Abstract
The use of electrical well logs for the quantitative determination of suchreservoir parameters as connate water saturation, formation permeability andconnate water salinity has recently been attracting the attention of a numberof workers. While the theory of the determination of connate water salinity from theself potential S.P. log has received rather detailed treatment, relativelylittle attention has been paid to the theoretical aspects involved in thequantitative interpretation of resistivity data. It is clear that if electricalwell logs can be used for the quantitative evaluation of physicalcharacteristics of reservoir rock, they will provide a valuable tool tosupplement cheaply information obtained by more laborious core analysis. Incertain cases it is conceivable that the coring program could be considerablycurtailed if the electric log could be relied upon to give reasonably accuratequantitative information. It is our object in this paper to examine the theoretical basis ofquantitative log interpretation as expressed in such well-established loggingconcepts as formation factor and cementation factor. It is also our object toinvestigate the physical aspects of the relationship which is presumed to existbetween resistivity index and brine saturation in reservoir rock. Inparticular, we will endeavor to draw attention to the fact that it is possibleto express these logging concepts in terms of capillary pressure-saturationrelationships, permeability and tortuosity parameters which we will consider inthis paper to be fundamentally indicative of rock texture. The probability ofbeing able to obtain from log recordings alone the data theoretically essentialto permit quantitative log interpretation will be examined, and considerationwill also be given to the problem of formulating simple semiempiricalrelationships for use in the field.
Cite
CITATION STYLE
Wyllie, M. R. J., & Rose, W. D. (1950). Some Theoretical Considerations Related To The Quantitative Evaluation Of The Physical Characteristics Of Reservoir Rock From Electrical Log Data. Journal of Petroleum Technology, 2(04), 105–118. https://doi.org/10.2118/950105-g
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