Changes

  | part    = Predicting the occurrence of oil and gas traps

  | part    = Predicting the occurrence of oil and gas traps

  | chapter = Predicting reservoir system quality and performance

  | chapter = Predicting reservoir system quality and performance

  | frompg  = 9-1

  | frompg  = 9-29

  | topg    = 9-156

  | topg    = 9-33

  | author  = Dan J. Hartmann, Edward A. Beaumont

  | author  = Dan J. Hartmann, Edward A. Beaumont

  | link    = http://archives.datapages.com/data/specpubs/beaumont/ch09/ch09.htm

  | link    = http://archives.datapages.com/data/specpubs/beaumont/ch09/ch09.htm

==Methods==

==Methods==

Analyzing air [[permeability]] (K_a and [[porosity]] (Φ) data separately to characterize rock quality can be deceiving. Analyzing K_a and Φ data using the K_a/Φ ratio or the r₃₅ method<ref name=ch09r46>Pittman, E., D., 1992, Relationship of porosity to permeability to various parameters derived from mercury injection–[[capillary pressure]] curves for sandstone: AAPG Bulletin, vol. 76, no. 2, p. 191–198.</ref> is much more effective for determining quality. The K_a/Φ ratio or the r₃₅ method yields information about the fluid flow and storage quality of a rock.

Analyzing air [[permeability]] (K_a and [[porosity]] (Φ) data separately to characterize rock quality can be deceiving. Analyzing K_a and Φ data using the K_a/Φ ratio or the r₃₅ method<ref name=ch09r46>Pittman, E., D., 1992, [http://archives.datapages.com/data/bulletns/1992-93/data/pg/0076/0002/0000/0191.htm Relationship of porosity to permeability to various parameters derived from mercury injection–capillary pressure curves for sandstone]: AAPG Bulletin, vol. 76, no. 2, p. 191–198.</ref> is much more effective for determining quality. The K_a/Φ ratio or the r₃₅ method yields information about the fluid flow and storage quality of a rock.

[[file:predicting-reservoir-system-quality-and-performance_fig9-16.png|thumb|{{figure number|1}}See text for explanation.]]

 

[[file:predicting-reservoir-system-quality-and-performance_fig9-16.png|300px|thumb|{{figure number|1}}SEM microphotographs.]]

Using K_a and Φ data separately to characterize reservoir rock quality is misleading. Consider the rocks shown in the SEM microphotographs in [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]. Flow unit 1 is a [[Wikipedia:Mesoporous material|mesoporous]], sucrosic [[dolomite]]. Its average Φ is 30% and average K_a is 10 md. Flow unit 2 is a macroporous, oolitic [[limestone]]. Its average Φ is 10% and average K_a is 10 md.

Using K_a and Φ data separately to characterize reservoir rock quality is misleading. Consider the rocks shown in the SEM microphotographs in [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]. Flow unit 1 is a mesoporous, sucrosic dolomite. Its average Φ is 30% and average K_a is 10 md. Flow unit 2 is a macroporous, oolitic limestone. Its average Φ is 10% and average K_a is 10 md.

Initially, we might think that flow unit 1 is higher quality because it has three times more porosity and the same permeability as flow unit 2. However, in terms of fluid flow efficiency and storage, as shown by the K_a/Φ ratio or r₃₅, flow unit 2 is actually the better rock.

Initially, we might think that flow unit 1 is higher quality because it has three times more porosity and the same permeability as flow unit 2. However, in terms of fluid flow efficiency and storage, as shown by the K_a/Φ ratio or r₃₅, flow unit 2 is actually the better rock.

In [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]], flow unit 1 has a K_a/Φ value of 33 and flow unit 2 has a K_a/Φ value of 100. Even though Φ is greater and K_a is the same for flow unit 1, the lower K_a/Φ value indicates its quality is lower than flow unit 2.

In [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]], flow unit 1 has a K_a/Φ value of 33 and flow unit 2 has a K_a/Φ value of 100. Even though Φ is greater and K_a is the same for flow unit 1, the lower K_a/Φ value indicates its quality is lower than flow unit 2.

==K_a/Φ plot==

[[file:Oiloil-and-oilsource-rock-correlations fig8-17.png|300px|thumb|{{figure number|2}}Contour plot.]]

On the plot in [[:file:predicting-reservoir-system-quality-and-performance_fig9-17.png|Figure 2]], the contours represent a constant K_a/Φ ratio and divide the plot into areas of similar pore types. Data points that plot along a constant ratio have similar flow quality across a large range of porosity and/or permeability. The clusters of points on the plot  in [[:file:predicting-reservoir-system-quality-and-performance_fig9-17.png|Figure 2]] represent hypothetical K_a/Φ values for flow units 1 and 2 presented i in [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]. The position of the clusters relative to the K_a/Φ contours indicates flow unit 2 has higher quality in terms of K_a/Φ ratio than flow unit 1.

 

On the plot in [[:file:Oiloil-and-oilsource-rock-correlations fig8-17.png|Figure 2]], the contours represent a constant K_a/Φ ratio and divide the plot into areas of similar pore types. Data points that plot along a constant ratio have similar flow quality across a large range of porosity and/or permeability. The clusters of points on the plot  in [[:file:Oiloil-and-oilsource-rock-correlations fig8-17.png|Figure 2]] represent hypothetical K_a/Φ values for flow units 1 and 2 presented in [[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]. The position of the clusters relative to the K_a/Φ contours indicates flow unit 2 has higher quality in terms of K_a/Φ ratio than flow unit 1.

==What is r₃₅?==

==What is r₃₅?==

[[file:predicting-reservoir-system-quality-and-performance_fig9-18.png|thumb|{{figure number|3}}Modified from .<ref name=ch09r15>Doveton, J., H., 1995, Wireline Petrofacies Analysis: Notes from short course presented in Calgary, Alberta, April 24–28, 176 p.</ref>]]

[[file:predicting-reservoir-system-quality-and-performance_fig9-18.png|300px|thumb|{{figure number|3}}Capillary pressure curve and pore throat size histogram. Modified from Doveton.<ref name=ch09r15>Doveton, J., H., 1995, Wireline Petrofacies Analysis: Notes from short course presented in Calgary, Alberta, April 24–28, 176 p.</ref>]]

H.D. Winland of Amoco used mercury injection-capillary pressure curves to develop an empirical relationship among Φ, K_a, and pore throat radius (r). He tested 312 different water-wet samples. The data set included 82 samples (56 sandstone and 26 carbonate) with low permeability corrected for gas slippage and 240 other uncorrected samples. Winland found that the effective pore system that dominates flow through a rock corresponds to a mercury saturation of 35%. That pore system has pore throat radii (called port size, or r₃₅) equal to or smaller than the pore throats entered when a rock is saturated 35% with a nonwetting phase. After 35% of the pore system fills with a non-wetting phase fluid, the remaining pore system does not contribute to flow. Instead, it contributes to storage.

H.D. Winland of Amoco used mercury injection-capillary pressure curves to develop an empirical relationship among Φ, K_a, and pore throat radius (r). He tested 312 different water-wet samples. The data set included 82 samples (56 sandstone and 26 carbonate) with low permeability corrected for gas slippage and 240 other uncorrected samples. Winland found that the effective pore system that dominates flow through a rock corresponds to a mercury saturation of 35%. That pore system has pore throat radii (called port size, or r₃₅) equal to or smaller than the pore throats entered when a rock is saturated 35% with a nonwetting phase. After 35% of the pore system fills with a non-wetting phase fluid, the remaining pore system does not contribute to flow. Instead, it contributes to storage.

Pittman<ref name=ch09r46 />) speculates, “Perhaps Winland found the best correlation to be r₃₅ because that is where the average modal pore aperture occurs and where the pore network is developed to the point of serving as an effective pore system that dominates flow.” The capillary pressure curve and pore throat size histogram in [[:file:predicting-reservoir-system-quality-and-performance_fig9-18.png|Figure 3]] illustrate Pittman's point.

Pittman<ref name=ch09r46 /> speculates, “Perhaps Winland found the best correlation to be r₃₅ because that is where the average modal pore aperture occurs and where the pore network is developed to the point of serving as an effective pore system that dominates flow.” The capillary pressure curve and pore throat size histogram in [[:file:predicting-reservoir-system-quality-and-performance_fig9-18.png|Figure 3]] illustrate Pittman's point.

==The winland r₃₅ equation==

==The Winland r₃₅ equation==

Winland<ref name=ch09r70>Winland, H., D., 1972, Oil accumulation in response to pore size changes, Weyburn field, Saskatchewan: Amoco Production Company Report F72-G-25, 20 p. (unpublished).</ref><ref name=ch09r71>Winland, H., D., 1976, Evaluation of gas slippage and pore aperture size in carbonate and sandstone reservoirs: Amoco Production Company Report F76-G-5, 25 p. (unpublished).</ref> developed the following equation to calculate r₃₅ for samples with intergranular or intercrystalline porosity:

Winland<ref name=ch09r70>Winland, H., D., 1972, Oil accumulation in response to pore size changes, Weyburn field, Saskatchewan: Amoco Production Company Report F72-G-25, 20 p. (unpublished).</ref><ref name=ch09r71>Winland, H., D., 1976, Evaluation of gas slippage and pore aperture size in carbonate and sandstone reservoirs: Amoco Production Company Report F76-G-5, 25 p. (unpublished).</ref> developed the following equation to calculate r₃₅ for samples with intergranular or intercrystalline porosity:

==Characterizing rock quality with r₃₅==

==Characterizing rock quality with r₃₅==

[[file:predicting-reservoir-system-quality-and-performance_fig9-19.png|thumb|{{figure number|4}}See text for explanation.]]

[[file:predicting-reservoir-system-quality-and-performance_fig9-19.png|300px|thumb|{{figure number|4}}K_a/Φ plot.]]

Rock quality is easily characterized using r₃₅. Consider the clusters of points representing flow units 1 and 2 ([[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]) on the K_a/Φ plot in [[:file:predicting-reservoir-system-quality-and-performance_fig9-19.png|Figure 4]]. The diagonal curved lines represent equal r₃₅ values. Points plotting along the same lines represent rocks with similar r₃₅ values and have similar quality. By interpolation, r₃₅ for flow unit 1 is approximately 1.1μ, and r₃₅ for flow unit 2 is approximately 3μ. The r₃₅ in flow unit 2 is almost three times as large as flow unit 1. Therefore, flow unit 2 has better flow quality.

Rock quality is easily characterized using r₃₅. Consider the clusters of points representing flow units 1 and 2 ([[:file:predicting-reservoir-system-quality-and-performance_fig9-16.png|Figure 1]]) on the K_a/Φ plot in [[:file:predicting-reservoir-system-quality-and-performance_fig9-19.png|Figure 4]]. The diagonal curved lines represent equal r₃₅ values. Points plotting along the same lines represent rocks with similar r₃₅ values and have similar quality. By interpolation, r₃₅ for flow unit 1 is approximately 1.1μ, and r₃₅ for flow unit 2 is approximately 3μ. The r₃₅ in flow unit 2 is almost three times as large as flow unit 1. Therefore, flow unit 2 has better flow quality.

==Example capillary pressure curves==

==Example capillary pressure curves==

Hypothetical capillary pressure curves can be drawn by using r₃₅ as a point on the curve. The capillary pressure curves below are hypothetical curves for the example presented in Figure 9-19. The curves demonstrate that entry pressures for flow unit 2 are less than those for flow unit 1; therefore, fluid flow in flow unit 2 is more efficient. In the figure below, it takes [[length::28 ft]] of oil column for oil to enter 35% of pore space of flow unit 2 and [[length::70 ft]] to enter 35% of pore space of flow unit 1.

<gallery mode=packed widths=300px heights=300px>

file:predicting-reservoir-system-quality-and-performance_fig9-20.png|{{figure number|5}}Hypothetical capillary pressure curves.

file:predicting-reservoir-system-quality-and-performance_fig9-21.png|{{figure number|6}}Hypothetical drainage relative permeability curves.

[[file:predicting-reservoir-system-quality-and-performance_fig9-20.png|thumb|{{figure number|9-20}}See text for explanation.]]

Hypothetical capillary pressure curves can be drawn by using r₃₅ as a point on the curve. The capillary pressure curves below are hypothetical curves for the example presented in [[:file:predicting-reservoir-system-quality-and-performance_fig9-19.png|Figure 4]]. The curves demonstrate that entry pressures for flow unit 2 are less than those for flow unit 1; therefore, fluid flow in flow unit 2 is more efficient. In [[:file:predicting-reservoir-system-quality-and-performance_fig9-20.png|Figure 5]], it takes [[length::28 ft]] of oil column for oil to enter 35% of pore space of flow unit 2 and [[length::70 ft]] to enter 35% of pore space of flow unit 1.

===Example relative permeability curves===

===Example relative permeability curves===

[[:file:predicting-reservoir-system-quality-and-performance_fig9-21.png|Figure 6]] depicts hypothetical drainage relative permeability curves to represent flow units 1 and 2.

 

[[file:predicting-reservoir-system-quality-and-performance_fig9-21.png|thumb|{{figure number|9-21}}See text for explanation.]]

==See also==

==See also==

* [[Pore–fluid interaction]]

* [[Pore-fluid interaction]]

* [[Hydrocarbon expulsion, migration, and accumulation]]

* [[Hydrocarbon expulsion, migration, and accumulation]]

* [[Pc curves and saturation profiles]]

* [[Pc curves and saturation profiles]]

[[Category:Predicting the occurrence of oil and gas traps]]  

[[Category:Predicting the occurrence of oil and gas traps]]  

[[Category:Predicting reservoir system quality and performance]]

[[Category:Predicting reservoir system quality and performance]]