1 Introduction
Extracting a fluid stored in a porous medium is a problem of fundamental interest to many applications, such as hydrocarbon recovery, geothermal energy harvesting, filtration and bioengineering. When the porous medium is rigid and no fresh fluid is injected into the fluid-bearing reservoir to drive the in situ fluid out of the pore space, fluid recovery relies entirely on the volumetric expansion of the fluid; such a process is called primary recovery in the petroleum literature (Muskat Reference Muskat1949). Primary recovery is the first and the most important stage of hydrocarbon recovery, as it often accounts for more than half of the total amount of hydrocarbon recovered from a petroleum reservoir (Dake Reference Dake1978). Like all flows through porous media, primary fluid recovery has been studied using Darcy’s law (Darcy Reference Darcy1856) for more than 80 years (Muskat Reference Muskat1937, Reference Muskat1949; Bear Reference Bear1972; Scheidegger Reference Scheidegger1974; Dake Reference Dake1978). As reviewed by Lasseux & Valdes Parada (Reference Lasseux and Valdes Parada2017), theoretical justification of Darcy’s law did not appear until more than 100 years after Darcy’s experiment, when it was shown that the macroscopic-scale Darcy’s law can be derived from the pore-scale Stokes flow equation by the method of volume averaging or homogenization (Whitaker Reference Whitaker1966, Reference Whitaker1986; Keller Reference Keller, Sternberg, Kalinowski and Papadakis1980; Auriault Reference Auriault1987). This direct connection to the fundamental equations of fluid dynamics provides a solid theoretical support for broad application of Darcy’s law to flows in porous media. While many of these derivations were based on the steady incompressible Stokes equation at the pore scale, notably Keller (Reference Keller, Sternberg, Kalinowski and Papadakis1980) and more recently Masmoudi (Reference Masmoudi2002) employed general compressible Navier–Stokes equations in their derivations. The leading-order problem from which Darcy’s law is derived, however, is still an incompressible flow problem.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig1g.gif?pub-status=live)
Figure 1. Schematic of primary fluid recovery from a porous reservoir. The outer boundary is impenetrable and the fluid is produced from the inner boundary (e.g. wellbore).
Primary fluid recovery from a porous medium is an inherently unsteady process occurring in a reservoir with a sealed outer boundary (figure 1). For a hydrocarbon reservoir, the outer boundary can be considered as impenetrable by fluids from the outside on the production time scale, which is of the order of several months to several years (but not on a geological time scale). Since no fresh fluid is injected into the reservoir, primary fluid recovery is driven by the volumetric expansion of the in situ fluid. Expansion of the porous rock occurs over a much larger time scale, since the rock’s bulk modulus is several orders of magnitude higher than that of the fluid; and rock expansion also requires a significant drawdown in the pore pressure, which can only occur in the very late stage of primary recovery when significant fluid depletion has already taken place. Thus, despite a very low fluid velocity, which would normally justify the incompressible flow approximation from the classical gas dynamics arguments based on a vanishing Mach number, the flow during primary fluid recovery is physically dominated by the fluid’s compressible effect. Recently, Chen & Shen (Reference Chen and Shen2018a ,Reference Chen and Shen b ) have studied fluid-expansion-driven drainage flow of a viscous compressible fluid from a semi-sealed small cylindrical capillary, which can be considered as a simple pore-scale model for primary recovery (figure 2). They solved the linearized compressible Navier–Stokes equations subject to the no-slip condition. Their results show that the fluid mass production rate from the capillary is proportional to the fluid’s kinematic viscosity; and the no-slip drainage flow exhibits a slip-like mass flow rate proportional to the square of the capillary radius. These pore-scale results differ fundamentally from those for a Poiseuille-type flow, which produces a mass flow rate inversely proportional to the fluid’s kinematic viscosity and proportional to the quartic of the pore radius. Thus, it is expected that, when these pore-scale results are upscaled, the corresponding macroscopic mass flow rate will not obey Darcy’s law, which is the upscaled version of the pore-scale Poiseuille’s law. This indicates that, at the macroscopic scale, primary fluid recovery is not governed by Darcy’s law.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig2g.gif?pub-status=live)
Figure 2. Primary recovery: a simple pore-scale model of draining a compressed fluid from a semi-sealed small capillary (from Chen & Shen Reference Chen and Shen2018a
). The exit density
$\unicode[STIX]{x1D70C}_{e}$
is lower than the initial density
$\unicode[STIX]{x1D70C}_{i}$
.
The present study on primary fluid recovery starts from the pore-scale compressible Navier–Stokes equations with no-slip condition and derives the corresponding macroscopic-scale governing equations. It assumes that the condition for slip at the pore scale (Lasseux et al.
Reference Lasseux, Valdes Parada, Ochoa Tapia and Goyeau2014; Lasseux, Valdes Parada & Porter Reference Lasseux, Valdes Parada and Porter2016) is not met and the no-slip condition applies. For simplicity and clarity, the present work is limited to a single-phase fluid; and the motion of a compressible fluid in the pore space is treated as a viscous compressible flow. Such a compressible flow is characterized by a small global Mach number, which is defined as the ratio between a reference fluid speed
$v_{ref}$
and a reference speed of sound
$c_{ref}$
,
$M=v_{ref}/c_{ref}\ll 1$
. An appropriate choice of the reference speed is the diffusion speed based on the longitudinal mass diffusion,
$D/L_{ref}$
, with
$D$
being the mass diffusion coefficient and
$L_{ref}$
the length of the medium. The flow is close to the incompressible limit of compressible flows, yet the compressible effect dominates the dynamics, as the flow in primary fluid recovery is solely driven by the volumetric expansion of the fluid. While it is widely known that the vanishing-Mach-number limit of the compressible Navier–Stokes equations converges to the incompressible Navier–Stokes equations, this limiting process is actually subtle, since the speed of sound tends to infinity and the governing equations change their type (Klainerman & Majda Reference Klainerman and Majda1981). This low-Mach-number limit has attracted significant attention since the pioneering work of Ebin (Reference Ebin1977, Reference Ebin1982) and Klainerman & Majda (Reference Klainerman and Majda1981, Reference Klainerman and Majda1982) (see e.g. Schochet Reference Schochet1987a
,Reference Schochet
b
, Reference Schochet2005; Klein Reference Klein1995; Lions & Masmoudi Reference Lions and Masmoudi1998; Desjardins & Grenier Reference Desjardins and Grenier1999; Desjardins & Lin Reference Desjardins and Lin1999; Desjardins et al.
Reference Desjardins, Grenier, Lions and Masmoudi1999; Masmoudi Reference Masmoudi, Málek, Nečas and Rokyta2000, Reference Masmoudi, Dafermos and Feireisl2007; Danchin Reference Danchin2001, Reference Danchin2002, Reference Danchin2005; Alazard Reference Alazard2006; Feireisl & Novotny Reference Feireisl and Novotny2009). We will first employ asymptotic expansions based on the work of Klainerman & Majda (Reference Klainerman and Majda1982) and the Helmholtz decomposition theorem to derive asymptotic equations for low-Mach-number viscous compressible flow at the pore scale for primary recovery. It will be shown that, for primary fluid recovery, the limiting incompressible field at a vanishing Mach number is identically zero and density is the primary variable of concern. The leading-order equations show that density change is controlled by the longitudinal mode of the acoustic field; while the role of the transverse mode (or solenoidal field) is to enforce the no-slip boundary condition on the pore wall. Density change obeys a damped wave equation; and at large times, this damped wave equation reduces to a diffusion equation with mass transport driven by the self-diffusion of the compressible fluid. The pore-scale density diffusion equation is then upscaled using the method of volume averaging (Whitaker Reference Whitaker1999) to obtain a macroscopic-level density diffusion equation. The new macroscopic-scale diffusion equation is compared to the classical macroscopic-scale equation based on Darcy’s law. It will be shown that there is a fundamental difference in the diffusion coefficients between the present and the classical results. The new macroscopic-level diffusion equation for the averaged density possesses a diffusion coefficient that is independent of the permeability but proportional to the fluid’s kinematic viscosity, instead of proportional to the permeability and inversely proportional to the kinematic viscosity for the classical diffusion coefficient based on Darcy’s law. The new diffusion coefficient can be several orders of magnitude larger than the classical diffusion coefficient. The analysis will show that Darcy’s law is not applicable to, and permeability plays no role in determining the production rate for, primary fluid recovery. A new macroscopic mass flux equation is derived and it can be used to replace Darcy’s law for primary fluid recovery.
2 Asymptotic expansion of the governing equations for low-Mach-number flow
Pore-scale flow of a compressible fluid is governed by the continuity and compressible Navier–Stokes equations (Anderson Reference Anderson1995)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn1.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn2.gif?pub-status=live)
where
$\boldsymbol{v},~p,~\unicode[STIX]{x1D70C}$
are the velocity, pressure and density, and
$\unicode[STIX]{x1D707},~\unicode[STIX]{x1D707}_{b}$
are the shear and bulk viscosity of the fluid, respectively. Temperature change is assumed to be negligible. We follow Klainerman & Majda (Reference Klainerman and Majda1982) in making the governing equations dimensionless. Let
$v_{ref}$
be the magnitude of a reference fluid particle velocity,
$L_{ref}$
a reference length, and a reference time is defined as
$t_{ref}=L_{ref}/v_{ref}$
. The reference pressure and density are
$p_{ref}$
and
$\unicode[STIX]{x1D70C}_{ref}$
, respectively. A reference speed of sound can be defined as
$c_{ref}=\sqrt{p_{ref}/\unicode[STIX]{x1D70C}_{ref}}$
(a constant factor is dropped for convenience; see Klainerman & Majda (Reference Klainerman and Majda1982)). We define dimensionless velocity, pressure, density, coordinates and time as
$\bar{\boldsymbol{v}}=\boldsymbol{v}/v_{ref},~\bar{p}=p/p_{ref},~\bar{\unicode[STIX]{x1D70C}}=\unicode[STIX]{x1D70C}/\unicode[STIX]{x1D70C}_{ref},~\bar{\boldsymbol{x}}=\boldsymbol{x}/L_{ref}$
and
$\bar{t}=t/t_{ref}$
. A global Mach number is defined as
$M=v_{ref}/c_{ref}$
, and it will be assumed small. A Reynolds number is defined as
$Re=\unicode[STIX]{x1D70C}_{ref}v_{ref}L_{ref}/\unicode[STIX]{x1D707}$
. The dimensionless equations are
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn3.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn4.gif?pub-status=live)
Using these equations and for inviscid isentropic flow, Klainerman & Majda (Reference Klainerman and Majda1982) have rigorously proved that, for given initial data, the linearized acoustics is a uniformly valid principal correction in the deviation of the compressible flow solution from the incompressible solution as the global Mach number
$M\rightarrow 0$
, i.e.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn5.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn6.gif?pub-status=live)
where
$|~|$
stands for the magnitude, and superscripts ‘
$I$
’ and ‘
$A$
’ stand for incompressible and acoustic quantities, respectively;
$\bar{\boldsymbol{v}}^{I}=\lim _{M\rightarrow 0}\bar{\boldsymbol{v}}$
with
$\bar{\unicode[STIX]{x1D735}}\boldsymbol{\cdot }\bar{\boldsymbol{v}}^{I}=0$
is the incompressible solution at vanishing Mach number;
$\unicode[STIX]{x1D6E5}_{5}>0,~\unicode[STIX]{x1D6E5}_{6}>0$
are fixed constants, and
$\bar{p}_{0}$
is a background thermodynamic pressure. This asymptotic result has been extended by Klein (Reference Klein1995) to non-isentropic flows and by Munz et al. (Reference Munz, Roller, Klein and Geratz2003) and Munz, Dumbser & Rolle (Reference Munz, Dumbser and Rolle2007) to the general heat-conducting viscous compressible Navier–Stokes equations. These asymptotic results have been used to construct efficient numerical schemes such as the multiple-pressure-variable method to overcome slow convergence, even failure, of fully compressible solvers for small-Mach-number flows (Klein Reference Klein1995; Klein & Munz Reference Klein and Munz1995; Bijl & Wesseling Reference Bijl and Wesseling1998; Bailly, Bogey & Juve Reference Bailly, Bogey and Juve1999; Wesseling Reference Wesseling2001; Munz et al.
Reference Munz, Roller, Klein and Geratz2003, Reference Munz, Dumbser and Rolle2007).
The above asymptotic theory allows us to decompose a low-Mach-number flow into the sum of two fields, the limiting incompressible field
$\bar{\boldsymbol{v}}^{I}$
and a linearized acoustic field
$\bar{\boldsymbol{v}}^{A}$
,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn7.gif?pub-status=live)
For primary recovery, the outer boundary of the reservoir is non-penetrable. Thus, except for isolated dead pores, all pores in the reservoir are half-sealed, with the sealed ends located on the outer boundary or in the interior of the reservoir, and the open ends located at the wellbore where the fluid is being produced. Therefore, an incompressible velocity field does not contribute to the mass flow rate at the wellbore, since integration of the incompressibility condition over the connected pore space gives the corresponding volumetric flow rate at the wellbore as zero:
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn8.gif?pub-status=live)
where
$\boldsymbol{n}$
is the unit outward normal vector on the corresponding boundaries. Since the flow in half-sealed pores relies entirely on the volumetric expansion or compressibility of the fluid, the limiting incompressible velocity
$\bar{\boldsymbol{v}}^{I}=\lim _{M\rightarrow 0}\bar{\boldsymbol{v}}$
must be identically zero in primary recovery,
$\bar{\boldsymbol{v}}^{I}=0$
. For
$\bar{\boldsymbol{v}}^{I}$
to be non-zero, the pores must have two open ends. Physically, an incompressible fluid cannot expand in volume; and in half-sealed pores, there is no fresh fluid to take the place of the volume in the pore space that would have been vacated by the produced fluid. In other words, to leading order, flow in primary recovery is completely characterized by the acoustic field
$\bar{\boldsymbol{v}}^{A}$
(since
$\bar{\boldsymbol{v}}^{I}=0$
), which is coupled to the density change of the fluid. Primary recovery is determined by how a fluid expands in volume in semi-sealed pores, not by how it is pushed out of the pores such as in a tube with open ends.
The acoustic velocity field
$\bar{\boldsymbol{v}}^{A}$
can be further decomposed into the sum of an irrotational part
$\bar{\boldsymbol{v}}_{IR}$
and a rotational part
$\bar{\boldsymbol{v}}_{RT}$
using the Helmholtz decomposition theorem (Aris Reference Aris1989; Leal Reference Leal2010; Panton Reference Panton2013),
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn9.gif?pub-status=live)
where the irrotational part is a potential flow and the rotational part is solenoidal (divergence-free):
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn10.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn11.gif?pub-status=live)
In the above,
$\unicode[STIX]{x1D6F7}$
is the scalar velocity potential for the irrotational part of the velocity. Thus, for primary recovery,
$\bar{\boldsymbol{v}}^{I}=0$
, and the asymptotic results (2.5) and (2.6) suggest the following small-Mach-number expansions for the velocity and pressure:
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn12.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn13.gif?pub-status=live)
where
$\bar{\boldsymbol{v}}_{RT}=M\,\tilde{\boldsymbol{v}}_{RT}$
and
$\bar{\boldsymbol{v}}_{IR}=M\,\tilde{\boldsymbol{v}}_{IR}$
. The pressure
$\bar{p}_{1}=M^{2}\,\tilde{p}_{1}$
is the Lagrangian multiplier associated with the solenoidal field
$\bar{\boldsymbol{v}}_{RT}$
to ensure that the incompressibility condition for
$\bar{\boldsymbol{v}}_{RT}$
is satisfied. The pressure
$\bar{p}_{1}$
is thus a hydrodynamic pressure induced by the solenoidal field
$\bar{\boldsymbol{v}}_{RT}$
and it is not described by the equation of state. The necessity to include
$\tilde{p}_{1}$
in the pressure expansion has been discussed by Klein (Reference Klein1995) and Munz et al. (Reference Munz, Roller, Klein and Geratz2003, Reference Munz, Dumbser and Rolle2007). The estimates (2.5) and (2.6) guarantee the convergence of the series (2.12) and (2.13) in the limit
$M\rightarrow 0$
. Density can be similarly expanded as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn14.gif?pub-status=live)
Density change is only related to the acoustic pressure
$\bar{p}^{A}=M^{2}\tilde{p}^{A}$
via the equation of state
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn15.gif?pub-status=live)
When the expansions (2.12) and (2.13) are substituted into the governing equations, to leading order we obtain the following equations for the irrotational field:
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn16.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn17.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn18.gif?pub-status=live)
where the fast-time variable
$\tilde{t}=\bar{t}/M=t/t_{ref,AC}$
, with
$t_{ref,AC}=L_{ref}/c_{ref}$
being the acoustic time scale; and the acoustic Reynolds number
$Re_{AC}=\unicode[STIX]{x1D70C}_{ref}c_{ref}L_{ref}/\unicode[STIX]{x1D707}$
, which is related to the Reynolds number by
$Re=MRe_{AC}$
. The leading-order solenoidal field equations are
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn19.gif?pub-status=live)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn20.gif?pub-status=live)
In the acoustic literature, the irrotational field and the solenoidal field are called the longitudinal mode and the transverse mode, respectively (Morse & Ingard Reference Morse and Ingard1968; Pierce Reference Pierce1981).
It is noted that the solenoidal field is absent in the leading-order irrotational velocity equations (2.16)–(2.18). The irrotational velocity, however, should not be expected to satisfy the no-slip condition on a solid boundary. The solenoidal field
$\bar{\boldsymbol{v}}_{RT}$
is induced by the irrotational velocity
$\bar{\boldsymbol{v}}_{IR}$
at the boundary so that the no-slip condition for the overall velocity
$\bar{\boldsymbol{v}}^{A}=\bar{\boldsymbol{v}}_{RT}+\bar{\boldsymbol{v}}_{IR}$
on the pore wall is satisfied:
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn21.gif?pub-status=live)
For primary recovery, the solenoidal field
$\bar{\boldsymbol{v}}_{RT}$
does not generate a net flow rate (see (2.8)).
It is noted that mode decomposition of the linear acoustic field has been used for a long time and it was examined theoretically in detail by Lagerstrom, Cole & Trilling (Reference Lagerstrom, Cole and Trilling1949) and Wu (Reference Wu1956). However, there is one major difference between these earlier works and the one presented here: in the earlier studies, the pressure
$\tilde{p}_{1}$
in the solenoidal field momentum equation (2.20) has been set to zero identically,
$\tilde{p}_{1}=0$
(Lagerstrom et al.
Reference Lagerstrom, Cole and Trilling1949; Wu Reference Wu1956; Morse & Ingard Reference Morse and Ingard1968; Pierce Reference Pierce1981; Temkin Reference Temkin1981; Friend & Yeo Reference Friend and Yeo2011). However, without this induced pressure, which serves as a Lagrangian multiplier to enforce the incompressibility condition for the solenoidal field, the solenoidal equations (2.19) and (2.20) are, in general, overdetermined, as there would be four equations for three unknowns (the three velocity components). Thus, in the absence of
$\tilde{p}_{1}$
, except for a few special cases, the set of equations (2.19) and (2.20) is likely to give rise to solutions that are internally incompatible due to overconstraint. In fact, a key result of the asymptotic theory of Klainerman & Majda (Reference Klainerman and Majda1982) is the splitting of the pressure into the sum of a thermodynamic pressure, a hydrodynamic pressure and an acoustic pressure for small-Mach-number flows. The distinct multiple roles that pressure plays physically in the small-Mach-number limit of a compressible flow and the necessity to include
$\tilde{p}_{1}$
in the pressure expansion have been discussed in detail in Klein (Reference Klein1995), Klein & Munz (Reference Klein and Munz1995) and Munz et al. (Reference Munz, Roller, Klein and Geratz2003, Reference Munz, Dumbser and Rolle2007). These results form the basis for the multiple-pressure-variable numerical method for small-Mach-number flows (Klein Reference Klein1995; Klein & Munz Reference Klein and Munz1995; Bijl & Wesseling Reference Bijl and Wesseling1998; Bailly et al.
Reference Bailly, Bogey and Juve1999; Klein et al.
Reference Klein, Botta, Schneider, Munz, Roller, Meister, Hoffmann and Sonar2001; Wesseling Reference Wesseling2001; Munz et al.
Reference Munz, Roller, Klein and Geratz2003, Reference Munz, Dumbser and Rolle2007).
3 The damped wave equation for density and its asymptotic form at large times
For primary fluid recovery, integration of the continuity equation (2.1) in the entire interconnected pore space gives the mass flow rate at the wellbore as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn22.gif?pub-status=live)
where the property that the outer boundary is non-penetrable has been used. Thus, density change in the pore space determines the mass production rate at the wellbore. Density change appears only in the equations (2.16)–(2.18) for the irrotational field, which leads to a decoupled damped wave equation for the density:
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn23.gif?pub-status=live)
This equation is based on the fast acoustic time scale
$\tilde{t}$
. The dimensional form of the damped wave equation is
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn24.gif?pub-status=live)
where
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn25.gif?pub-status=live)
with
$\unicode[STIX]{x1D708}_{ref}=\unicode[STIX]{x1D707}/\unicode[STIX]{x1D70C}_{ref}$
being the kinematic viscosity. Here
$D_{\unicode[STIX]{x1D70C},0}$
is a damping coefficient, as the last term on the right-hand side of (3.3) represents viscous damping of the acoustic (density) waves;
$D_{\unicode[STIX]{x1D70C},0}$
is also the self-diffusion coefficient of the fluid, as the damping stems from the self-diffusion of the fluid mass due to a local density gradient. When the bulk viscosity is zero as in the Stokes hypothesis,
$D_{\unicode[STIX]{x1D70C},0}=4\unicode[STIX]{x1D708}_{ref}/3$
. This result is consistent with the kinetic theory of gases, which shows that the self-diffusivity of a gas is proportional to the momentum diffusion coefficient
$\unicode[STIX]{x1D708}$
(Hirschfelder, Curtiss & Bird Reference Hirschfelder, Curtiss and Bird1954). Damping presented by the last term on the right-hand side of (3.3) is also called sound absorption, as the acoustic waves are absorbed by the bulk of the fluid. In the absence of a source for continuous excitation, an acoustic wave is expected to be absorbed by the fluid as well as the boundaries and damped out over large times (here ‘large’ is relative to the acoustic time scale). The linear damped wave equation (3.3), called the Stokes equation by Rayleigh (Reference Rayleigh1945), is well known in the acoustic literature and it has appeared in many textbooks (e.g. Morse & Ingard Reference Morse and Ingard1968; Temkin Reference Temkin1981).
When the damped wave equation (3.2) is expressed in terms of the slow time variable
$\bar{t}=M\,\tilde{t}$
, which is suitable for large times, we have
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn26.gif?pub-status=live)
where the relation
$Re=MRe_{AC}$
has been used. Thus, when viewed on the large time scale, to leading order in Mach number,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn27.gif?pub-status=live)
This is the equation for
$\bar{t}\rightarrow \infty$
that corresponds to the final equilibrium state. At the next order, i.e. for finite
$\bar{t}$
, we have a diffusion equation,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn28.gif?pub-status=live)
Consider an initial value problem starting from the state of rest. Then, the initial condition
$\tilde{t}=0:~\unicode[STIX]{x2202}\tilde{\unicode[STIX]{x1D70C}}_{2}/\unicode[STIX]{x2202}\tilde{t}=0$
can be approximated as
$\bar{t}=0:~\unicode[STIX]{x2202}\tilde{\unicode[STIX]{x1D70C}}_{2}/\unicode[STIX]{x2202}\bar{t}=0$
for the diffusion equation (3.7) if the acoustic waves are damped rapidly when measured on the large time scale
$\bar{t}$
. Integration of the diffusion equation (3.7) yields the standard diffusion equation
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn29.gif?pub-status=live)
Thus, at large times, the density wave becomes purely diffusive, controlled by diffusion with a diffusive velocity scale
$v_{ref}=D_{\unicode[STIX]{x1D70C},0}/L_{ref}$
. The Reynolds number is then
$Re=\unicode[STIX]{x1D707}_{b}/\unicode[STIX]{x1D707}+4/3$
, and the dimensionless diffusion equation (3.8) becomes
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn30.gif?pub-status=live)
where
$\bar{t}=t/t_{ref}=D_{\unicode[STIX]{x1D70C},0}t/L_{ref}^{2}$
. Once the density is solved from the diffusion equation (3.9), the irrotational velocity can be obtained from the continuity equation (2.16) and the solenoidal field from solving (2.19) and (2.20).
It should be noted that, with an error of the order of
$O(M^{4})$
, equation (3.9) can be written as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn31.gif?pub-status=live)
In dimensional form,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn32.gif?pub-status=live)
where
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn33.gif?pub-status=live)
with
$\unicode[STIX]{x1D708}=\unicode[STIX]{x1D707}/\unicode[STIX]{x1D70C}$
being the variable kinematic viscosity, is a density-dependent diffusion coefficient. It can be easily shown from (3.11) and the continuity equation that the mass flux of the irrotational field
$\dot{\boldsymbol{m}}_{IR}=\unicode[STIX]{x1D70C}\boldsymbol{v}_{IR}$
for primary recovery is given by a Fick’s law type of relation,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn34.gif?pub-status=live)
Since the solenoidal field does not contribute to the mass flow rate in primary recovery, the irrotational mass flux
$\dot{\boldsymbol{m}}_{IR}$
is also the pore-scale mass flux
$\dot{\boldsymbol{m}}=\unicode[STIX]{x1D70C}\boldsymbol{v}$
for primary recovery, i.e.
$\dot{\boldsymbol{m}}=\dot{\boldsymbol{m}}_{IR}$
.
The above analysis shows that, at large times, density in the pore space diffuses according to the diffusion equation (3.11) with the diffusion coefficient given by (3.12). We emphasize that the diffusive time scale
$t_{ref}=L_{ref}^{2}/D_{\unicode[STIX]{x1D70C},0}$
is always much larger than the acoustic time scale
$t_{ref,AC}=L_{ref}/c_{ref}$
; and ‘large’ or ‘long’ time is measured relative to the acoustic time scale. The density diffusion equation (3.11) is derived from an asymptotic analysis of the compressible Navier–Stokes equations at low Mach numbers, and it is the fundamental pore-scale transport equation from which upscaling can be performed.
For a semi-sealed cylindrical pore with a radius
$R$
and length
$L$
, Chen & Shen (Reference Chen and Shen2018a
,Reference Chen and Shen
b
) obtained the complete solution for drainage flow using the linearized damped wave equation (3.3). A prominent feature of the pore-scale flow is that density relaxes quickly in the transverse direction after the start-up and density becomes uniform in the tube cross-section. The velocity field satisfies the no-slip condition and the fluid production rate at large times is given by
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn35.gif?pub-status=live)
where
$M_{L}=\unicode[STIX]{x03C0}R^{2}L(\unicode[STIX]{x1D70C}_{i}-\unicode[STIX]{x1D70C}_{e})$
is the amount of producible fluid for the given density drop; and
$\unicode[STIX]{x1D70C}_{i}$
and
$\unicode[STIX]{x1D70C}_{e}$
are the initial density and exit density, respectively. The same result can be obtained by solving the linearized density diffusion equation (3.9). Clearly, the fluid production rate exhibits a slip-like behaviour as it is proportional to
$R^{2}$
. The fluid production rate is proportional to the fluid’s kinematic viscosity instead of the reciprocal of the kinematic viscosity as provided by the classical Poiseuille’s law. These pore-scale results are indicative of the invalidity of the Poiseuille–Darcy framework for flow in primary recovery at the pore scale, and consequently at the macroscale.
4 Macroscopic equations for primary recovery
At the pore scale, density change is controlled by self-diffusion and it obeys the diffusion equation (3.11). Thus, to compute the fluid production rate for primary recovery using the macroscopic equation (A 4) given in appendix A, we only need to upscale the density diffusion equation (3.11) subject to the zero-mass-flux condition on the pore wall,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn36.gif?pub-status=live)
The spatial deviation of the density,
$\unicode[STIX]{x1D70C}-\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
, as defined in Whitaker (Reference Whitaker1986) with
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
being the intrinsic average of the density (appendix A), also satisfies the boundary condition (4.1).
The problem of upscaling a diffusion equation with a heterogeneous reaction in porous media has been studied in detail by Whitaker (Reference Whitaker1999) and more recently by Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015). Other works on upscaling of a diffusion equation using the same methodology include, but are not limited to, Wood & Whitaker (Reference Wood and Whitaker1997, Reference Wood and Whitaker1999), Valdes-Parada et al. (Reference Valdes-Parada, Porter, Narayanaswamy, Ford and Wood2009), Valdes-Parada & Aguilar-Madera (Reference Valdes-Parada and Aguilar-Madera2011), Valdes-Parada, Aguilar-Madera & Alvarez-Ramirez (Reference Valdes-Parada, Aguilar-Madera and Alvarez-Ramirez2011), Benitez-Olivares, Valdes-Parada & Saucedo-Castaneda (Reference Benitez-Olivares, Valdes-Parada and Saucedo-Castaneda2016), Santos-Sanchez, Valdes-Parada & Chirino (Reference Santos-Sanchez, Valdes-Parada and Chirino2016) and Valdes-Parada, Lasseux & Whitaker (Reference Valdes-Parada, Lasseux and Whitaker2017). In the absence of reaction, the microscopic-scale diffusion problem studied by Whitaker (Reference Whitaker1999) and Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015) is exactly the same as the diffusion equation (3.11) with the no-penetration condition on the fluid–solid surface (4.1). Thus, the upscaled density diffusion equation for the present problem is a special case of the upscaled diffusion equation of Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015, equation (41)), which takes the form
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn37.gif?pub-status=live)
where the diffusion coefficient is valued at the averaged density,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn38.gif?pub-status=live)
The upscaled equation (4.2) is derived under the condition that the closure problem for the spatial deviation of the density is local, periodic, quasi-steady and linear. Under this condition and in the absence of reaction, the local closure problem for the spatial deviation of the density (equations (18a–e) of Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015)), is homogeneous when subject to the no-penetration boundary condition and zero initial deviation. Thus, the spatial deviation of the density is identically zero. The specific time- and length-scale constraints corresponding to the above condition for simplifying the closure problem have been examined in detail by Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015), which become (note that the so-called Thiele modulus for the closure problem is zero in the absence of reaction)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn39.gif?pub-status=live)
In (4.4),
$\ell _{\unicode[STIX]{x1D6FE}}$
is the characteristic length for the fluid phase, which can be taken as the pore throat diameter;
$r_{0}$
is the characteristic size of the averaging volume;
$L$
is the characteristic length of the porous system, which can be taken as the size of the reservoir; and
$t^{\ast }$
is a characteristic time for the fluid production. The characteristic time for primary recovery is the diffusive time scale
$L^{2}/D_{\unicode[STIX]{x1D70C},0}$
; thus, the third condition in (4.4) coincides with the second condition. The diffusion coefficient (4.3) is valued at the mean density
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
of the averaging cell. This can be obtained by a Taylor-series expansion and neglecting the nonlinear terms under the local theory, as shown by Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015). In cases where the length-scale constraints prevent such a linearization, Lugo-Mendez et al. (Reference Lugo-Mendez, Valdes-Parada, Porter, Wood and Ochoa-Tapia2015) have also developed an iterative procedure for the nonlinear closure problem.
The new diffusion equation (4.2) for
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
can be compared to the classical diffusion equation (A 6) for
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
based on Darcy’s law listed in appendix A. The diffusion coefficient
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
for (4.2) differs significantly, both physically and magnitude-wise, from the classical diffusion coefficient
$D_{Darcy}$
in (A 6) given by (A 7),
$D_{Darcy}=\unicode[STIX]{x1D705}c_{T}^{2}\langle \unicode[STIX]{x1D70C}\rangle ^{f}/(\unicode[STIX]{x1D707}\unicode[STIX]{x1D719})$
, with
$\unicode[STIX]{x1D705},~\unicode[STIX]{x1D719},~c_{T}$
being the permeability and porosity of the porous medium and the isothermal speed of sound of the fluid, respectively. The diffusion coefficient
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
is directly related to the self-diffusion coefficient of the fluid,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn40.gif?pub-status=live)
When the bulk viscosity is zero,
$D_{11}=1.33\unicode[STIX]{x1D708}$
for a dilute gas (Hirschfelder et al.
Reference Hirschfelder, Curtiss and Bird1954). The appearance of the self-diffusion coefficient in the pore-scale fluid density diffusion equation (3.11) as well as the upscaled fluid density diffusion equation (4.2) for the intrinsic average density
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
is natural and expected, as the density diffusion equation describes the mass transport process in the diffusion-dominated flow regime. On the other hand,
$D_{Darcy}$
is inversely proportional to the self-diffusion coefficient
$D_{11}$
, since
$D_{Darcy}$
is inversely proportional to the kinematic viscosity
$\unicode[STIX]{x1D708}$
. Darcy’s law is only appropriate for incompressible flows and it is irrelevant to the self-diffusion process. Therefore, the classical diffusion coefficient
$D_{Darcy}$
cannot be the correct diffusion coefficient for the intrinsic average density
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
.
In addition, the magnitude of
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
can be several orders of magnitude higher than
$D_{Darcy}$
. If we evaluate the diffusivities
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
and
$D_{Darcy}$
for methane at typical shale conditions at temperature
$80\,^{\circ }\text{C}$
and pressure of 25 MPa (appendix B), we have
$D_{Darcy}=4.53\times 10^{-8}~\text{m}^{2}~\text{s}^{-1}$
when the porosity is
$\unicode[STIX]{x1D719}=0.1$
and the permeability is one nanodarcy (
$\unicode[STIX]{x1D705}\approx 10^{-21}~\text{m}^{2}$
); while
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}=4.82\times 10^{-5}~\text{m}^{2}~\text{s}^{-1}$
. Thus, for methane in shale,
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
is three orders of magnitude higher than
$D_{Darcy}$
. At a lower pressure, the difference between these two diffusion coefficients becomes even larger, since, as the pressure is decreased,
$D_{\langle \unicode[STIX]{x1D70C}\rangle ^{f}}$
increases while
$D_{Darcy}$
decreases.
To find the mass flux
$\boldsymbol{J}$
, which is the mass flow rate per unit porous medium area, the density diffusion equation (4.2) needs to be written in the form
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn41.gif?pub-status=live)
where
$m$
is fluid mass per unit porous medium volume, i.e. the superficial average density
$\langle \unicode[STIX]{x1D70C}\rangle$
, which is related to intrinsic averaged density
$\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
by
$\langle \unicode[STIX]{x1D70C}\rangle =\unicode[STIX]{x1D719}\langle \unicode[STIX]{x1D70C}\rangle ^{f}$
(appendix A). Thus,
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn42.gif?pub-status=live)
Equation (4.7) is the effective (i.e. homogenized) medium equation, which shows that, in the effective medium, mass (density) diffuses with a mass diffusion coefficient
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn43.gif?pub-status=live)
Clearly,
$D_{m}$
depends on the porosity, but not on the permeability. The mass flux
$\boldsymbol{J}$
is given by
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn44.gif?pub-status=live)
which is also independent of permeability. Permeability is a property introduced by Darcy’s law for incompressible flows and it plays no role in determining the mass flow rate in primary recovery. Thus, Darcy’s law should be replaced by the mass flux equation (4.9) for primary fluid recovery.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig3g.gif?pub-status=live)
Figure 3. Top: Microscale simulation for density in drainage flow (primary recovery) with 100 horizontally repeated identical unit cells. The solid circles (totalling 49 for
$\unicode[STIX]{x1D719}=0.5840$
) are randomly distributed in the unit cell. Bottom: Macroscale effective medium simulation for density distribution. Three porosities
$\unicode[STIX]{x1D719}=0.5840,~0.4630,~0.3202$
are considered.
5 Comparison of macroscale equation with pore-scale simulation
In this section, we solve the upscaled and the microscale density diffusion equations for drainage of a compressible fluid from a semi-sealed two-dimensional porous medium channel and compare the average density distributions (figure 3). The porous medium is made of 100 identical unit cells with a compressible fluid saturating the pore space with an initial density
$\unicode[STIX]{x1D70C}_{i}$
. The solids in a unit cell with a size of 0.02 m
$\times$
0.02 m are randomly distributed circles with various diameters between 0.0004 m and 0.0025 m obeying the normal size distribution (several such random generated patterns have been tested and they produce the same cell averaged densities). The left end of the channel is sealed while the right end is opened at
$t=0$
, with an exit density
$\unicode[STIX]{x1D70C}_{e}<\unicode[STIX]{x1D70C}_{i}$
. We solve the microscale density diffusion equation (3.11) in the pore space, together with the no-penetration condition (4.1) imposed on the solid surfaces, including the channel walls. We then compute the average density in each unit cell and compare the result to the corresponding macroscale density. The macroscale density is obtained by solving the effective medium density diffusion equation (4.7) subject to the no-penetration condition on the channel walls. Both calculations are carried out using COMSOL (COMSOL 2016). In these computations,
$\unicode[STIX]{x1D70C}_{i}=1~\text{kg}~\text{m}^{-3}$
,
$\unicode[STIX]{x1D70C}_{e}=0.9~\text{kg}~\text{m}^{-3}$
,
$\unicode[STIX]{x1D707}=10^{-3}~\text{Pa}~\text{s}$
,
$r_{0}=0.02~\text{m}$
,
$L=2~\text{m}$
and three porosities
$\unicode[STIX]{x1D719}=0.5840,0.4630,0.3202$
have been used. A large viscosity value is chosen in order to shorten the computational time required for draining out the fluid from the channel. Convergence tests have been conducted by mesh refinements.
Figure 4 shows the local density distributions for each system for the case
$\unicode[STIX]{x1D719}=0.5840$
in three segments of the channel at time
$t=1000$
s, for cells 6–15, cells 46–55 and cells 85–94. It is observed that the microscale density distribution in each unit cell is fairly uniform despite the presence of the solid fractions, and there is little difference between the microscale and macroscale densities in these three segments. Figure 5 shows a specific comparison of the cell-averaged dimensionless density
$\unicode[STIX]{x1D70C}_{avg}/\unicode[STIX]{x1D70C}_{i}$
for these two systems for cells 10, 50 and 90 (marked as A, B and C, respectively). For the microscale model, the average density
$\unicode[STIX]{x1D70C}_{avg,mic}$
is the intrinsically averaged density in the unit cell; while for the macroscale model,
$\unicode[STIX]{x1D70C}_{avg,mac}$
is averaged over the entire unit cell area since the medium is homogenized. The relative error of the cell-averaged density between these two models, defined as
$|\unicode[STIX]{x1D70C}_{avg,mac}-\unicode[STIX]{x1D70C}_{avg,mic}|/\unicode[STIX]{x1D70C}_{avg,mic}$
, is plotted against time for each of these three cells in figure 6(a). The maximum relative errors for these three cells (A, B and C) are 0.6 %, 0.4 % and 0.1 %, respectively. Similarly, for
$\unicode[STIX]{x1D719}=0.4630$
, the maximum relative errors for these three cells are 0.65 %, 0.45 % and 0.15 %, respectively, as shown in figure 6(b). For
$\unicode[STIX]{x1D719}=0.3202$
, the maximum relative errors for these three cells are 1 %, 0.7 % and 0.3 %, respectively (figure 6
c). This range of relative error is acceptable for many practical applications. Together, these comparisons provide a numerical validation of the upscaled density equation.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig4g.gif?pub-status=live)
Figure 4. Computed local density distributions in the various cells indicated for the two systems, microscale (top) and macroscale (effective medium) (bottom) at time
$t=1000~\text{s}$
, for
$\unicode[STIX]{x1D719}=0.5840$
and
$\unicode[STIX]{x1D707}=10^{-3}~\text{Pa}~\text{s}$
. Initial density
$\unicode[STIX]{x1D70C}_{i}=1~\text{kg}~\text{m}^{-3}$
and exit density
$\unicode[STIX]{x1D70C}_{e}=0.9~\text{kg}~\text{m}^{-3}$
.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig5g.gif?pub-status=live)
Figure 5. Comparison of the dimensionless average density for the three cells (A, B and C) computed from the macroscale equation and the microscale equation, for
$\unicode[STIX]{x1D719}=0.5840$
.
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_fig6g.gif?pub-status=live)
Figure 6. Relative error
$|\unicode[STIX]{x1D70C}_{avg,mac}-\unicode[STIX]{x1D70C}_{avg,mic}|/\unicode[STIX]{x1D70C}_{avg,mic}$
versus time for the three representative cells: (a)
$\unicode[STIX]{x1D719}=0.5840$
, (b)
$\unicode[STIX]{x1D719}=\text{0.4630}$
and (c)
$\unicode[STIX]{x1D719}=\text{0.3202}$
.
6 Conclusions
The work reported in this study shows that the macroscopic equation for primary fluid recovery is fundamentally different from Darcy’s law. The key reason for this difference is that primary fluid recovery is entirely driven by the fluid’s volumetric expansion; as a result, the corresponding incompressible limit of the velocity is identically zero. Since Darcy’s law arises from the upscaling of this incompressible limit velocity, it then becomes irrelevant to primary recovery. Instead, Darcy’s law should be replaced by the mass flux equation (4.9) for such a process. In particular, the mass production rate depends on the porosity, but not on the permeability, of the porous medium. The implication of this result can be significant for hydrocarbon recovery and possibly for other applications.
Acknowledgements
We thank Professor M. Hermann for bringing the work of R. Klein to our attention and the reviewers for their helpful suggestions.
Appendix A. Classical macroscopic equations
Consider the motion of a single-phase compressible fluid in a fully saturated isotropic homogeneous and rigid porous medium. The superficial averages of the fluid density
$\unicode[STIX]{x1D70C}$
and velocity
$\boldsymbol{v}$
are defined in terms of the porous medium volume as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn45.gif?pub-status=live)
where
$V,~V_{f}$
are the local volumes of the porous medium and the fluid, respectively. The superficial averages are related to the intrinsic phase averages, denoted by superscript ‘
$f$
’ and defined in terms of the fluid volume, by the simple relations
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn46.gif?pub-status=live)
where
$\unicode[STIX]{x1D719}=V_{f}/V$
is the porosity or volume fraction of the fluid phase. The superficial average velocity
$\langle \boldsymbol{v}\rangle$
is also known as the specific discharge, which is the volumetric flow rate per unit area of the porous medium. The macroscopic-level continuity equation expressed for unit medium volume, which for a rigid porous medium,
$\unicode[STIX]{x1D719}=\text{const.}$
, can be written (Lasseux et al.
Reference Lasseux, Valdes Parada, Ochoa Tapia and Goyeau2014) as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn47.gif?pub-status=live)
In primary fluid recovery, the outer boundary of the reservoir is non-penetrable and the inner boundary, for example a wellbore, is where the fluid is produced (figure 1). Integrating the continuity equation (A 3) over the entire reservoir volume and applying the divergence theorem gives the mass flow rate (production rate) at the wellbore as
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn48.gif?pub-status=live)
where
$\boldsymbol{n}$
is the unit outward normal on the respective boundary. The integral on the right-hand side of (A 4) is the fluid mass in the reservoir, and (A 4) simply states that the rate of fluid produced at the wellbore is the time rate of decrease of the fluid mass in the reservoir. Equation (A 4) shows that density change is the most fundamental variable for primary fluid recovery. This result was well recognized a long time ago by Muskat (Reference Muskat1937) in his pioneering work on flow in porous media, as he formulated his macroscopic governing equations using density change instead of pressure change almost exclusively. In the classical approach, Darcy’s law (Darcy Reference Darcy1856; Bear Reference Bear1972; Whitaker Reference Whitaker1986)
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn49.gif?pub-status=live)
is used to derive the governing equation for the density change at the macroscopic level. In (A 5),
$\unicode[STIX]{x1D705}$
is the permeability and
$\unicode[STIX]{x1D707}$
is the fluid’s shear viscosity. Substituting (A 5) into (A 3) yields
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn50.gif?pub-status=live)
with the diffusion coefficient
![](https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20181221172459483-0019:S0022112018008741:S0022112018008741_eqn51.gif?pub-status=live)
where
$c_{T}^{2}=\unicode[STIX]{x2202}\langle p\rangle ^{f}/\unicode[STIX]{x2202}\langle \unicode[STIX]{x1D70C}\rangle ^{f}|_{T}$
is the square of the isothermal speed of sound in the fluid.
Appendix B. Methane properties
The following properties of methane at
$80\,^{\circ }\text{C}$
and 25 MPa, typical for shale formation, are taken from http://www.peacesoftware.de/einigewerte/methane.html:
$\unicode[STIX]{x1D707}=$
$1.99\times 10^{-5}~\text{Pa}~\text{s}$
,
$\unicode[STIX]{x1D707}_{b}=6.368\times 10^{-3}~\text{Pa}~\text{s}$
,
$\unicode[STIX]{x1D70C}=136.78~\text{kg}~\text{m}^{-3}$
,
$c=584~\text{m}~\text{s}^{-1}$
. In particular, the bulk viscosity for methane is estimated to be 320 times its shear viscosity at
$80\,^{\circ }\text{C}$
(Cramer Reference Cramer2012).