Stratum capture cross section curve correction method, device and equipment

Abstract

The invention discloses a stratum capture cross section curve correction method, device and equipment, and the method comprises the steps: building a Monte Carlo calculation model of a stratum capturecross section, and analyzing an influence factor obtained by the stratum capture cross section according to the Monte Carlo calculation model; the method comprises the steps that actual well data anda capture cross section curve of a marker bed in existing bare well data are obtained, an abnormal well section in an actual well is selected according to the capture cross section curve of the marker bed, influence factors in the abnormal well section are corrected, and the marker bed comprises a pure mud rock layer and a pure water layer; and obtaining a corrected stratum capture cross sectioncurve according to the corrected abnormal well section data. On the basis of a Monte Carlo method, a marker bed method is adopted to correct influence factors, the application condition of PNN loggingis obtained, and production practice can be guided to a certain extent.

Description

technical field [0001] The invention relates to the field of PNN logging technology, in particular to a method, device, equipment and storage medium for correcting formation capture section curves. Background technique [0002] PNN logging is affected by many factors, mainly including pipe string structure, casing size, wellbore fluid, formation porosity, etc. Difficulty of extraction. In order to accurately determine the start and end of the calculation of the macroscopic capture cross section of the formation, Monte Carlo simulation method is used to simulate the above influencing factors with a single factor to understand the law of thermal neutron attenuation spectrum and guide the extraction of the macroscopic capture cross section of the formation. Through the analysis of Monte Carlo simulation results, it is found that different influencing factors have different influences on PNN logging. Through the analysis, suggestions on the extraction of formation macro-capture...

AI Technical Summary

Problems solved by technology

Since Monte Carlo is a single influencing factor analysis method, its simulation results cannot be fully consistent with the actual situation, making it difficult to solve the actual production problems in actual application.

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