A New Method for Response Correction of Thin Layer Resistivity Logging

Abstract

The invention belongs to the technical field of resistivity log, and particularly relates to a novel thin bed resistivity log response correction method. The method comprises the following steps of: A, calculating a longitudinal geometric factor of a thin bed resistivity log curve; B, calculating a total receipt signal of the thin bed resistivity log curve according to the longitudinal geometric factor and a thin bed conductivity; C, establishing a thin bed resistivity log response quantitative correction model and deducing a corresponding correction formula; D, carrying out point-by-point correction on a thin bed actually measured resistivity log curve by selecting a suitable correction formula; and E, drawing a corrected thin bed resistivity log curve. According to the method, a geometric factor correction model is established through analyzing thin bed geometric factors; a novel thin bed resistivity correction method is given; and the novel method is capable of obtaining more real resistivity of thin beds, improving log interpretation precision of the thin beds, laying a solid foundation for the calculation of parameters such as oil saturation and the like of the thin beds, and avoiding the loss of thin oil pays with industrial mining value.

Description

technical field [0001] The invention relates to a new method for correcting response of thin layer resistivity logging, which belongs to the technical field of resistivity logging. Background technique [0002] The resistivity logging response is an important basis for judging oil and gas water layers, qualitatively analyzing lithology, determining the diameter of mud invasion zones, and calculating the oil saturation of reservoirs. Resistivity information over a large formation range. Therefore, the measured value of the resistivity of the thin layer must be affected by the upper and lower surrounding rocks and other environmental factors, and the resulting errors are enough to interfere with the evaluation of lithology and fluid properties, and bring large errors to the calculation of parameters such as oil saturation. The main reason affecting the success rate of thin layer evaluation is that the well logging curve with large detection depth has poor vertical resolution,...

AI Technical Summary

Problems solved by technology

Although various high-resolution logging tools, high-resolution processing techniques, and fine interpretation techniques have emerged one after another, none of them are absolutely effective. There is a large error between the measured sheet resistivity and the real resistivity, which seriously affects the measured Well interpretation accuracy, resulting in many thin oil layers with industrial value not being discovered

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