The effect of overburden and fluid pressure on the resistivity of reservoir rock has been generally ignored in the quantitative interpretation of electrical logs. This paper shows from laboratory tests of two sandstone, two limestone and one dolomite formation that theoretical reservoir stress increases resistivity in varying amounts, depending upon depth (or stress) of formation, porosity, texture of rock and degree of water saturation.
The increased resistivity develops from increased formation resistivity factor and saturation exponent. In medium to low porosity the formation factor vs porosity relation is affected in such a manner that a given porosity represents a higher formation factor in stressed rock. Indications are that pressure effect is probably significant in many reservoirs of medium to low porosity, especially at greater depths, and should be considered in the interpretation of their electrical log resistivities.
A simple and useful technique for pressure analysis of core plug samples was developed in the study which should be adaptable for routine measurements (Fig. 1).
The electrical resistivity measurement of reservoir rock has long been recognized as a reliable indicator of many important properties of the rock and of the fluids which it contains. Efforts to derive practical methods for analyzing electrical log recordings have been directed along two lines:
correcting the "apparent" log resistivity to a "true" value by considering effects of the borehole, bed thickness, measuring system, etc., and
interpreting the true value of resistivity for whatever data it may reveal which is of practical value in the detection and/or evaluation of an oil or gas reservoir.
This paper deals only in the realm of the second item.
Among the most important factors known to affect the reservoir rock resistivity are temperature, porosity, permeability, salinity of contained water, degree of water saturation and abundance of clay minerals or "conductive solids". Much progress has been made by many investigators to express the effects of these variables.
