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Evaluation of Shaly Clastic Reservoir Rocks
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Log-derived spectral gamma ray data have been correlated to core-derived Qv data (i.e., cation exchange capacity per total pore volume) in a Texas coast Tertiary sand, east Texas Jurassic sands, and an Alaskan elastic formation. Such correlations can be used to provide a continuous in-situ water saturation estimate in shaly sands based on the Waxman-Smits equation.
Introduction
Exceptionally few hydrocarbon-bearing clastic reservoir rocks are essentially free of clay minerals. The significant effect of the latter on important reservoir properties such as porosity, water saturation, and permeability and on most geophysical well log responses is well-established.In clastic reservoirs, various types of clay minerals may occur in dispersed, laminated, or structural form. The types of clay distribution, each with a differing effect on effective porosity, can be inferred from crossplots of well logs, visual study of cores, or detailed SEM investigations. The latter distinguish dispersed-clay occurrences such as discrete particles (patchy kaolinite), pore lining, and pore bridging (illite, chlorite, and smectite), each of which have a pronounced but different effect on reservoir permeability.Clay minerals may be characterized in several ways. Table 1 lists composition, density, hydrogen index, cation exchange capacity C ec, and distribution of potassium, thorium, and uranium based on spectral gamma ray information for some of the more common clay minerals.Furthermore, numerous log-derived clay content (shaliness) indicators are reviewed and discussed (Table 2). These techniques basically assume identical properties for clay present in clastic reservoir rocks and adjacent shales. However, this assumption is often unrealistic.With the advent of the Waxman-Smits model to calculate reliable water saturation in shaly sands, emphasis has been focused on log-derived evaluation of C ec per total pore volume, Qv. The novel application of spectral gamma ray data will be discussed in detail.
Water Saturation Calculation Models and Associated Parameters
Archie, in his classic empirical equation, relates formation conductivity Ct, formation-water conductivity Cw, and the formation resistivity factor F (a function of porosity phi and cementation exponent m) to the formation-water saturation Sw.
Ct =Sw CwF(-1),
where F= phi (-m).
Archie's equation satisfactorily applies to clean sands. The presence of clay minerals, however, has a detrimental effect on Sw calculations. Since such Sw results are often too pessimistic, several clay/quartz distribution models and Sw calculation concepts have been proposed.
JPT
P. 1641^
Society of Petroleum Engineers (SPE)
Title: Evaluation of Shaly Clastic Reservoir Rocks
Description:
Log-derived spectral gamma ray data have been correlated to core-derived Qv data (i.
e.
, cation exchange capacity per total pore volume) in a Texas coast Tertiary sand, east Texas Jurassic sands, and an Alaskan elastic formation.
Such correlations can be used to provide a continuous in-situ water saturation estimate in shaly sands based on the Waxman-Smits equation.
Introduction
Exceptionally few hydrocarbon-bearing clastic reservoir rocks are essentially free of clay minerals.
The significant effect of the latter on important reservoir properties such as porosity, water saturation, and permeability and on most geophysical well log responses is well-established.
In clastic reservoirs, various types of clay minerals may occur in dispersed, laminated, or structural form.
The types of clay distribution, each with a differing effect on effective porosity, can be inferred from crossplots of well logs, visual study of cores, or detailed SEM investigations.
The latter distinguish dispersed-clay occurrences such as discrete particles (patchy kaolinite), pore lining, and pore bridging (illite, chlorite, and smectite), each of which have a pronounced but different effect on reservoir permeability.
Clay minerals may be characterized in several ways.
Table 1 lists composition, density, hydrogen index, cation exchange capacity C ec, and distribution of potassium, thorium, and uranium based on spectral gamma ray information for some of the more common clay minerals.
Furthermore, numerous log-derived clay content (shaliness) indicators are reviewed and discussed (Table 2).
These techniques basically assume identical properties for clay present in clastic reservoir rocks and adjacent shales.
However, this assumption is often unrealistic.
With the advent of the Waxman-Smits model to calculate reliable water saturation in shaly sands, emphasis has been focused on log-derived evaluation of C ec per total pore volume, Qv.
The novel application of spectral gamma ray data will be discussed in detail.
Water Saturation Calculation Models and Associated Parameters
Archie, in his classic empirical equation, relates formation conductivity Ct, formation-water conductivity Cw, and the formation resistivity factor F (a function of porosity phi and cementation exponent m) to the formation-water saturation Sw.
Ct =Sw CwF(-1),
where F= phi (-m).
Archie's equation satisfactorily applies to clean sands.
The presence of clay minerals, however, has a detrimental effect on Sw calculations.
Since such Sw results are often too pessimistic, several clay/quartz distribution models and Sw calculation concepts have been proposed.
JPT
P.
1641^.
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