1.4.1 Volumetric Calculation
A general formula for the calculation of the volume of hydrocarbons in a reservoir is represented as:
(1.17)
In Eq. (1.17), hydrocarbon pore volume; hydrocarbon-bearing area of the reservoir; net productive thickness or pay of the reservoir; porosity, frac-tion; and water saturation, fraction. The hydrocarbon volumes of specific types of fluids (oil and/or gas) in the reservoir can be calculated with minor modifications of Eq. (1.17) as demonstrated in Chapter 8 for Gas Reservoirs, and Chapter 9 for Oil Reservoirs. Note the promi-nence of porosity in Eq. (1.17) for the calculation of volumes of hydrocarbons present in a reservoir.
It is evident from Eq. (1.17) that inaccurate porosity data can directly cause underestimation or Sw =
f = Thickness =
Area = HCPV =
HCPV = Area * Thickness * f * (1 - Sw)
25.0 22.5 20.0 17.5 15.0 12.5 10.0 7.5 5.0 2.5 0.0 0.0 2.5 5.0 7.5 10.0
NMR porosity, percent
12.5 15.0 17.5 20.0 22.5 25.0
Core porosity, percent
Figure 1.3 NMR porosity versus core porosity based on core samples from a reservoir.
ptg overestimation of the hydrocarbon volumes in the reservoir. For marginal reservoirs,
underesti-mation of in-place hydrocarbon volumes may contribute to a decision not to pursue development of the reservoir. Overestimation of in-place hydrocarbon volumes may lead to economic losses, if projected reserves estimated prior to development are far below actual reservoir performance.
Note that there are other geologic and reservoir factors (such as permeability barriers, faults, compartments, recovery mechanisms) which can also cause reservoir performance to be below projected levels. The impact of these other factors on reservoir performance are presented and discussed in more details in several chapters in this book.
1.4.2 Calculation of Fluid Saturations
For clean, non-shaly rocks, water saturations can be calculated from the Archie equation1as:
(1.18)
In Eq. (1.18), formation conductivity; total porosity; water saturation;
formation water conductivity; cementation factor; and saturation exponent. The param-eters are also called the electrical properties of the rock.
For shaly sands, water saturations can be calculated from modified forms1of the Archie equation, which are shown as:
(1.19) (1.20)
In Eqs. (1.19) and (1.20), effective conductivity; and mv, nvare general forms of the electrical properties. In Eq. (1.19), is expressed in terms of and a function of shale (in the shale model) or a function of clay (in the clay model). In Eq. (1.20), is a function that accounts for the conductivity caused by shale or clay that occur in shaly sands. Note that in Eq.
(1.20) as approaches zero, Eq. (1.20) becomes equivalent to Eq. (1.18).
The main point to note from Eqs. (1.18), (1.19), and (1.20) is that total porosity is an important data input for calculation of water saturation with water saturation models. If errors exist in the calculations of total porosity, these errors will be transferred to the calculation of water saturations. This could ultimately lead to errors in the estimation of reservoir in place hydrocarbon volumes as shown in Eq. (1.17). The calculation of water (fluid) saturation is pre-sented in more detail in Chapter 3.
1.4.3 Reservoir Characterization
Porosities can be measured directly from cores or indirectly determined from well logs as dis-cussed previously in this chapter. On the one hand, rock permeability can be measured most reli-ably from cores or in aggregate sense from well tests. Indirect methods for acquiring permeability data are discussed in Chapter 2. There are usually more porosity data than permeability data avail-able on a reservoir. A cross-plot of permeability versus porosity data (Figure 1.4) to create a poros-ity-permeability transform is sometimes used to assign permeability values to areas of the
X
1.4 Applications of Porosity Data 11
ptg
reservoir where permeability data do not exist. The practice of using porosity-permeability trans-forms in reservoir characterization is presented in Chapter 18.
Facies or rock types can be defined or assigned to parts of a reservoir by using porosity values as part of a system of criteria for rock classification. This process of classifying reservoir rock in terms of facies or rock types is useful in the process of reservoir characterization. This is also presented in Chapter 18.
Nomenclature
formation conductivity effective conductivity formation water conductivity length of core plug
cementation factor m
l Cw Cwe Ct
1000
100
10
1
0.1
0.0110 14 18 22 26 30
Porosity, percent
Permeability, md
Figure 1.4 Porosity-permeability cross-plot based on core samples from a reservoir.
ptg saturation exponent
radius of core plug water saturation, fraction volume of clay-bound water volume of clay
bulk volume pore volume shale volume function in Eq. 1.20 porosity
density-derived porosity density-derived shale porosity effective porosity
neutron-derived porosity neutron-derived porosity in clay neutron-derived porosity in shale sonic-derived porosity
shale porosity
sonic-derived porosity in clay sonic-derived porosity in shale total porosity
bulk density fluid density rock matrix density
formation interval transit time fluid transit time
rock matrix transit time
Abbreviations
LWD Logging-While-Drilling NMR Nuclear Magnetic Resonance ECS Elemental Capture Spectroscopy HCPV Hydrocarbon Pore Volume
References
1. Al-Ruwaili, S.A., and Al-Waheed, H.H.: “Improved Petrophysical Methods and Techniques for Shaly Sands Evaluation,” paper SPE 89735 presented at the 2004 SPE International Petroleum Conference in Puebla, Mexico, November 8–9, 2004.
2. Amyx, J.W., Bass, D.M., Jr., and Whiting, R.L.: Petroleum Reservoir Engineering, Physical Properties, McGraw-Hill, New York, 1960.
¢tma
ptg 3. Coates, G.R., Menger, S., Prammer, M., and Miller, D.: “Applying NMR Total and Effective
Porosity to Formation Evaluation,” paper SPE 38736 presented at the 1997 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, October 5–8, 1997.
4. Ellis, D.: “Formation Porosity Estimation from Density Logs,” Petrophysics, (September–
October, 2003) 306–316.
5. Wyllie, M.R.J., Gregory, A.R., and Gardner, G.H.F.: “Elastic Wave Velocity in Heteroge-neous and Porous Media,” Geophysics, (1956) 41–70.
6. Raymer, L.L., Hunt, E.R., and Gardner, J.S.: “An Improved Sonic Transit Time-To-Porosity Transform,” SPWLA Twenty-First Annual Logging Symposium, July 8–11, 1980.
7. Freedman, R.: “Advances in NMR Logging,” SPE 89177, Distinguished Author Series, JPT, (January 2006) 60–66.
8. Bachman, H.N., Crary, S., Heidler, R., LaVigne, J., and Akkurt, R.: “Porosity Determination from NMR Log Data: The Effects of Acquisition Parameters,” paper SPE 110803 presented at the 2007 SPE Annual Technical Conference and Exhibition, Anaheim, California, November 11–14, 2007.
9. Akkurt, R., Kersey, D.G., and Zainalabedin, K.: “Challenges for Everyday NMR: An Operator’s Perspective,” paper SPE 102247 presented at the 2006 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 24–27, 2006.
10. Seifert, D.J., Akkurt, R., Al-Dossary, S., Shokeir, R., and Ersoz, H.: “Nuclear Magnetic Resonance Logging: While Drilling, Wireline, and Fluid Sampling,” paper SPE 105605 pre-sented at the 15th SPE Middle East Oil & Gas Show and Conference, Bahrain, Kingdom of Bahrain, March 11–14, 2007.