Moine Thrust Belt, NW Scotland

Watkins, Hannah; Healy, David; Bond, Clare E.; Butler, Robert W.

doi:10.1016/j.jsg.2017.06.002

Cited by 60 publications

(49 citation statements)

References 43 publications

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“…Wellbore and seismic analysis, among the most commonly applied in petroleum industry, although allowing an accurate characterization and mapping of geological structures in the subsurface, show some limitations: the former method is quite restricted in space and number, since well data provide linear information and are relatively expensive; the latter is a very common tool for subsurface structure analysis in exploration industry, but its data resolution is not always adequate for a proper meso-scale fracture analysis. Reservoir analogues can provide an important tool to integrate the abovementioned methods in the analysis of fractured carbonate reservoirs, allowing a detailed observation of some fracture system properties difficult or impossible to be quantified by means of subsurface data [1][2][3]. Although the selected analogue shows similar depositional and geometric features with respect to the subsurface reservoir, the different burial history and boundary conditions, mainly temperature and pressure, need to be taken into account for a proper comparison of information related to the outcropping analogue and the buried reservoir.…”

Section: Introductionmentioning

confidence: 99%

Discrete Fracture Network Modelling in Triassic–Jurassic Carbonates of NW Lurestan, Zagros Fold-and-Thrust Belt, Iran

et al. 2019

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In this study, discrete fracture network (DFN) modelling was performed for Triassic–Jurassic analogue reservoir units of the NW Lurestan region, Iran. The modelling was elaborated following a multi-scale statistical sampling of the fracture systems characterising the analysed succession. The multi-scale approach was performed at two different observation scales. At the macro-scale, a digital outcrop analysis was carried out by means of a digital line-drawing based on camera-acquired images, focussing on the distribution of major throughgoing fractures; at the meso-scale, the scan line method was applied to investigate the background fractures of the examined formations. The gathered data were statistically analysed in order to estimate the laws governing the statistical distribution of some key fracture set attributes, namely, spacing, aperture, and height. The collected dataset was used for the DFN modelling, allowing the evaluation of the relative connectivity of the fracture systems and, therefore, defining the architecture and the geometries within the fracture network. The performed fracture modelling, confirmed, once again, the crucial impact that large-scale throughgoing fractures have on the decompartmentalization of a reservoir and on the related fluid flow migration processes. The derived petrophysical properties distribution showed in the models, defined the Kurra Chine Fm. and, especially, the Sehkaniyan Fm. as good-quality reservoir units, whereas the Sarki Fm was considered a poor-quality reservoir unit.

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Section: Introductionmentioning

confidence: 99%

Discrete Fracture Network Modelling in Triassic–Jurassic Carbonates of NW Lurestan, Zagros Fold-and-Thrust Belt, Iran

et al. 2019

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“…The variability of these and other petrophysical parameters increases with scale (Alava et al, 2009;Freudenthal, 1968;Krumbholz et al, 2014a). In addition, their heterogeneous distribution and their property values are often anisotropic in terms of orientation, e.g., permeability caused by fractures often has a preferred orientation (e.g., Laubach et al, 2004;Marrett et al, 2007;Nelson, 1985;Watkins et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…10b). Furthermore, permeability anisotropy in fracture networks can reach several orders of magnitude (e.g., Bense and Person, 2006;Caine and Forster, 1999;Jourde et al, 2002;Watkins et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…When considering the Cubic Law, a single fracture, if it is wide enough, can control the fluid flow in a reservoir (e.g., De Marsily, 1986;Nelson, 1985;Odling et al, 1999). In consequence, the prediction of fracture anisotropy at depth with the necessary accuracy is, at least, challenging and, at the most, impossible (e.g., Laubach et al, 2004;Ortega and Marrett, 2000;Watkins et al, 2018). Our models show that a fracture anisotropy of 1 order of magnitude ( Fig.…”

Section: Fracture Anisotropymentioning

confidence: 90%

“…If the anisotropy reaches just 2 orders of magnitude, which according to the literature (e.g., Bense and Person, 2006;Caine and Forster, 1999;Jourde et al, 2002;Watkins et al, 2018) must be considered to be a typical value, this suppression effect becomes saturated. In our models, even high BHGs cannot counteract this behaviour.…”

Section: Fracture Anisotropymentioning

confidence: 99%

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A numerical sensitivity study of how permeability, geological structure, and hydraulic gradient control the lifetime of a geothermal reservoir

Bauer¹,

Krumbholz²,

Luijendijk³

et al. 2019

Preprint

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Abstract. Geothermal energy is an important and sustainable resource that has more potential than is currently utilized. Whether or not a deep geothermal resource can be exploited, depends on, besides temperature, mostly the utilizable reservoir volume over time, which in turn largely depends on petrophysical parameters. We show, using a large series (n = 1027) of 4-dimensional finite element models of a simple geothermal doublet, that the lifetime of a reservoir is a complex function of its geological parameters, their heterogeneity, and the background hydraulic gradient (BHG). In our models, we test the effects of porosity, permeability, and BHG in an isotropic medium. Further, we simulate the effect of permeability contrast and anisotropy induced by layering, fractures, and a fault. We quantify the lifetime of the reservoir by measuring the time to thermal breakthrough, i.e., how many years pass before the 100 °C isotherm (HDI) reaches the production well. Our results attest to the positive effect of high porosity; however, high permeability and BHG can combine to outperform the former. Certain configurations of all the parameters can cause either early thermal breakthrough or extreme longevity of the reservoir. For example, the presence of high permeability fractures, e.g., in a fault damage zone, can provide initially high yields, but channels fluid flow and therefore dramatically restricts the exploitable reservoir volume. We demonstrate that the magnitude and orientation of the BHG, provided permeability is sufficiently high, are prime parameters that affect the lifetime of a reservoir. Our numerical experiments show also that BHGs (low and high) can be outperformed by comparatively small variations in permeability contrast (103) and fracture-induced permeability anisotropy (101) that thus strongly affect the performance of geothermal reservoirs.

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2019

Static Conceptual Fracture Modeling

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Implications of heterogeneous fracture distribution on reservoir quality; an analogue from the Torridon Group sandstone, Moine Thrust Belt, NW Scotland

Cited by 60 publications

References 43 publications

Discrete Fracture Network Modelling in Triassic–Jurassic Carbonates of NW Lurestan, Zagros Fold-and-Thrust Belt, Iran

Discrete Fracture Network Modelling in Triassic–Jurassic Carbonates of NW Lurestan, Zagros Fold-and-Thrust Belt, Iran

A numerical sensitivity study of how permeability, geological structure, and hydraulic gradient control the lifetime of a geothermal reservoir

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