Discrete Fracture Network modelling of a hydrocarbon-bearing, oblique-slip fault zone: Inferences on fault-controlled fluid storage and migration properties of carbonate fault damage zones

Panza, Elisa; Sessa, Emilio; Agosta, Fabrizio; Giorgioni, Maurizio

doi:10.1016/j.marpetgeo.2017.09.009

Cited by 35 publications

(12 citation statements)

References 66 publications

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“…Based on data collected from field surveys, the software allows one to elaborate a stochastic distribution of the fracture network. As demonstrated by Panza et al [82], who performed seeding and sensitivity analysis testing multiple configurations of DFN models, the error associated with the modalities of stochastic fracture generation provided by the software Move can be considered negligible. The required input data were, per individual set, fracture intensity, length, azimuth, dip, K-fisher value, aspect ratio, and aperture.…”

Section: Modellingmentioning

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: Modellingmentioning

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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“…Over the past decades, several methodologies to calculate an equivalent elastic compliance and permeability tensors have been proposed and examined (Cui et al., 2016; Huang et al., 1995; Jiang et al., 2017; Laghaei et al., 2018; J. Liu, et al., 2019; Min & Jing, 2003; Oda, 1986; Sitharam et al., 2001). Amongst the models, the crack tensor theory proposed by Oda (1986) appears to be one of the most widely employed models (Gan & Elsworth, 2016; Gutierrez & Youn, 2015; Panza et al., 2018; Rutqvist et al., 2013), because of its simplicity and a relatively small number of input parameters. The equivalent compliance tensor is calculated as below (Oda, 1986; Rutqvist et al., 2013).…”

Section: Methodsmentioning

confidence: 99%

“…Liu, et al, 2019;Min & Jing, 2003;Oda, 1986;Sitharam et al, 2001). Amongst the models, the crack tensor theory proposed by Oda (1986) appears to be one of the most widely employed models (Gan & Elsworth, 2016;Gutierrez & Youn, 2015;Panza et al, 2018;Rutqvist et al, 2013), because of its simplicity and a relatively small number of input parameters. The equivalent compliance tensor is calculated as below (Oda, 1986;Rutqvist et al, 2013).…”

Section: Overall Proceduresmentioning

confidence: 99%

Numerical Modeling of Complex Stress State in a Fault Damage Zone and Its Implication on Near‐Fault Seismic Activity

et al. 2021

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“…The widely used discrete fracture network (DFN) stochastic modelling tools provide statistical representation of fracture networks generally constrained by a univariate and random distribution of orientation, size, spacing and density/intensity data (Bisdom et al, 2014(Bisdom et al, , 2017aHuang et al, 2017;Panza et al, 2018). The models generated follow a local stationarity hypothesis.…”

Section: Modelling Approaches Classically Used To Model Fracture Netwmentioning

confidence: 99%

A new methodology to train fracture network simulation using multiple-point statistics

Bruna¹,

Straubhaar²,

Prabhakaran³

et al. 2019

Solid Earth

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Abstract. Natural fracture network characteristics can be establishes from high-resolution outcrop images acquired from drone and photogrammetry. Such images might also be good analogues of subsurface naturally fractured reservoirs and can be used to make predictions of the fracture geometry and efficiency at depth. However, even when supplementing fractured reservoir models with outcrop data, gaps will remain in the model and fracture network extrapolation methods are required. In this paper we used fracture networks interpreted from two outcrops from the Apodi area, Brazil, to present a revised and innovative method of fracture network geometry prediction using the multiple-point statistics (MPS) method. The MPS method presented in this article uses a series of small synthetic training images (TIs) representing the geological variability of fracture parameters observed locally in the field. The TIs contain the statistical characteristics of the network (i.e. orientation, spacing, length/height and topology) and allow for the representation of a complex arrangement of fracture networks. These images are flexible, as they can be simply sketched by the user. We proposed to simultaneously use a set of training images in specific elementary zones of the Apodi outcrops in order to best replicate the non-stationarity of the reference network. A sensitivity analysis was conducted to emphasise the influence of the conditioning data, the simulation parameters and the training images used. Fracture density computations were performed on selected realisations and compared to the reference outcrop fracture interpretation to qualitatively evaluate the accuracy of our simulations. The method proposed here is adaptable in terms of training images and probability maps to ensure that the geological complexity in the simulation process is accounted for. It can be used on any type of rock containing natural fractures in any kind of tectonic context. This workflow can also be applied to the subsurface to predict the fracture arrangement and fluid flow efficiency in water, geothermal or hydrocarbon fractured reservoirs.

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Discrete Fracture Network modelling of a hydrocarbon-bearing, oblique-slip fault zone: Inferences on fault-controlled fluid storage and migration properties of carbonate fault damage zones

Cited by 35 publications

References 66 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

Numerical Modeling of Complex Stress State in a Fault Damage Zone and Its Implication on Near‐Fault Seismic Activity

A new methodology to train fracture network simulation using multiple-point statistics

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