Statistical Segmentation of Geophysical Log Data

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 adj...

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Detalles Bibliográficos
Autor principal: Velis, Danilo Rubén
Formato: Articulo
Lenguaje:Inglés
Publicado: 2007
Materias:
Astronomía
Data mining
Segmentation
Zonation
Change point
Probability density function
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/139406
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-139406
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Astronomía
Data mining
Segmentation
Zonation
Change point
Probability density function
spellingShingle Astronomía
Data mining
Segmentation
Zonation
Change point
Probability density function
Velis, Danilo Rubén
Statistical Segmentation of Geophysical Log Data
topic_facet Astronomía
Data mining
Segmentation
Zonation
Change point
Probability density function
description 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.
format Articulo
Articulo
author Velis, Danilo Rubén
author_facet Velis, Danilo Rubén
author_sort Velis, Danilo Rubén
title Statistical Segmentation of Geophysical Log Data
title_short Statistical Segmentation of Geophysical Log Data
title_full Statistical Segmentation of Geophysical Log Data
title_fullStr Statistical Segmentation of Geophysical Log Data
title_full_unstemmed Statistical Segmentation of Geophysical Log Data
title_sort statistical segmentation of geophysical log data
publishDate 2007
url http://sedici.unlp.edu.ar/handle/10915/139406
work_keys_str_mv AT velisdaniloruben statisticalsegmentationofgeophysicallogdata
bdutipo_str Repositorios
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