Method for reconstructing logging curve

Abstract

The invention discloses a method for reconstructing a logging curve, and relates to the technical field of exploration and development of petroleum and natural gas. The method comprises the steps of collecting general logging materials of a well adjacent to a target well; selecting a standard layer of a target curve; building a multi-regression model including linearity, index, logarithm and power function; acquiring a corresponding multi-regression equation; calculating the correlation between the target curve of the standard layer and other curves; selecting a base curve for reconstructing the target curve; selecting the optimal multi-regression model based on the selected base curve and according to the maximum correlation principle; deducing the corresponding multi-regression equation; substituting the regression constants, coefficients and the base curve value into the multi-regression equation at the well section suffering from deletion or distortion of the target curve, so as to finish the reconstruction of the target curve. According to the method, the logging curve can be quickly and accurately reconstructed; the operation is simple and convenient; the popularization is easily carried out; the field construction applies, and geological personnel can quick evaluate the stratum information.

Description

technical field [0001] The invention relates to the technical field of oil and gas exploration and development, in particular to a method for reconstructing logging curves. Background technique [0002] In the process of logging while drilling, the quality of the measured acoustic time difference is often unsatisfactory due to drilling tool vibration, eccentricity, cuttings collision, etc., so acoustic logging while drilling cannot be performed in most oil fields (especially production wells). Mass promotion. However, acoustic transit time curves play an extremely important role in reservoir evaluation operations such as reservoir identification, gas layer evaluation, fracture identification, and formation pressure monitoring, so the construction of acoustic transit time while drilling is particularly important. The method is mainly to use the wells with complete logging series in the work area to try to establish the mathematical relationship between the logging curves and...

AI Technical Summary

Problems solved by technology

However, the application of this technology is still based on the multiple linear regression method. Due to the complex relationship between the physical properties of formation rocks, it is difficult to describe the correlation properties between them only by linear regression.

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