Abstract: The fluctuation of interval transit time data can be caused by factors such as variable formation lithology which affects the accurate identification of abnormally compacted strata by interval transit time. Therefore, the fluctuation of interval transit time data in normally compacted sections was analyzed according to the relationship between the interval transit time and well depth at normally compacted mudstone section, by eliminating the invalid data points using a density data clustering method, made possible by means of wavelet theory and the probability analysis method. Research results showed that the density clustering method could effectively remove the anomalous data points. One wavelet decomposition could meet the requirement to describe the fluctuation of interval transit time data at the normally compacted section; the distribution fitting test indicated that the fluctuation of interval transit time data was consistent with tLocation–Scale probability distribution. Thus the abnormally compacted section could be quantitatively identified by constructing a probability calculation formula. The calculation results showed that the abnormally compacted section could be quantitatively identified by calculating the fluctuation probability of interval transit time, improve the identification accuracy of abnormally compacted section, and avoid the blindness and randomness of analysis. Similar analyses can be performed for other conventional logging data analyses based on the normal compaction curve of shale.