Statistical Segmentation of Geophysical Log Data |
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Authors: | Danilo R Velis |
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Institution: | (1) Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, La Plata, Argentina;(2) CONICET, Paseo del Bosque s/n, B1900FWA La Plata, Argentina |
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Abstract: | 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. |
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Keywords: | Data mining Segmentation Zonation Change point Probability density function |
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