Rock type identification method based on logging curve wavelet Mallet algorithm

Abstract

The invention belongs to the technical field of geophysical logging, and a rock type identification method based on the logging curve wavelet Mallet algorithm. The rock type identification method comprises the following steps: step 1, preprocessing an original logging curve acquired in the field, step 2, analyzing logging response characteristics of the logging curve preprocessed in the step 1 todifferent lithology, and determining the logging curve sensitive to the reflection of the different lithology; 3, carrying out normalization processing on the sensitive logging curve L determined in the step 2; 4, performing Mallet decomposition of different wavelet functions and different scales on the normalized logging curve L1 in the step 3, and determining an optimal wavelet function and a decomposition scale for identifying lithology; and 5, performing lithology identification on the drill hole with the unknown lithology type according to the optimal wavelet function and the optimal decomposition scale determined in the step 4, and determining the lithology type of each interval in the drill hole.

Description

technical field [0001] The invention belongs to the technical field of geophysical well logging, and in particular relates to a rock type identification method based on well logging curve wavelet Mallet algorithm. Background technique [0002] At present, the traditional method of identifying the rock type of the formation in the borehole mainly relies on the lithology catalog of the core by geologists, but this method relies on the placement of the core by the driller. When the core is reversed or lost, it cannot Depth pinpoints rock types. With the demand of geological personnel for refined interpretation of formation lithology, some multivariate statistical analysis methods, such as neural network, Bayesian discrimination and other methods, are applied to the interpretation of formation lithology, but these methods rely on experienced logging experts, Selecting multiple logging curves based on regional characteristics to comprehensively identify rock types, and the calcu...

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Problems solved by technology

[0002] At present, the traditional method of identifying the rock type of the formation in the borehole mainly relies on the lithology catalog of the core by geologists, but this method relies on the placement of the core by the driller. When the core is reversed or lost, it cannot Depth-wise pinpoint rock type

With the demand of geological personnel for refined interpretation of formation lithology, some multivariate statistical analysis methods, such as neural network, Bayesian discrimination and other methods, are applied to the interpretation of formation lithology, but these methods rely on experienced logging experts, Select multiple well logging curves to comprehensively identify rock types according to regional characteristics, and the calculation speed is slow, which cannot meet the needs of actual field production

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