Changes

==Model specification==

==Model specification==

A simulation study begins by choosing a model type from among those shown in Figure 1. A grid, which determines the resolution at which the complex reservoir flow equations are solved, is then selected. The model's size is defined by the number of grid blocks resulting from the grid overlain on the field or field segment being studied. In general, the accuracy of results from simulation studies is greater for smaller grid block sizes. Smaller grid block sizes permit more detailed descriptions of reservoir heterogeneity and more accurate resolution of fluid fronts and phase behavior. An optimum grid size is often determined by running test cases at several different grid sizes. The largest grid size at which no appreciable change in the results occurs is selected for the study.

[[file:conducting-a-reservoir-simulation-study-an-overview_fig1.png|left|thumb|{{figure number|1}}Typical models used in reservoir simulation. (a) Zero-dimensional tank. (b) One-dimensional linear. (c) One-dimensional radial. (d) Two-dimensional cross-sectional. (e) Two-dimensional area. (f) Two-dimensional radial. (g) Three-dimensional. (From <ref name=pt10r22>Mattax, C. C., Dalton, R. L., 1990, Reservoir simulation: Richardson, TX, Society of Petroleum Engineers.</ref>; © 1990 Society of Petroleum Engineers.)]]

[[file:conducting-a-reservoir-simulation-study-an-overview_fig1.png|thumb|{{figure number|1}}Typical models used in reservoir simulation. (a) Zero-dimensional tank. (b) One-dimensional linear. (c) One-dimensional radial. (d) Two-dimensional cross-sectional. (e) Two-dimensional area. (f) Two-dimensional radial. (g) Three-dimensional. (From <ref name=pt10r22>Mattax, C. C., Dalton, R. L., 1990, Reservoir simulation: Richardson, TX, Society of Petroleum Engineers.</ref>; © 1990 Society of Petroleum Engineers.)]]

A simulation study begins by choosing a model type from among those shown in [[:file:conducting-a-reservoir-simulation-study-an-overview_fig1.png|Figure 1]]. A grid, which determines the resolution at which the complex reservoir flow equations are solved, is then selected. The model's size is defined by the number of grid blocks resulting from the grid overlain on the field or field segment being studied. In general, the accuracy of results from simulation studies is greater for smaller grid block sizes. Smaller grid block sizes permit more detailed descriptions of reservoir heterogeneity and more accurate resolution of fluid fronts and phase behavior. An optimum grid size is often determined by running test cases at several different grid sizes. The largest grid size at which no appreciable change in the results occurs is selected for the study.

Practical limits on the size of reservoir simulation models are often imposed by computational expense or capabilities. These constraints may dictate that the size of the reservoir segment being simulated must be reduced or the grid block size increased. Simulating small characteristic segments of a field using a fine grid may be preferable to simulating larger segments using a coarse grid. Small models can provide insight into the mechanics of production performance (such as viscous flow, gravity, or heterogeneity). For example, a fluid injection project can be studied using detailed areal and vertical models rather than a coarse grid three-dimensional model. Extrapolating results from these mechanistic models to field performance can be accomplished using their results to modify general recovery characteristics defined by coarse grid models.

Practical limits on the size of reservoir simulation models are often imposed by computational expense or capabilities. These constraints may dictate that the size of the reservoir segment being simulated must be reduced or the grid block size increased. Simulating small characteristic segments of a field using a fine grid may be preferable to simulating larger segments using a coarse grid. Small models can provide insight into the mechanics of production performance (such as viscous flow, gravity, or heterogeneity). For example, a fluid injection project can be studied using detailed areal and vertical models rather than a coarse grid three-dimensional model. Extrapolating results from these mechanistic models to field performance can be accomplished using their results to modify general recovery characteristics defined by coarse grid models.