Rigorous Calculation of Miscible Displacement Using Immiscible Reservoir Simulators

1970 ◽  
Vol 10 (02) ◽  
pp. 192-202 ◽  
Author(s):  
R.B. Lantz

Abstract In the past miscible displacement calculations have been approximated with two-phase reservoir simulators. Such calculations have neglected diffusional mixing between miscible components. In fact, no analog bas been proposed for rigorously treating miscible simulations with two-phase programs. This paper describes requirements that programs. This paper describes requirements that permit such a rigorous simulation. permit such a rigorous simulation. The sets of partial differential equations describing each of the displacement processes are shown to be exactly analogous if relative permeability and capillary pressure functions are permeability and capillary pressure functions are adjusted in a special manner. Application of the "miscible" analogy in a two-phase simulator, however, has several limitations, the most severe of which is the truncation error (numerical diffusion) typical of an immiscible formulation. Since this error is time-step and/or block-size dependent, numerical smearing can, in principle, be made as small as necessary. But this feature limits the practical applicability of the "miscible" analogy practical applicability of the "miscible" analogy to cases with rather large physical diffusion. The range of applicability and other limitations are outlined in the paper. Also, illustrative sample calculations are presented for linear, radial and layer-cake systems. Component densities and viscosities are varied in the linear model. Introduction In recent years, use of two- and three-phase reservoir simulators to calculate the performance of immiscible fluid displacement has become widespread. Reservoir simulators capable of calculating miscible displacement problems, however, have been limited to special use programs. The primary reason for this limitation has been the significant truncation error (numerical diffusion) typical of ordinary finite difference approximations to the miscible equations. The method of characteristics provided a means of making miscible displacement calculations without significant truncation error. A recently proposed second calculation technique, based on variational methods, also reduces numerical diffusion. Both of these calculational techniques can be used for immiscible calculations. Still, general miscible displacement applications such as gas cycling, enriched-gas injection, or tracer injection have historically required use of immiscible reservoir simulators for performance predictions. Larson et al. have reported an example of such use of a two-phase computer program. Displacement involving two components flowing within a single phase would appear to be analogous to a two-phase displacement. Yet, past miscible calculations using immiscible simulators made the two-phase saturation profile as near piston-like as possible and neglected component mixing due to possible and neglected component mixing due to diffusional processes. The capillary pressure function was chosen to minimize capillary flow. Also, in these miscible approximations, no provision had been made for viscosity variations provision had been made for viscosity variations with component concentration. Though mixing due to diffusional processes had been neglected, countercurrent diffusion due to component concentration differences in a miscible process should be essentially analogous to countercurrent capillary flow due to saturation differences in a two-phase system. This paper describes a method by which two- and three-phase reservoir simulators can be made to calculate miscible displacement rigorously. The only requirement of the method is that relative permeability and capillary pressure be special permeability and capillary pressure be special functions of saturation. With these properly chosen functions, the set of partial differential equations describing immiscible displacement becomes completely analogous to the partial differential equations describing miscible displacement. SPEJ P. 192

1971 ◽  
Vol 11 (03) ◽  
pp. 315-320 ◽  
Author(s):  
R.B. Lantz

Abstract Numerical diffusion (truncation error) can limit the usefulness of numerical finite-difference approximations to solve partial differential equations. Many reservoir simulation users are aware of these limitations but are not as familiar with actually quantifying the magnitude of the truncation error. This paper illustrates that, over a wide range of block size and time step, the truncation error expressions for convective-diffusion partial differential equations are quantitative. Since miscible, thermal, and immiscible processes can be of the convective-diffusion equation form, the truncation error expressions presented can provide guidelines for choosing block size-time step combinations that minimize the effect of numerical diffusion. Introduction Truncation error limits the use of numerical finite-difference approximations to solve partial differential equations. In the solution of convection-diffusion equations, such as occur in miscible displacement and thermal transport, truncation error results in an artificial dispersion term often denoted as numerical diffusion. The differential equations describing two-phase fluid flow can also be rearranged into a convection-diffusion form. And, in fact, miscible and immiscible differential equations have been shown to be completely analogous. In this form, it is easy to infer that numerical diffusion will result in an additional term resembling flow due to capillarity. Many users of numerical programs, and probably all numerical analysts, recognize that the magnitude of the numerical diffusivity for convection-diffusion equations can depend on both block size and time step. Most expressions developed in the literature have been used primarily to determine the order of the error rather than to quantify it. The primary purpose of this paper is to give the user more than just a qualitative feel for the importance of truncation error. In this paper, insofar as possible, analytical expressions for truncation error are compared by experiment to computed values for the numerical diffusivity. Consequently, the reservoir simulator user can observe that these expressions are quantitative and can use them as guidelines for choosing block sizes and time steps that keep the numerical diffusivity small. DEVELOPMENT OF EXPRESSIONS FOR TRUNCATION ERROR APPLICATION TO CONVECTION-DIFFUSION EQUATION To illustrate the method of quantifying numerical diffusivity, consider a convective-diffusion equation of the form: ..............(1) Symbols are defined in the Nomenclature. The first term on the right-hand side represents the diffusion, and the second term represents convection. Such an equation describes the flow of either a two-component miscible mixture or heat in one dimension with constant diffusivity. EXPLICIT DIFFERENCE FORMS An explicit expression for the truncation error (the space derivatives are approximated at a known time level) can be developed by examining the Taylor's series expansion representing first- and second-order derivatives. For the time derivative: .....(2) SPEJ P. 315


1969 ◽  
Vol 9 (02) ◽  
pp. 255-269 ◽  
Author(s):  
M. Sheffield

Abstract This paper presents a technique for predicting the flow, of oil, gas and water through a petroleum reservoir. Gravitational, viscous and capillary forces are considered, and all fluids are considered to be slightly compressible. Some theoretical work concerning the fluid flow in one-, two- and three-space dimensions is given along with example performance predictions in one- and two-space dimensions. predictions in one- and two-space dimensions Introduction Since the introduction of high speed computing equipment one of the goals of reservoir engineering research has been to develop more accurate methods of describing fluid movement through underground reservoirs. Various mathematical methods have been developed or used by reservoir engineers to predict reservoir performance. The work reported in this paper extends previously published work on three-phase fluid flow (1) by including a rigorous treatment of capillary forces and (2) by showing certain theoretical mathematical results proving that these equations can be approximated by certain numerical techniques and that a unique solution exists. Discussion The method of predicting three-phase compressible fluid flow in a reservoir can be summarized briefly by the following steps. 1.The reservoir, or a section of a reservoir, is characterized by a series of mesh points with varying rock and fluid properties simulated at each mesh point. point. 2.Three partial differential equations are written to describe the movement at any point in the reservoir of each of the three compressible fluids. All forces influencing movement are considered in the equations. 3. At each mesh point, the partial differential equations are replaced by a system of analogous difference equations. 4. A numerical technique is used to solve the resulting system of difference equations. Capillary forces have been included in two-phase flow calculations. The literature, however, does not contain examples of prediction techniques for three-phase flow that include capillary forces. Where capillary Races are considered, each of the three partial differential equations previously discussed has a different dependent variable, namely pressure in one of the three fluid phases. Therefore, pressure in one of the three fluid phases. Therefore, three difference equations must be solved at each point in the reservoir. Where large systems of point in the reservoir. Where large systems of equations must be solved simultaneously, an engineer might question whether a unique solution to this system of equations actually exists and, if so, what numerical techniques may be used to obtain a good approximation to the solution. It is shown in the Appendix that a unique solution to the three-phase flow problem, as formulated, always exists. It is also shown that several methods may be used to obtain a good approximation to the solution. The partial differential equations and difference equations partial differential equations and difference equations used are shown in the Appendix. Matrix notation has been used in developing the mathematical results. Two sample problems were solved on a CDC 1604. They illustrate the type of problems that can be solved using a three-phase prediction technique. SAMPLE ONE-DIMENSIONAL RESERVOIR PERFORMANCE PREDICTION A hypothetical reservoir was studied to provide an example of a one-dimensional problem that can be solved. Of the several techniques available, the direct method A solution as shown in the Appendix was used. The reservoir section studied was a truncated, wedge-shaped section, 2,400 ft long, with a 6' dip. (A schematic is shown in Fig. 1.) This section was represented by 49 mesh points, uniformly spaced at 50-ft intervals. The upper end of the wedge was 2 ft wide, and the lower end was 6 ft wide. SPEJ P. 255


Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1480
Author(s):  
Tao Liu ◽  
Runqi Xue ◽  
Chao Liu ◽  
Yunfei Qi

The main difficulty posed by the parameter inversion of partial differential equations lies in the presence of numerous local minima in the cost function. Inversion fails to converge to the global minimum point unless the initial estimate is close to the exact solution. Constraints can improve the convergence of the method, but ordinary iterative methods will still become trapped in local minima if the initial guess is far away from the exact solution. In order to overcome this drawback fully, this paper designs a homotopy strategy that makes natural use of constraints. Furthermore, due to the ill-posedness of inverse problem, the standard Tikhonov regularization is incorporated. The efficiency of the method is illustrated by solving the coefficient inversion of the saturation equation in the two-phase porous media.


2011 ◽  
Vol 10 (3) ◽  
pp. 509-576 ◽  
Author(s):  
M. J. Baines ◽  
M. E. Hubbard ◽  
P. K. Jimack

AbstractThis article describes a number of velocity-based moving mesh numerical methods for multidimensional nonlinear time-dependent partial differential equations (PDEs). It consists of a short historical review followed by a detailed description of a recently developed multidimensional moving mesh finite element method based on conservation. Finite element algorithms are derived for both mass-conserving and non mass-conserving problems, and results shown for a number of multidimensional nonlinear test problems, including the second order porous medium equation and the fourth order thin film equation as well as a two-phase problem. Further applications and extensions are referenced.


1984 ◽  
Vol 24 (04) ◽  
pp. 391-398 ◽  
Author(s):  
B.L. Darlow ◽  
R.E. Ewing ◽  
M.F. Wheeler

Abstract Effective numerical simulation of many EOR problems requires very accurate approximation of the Darcy velocities of the respective fluids. In this paper we describe a new method for the accurate determination of the Darcy velocity of the total fluid in the miscible displacement of one incompressible fluid by another in a porous medium. The new mixed finite-element porous medium. The new mixed finite-element procedure solves for both the pressure and velocity of the procedure solves for both the pressure and velocity of the total fluid simultaneously as a system of first-order partial differential equations. By solving for u = (-k/mu) delta p partial differential equations. By solving for u = (-k/mu) delta p as one term, we minimize the difficulties occurring in standard methods caused by differentiation or differencing of p and multiplication by rough coefficients k/mu. By using mixed finite elements for the pressure equation coupled in a sequential method with a finite element procedure for the concentration of the invading fluid, we procedure for the concentration of the invading fluid, we are able to treat a variety of problems with variable permeabilities, different mobility ratios, and a fairly permeabilities, different mobility ratios, and a fairly general location of injection and production wells. Mixed finite-element methods also produce minimal grid-orientation effect. Computational results on a variety of two-dimensional (2D) problems are presented. Introduction This paper considers the miscible displacement of one incompressible fluid by another in a horizontal reservoir Omega R2 over a time period J=[0, T]. If p is the pressure of the total fluid with viscosity mu in a medium with permeability k, we define the Darcy velocity of the total permeability k, we define the Darcy velocity of the total fluid by (1) Then, letting c denote the concentration of the invading fluid and phi denote the porosity of the medium, the coupled quasilinear system of partial differential equations describing the fluid flow is given by (2)(3) Hen q=q(x, t) represents the total flow into or out of the region omega (q greater than 0 at injection wells and q less than 0 at production wells in this setting), c=c(x, t) is equal to the value of c production wells in this setting), c=c(x, t) is equal to the value of c at a producing well and the specified inlet concentration at an injection well, and D=D(x, u) is the diffusion-dispersion tensor given by (4) where dm, a small molecular diffusion coefficient, and dc and dt, the magnitudes of longitudinal and transverse dispersion, are given constants. Here absolute value of mu is the standard Euclidean norm of the vector mu. To complete the description of the flow we augment the system (Eqs. 2 and 3) with a prescription of an initial concentration distribution of the invading fluid and no-flow conditions across the boundary, delta omega, given by (5)(6)(7) where vi are components of the outward normal vector to delta omega. Incompressibility requires that (8) SPEJ P. 391


SIMULATION ◽  
1964 ◽  
Vol 3 (5) ◽  
pp. 45-52 ◽  
Author(s):  
Michael E. Fisher

The solution of partial differential equations by a differential analyser is considered with regard to the effects of noise, computational instability and the deviation of components from their ideal values. It is shown that the 'serial' method of solving parabolic, hyperbolic and elliptic equations leads to serious in stability which increases as the finite difference interval is reduced. The truncation error (due to the difference approximations) decreases as the interval is made smaller and consequently an 'optimal' ac curacy is reached when the unstable noise errors match the truncation errors. Evaluation shows that the attainable accuracy is severely limited, especially for hyperbolic and elliptic equations. The 'parallel' method is stable when applied to parabolic and hyperbolic (but not elliptic) equations and the attainable accuracy is then limited by the accumulation of component tolerances. Quantitative investigation shows how reasonably high accuracy can be achieved with a minimum of precise adjustments.


2020 ◽  
Vol 206 ◽  
pp. 03031
Author(s):  
Liu Bin ◽  
Wang Bo ◽  
Li Zhuo ◽  
Lv Yanfang

The migration of CO2 is stochastic in heterogeneous porous media. This paper considers the CO2 diffusion with the case of steady flow in heterogeneous porous media. The partial differential equations of CO2 diffusion in random velocity field are established based on the mass conservation equations of CO2- brine two-phase flow with the change of time scale and spatial scale under the influence of heterogeneity such as permeability and porosity. The random travel process of CO2 is quantified by joint probability distributions and joint statistical moments (mean and variance), and the diffusion model of CO2 particle in random velocity field is established under the condition of non-linear and immiscibility in heterogeneous porous media. The micro mechanism of diffusion in heterogeneous porous media is revealed by numerical simulation. The general conclusion of steady state flow of CO2 diffusion in heterogeneous porous media was verified by simulating Sleipner CO2-brine storage in Norway.


Author(s):  
Umar Saidu Bashir ◽  

This paper explores the use of the software package, Matlab and Excel in the implementation of the finite difference method to solve partial differential equations (PDE’s.). It aimed to examine the strength of the forward explicit method and backward implicit method in solving PDE’s. A comparison was made between the forward explicit method and the backward implicit method for their stability. The FDM method was used to solve partial differential equations of heat. Numerical examples were also created and analysed to show the strengths of each method. The results shows that the forward explicit method is conditionally stable because the stability it requires a small step size of time ‘t’ compared to space ‘x’ for stability. The backward implicit method is unconditionally stable because it depends on the local truncation error considerations.


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