Stationary segments in well log sequences can be automatically detected by searching for change points in the data. These change points, which correspond to abrupt changes in the statistical nature of the underlying process, can be identified by analysing the probability density functions of two adjacent sub-samples as they move along the data sequence. A statistical test is used to set a significance level of the probability that the two distributions are the same, thus providing a means to decide how many segments comprise the data by keeping those change points that yield low probabilities. Data from the Ocean Drilling Program were analysed, where a high correlation between the available core-log lithology interpretation and the statistical segmentation was observed. Results show that the proposed algorithm can be used as an auxiliary tool in the analysis and interpretation of geophysical log data for the identification of lithology units and sequences.Facultad de Ciencias Astronómicas y Geofísicas