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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Main Authors: Ahmed Amara Konaté, Houalin Ma, Heping Pan, Nasir Khan
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Results in Geophysical Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666828921000213
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spelling 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
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