Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-03-30
2002-10-22
McElheny, Jr., Donald E. (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
C702S012000
Reexamination Certificate
active
06470274
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention is related generally to the field of interpretation of measurements made by well logging instruments for the purpose of determining the fluid content of earth formations. More specifically, the invention is related to methods for calculating fractional volumes of various fluids disposed in the pore spaces of earth formations where these earth formations include laminations of shale or laminated shale distribution with reservoir rock that may include dispersed shales.
2. Background of the Art
A significant number of hydrocarbon reservoirs include deep water turbidite deposits that consist of thin bedded, laminated sands and shales. A common method for evaluating the hydrocarbon content of reservoirs is the use of resistivity measurements. In interpretation techniques known in the art, typically one or more types of porosity-related measurement will be combined with measurements of the electrical resistivity (or its inverse, electrical conductivity) of the earth formations to infer the fluid content within the pore spaces of the earth formations. The fractional volumes of connate water and hydrocarbons can be inferred from empirical relationships of formation resistivity Rt with respect to porosity and connate water resistivity such as, for example, the well known Archie relationship. In the Archie relationship fractional volume of water in the pore space is represented, as shown in the following expression, by Sw—known as “water saturation”:
S
w
n
=
R
0
R
t
=
1
R
t
a
R
w
φ
m
(
1
)
where a and m are empirically determined factors which relate the porosity (represented by &PHgr;) to the resistivity of the porous rock formation when it is completely water-saturated (R
0
), R
w
represents the resistivity of the connate water disposed in the pore spaces of the formation, and m represents an empirically determined “icementation” exponent, n is the saturation exponent.
Relationships such as the Archie formula shown in equation (1) do not work very well when the particular earth formation being analyzed includes some amount of extremely fine-grained, clay mineral-based components known in the art as “shale”. Shale typically occurs, among other ways, in earth formations as “dispersed” shale, where particles of clay minerals occupy some of the pore spaces in the hydrocarbon-bearing earth formations, or as laminations (layers) of clay mineral-based rock interleaved with layers of reservoir-type rock in a particular earth formation.
In the case of dispersed shale, various empirically derived relationships have been developed to calculate the fractional volume of pore space which is capable of containing movable (producible) hydrocarbons. The fractional volume of such formations which is occupied by dispersed shale can be estimated using such well logging devices as natural gamma ray radiation detectors. See for example, M. H. Waxman et al, “Electrical Conductivities in Oil Bearing Shaly Sands”, SPE Journal, vol. 8, no. 2, Society of Petroleum Engineers, Richardson, Tex. (1968).
In the case of laminated shale, the layers sometimes are thick enough to be within the vertical resolution of, and therefore are determinable by, well logging instruments such as a natural gamma ray detector. In these cases, the shale layers are determined not to be reservoir rock formation and are generally ignored for purposes of determining hydrocarbon content of the particular earth formation. A problem in laminated shale reservoirs is where the shale laminations are not thick enough to be fully determined using gamma ray detectors and are not thick enough to have their electrical resistivity accurately determined by electrical resistivity measuring devices known in the art.
Sands that have high hydrocarbon saturation are typically more resistive than shales. In reservoirs consisting of thin laminations of sands and shales, conventional induction logging tools greatly underestimate the resistivity of the reservoir: the currents induced in the formation by the logging tool flow preferentially through the conductive shale laminations creating a bias towards a higher formation conductivity. This could lead to an underestimation of hydrocarbon reserves.
One method for estimating hydrocarbon content of earth formations where shale laminations are present was developed by Poupon. See A. Poupon et al, “A Contribution to Electrical Log Interpretation in Shaly Sands”, Transactions AIME, Vol. 201, pp. 138-145 (1959). Generally the Poupon relationship assumes that the shale layers affect the overall electrical conductivity of the earth formation being analyzed in proportion to the fractional volume of the shale layers within the particular earth formation being analyzed. The fractional volume is typically represented by Vsh (shale “volume”). Poupon's model also assumes that the electrical conductivity measured by the well logging instrument will include proportional effects of the shale layers, leaving the remainder of the measured electrical conductivity as originating in the “clean” (non-shale bearing) reservoir rock layers as shown in the following expression:
1
R
t
=
(
1
-
V
sh
)
(
a
R
w
φ
m
)
-
1
S
w
n
+
V
sh
R
sh
(
2
)
where R
t
represents the electrical resistivity (inverse of conductivity) in the reservoir rock layers of the formation and R
sh
represents the resistivity in the shale layers.
The analysis by Poupon overlooks the effect of anisotropy in the resistivity of a reservoir including thinly laminated sands and shales. Use of improper evaluation models in many cases may result in an underestimation of reservoir producibility and hydrocarbon reserves by 40% or more as noted by van den Berg and Sandor. Analysis of well logging instrument measurements for determining the fluid content of possible hydrocarbon reservoirs includes calculating the fractional volume of pore space (“porosity”) and calculating the fractional volumes within the pore spaces of both hydrocarbons and connate water. As noted above, Archie's relationship may be used.
In thinly laminated reservoirs where the wavelength of the interrogating electromagnetic wave is greater than the thickness of the individual layers, the reservoir exhibits an anisotropy in the resistivity. This anisotropy may be detected by using a logging tool that has, in addition to the usual transmitter coil and receiver coil aligned along with the axis of the borehole, a receiver or a transmitter coil aligned at an angle to the borehole axis. Such devices have been well described in the past for dip determination. See, for example, U.S. Pat. No. 3,510,757 to Huston and U.S. Pat. No. 5,115,198 to Gianzero,
U.S. Pat. No. 5,656,930 issued to Hagiwara discloses a method of determining the horizontal resistivity, the vertical resistivity, and the anisotropy coefficient of a subterranean formation by means of an induction type logging tool positioned in a deviated borehole within the subterranean formation. In a preferred implementation, the induction type logging tool is first calibrated to determine a proportionality constant. A predetermined relationship between the proportionality constant, the phase shift derived resistivity, the attenuation derived resistivity, the horizontal resistivity, the vertical resistivity, and the anisotropy coefficient is then generated and stored in the memory of a programmed central processing unit. During an induction logging operation, the phase shift derived resistivity and attenuation derived resistivity are then received and processed by the programmed central processing unit in accordance with the predetermined relationship to generate the horizontal resistivity, the vertical resistivity, and the anisotropy coefficient. These measured values of horizontal and vertical resistivities when combined with a predetermined relationship between the horizontal resistivity, the vertical resistivity, the net/gross ratio, and the ratio of the sand layer resistivity to the shale
Fanini Otto N.
Kriegshauser Berthold
Mollison Richard A.
Pavlovic Milomir
Baker Hughes Incorporated
Madan Mossman & Sriram P.C.
McElheny Jr. Donald E.
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