Changes

Matrix properties describe reservoir characteristics specified at each point of the grid (matrix) overlying the reservoir model (Figure 3). Once a grid has been selected, the average depth, thickness, porosity, and permeability are calculated for each grid block. Digitized structure and isopach maps may be used with mapping and gridding software to calculate average depths and thicknesses. Mapping software is used to convert the digitized contour maps to an interpolated grid of values. The mapping grid should be several times finer than the reservoir simulation grid since the values in the mapping grid falling within grid block boundaries are used to calculate the depths and thicknesses for each grid block. If the mapping grids are fine enough, a simple averaging of the values within each grid block will suffice to calculate their values corresponding to the grid block centers.

Matrix properties describe reservoir characteristics specified at each point of the grid (matrix) overlying the reservoir model (Figure 3). Once a grid has been selected, the average depth, thickness, porosity, and permeability are calculated for each grid block. Digitized structure and isopach maps may be used with mapping and gridding software to calculate average depths and thicknesses. Mapping software is used to convert the digitized contour maps to an interpolated grid of values. The mapping grid should be several times finer than the reservoir simulation grid since the values in the mapping grid falling within grid block boundaries are used to calculate the depths and thicknesses for each grid block. If the mapping grids are fine enough, a simple averaging of the values within each grid block will suffice to calculate their values corresponding to the grid block centers.

[[file:conducting-a-reservoir-simulation-study-an-overview_fig3.png|thumb|{{figure number|3}}Model grid overlain on Khursaniyah field, Saudi Arabia. (From <ref name=pt10r2>Boberg, T. C., 1974, Application of inverse simulation to a complex multireservoir system: Journal of Petroleum Technology, July, p. 801–808; Transactions, AIME, v. 257.</ref>; Copyright © 1974 Society of Petroleum Engineers.)]]

[[file:conducting-a-reservoir-simulation-study-an-overview_fig3.png|thumb|{{figure number|3}}Model grid overlain on Khursaniyah field, Saudi Arabia. (From <ref name=pt10r2>Boberg, T. C., 1974, Application of inverse simulation to a complex multireservoir system: Journal of Petroleum Technology, July, p. 801–808; Transactions, AIME, v. 257.</ref>; © 1974 Society of Petroleum Engineers.)]]

Porosities are calculated for each grid block in a method similar to that described for reservoir depths and thicknesses. First, the porosities calculated at 0.5- to 1-ft intervals from well logs must be averaged for each simulator layer. These layer porosities are then contoured and gridded. More advanced techniques for calculating three-dimensional porosity distributions (such as stochastic and geostatistical methods) are topics of current research, but they are beyond the scope of this chapter. The porosity values for each grid block are calculated by averaging the porosity grid values that lie within the boundaries of each grid block.

Porosities are calculated for each grid block in a method similar to that described for reservoir depths and thicknesses. First, the porosities calculated at 0.5- to 1-ft intervals from well logs must be averaged for each simulator layer. These layer porosities are then contoured and gridded. More advanced techniques for calculating three-dimensional porosity distributions (such as stochastic and geostatistical methods) are topics of current research, but they are beyond the scope of this chapter. The porosity values for each grid block are calculated by averaging the porosity grid values that lie within the boundaries of each grid block.