Changes

[[file:geological-heterogeneities_fig4.png|thumb|{{figure number|4}}Synthetic reservoir cross section showing the vertical and lateral distribution of shales (black) within a sandstone (white) sequence. (Modified from <ref name=pt06r44 />.)]]

[[file:geological-heterogeneities_fig4.png|thumb|{{figure number|4}}Synthetic reservoir cross section showing the vertical and lateral distribution of shales (black) within a sandstone (white) sequence. (Modified from <ref name=pt06r44 />.)]]

In the absence of sufficient quantitative information on different depositional systems, [[Introduction to geological methods#Statistics|statistical methods]] of predicting interwell variability have proven useful. For example, the literature contains many examples of statistics applied to analysis of the lateral continuity and spatial distribution of [[shales]], since fluid flow in a reservoir is particularly sensitive to shale distribution. One commonly cited example<ref name=pt06r152>Weber, K. J., 1982, Influence of common sedimentary structures on [[fluid flow]] in reservoir models: Journal of Petroleum Technology, March, p. 665–772.</ref> predicts the anticipated lengths of shales as a function of depositional environments, so that if the depositional environment of a reservoir sequence is known, measurements of shale thicknesses in wells can be used to generate (using a [[random number generator]]) a synthetic reservoir cross section ([[:file:geological-heterogeneities_fig4.png|Figure 4]]). This approach is particularly fruitful when the lateral dimensions of the shale are thought to be less than well spacings (uncorrelatable or ''stochastic'' shales, as opposed to correctable or ''deterministic'' shales whose lateral dimensions are greater than well spacings.<ref name=pt06r44>Haldorsen, H. H., Lake, L. W., 1984, A new approach to shale management in field-scale models: Society of Petroleum Engineers Journal, Aug., p. 447–452.</ref> Statistical methods have also been used to evaluate lateral variations in reservoir properties of sandstones. For example, Stalkup<ref name=pt06r134>Stalkup, F. I., 1986, [[Permeability]] variations observed at the faces of crossbedded sandstone outcrops, in Lake, L. W., Carroll, H. B., Jr., eds., Reservoir Characterization: Orlando, FL, Academy Press, p. 141–180.</ref> found considerable lateral variability in outcrop measurements of permeability of shallow marine and fluvial sandstones and suggested that [[permeability]] distribution should also be described stochastically rather than deterministically.

In the absence of sufficient quantitative information on different depositional systems, [[Introduction to geological methods#Statistics|statistical methods]] of predicting interwell variability have proven useful. For example, the literature contains many examples of statistics applied to analysis of the lateral continuity and spatial distribution of [[shales]], since [[fluid flow]] in a reservoir is particularly sensitive to shale distribution. One commonly cited example<ref name=pt06r152>Weber, K. J., 1982, Influence of common sedimentary structures on [[fluid flow]] in reservoir models: Journal of Petroleum Technology, March, p. 665–772.</ref> predicts the anticipated lengths of shales as a function of depositional environments, so that if the depositional environment of a reservoir sequence is known, measurements of shale thicknesses in wells can be used to generate (using a [[random number generator]]) a synthetic reservoir cross section ([[:file:geological-heterogeneities_fig4.png|Figure 4]]). This approach is particularly fruitful when the lateral dimensions of the shale are thought to be less than well spacings (uncorrelatable or ''stochastic'' shales, as opposed to correctable or ''deterministic'' shales whose lateral dimensions are greater than well spacings.<ref name=pt06r44>Haldorsen, H. H., Lake, L. W., 1984, A new approach to shale management in field-scale models: Society of Petroleum Engineers Journal, Aug., p. 447–452.</ref> Statistical methods have also been used to evaluate lateral variations in reservoir properties of sandstones. For example, Stalkup<ref name=pt06r134>Stalkup, F. I., 1986, [[Permeability]] variations observed at the faces of crossbedded sandstone outcrops, in Lake, L. W., Carroll, H. B., Jr., eds., Reservoir Characterization: Orlando, FL, Academy Press, p. 141–180.</ref> found considerable lateral variability in outcrop measurements of permeability of shallow marine and fluvial sandstones and suggested that [[permeability]] distribution should also be described stochastically rather than deterministically.

Standard seismic reflection methods generally cannot resolve reservoir heterogeneities at the interwell scale. [[Cross-borehole tomography in development geology|Crosshole seismic tomography]]<ref name=pt06r136>Stewart, R. R., 1987, Seismic tomography: SEG Continuing Education Program Notes, GENIX Tech. Ltd.</ref> offers promise for high resolution reservoir description at the interwell and fieldwide scales, as well as for monitoring [[enhanced oil recovery]] projects.

Standard seismic reflection methods generally cannot resolve reservoir heterogeneities at the interwell scale. [[Cross-borehole tomography in development geology|Crosshole seismic tomography]]<ref name=pt06r136>Stewart, R. R., 1987, Seismic tomography: SEG Continuing Education Program Notes, GENIX Tech. Ltd.</ref> offers promise for high resolution reservoir description at the interwell and fieldwide scales, as well as for monitoring [[enhanced oil recovery]] projects.