Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study
Metamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metam...
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doaj-a849352e3e7c458ebee78d088e5f15692021-10-03T04:44:21ZengElsevierResults in Geophysical Sciences2666-82892021-12-018100030Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case studyAhmed Amara Konaté0Houalin Ma1Heping Pan2Nasir Khan3Laboratoire de Recherche Appliquée en Géoscience et Environnement, Institut Supérieur des Mines et Géologie de Boké, BP: 84, Baralandé, Tamakéné, Boké, Republic of Guinea; Corresponding author.Institute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Lumo Road 388, Postal code: 430074, Wuhan, Hubei, ChinaInstitute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Lumo Road 388, Postal code: 430074, Wuhan, Hubei, ChinaInstitute of Geophysics and Geomatics, China University of Geosciences (Wuhan), Lumo Road 388, Postal code: 430074, Wuhan, Hubei, ChinaMetamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metamorphic rocks interpretation using borehole geochemical data from the 4390–5089 m interval depth of the Chinese Continental Scientific Drilling Main hole. Lithological identification abilities, correlation between geochemical and geophysical logs, and build a factor model which link in situ chemical element to minerals were studied. The results show that Potassium and Thorium logs are the most discriminating logs in metamorphic rocks. Pearson correlation shows that Potassium and Thorium are the largest contributors to the gamma ray responses. Factor analysis results show a 2 factor model-where factor 1 (amphibole mineral) and factor 2 (K-feldspar mineral) described 76.261% of the variation in log responses. These statistical methods can be a very helpful tool in helping the task of geoscientists in the context of research drillings.http://www.sciencedirect.com/science/article/pii/S2666828921000213Metamorphic rocksGeochemical log interpretationCCSD-MHPearson correlationCross plotFactor analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ahmed Amara Konaté Houalin Ma Heping Pan Nasir Khan |
spellingShingle |
Ahmed Amara Konaté Houalin Ma Heping Pan Nasir Khan Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study Results in Geophysical Sciences Metamorphic rocks Geochemical log interpretation CCSD-MH Pearson correlation Cross plot Factor analysis |
author_facet |
Ahmed Amara Konaté Houalin Ma Heping Pan Nasir Khan |
author_sort |
Ahmed Amara Konaté |
title |
Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study |
title_short |
Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study |
title_full |
Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study |
title_fullStr |
Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study |
title_full_unstemmed |
Analysis of situ elemental concentration log data for lithology and mineralogy exploration— A case study |
title_sort |
analysis of situ elemental concentration log data for lithology and mineralogy exploration— a case study |
publisher |
Elsevier |
series |
Results in Geophysical Sciences |
issn |
2666-8289 |
publishDate |
2021-12-01 |
description |
Metamorphic rocks are diverse with more compositions, structures, and textures that are complex. Rock type identification and prediction from metamorphic rocks using well log data are difficult tasks. This study shows the use of cross plot technique, Pearson correlation, and factor analysis in metamorphic rocks interpretation using borehole geochemical data from the 4390–5089 m interval depth of the Chinese Continental Scientific Drilling Main hole. Lithological identification abilities, correlation between geochemical and geophysical logs, and build a factor model which link in situ chemical element to minerals were studied. The results show that Potassium and Thorium logs are the most discriminating logs in metamorphic rocks. Pearson correlation shows that Potassium and Thorium are the largest contributors to the gamma ray responses. Factor analysis results show a 2 factor model-where factor 1 (amphibole mineral) and factor 2 (K-feldspar mineral) described 76.261% of the variation in log responses. These statistical methods can be a very helpful tool in helping the task of geoscientists in the context of research drillings. |
topic |
Metamorphic rocks Geochemical log interpretation CCSD-MH Pearson correlation Cross plot Factor analysis |
url |
http://www.sciencedirect.com/science/article/pii/S2666828921000213 |
work_keys_str_mv |
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