Statistical Segmentation of Geophysical Log Data
- Autores
- Velis, Danilo Rubén
- Año de publicación
- 2007
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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 - Materia
-
Astronomía
Data mining
Segmentation
Zonation
Change point
Probability density function - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/139406
Ver los metadatos del registro completo
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Statistical Segmentation of Geophysical Log DataVelis, Danilo RubénAstronomíaData miningSegmentationZonationChange pointProbability density functionStationary 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 Geofísicas2007-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf409-417http://sedici.unlp.edu.ar/handle/10915/139406enginfo:eu-repo/semantics/altIdentifier/issn/0882-8121info:eu-repo/semantics/altIdentifier/issn/1573-8868info:eu-repo/semantics/altIdentifier/doi/10.1007/s11004-007-9103-yinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:14:46Zoai:sedici.unlp.edu.ar:10915/139406Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:14:46.961SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Statistical Segmentation of Geophysical Log Data |
title |
Statistical Segmentation of Geophysical Log Data |
spellingShingle |
Statistical Segmentation of Geophysical Log Data Velis, Danilo Rubén Astronomía Data mining Segmentation Zonation Change point Probability density function |
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 |
dc.creator.none.fl_str_mv |
Velis, Danilo Rubén |
author |
Velis, Danilo Rubén |
author_facet |
Velis, Danilo Rubén |
author_role |
author |
dc.subject.none.fl_str_mv |
Astronomía Data mining Segmentation Zonation Change point Probability density function |
topic |
Astronomía Data mining Segmentation Zonation Change point Probability density function |
dc.description.none.fl_txt_mv |
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 |
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. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/139406 |
url |
http://sedici.unlp.edu.ar/handle/10915/139406 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/0882-8121 info:eu-repo/semantics/altIdentifier/issn/1573-8868 info:eu-repo/semantics/altIdentifier/doi/10.1007/s11004-007-9103-y |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
dc.format.none.fl_str_mv |
application/pdf 409-417 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) |
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SEDICI (UNLP) |
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Universidad Nacional de La Plata |
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UNLP |
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UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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alira@sedici.unlp.edu.ar |
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13.001348 |