From Local Effective Stresses to a Theoretical Sub Critical Fracture Propagation Rate
While the formation of mode I fractures driven by effective stresses that reach the tensile rock strength (\({T_0}\)) is understood (Fig. 4), describing closely spaced mode I fractures is more difficult, since local tensile driving stresses in between a set of parallel mode I fractures get greatly reduced (Bai and Pollard 2000) (Fig. 2). This implies that the development of closely spaced mode I fractures and therefore orthogonal networks often occurs under sub critical stress conditions, since the local effective tensile stress never reach the theoretical rock strength. Therefore, in geoscience, rock failure under these sub critical stresses is often described using the empirical theory of Sub Critical Crack Growth (SCCG) (Atkinson 1984),which is based on the relation between the stress intensity (\({K_{\text{i}}}\)), fracture toughness (\({K_{{\text{ic}}}}\)) and measured fracture propagation rates. This fracture behaviour is often observed in laboratory experiments. For instance, double torsion experiments show fractures developing subcritically when the stress intensity factors fall below the critical value, i.e., \({K_{\text{i}}}<{K_{{\text{ic}}}}\) (Nara et al. 2012; Shyam and Lara-Curzio 2006) Therefore, in geology, SCCG is considered to be an important mechanism for the development of complex fracture networks (Olson 2007).
Our study uses linear elastic fracture mechanics to incorporate SCCG in to our static models. This is done by calculating the stress intensity (\({K_{\text{i}}}\)) on the implemented micro cracks, using the modelled crack opening and the LEFM relations first described by Pollard and Segall (1987). These authors showed that the local stress intensity can be calculated using Eq. (3):
$${K_{\left( {{\text{Itip}}} \right)}}=Y\frac{{\sqrt \pi E}}{{4\left( {1 - {\nu ^2}} \right)\sqrt a }}{C_{{\text{open}}}},$$
(3)
where \(~E\) is the Young’s modulus of the matrix, \(~\nu\) the Poisson ratio, Y is a geometrical factor (set at 1 in this modelling study), a is half the crack length and \({C_{{\text{open}}}}\) is the maximum opening on a crack plane. The calculated stress intensity on each crack tip can then be related to a sub critical propagation rate using the stress corrosion cracking power–law (Atkinson 1984). This power–law relation is shown by Eq. (4) and is used in multiple lab an modelling studies describing SCCG (Atkinson 1984; Ko and Kemeny 2011; Nara et al. 2012; Olson et al. 2009; Shen and Rinne 2007):
$$v={v_{{\text{max}}}}{\left( {\frac{{{K_{{\text{I(tip)}}}}}}{{{K_{{\text{Ic}}}}}}} \right)^n},\;{\text{if}}\;{K_{\text{I}}}<{K_{{\text{Ic}}}},$$
(4)
where \(v\) is theoretical sub critical growth rate (m/s), \({v_{{\text{max}}}}\) is the maximum crack propagation rate, \({K_{{\text{I(tip)}}}}\) is the stress intensity on the crack tip, \(~{K_{{\text{Ic}}}}\) is the mode I fracture toughness (material property) and \(n\) is the sub critical crack growth index. We assume that \({K_{{\text{Ic}}}}\) can be related to the tensile rock strength and an initial crack length (\({K_{{\text{Ic}}}}=~Y{T_0}\sqrt {\pi {a_{{\text{initial}}}}}\), where \({a_{{\text{initial}}}}\) = 0.0125 m), and the magnitudes of \(n\) and \({v_{{\text{max}}}}\) are set to 35 and 100 (m/s), respectively, which is similar to other modelling studies (Ko and Kemeny 2011; Olson et al. 2007, 2009; Rijken 2005; Shen and Rinne 2007). The implemented SCCG approach states that low local tensile stresses result in a low fracture opening, which results in low stress intensities on the crack tip and therefore low calculated fracture propagation velocities. This implies that the reduction of effective stresses (Fig. 2) would result in a saturated network at which no implemented fractures will grow. In this study we will not focus on the impact of changing the sub critical crack growth index (\(n\)), which is known to have a significant impact on the fracture spacing in mode I fracture networks (Olson 2004, 2007).
Another method of measuring the fracturing potential within an elastic material is using the strain energy density (\(u\)), which represents the elastic work stored in an elastically deformed body (Jaeger et al. 2007). This elastic energy is related to the applied principal stresses and elastic material parameters which is shown by Eq. (5):
$$u=~\frac{1}{{2E}}\left[ {\left( {\sigma _{z}^{{'L2}}+~\sigma _{H}^{{'L2}}+\sigma {{_{h}^{{'L2}}}^{}}} \right) - 2\nu \left( {\sigma _{z}^{{'L}}\sigma _{H}^{{'L}}+~\sigma _{H}^{{'L}}\sigma _{h}^{{'L}}+~\sigma _{h}^{{'L}}\sigma _{z}^{{'L}}} \right)} \right],$$
(5)
where \(u\) is the strain energy per unit volume, \(E\) is the Young’s modulus, \(\nu\) is the Poisson ratio and \(\sigma _{i}^{{'L}}\) are the local principal stress components. This equation states that minimising the available strain energy, will inhibit further fracture development and results in a saturated fractured material (Kemeny 1985).
A Step-by-Step Modelling Approach: Developing an Orthogonal Network Under Fixed Remote Stress Conditions
In the following, we take the computed 3D stress field, apply the relation between LEFM and SCCG and calculate local propagation velocities of implemented micro cracks, to depict the development a saturated fracture network under fixed remote stress conditions, assuming steady state conditions and no transient pressure effects. For this modelling scenario, a remote tensile stress ratio of (\(\frac{{\sigma _{{\text{H}}}^{'}}}{{\sigma _{{\text{h}}}^{'}}}=0.7\)) (\(\sigma _{{\text{h}}}^{'}=5.0{\text{MPa}},~\;\sigma _{{\text{H}}}^{'}=3.5~{\text{MPa}}\)) and a Poisson ratio (ν) of 0.25 are applied to the boundaries and matrix of the model, respectively. The results depict a z-slice through the model, essentially cutting the model in half.
The initial fracture network (Fig. 5) depicts two initially widely spaced parallel fractures (\(S/H\) = 4.0, spacing = 0.4 m) placed perpendicular to the highest effective tensile stress. In between these fractures, 17 microfractures are placed perpendicular to one of the principal stress directions. These microfractures have an initial length of 0.025 m (2*element size) and have an initial spacing of x = 0.1 m for parallel fractures, and y = 0.15 m for orthogonal fractures, respectively. The fractures are illustrated by the aligned circles, which size is proportional to the local fracture aperture. This geometry (Fig. 5) is used as an initial fracture network for all modelling scenarios, which aim is not to represent a naturally imperfect rock volume, but to model and depict the mechanics controlling the development of an orthogonal fracture network. In our numerical analysis, the two outer fractures are not allowed to propagate throughout each timestep and we will only focus on the development of fractures within the area of interest (Fig. 6).The initial network geometry and the highest effective tensile stresses are shown by Fig. 6a. This figure depicts how the implemented mode I cracks open and perturb the local stress field following LEFM. Using Eqs. (3) and (4), the theoretical propagation velocity (m/s) of each micro crack is calculated. As shown by the local stress field, local tensile stresses, and therefore, local fracture opening is highest at the centre of the model (x = 0.0, − 0.2 < y < 0.2). This implies that the parallel fractures in these locations are most likely to grow. The resulting network derived from the first timestep is depicted in Fig. 6b and shows that the fractures in the centre of the model have indeed developed into a fully grown parallel fracture. Furthermore, some other micro cracks showed a few cm of growth (Fig. 6b).
At intermediate stage [2], the local stress field is perturbed by the active fractures (orthogonal/parallel). The results show how the principal effective stresses perpendicular to the active parallel fractures (\(\frac{{\sigma _{x}^{{\prime L}}}}{{{T_0}}}\)) are becoming shadowed following LEFM. However, the local principal tensile stresses in the y-direction remain present (Fig. 6b), resulting in a local stress flip (\(\frac{{\sigma _{x}^{{\prime L}}}}{{{T_0}}}<\frac{{\sigma _{y}^{{\prime L}}}}{{{T_0}}}\)). Despite the fact that a local stress flip occurs, the network geometry calculated during this stage is still a set off closely spaced parallel fractures (Fig. 6c), which can be explained by the fracture growth implemented during the previous timestep.
At the third timestep, the newly implemented fractures further perturb the local stress field (Fig. 6c). This figure shows how the effective stresses in the x-direction are now completely shadowed (\(\frac{{\sigma _{x}^{{\prime L}}}}{{{T_0}}}~ \approx 0\)), inhibiting further parallel fracturing. However, as was observed during the previous timestep, tensile stresses in the y-direction remain present (Fig. 6c), causing the orthogonal microfractures to remain open. Given enough time (Myr) and prolonging tensile stresses, these fractures will develop into orthogonal fractures and this is also derived by our model (Fig. 6d).
The results depicted by the final stage (Fig. 6d) show a saturated (fully developed) fracture network, where all initial tensile stresses are shadowed as a result of the emplaced fractures, essentially implying that: \(\frac{{\sigma _{x}^{{\prime L}}}}{{{T_0}}},~\frac{{\sigma _{y}^{{\prime L}}}}{{{T_0}}}~\) ≈ 0. This local stress field, therefore, indicates that no new mode I fracture can grow in between the current active fractures (as long as these fractures remain open and perturb the stress field). Hence, this figure represents the final network geometry which is most probable to form, regarding this specific initial network geometry, remote stress state, implemented Poisson ratio and sub critical crack growth parameters.
The development of a saturated orthogonal network (Fig. 6) also results in a minimization of the local available strain energies (Eq. 5). The step-by-step reduction in available energy as a function of continued mode I fracture infill is shown in Fig. 7. At the final development stage (Fig. 7d), the strain energy density created by the applied tensile stresses is reduced to 0, inhibiting further mode I fracture infill. Therefore, Fig. 7d depicts a mode I fracture network geometry at which the available strain energy density is minimized, and, therefore, has the highest probability of forming under these initial conditions.