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A semi-infinite hydraulic fracture with leak-off driven by a power-law fluid

Published online by Cambridge University Press:  20 December 2017

E. V. Dontsov*
Affiliation:
Department of Civil and Environmental Engineering, University of Houston, Houston, TX 77204, USA
O. Kresse
Affiliation:
Schlumberger, 110 Schlumberger Drive, MD-2, Sugar Land, TX 77478, USA
*
†Email address for correspondence: edontsov@central.uh.edu

Abstract

This study investigates the problem of a semi-infinite hydraulic fracture that propagates steadily in a permeable formation. The fracturing fluid rheology is assumed to follow a power-law behaviour, while the leak-off is modelled by Carter’s model. A non-singular formulation is employed to effectively analyse the problem and to construct a numerical solution. The problem under consideration features three limiting analytic solutions that are associated with dominance of either toughness, leak-off or viscosity. Transitions between all the limiting cases are analysed and the boundaries of applicability of all these limiting solutions are quantified. These bounds allow us to determine the regions in the parametric space, in which these limiting solutions can be used. The problem of a semi-infinite fracture, which is considered in this study, provides the solution for the tip region of a hydraulic fracture and can be used in hydraulic fracturing simulators to facilitate solving the moving fracture boundary problem. To cater for such applications, for which rapid evaluation of the solution is necessary, the last part of this paper constructs an approximate closed form solution for the problem and evaluates its accuracy against the numerical solution inside the parametric space.

Information

Type
JFM Papers
Copyright
© 2017 Cambridge University Press 
Figure 0

Figure 1.(a) Schematics of a semi-infinite hydraulic fracture model. (b) The triangular parametric space, see Garagash et al. (2011) for a similar representation for the case of Newtonian fluids. The solid lines inside the triangle schematically indicate trajectories of the solution in the parametric space for different values of leak-off.

Figure 1

Figure 2.Numerical solution for the normalized fracture width versus $\tilde{x}$ and $\unicode[STIX]{x1D712}$ for $n=\{0,0.5,1,1.5\}$, (a–d) respectively. Red, blue and green regions respectively indicate the applicability of the toughness ($k$), viscous ($m$) and leak-off ($\tilde{m}$) vertex solutions defined in (4.2a-c).

Figure 2

Figure 3.Numerical solution for the normalized fracture width versus $\tilde{x}$ for $n=\{0,0.25,0.5,0.75,1,1.25,1.5,175\}$ and $\unicode[STIX]{x1D712}=0$ (a), $\unicode[STIX]{x1D712}=10^{2}$ (b). Red, blue and green dashed lines respectively indicate the toughness ($k$), viscous ($m$) and leak-off ($\tilde{m}$) vertex solutions defined in (4.2).

Figure 3

Figure 4.Boundaries of the $km$, $k\tilde{m}$ and $m\tilde{m}$ transitions versus $n$. Quantities with the superscripts ‘$(1)$’ and ‘$(2)$’ correspond to the beginning and end of the transitions. Dashed lines represent the curves that are calculated based on the fitting (6.7).

Figure 4

Figure 5.Validity regions of the vertex solutions that are calculated using asymptotic expansions (6.8) and (6.9) (blue solid, dashed and dotted lines) for different values of the power-law exponent $n$. The black dashed lines indicate the bounds calculated using the equation and values in table 1.

Figure 5

Table 1.Coefficients of the second degree polynomial (6.7) that is used to approximate boundaries of the transitions.

Figure 6

Figure 6.(a) Maximum error of the approximate solution versus parameter $\unicode[STIX]{x1D703}$ for the case $n=0$ (results do not depend on $\unicode[STIX]{x1D712}$ for $n=0$). (b) Optimal values of $\unicode[STIX]{x1D703}$ versus $n$ for different values of the leak-off parameter $\unicode[STIX]{x1D712}$.

Figure 7

Figure 7.Relative difference between the numerical solution and the approximate solution for the normalized fracture width versus $\tilde{x}$ and $\unicode[STIX]{x1D712}$ for $n=\{0,0.5,1,1.5\}$, (a–d) respectively.

Figure 8

Figure 8.Maximum relative error of the approximate solution versus $n$.