scholarly journals The growth of faults and fracture networks in a mechanically evolving, mechanically stratified rock mass: a case study from Spireslack Surface Coal Mine, Scotland

Solid Earth ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 2119-2140
Author(s):  
Billy James Andrews ◽  
Zoe Kai Shipton ◽  
Richard Lord ◽  
Lucy McKay

Abstract. Fault architecture and fracture network evolution (and resulting bulk hydraulic properties) are highly dependent on the mechanical properties of the rocks at the time the structures developed. This paper investigates the role of mechanical layering and pre-existing structures on the evolution of strike–slip faults and fracture networks. Detailed mapping of exceptionally well exposed fluvial–deltaic lithologies at Spireslack Surface Coal Mine, Scotland, reveals two phases of faulting with an initial sinistral and later dextral sense of shear with ongoing pre-faulting, syn-faulting, and post-faulting joint sets. We find fault zone internal structure depends on whether the fault is self-juxtaposing or cuts multiple lithologies, the presence of shale layers that promote bed-rotation and fault-core lens formation, and the orientation of joints and coal cleats at the time of faulting. During ongoing deformation, cementation of fractures is concentrated where the fracture network is most connected. This leads to the counter-intuitive result that the highest-fracture-density part of the network often has the lowest open fracture connectivity. To evaluate the final bulk hydraulic properties of a deformed rock mass, it is crucial to appreciate the relative timing of deformation events, concurrent or subsequent cementation, and the interlinked effects on overall network connectivity.

Fractals ◽  
2019 ◽  
Vol 27 (04) ◽  
pp. 1950057 ◽  
Author(s):  
TONGJUN MIAO ◽  
SUJUN CHENG ◽  
AIMIN CHEN ◽  
YAN XU ◽  
GUANG YANG ◽  
...  

Fractures with power law length distributions abound in nature such as carbonate oil and gas reservoirs, sandstone, hot dry rocks, etc. The fluid transport properties and morphology characterization of fracture networks have fascinated numerous researchers to investigate for several decades. In this work, the analytical models for fracture density and permeability are extended from fractal fracture network to general fracture network with power law length distributions. It is found that the fracture density is related to the power law exponents [Formula: see text] and the area porosity [Formula: see text] of fracture network. Then, a permeability model for the fracture length distribution with general power law exponent [Formula: see text] and the power law exponent [Formula: see text] for fracture length versus aperture is proposed based on the well-known cubic law in individual fracture. The analytical expression for permeability of fractured networks is found to be a function of power law exponents [Formula: see text], area porosity [Formula: see text] of fracture network, and the micro-structural parameters (maximum fracture length [Formula: see text], fracture azimuth [Formula: see text] and fracture dip angle [Formula: see text]). The present model may shed light on the mechanism of seepage in fracture networks with power law length distributions.


Solid Earth ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 1731-1746
Author(s):  
Romesh Palamakumbura ◽  
Maarten Krabbendam ◽  
Katie Whitbread ◽  
Christian Arnhardt

Abstract. Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of applications in geosciences from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high-quality, oriented-fracture datasets in the field can be difficult and time-consuming, for example, due to constraints on field work time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe a method for generating a series of digital fracture traces in a geographic information system (GIS) environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field but to be used in conjunction with it, and it is well suited when field work time is limited or when the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. Advantages and limitations compared to other fracture network capture methods are discussed.


2020 ◽  
Author(s):  
Peter Bayer ◽  
Mohammad Javad Afshari Moein ◽  
Márk Somogyvári ◽  
Lisa Ringel ◽  
Mohammadreza Jalali

<p>Fracture network characterization is critical for many subsurface engineering problems in petroleum, mining, nuclear waste disposal and Enhanced Geothermal Systems (EGS). Due to limited exposure, direct measurement of fracture network properties at great depth is not possible and geophysical imaging techniques cannot resolve the fractures. Therefore, tomographic imaging techniques have been proposed and applied to reconstruct the structural discontinuities of rock mass. Stress-based tomography is a novel concept aiming at probabilistic imaging of the fracture network using the stress perturbations along deep boreholes. Currently, this approach has only been successfully tested on two-dimensional fracture networks. However, its great potential to unravel the heterogeneous structure of fractured rocks at great depth motivates further scientific effort. Here, we present the potential, open questions, current challenges and necessary future developments in order to apply this methodology to image three-dimensional multiscale structure of the rock mass in the field. Other tomographic approaches such as tracer and hydraulic tomography invert tracer breakthrough curves (BTCs) and pressure response in an observational well. We suggest a joint and comparative tomographic analysis in a Bayesian inversion framework to reconstruct Discrete Fracture Networks (DFN). This is expected to provide a new view of the strengths of each tomographic variant.</p>


2021 ◽  
Author(s):  
Amy Myers ◽  
Claire Harnett ◽  
Michael Heap ◽  
Eoghan Holohan ◽  
Thomas Walter

<p>Volcanic domes form when lava is too viscous to flow away from an active volcanic vent; instead, the lava accumulates into a mound consisting of a hotter, ductile core and a colder, brittle outer layer. An existing lava dome grows when new material is injected into the core of the dome, causing the  outer layer to stretch and develop tensile fractures. With continued dome growth, these weaknesses can propagate to form an extensive fracture network and the dome may fail. Collapse events often generate rock falls and debris avalanches, lahars, and high-speed pyroclastic flows, endangering populations residing at the base of a volcano. Since such fractures represent potential failure planes, in this project we aim to understand the role they have in destabilising lava domes.</p><p>This project will build on the work published by Harnett et al. (2018), which demonstrates the suitability of a discrete element modelling approach to simulate dome emplacement and evolution. Specifically, this project is designed to:</p><p>1. Use high-resolution photogrammetry to characterise the possible fracture states of a dome;</p><p>2. Establish up-scaled rock-mass properties by performing geomechanical experiments on both fractured and non-fractured samples of dome rock from prior collapses;</p><p>3. Develop a numerical model to investigate how the presence and properties of fracture networks influence dome stability.</p><p>The model, developed using PFC, will be used to identify critical fracture states that can signify a dome collapse is likely to occur. Under the current model, parallel bonds simulate the fluid magma core and flat joints simulate the solid talus material. This project will build on this original model by incorporating discrete fracture networks into the smooth-joint model to implement dome fracturing. The new model will look to investigate the effect  of a fracture network on a static dome that, when in its unfractured state, is stable under gravity. Additionally, the model will be designed such that inputs can include experimentally derived rock-mass properties. It is hoped that, by incorporating observational and experimental data into a more  complex model, the dynamic evolution of fractures in a growing lava dome can be investigated and the ongoing likelihood of a dome collapse event can be assessed.</p><p> </p><p>Harnett, C. E. et al., 2018. J. Volcanol. Geoth. Res., 359: 68-77.</p>


2018 ◽  
Vol 6 (2) ◽  
pp. SE49-SE61 ◽  
Author(s):  
Ellie P. Ardakani ◽  
Adam M. Baig ◽  
Ted Urbancic ◽  
Katie Bosman

The advent of horizontal drilling technology, combined with multistaged hydraulic fracturing to create a complex fracture network within the relatively impermeable rock mass, has made natural gas production from tight reservoirs economically feasible. Understanding of the generated fracture network properties, such as its spatial distribution, extension, connection, and ability to percolate, plays a significant role in evaluation of the stimulation efficiency, optimizing analytical frac models, and ultimately enhancing completion programs. We have developed a unique approach to understand the influence of fractures on fluid flow and production from impermeable reservoirs and evaluate completion effectiveness. We characterize the microseismicity-derived discrete fracture network in a North American shale-gas reservoir using modified scanline and topology methods. Using concepts of node and branch classification and assessing the number of connections (fracture intersections), the network connectivity is established volumetrically. The zones of permeability enhancement are then identified using the connection per branch and line ([Formula: see text] and [Formula: see text]), tied to percolation thresholds of the fracture system. These zones consist of a primary zone with a high proportion of doubly connected fractures, a secondary zone populated with partially connected fractures, and a tertiary or unstimulated zone dominated by isolated fractures. These divisions are reflected in the deformation that is observed in the reservoir as measured through a cluster-based description of the microseismicity. The primary and secondary zones are considered spanning fracture clusters, and they take part in production, whereas the tertiary zone is recognized as nonspanning fractures, and though it may enhance the bulk permeability of the rock mass, it is unlikely to contribute to reservoir production.


2009 ◽  
Vol 12 (01) ◽  
pp. 48-52 ◽  
Author(s):  
Shawn C. Maxwell ◽  
Charles Waltman ◽  
Norman R. Warpinski ◽  
Michael J. Mayerhofer ◽  
Neda Boroumand

Summary Microseismic mapping is extensively used in the Barnett Shale to map hydraulic fracture complexity associated with interactions of the stimulation with pre-existing fractures (fracs). Previous studies have indicated a fair correlation between the well performance and extent of the seismically active volume. However, in addition to this measure of the extent of the stimulated fracture network, the characteristics of this fracture network is also expected to impact the well performance. In particular, the fracture spacing is believed to be an important factor controlling the potential gas flow. In this paper, we use the density of the total seismic moment release (a robust measure of the microseism strength) as an indication of the seismic deformation that may correlate to the fracture density. The study uses a set of microseismic maps of hydraulic fracture stimulations, including cases in which the stimulated reservoir volume measured by the extent of the seismically active region poorly correlated with the well performance. Incorporating the seismic moment density to assess the fracture density with the network extent, an improved correlation with the well performance was observed. Introduction Microseismic mapping of hydraulic fracture stimulations has become a common technique to map the fracture growth and geometry (Warpinski et al. 2004; Fisher et al. 2002; Maxwell et al. 2002; Fisher et al. 2004; Rutledge et al. 2004; Shapiro et al. 2004; Chambers et al. 2008; Lu et al. 2008; Warpinski et al. 2005). Microseismic images provide details of the fracture azimuth, height, length, and complexity resulting from interaction with pre-existing fratures. The resulting images can be used to calibrate numerical simulations of the fracture growth, allowing more confident modeling of other stimulations in the field, and a better identification of the stimulated region that may ultimately be drained by the well. Arguably, the Barnett Shale is the field that has had the most fracs mapped over the last several years. Microseismic mapping in the Barnett Shale has repeatedly demonstrated extreme fracture complexity resulting from interaction between the injection and a pre-existing fracture network (Fisher et al. 2002; Maxwell et al. 2002; Fisher et al. 2004; Rutledge et al. 2004; Shapiro et al. 2004; Chambers et al. 2008; Lu et al. 2008; Warpinski et al. 2005; Mayerhofer et al. 2006). Even between neighboring wells, the geometry of the stimulated fracture network shows a high degree of variability caused by localized differences in the fracture network (Fisher et al. 2002). The Barnett Shale has a low-intrinsic matrix permeability, and the permeability enhancement associated with the fracture stimulation results in permeable fracture networks sufficient for economic gas recovery in the field. Previous studies have shown a correlation between the volume of the reservoir stimulated as measured by the volume of the reservoir that emits microseisms during the stimulation, and the production ultimately realized from the well (Fisher et al. 2002; Fisher et al. 2004; Mayerhofer et al. 2006). The correlation is attributed to larger fracture networks being stimulated in wells in which a large microseismically active volume of the reservoir has been realized, resulting in more permeable fracture pathways connected to the well and therefore a higher potential for gas flow to the well. Recently, many operators in the Barnett Shale have attempted horizontal completions, which have allowed large volumes of the reservoir to be stimulated with large fracture networks. Many of these completions use perforated, cemented liners, and the microseismic images allow for indentification of improved perforation staging to maximize the stimulated reservoir volume (SRV) (Fisher et al. 2004). Many of the Barnett Shale stimulations are water fracs in which large volumes of water are injected at a high rate (Mayerhofer et al. 1997). One possible mechanism for the success of waterfracs is that increased fluid pressure in natural fractures induced shear failure, resulting in fracture dilation associated with mismatched surfaces on opposite sides of the fracture. Within this conceptual framework, the microseismic events correspond to the actual fracture movement. The earlier investigations of the SRV measured the total volume of the microseismically active region. However, this measure of the stimulated volume does not take into account the properties of the fracture network, which has also been indicated to impact well performance (Mayerhofer et al. 2006). Furthermore, the permeability enhancement of the fracture may be related to deformation associated with fracturing. Beyond the basic hypocentral locations of the microseisms used to calculate the SRV, additional seismic signal characteristics allow investigation of the source of the mechanical deformation resulting in the microseisms. In particular, the seismic moment (Aki and Richards 1980), a robust measure of the strength of an earthquake or microearthquake can be used to quantify the seismic deformation (Maxwell et al. 2003). In this paper, we examine several published microseismic projects in the Barnett Shale formation for correlation between the production and seismic-deformation attributes. In the next section, we describe seismic moments and the calculation of seismic deformation. We illustrate how a seismic moment can be used to remove a recording bias present in most microseismic monitoring applications and the importance for calculating the seismic deformation. Finally, we present the comparison between production, seismic deformation, and SRV for several published datasets.


2019 ◽  
Author(s):  
Romesh Palamakumbura ◽  
Maarten Krabbendam ◽  
Katie Whitbread ◽  
Christian Arnhardt

Abstract. Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of fields in geosciences, from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high quality, oriented-fracture datasets in the field can be difficult and time consuming, for example due to constraints on time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe and evaluate the method for generating a series of digital fracture traces in GIS-environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field, but to be used in conjunction, and is well suited where fieldwork time is limited, or where the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS-environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. There are a number of advantages to using a digital method for gathering fracture data including: time efficiency, generating large fracture network datasets, flexibility during data gathering and consistency of data.


2021 ◽  
Vol 11 (2) ◽  
pp. 685-702
Author(s):  
Meysam Khodaei ◽  
Ebrahim Biniaz Delijani ◽  
Mastaneh Hajipour ◽  
Kasra Karroubi ◽  
Ali Naghi Dehghan

AbstractIn this study, the correlation between geometric properties of the fracture network and stress variability in a fractured rock was studied. Initially, discrete fracture networks were generated using a stochastic approach, then, considering the tensorial nature of stress, the stress field under various tectonic stress conditions was determined using finite-difference method. Ultimately, stress data were analyzed using tensor-based mathematical relations. Subsequently, the effects of four parameters including rock tensile strength, rock cohesion, fracture normal stiffness and fracture dilation angle on the stress perturbation distribution were evaluated. The obtained results indicated that stress perturbation and dispersion are directly related to fracture density, which is expressed as the number of fractures per unit area utilizing the window sampling approach. It was also demonstrated that they are inversely related to power-law length exponent which represents the length of fracture. It was observed that stress distribution, among the evaluated parameters, is more sensitive to the fracture normal stiffness and the effects of rock parameters on stress distribution are negligible. It was concluded that the highest stress distribution is created when the fracture network is dense with fractures having high length and low normal stiffness value.


2021 ◽  
Author(s):  
Fatemeh Nazari Vanani ◽  
Oscar Fernandez

<p>Adequately characterizing the properties of a fracture network is the first step in accurately modelling its behavior, be it mechanically or hydraulically. Characterizing fracture networks requires determining fracture frequency, orientation, connectivity, and fracture properties. This becomes particularly challenging in subsurface systems, where hard data on fracture networks comes mainly from boreholes, that are samples of very limited volume in relation to the fracture network. Because of this scale relationship between sample dimension and the dimension of natural fracture networks, boreholes capture a very partial picture of the fracture network. This is particularly relevant when attempting to estimate fracture frequency and network connectivity from borehole data. Corrections are normally used to account for sampling bias related to fracture size and orientation. Whereas these corrections are valid for the sample itself, the topology and heterogeneity of fracture networks means that measurements obtained in any given borehole are not necessarily representative of the broader fracture network.</p><p>To determine how “wrong” single-borehole analyses can be, we have conducted experiments on synthetic datasets to quantify how representative borehole samples are of entire fracture networks. Results show that properties that have an impact on the anisotropy of the fracture network (orientation, number of fracture sets) can be accurately resolved even in low data-density scenarios. On the contrary, accurately determining fracture frequency (which also impacts connectivity) for the entire fracture network is strongly dependent on the ratio between fracture frequency and the sampled volume. Measurements of fracture frequency in individual boreholes indicate that it frequency easily be overestimated or underestimated by a factor of 2 relative to the real network’s fracture frequency. The application of sampling bias corrections has a limited impact on reducing this error.</p><p>Based on the results from our experiments, we present methods to assess how representative of a fracture network a single borehole is. Representativity can be translated into uncertainty in fracture frequency, a metric that can be used in fracture modelling.</p>


Sign in / Sign up

Export Citation Format

Share Document