A Numerical Coning Model

1970 ◽  
Vol 10 (04) ◽  
pp. 418-424 ◽  
Author(s):  
J.P. Letkeman ◽  
R.L. Ridings

Abstract The numerical simulation of coning behavior bas been one of the most difficult applications of numerical analysis techniques. Coning simulations have generally exhibited severe saturation instabilities in the vicinity of the well unless time-step sizes were severely restricted. The instabilities were a result of using mobilities based on saturations existing at the beginning of the time step. The time-step size limitation, usually the order of a few minutes, resulted in an excessive amount of computer time required to simulate coning behavior. This paper presents a numerical coning model that exhibits stable saturation and production behavior during cone formation and after breakthrough. Time-step sizes a factor of 100 to 1,000 times as large as those previously possible may be used in the simulation. To ensure stability, both production rates and mobilities are extrapolated production rates and mobilities are extrapolated implicitly to the new time level. The finite-difference equations used in the model are presented together with the technique for incorporating the updated mobilities and rates. Example calculations which indicate the magnitude of the time-truncation errors are included. Various factors which affect coning behavior are discussed. Introduction The usual formulation of numerical simulation models for multiphase flow involves the evaluation of flow coefficient terms at the beginning of a time step and assumes that these terms do not change over the time step. These assumptions are valid only if the values of pressure and saturation in the system do not change significantly over the time step. The design of a finite-difference model to evaluate coning behavior of gas or water in a single well usually results in a model which uses radial coordinates. A two-dimensional single-well model is illustrated in Fig. 1. This type of model will often produce finite-difference blocks with pore volumes less than 1 bbl near the wellbore while producing large blocks with pore volumes greater producing large blocks with pore volumes greater than 1 million bbl near the external radius. If one chooses to use a reasonable time-step size of, say, 1 to 10 days, then normal well rates would result in a flow of several hundred pore volumes per time step through blocks near the wellbore. Therefore the assumption that saturations remain constant, for the purpose of coefficient evaluation, is not valid. Welge and Weber presented a paper on water coning which recognized the limitation of using explicit coefficients and applied an arbitrary limitation on the maximum saturation change over a time step. While this method is workable for a certain class of problems, it is not rigorous and is not generally applicable. In 1968, Coats proposed a method to solve the gas percolation problem which is similar in that it also results from explicit mobilities. This proposal involved adjusting the relative permeability to gas at the beginning of the time step so that an individual block would not be over-depleted of gas during a time step. This method is not conveniently extended to two dimensions nor to coning problems where a block is voided many times during a time step. Blair and Weinaug explored the problems resulting from explicitly determined coefficients and formulated a coning model with implicit mobilities and a solution technique utilizing Newtonian iteration. While this method is rigorous, achieving convergence on certain problems is difficult and, in many cases, time-step size is still severely restricted. In addition to the problems resulting from explicit flow-equation coefficients in coning models, the specification of rates requires attention to ensure that the saturations remain stable in the vicinity of the producing block. SPEJ P. 418

Author(s):  
Mahipal Jetta

The standard finite difference scheme (forward difference approximation for time derivative and central difference approximations for spatial derivatives) for fourth-order nonlinear diffusion filter allows very small time-step size to obtain stable results. The alternating directional implicit (ADI) splitting scheme such as Douglas method is highly stable but compromises accuracy for a relatively larger time-step size. In this paper, we develop [Formula: see text] stencils for the approximation of second-order spatial derivatives based on the finite pointset method. We then make use of these stencils for approximating the fourth-order partial differential equation. We show that the proposed scheme allows relatively bigger time-step size than the standard finite difference scheme, without compromising on the quality of the filtered image. Further, we demonstrate through numerical simulations that the proposed scheme is more efficient, in obtaining quality filtered image, than an ADI splitting scheme.


Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1290-1293 ◽  
Author(s):  
Ekkehart Tessmer

Numerical seismic modeling by finite‐difference methods usually works with a global time‐step size. Because of stability considerations, the time‐step size is determined essentially by the highest seismic velocity, i.e., the higher the highest velocity, the smaller the time step needs to be. Therefore, if large velocity contrasts exist within the numerical grid, domains of low velocity are oversampled temporally. Using different time‐step sizes in different parts of the numerical grid can reduce computational costs considerably.


Author(s):  
Yu Lu ◽  
Ankang Hu ◽  
Xin Chang

The main focus of this paper is on the uncertainty analysis methodology and procedure in CFD recommended by 22nd ITTC and the benchmark database for the verification and validation of the results of dredging dustpan’s inlet and outlet cross-section velocity ratio coefficient viur. Compared with the previous uncertainty analysis of CFD focused on the fluid grid-convergence in the steady flow, which is less to consider other factors that may affect the accuracy of the results of numerical simulation, this study compensates for this deficiency and implements the grid-convergence and time-step-size-convergence studies respectively by using three types of grids and time step sizes with refinement ratio under the condition of unsteady flow. Through confirming the validity of CFD uncertainty analysis, the agreement between the numerical simulation correction values from the grid-convergence and time-step-size-convergence and the benchmark test data is found to be quite satisfactory. The results obtained in this study have shown that it is indispensable to carry out the time-step-size-convergence studies for CFD uncertainty analysis during the unsteady flow calculation because the numerical simulation errors respectively caused by the grid and time-step-size in the convergence study have the same order of magnitude. In further the present study of simultaneously conducting both grid-convergence and time-step-size-convergence is demonstrated efficient and effective in the CFD uncertainty analysis.


2012 ◽  
Vol 442 ◽  
pp. 375-378 ◽  
Author(s):  
Wen Guang Zhang ◽  
Jun Wei Lei ◽  
Guo Qiang Liang

A modification to the synchronization law in [Zheng-Ming Ge, Pragmatical generalized synchronization of chaotic systems with uncertain parameters by adaptive control, Physica D (2007) 87-94] is proposed. To verify and demonstrate the effectiveness of the proposed method, a numerical simulation is done and the fourth-order Runge-Kutta method is used to solve the system with time step size 0.001.


1974 ◽  
Vol 14 (03) ◽  
pp. 216-220 ◽  
Author(s):  
J.E. Chappelear ◽  
W.L. Rogers

Introduction The semi-implicit reservoir simulator has become a very important part of the total simulation package necessary for the practicing reservoir engineer. Any multiphase simulation of a single well tom, problem (e.g., a study of water-oil coning) is very problem (e.g., a study of water-oil coning) is very expensive unless such a simulator is available. With a "standard" reservoir simulator, this difficulty arises because the relative permeabilities and capillary pressures, which depend upon saturations, lag one time step behind the pressure calculation. For this reason such a simulator is said to be implicit in pressure and explicit in saturation (abbreviated as IMPES). When "new" saturations are obtained, they are formed from "old" relative permeabilities and capillary pressures. The mathematical form of the equations is pressures. The mathematical form of the equations is such that an uncontrolled oscillation in the saturation values develops if the time step is too large. Only by taking smaller time steps can this oscillation be suppressed in an IMPES simulator, and very small time steps are then necessary for simulating coning behavior. The same problem can also appear in any production well model (in an IMPES simulator) that production well model (in an IMPES simulator) that distributes fluid production proportionally to phase mobilities. These saturation oscillations can be eliminated by making the well model "implicit in saturation." To overcome this instability, Blair and Weinaug developed a fully implicit simulator. All coefficients were updated iteratively until convergence occurred. It was necessary for them to stabilize their solution technique by the use of Newtonian iteration. Then it was found that a time-step limitation occurred because of nonlinearities, since the Newtonian iteration would not converge without a good initial estimate. Coats and MacDonald proposed an effective solution to this problem. They suggested estimating the relative permeabilities and capillary pressures by an extrapolation; e.g., pressures by an extrapolation; e.g.,(1) A mathematical investigation showed that since Sn + 1, the saturation at be new time step, is found simultaneously with the pressures as part of the solution, the mathematical time-step limitation inherent in the IMPES technique as a result of using "old" relative permeabilities would not occur. They also suggested that the equations be linearized by dropping products of (Sn+1 - Sn) and (pn+1 - pn). The equations are then more nearly linear. Hence, the difficulties in convergence of the solution technique are greatly reduced (Newtonian iteration is not needed). Nolen and Berry showed that linearization of the accumulation terms was not necessarily the best strategy (in problems that have solution gas), because material-balance errors would result. They felt that linearization of the flux terms made little difference. Many questions still remain unanswered by these papers. Nonlinearities remain in the equations, papers. Nonlinearities remain in the equations, particularly when a phase is near its immobile particularly when a phase is near its immobile saturation. Because of the use of upstream weighting of the relative permeabilities, another type of nonlinearity (potential reversal) can occur. Furthermore, the question of a practical procedure for selecting the time step must be settled. Finally, there are nonlinearities in the well model, which can cause slow convergence, or failure to converge, especially when dealing with a well completed in several layers or with a well that changes constraints. The problems just mentioned are all more severe if large time steps are used. Reducing time-step size is expensive, and in many cases difficult to automate. In this paper we present our experience in treating or circumventing these problems. We have felt that an important principle to follow is to eliminate time-step limitations due to mathematical instabilities. Thus, one should be able to run steady-state problems with essentially unlimited time-step size. For transient problems, it is expected that time truncation errors would normally govern the time-step size. One final, practical goal was to avoid running problems that would be annoying and mysterious to the field reservoir engineer. SPEJ P. 216


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
S. S. Ravindran

Micropolar fluid model consists of Navier-Stokes equations and microrotational velocity equations describing the dynamics of flows in which microstructure of fluid is important. In this paper, we propose and analyze a decoupled time-stepping algorithm for the evolutionary micropolar flow. The proposed method requires solving only one uncoupled Navier-Stokes and one microrotation subphysics problem per time step. We derive optimal order error estimates in suitable norms without assuming any stability condition or time step size restriction.


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