Changes

[[file:geological-heterogeneities_fig3.png|left|thumb|{{figure number|3}}Lateral and vertical bedding and permeability heterogeneity of a typical fluviodeltaic sequence. (From <ref name=pt06r144 />.)]]

[[file:geological-heterogeneities_fig3.png|left|thumb|{{figure number|3}}Lateral and vertical bedding and permeability heterogeneity of a typical fluviodeltaic sequence. (From <ref name=pt06r144 />.)]]

Elements of interwell scale heterogeneity include lateral bedding geometries, styles, and continuity; systematic lateral and vertical textural patterns; and resultant variations in [[reservoir quality]]. This scale of heterogeneity is probably the most difficult to quantify because wellbore data of the type previously described must be extrapolated to the interwell region. In many instances, between-well correlations are difficult because lithofacies may not be continuous at interwell spacings. Thus, interpretation must be guided by an understanding of depositional environments and facies (for more information, see [[Lithofacies and environmental analysis of clastic depositional systems#Clastic depositional lithofacies and environments|Clastic lithofacies]] and [[Carbonate reservoir models: facies, diagenesis, and flow characterization#Carbonate sediments and environments|Carbonate lithofacies]]), interpreted from core analysis and compared with modern environments or outcrop analogs where actual observations and measurements have been made.

Elements of interwell scale heterogeneity include lateral [[bedding geometries]], styles, and continuity; systematic lateral and vertical textural patterns; and resultant variations in [[reservoir quality]]. This scale of heterogeneity is probably the most difficult to quantify because wellbore data of the type previously described must be extrapolated to the interwell region. In many instances, between-well correlations are difficult because lithofacies may not be continuous at interwell spacings. Thus, interpretation must be guided by an understanding of depositional environments and facies (for more information, see [[Lithofacies and environmental analysis of clastic depositional systems#Clastic depositional lithofacies and environments|Clastic lithofacies]] and [[Carbonate reservoir models: facies, diagenesis, and flow characterization#Carbonate sediments and environments|Carbonate lithofacies]]), interpreted from core analysis and compared with modern environments or outcrop analogs where actual observations and measurements have been made.

Relatively few reliable quantitative studies of depositional environments and facies have been published, and those that have suggest considerable variability in interwell-scale heterogeneities among different depositional systems, as well as within any one system. Excellent examples include Scheihing and Gaynor<ref name=pt06r38>Gaynor, G. C., Scheihing, M. H., 1988, Shelf depositional environments and reservoir characteristics of the Kuparuk River Formation (Lower Cretaceous), Kuparuk field, North Slope, Alaska, in Lomando, A. J., Harris, P. M., eds., Giant oil and gas fields—A core workshop: Society of Economic Paleontologists and Mineralogists Core Workshop 12, p. 333–389.</ref> and Krause et al.<ref name=pt06r67>Krause, F. F., Collins, H. N., Nelson, D. A., Mochemer, S. D., French, P. R., 1987, [http://archives.datapages.com/data/bulletns/1986-87/data/pg/0071/0010/1200/1233.htm Multiscale anatomy of a reservoir— geological characterization of Pembina-Cardium pool, west-central Alberta, Canada]: AAPG Bulletin, v. 71, p. 1233–2260.</ref> for [[Lithofacies and environmental analysis of clastic depositional systems#Shallow marine clastic deposits|shelf sandstones]]; van de Graaff and Ealey<ref name=pt06r144 /> for [[Lithofacies and environmental analysis of clastic depositional systems#Deltas|fluviodeltaic sequences]] ([[:file:geological-heterogeneities_fig3.png|Figure 3]]); and Jordan and Pryor<ref name=pt06r61>Jordan, D. W., Pryor, W. A., 1992, [http://archives.datapages.com/data/bulletns/1992-93/data/pg/0076/0010/0000/1601.htm Hierarchical levels of heterogeneity in a Mississippi River meander belt and application to reservoir systems]: AAPG Bulletin, v. 76, p. 1601–1624.</ref> for [[Lithofacies and environmental analysis of clastic depositional systems#Braided and meandering fluvial deposits|fluvial sands]].

Relatively few reliable quantitative studies of depositional environments and facies have been published, and those that have suggest considerable variability in interwell-scale heterogeneities among different depositional systems, as well as within any one system. Excellent examples include Scheihing and Gaynor<ref name=pt06r38>Gaynor, G. C., Scheihing, M. H., 1988, Shelf depositional environments and reservoir characteristics of the Kuparuk River Formation (Lower Cretaceous), Kuparuk field, North Slope, Alaska, in Lomando, A. J., Harris, P. M., eds., Giant oil and gas fields—A core workshop: Society of Economic Paleontologists and Mineralogists Core Workshop 12, p. 333–389.</ref> and Krause et al.<ref name=pt06r67>Krause, F. F., Collins, H. N., Nelson, D. A., Mochemer, S. D., French, P. R., 1987, [http://archives.datapages.com/data/bulletns/1986-87/data/pg/0071/0010/1200/1233.htm Multiscale anatomy of a reservoir— geological characterization of Pembina-Cardium pool, west-central Alberta, Canada]: AAPG Bulletin, v. 71, p. 1233–2260.</ref> for [[Lithofacies and environmental analysis of clastic depositional systems#Shallow marine clastic deposits|shelf sandstones]]; van de Graaff and Ealey<ref name=pt06r144 /> for [[Lithofacies and environmental analysis of clastic depositional systems#Deltas|fluviodeltaic sequences]] ([[:file:geological-heterogeneities_fig3.png|Figure 3]]); and Jordan and Pryor<ref name=pt06r61>Jordan, D. W., Pryor, W. A., 1992, [http://archives.datapages.com/data/bulletns/1992-93/data/pg/0076/0010/0000/1601.htm Hierarchical levels of heterogeneity in a Mississippi River meander belt and application to reservoir systems]: AAPG Bulletin, v. 76, p. 1601–1624.</ref> for [[Lithofacies and environmental analysis of clastic depositional systems#Braided and meandering fluvial deposits|fluvial sands]].

[[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.