Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland

We use self-organizing map (SOM) analysis to predict missing seismic velocity values from other available borehole data. The site of this study is the Kevitsa Ni-Cu-PGE deposit within the mafic-ultramafic Kevitsa intrusion in northern Finland. The site has been the target of extensive seismic reflec...

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Published in:Minerals
Main Authors: Niina Junno, Emilia Koivisto, Ilmo Kukkonen, Alireza Malehmir, Markku Montonen
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2019
Subjects:
Online Access:https://doi.org/10.3390/min9090529
https://doaj.org/article/c6cfb8ab5588453ea1d6886bc0b2bc60
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spelling ftdoajarticles:oai:doaj.org/article:c6cfb8ab5588453ea1d6886bc0b2bc60 2024-10-29T17:46:21+00:00 Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland Niina Junno Emilia Koivisto Ilmo Kukkonen Alireza Malehmir Markku Montonen 2019-08-01T00:00:00Z https://doi.org/10.3390/min9090529 https://doaj.org/article/c6cfb8ab5588453ea1d6886bc0b2bc60 EN eng MDPI AG https://www.mdpi.com/2075-163X/9/9/529 https://doaj.org/toc/2075-163X doi:10.3390/min9090529 https://doaj.org/article/c6cfb8ab5588453ea1d6886bc0b2bc60 Minerals, Vol 9, Iss 9, p 529 (2019) self-organizing map missing data geophysical borehole data seismic interpretation Mineralogy QE351-399.2 article 2019 ftdoajarticles https://doi.org/10.3390/min9090529 2024-10-09T17:27:40Z We use self-organizing map (SOM) analysis to predict missing seismic velocity values from other available borehole data. The site of this study is the Kevitsa Ni-Cu-PGE deposit within the mafic-ultramafic Kevitsa intrusion in northern Finland. The site has been the target of extensive seismic reflection surveys, which have revealed a series of reflections beneath the Kevitsa resource area. The interpretation of these reflections has been complicated by disparate borehole data, particularly because of the scarce amount of available sonic borehole logs and the varying practices in logging of borehole lithologies. SOM is an unsupervised data mining method based on vector quantization. In this study, SOM is used to predict missing seismic velocities from other geophysical, geochemical, geological, and geotechnical data. For test boreholes, for which measured seismic velocity logs are also available, the correlation between actual measured and predicted velocities is strong to moderate, depending on the parameters included in the SOM analysis. Predicted reflectivity logs, based on measured densities and predicted velocities, show that some contacts between olivine pyroxenite/olivine websterite-dominant host rocks of the Kevitsa disseminated sulfide mineralization—and metaperidotite—earlier extensively used “lithology” label that essentially describes various degrees of alteration of different olivine pyroxenite variants—are reflective, and thus, alteration can potentially cause reflectivity within the Kevitsa intrusion. Article in Journal/Newspaper Northern Finland Directory of Open Access Journals: DOAJ Articles Minerals 9 9 529
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic self-organizing map
missing data
geophysical borehole data
seismic interpretation
Mineralogy
QE351-399.2
spellingShingle self-organizing map
missing data
geophysical borehole data
seismic interpretation
Mineralogy
QE351-399.2
Niina Junno
Emilia Koivisto
Ilmo Kukkonen
Alireza Malehmir
Markku Montonen
Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
topic_facet self-organizing map
missing data
geophysical borehole data
seismic interpretation
Mineralogy
QE351-399.2
description We use self-organizing map (SOM) analysis to predict missing seismic velocity values from other available borehole data. The site of this study is the Kevitsa Ni-Cu-PGE deposit within the mafic-ultramafic Kevitsa intrusion in northern Finland. The site has been the target of extensive seismic reflection surveys, which have revealed a series of reflections beneath the Kevitsa resource area. The interpretation of these reflections has been complicated by disparate borehole data, particularly because of the scarce amount of available sonic borehole logs and the varying practices in logging of borehole lithologies. SOM is an unsupervised data mining method based on vector quantization. In this study, SOM is used to predict missing seismic velocities from other geophysical, geochemical, geological, and geotechnical data. For test boreholes, for which measured seismic velocity logs are also available, the correlation between actual measured and predicted velocities is strong to moderate, depending on the parameters included in the SOM analysis. Predicted reflectivity logs, based on measured densities and predicted velocities, show that some contacts between olivine pyroxenite/olivine websterite-dominant host rocks of the Kevitsa disseminated sulfide mineralization—and metaperidotite—earlier extensively used “lithology” label that essentially describes various degrees of alteration of different olivine pyroxenite variants—are reflective, and thus, alteration can potentially cause reflectivity within the Kevitsa intrusion.
format Article in Journal/Newspaper
author Niina Junno
Emilia Koivisto
Ilmo Kukkonen
Alireza Malehmir
Markku Montonen
author_facet Niina Junno
Emilia Koivisto
Ilmo Kukkonen
Alireza Malehmir
Markku Montonen
author_sort Niina Junno
title Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
title_short Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
title_full Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
title_fullStr Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
title_full_unstemmed Predicting Missing Seismic Velocity Values Using Self-Organizing Maps to Aid the Interpretation of Seismic Reflection Data from the Kevitsa Ni-Cu-PGE Deposit in Northern Finland
title_sort predicting missing seismic velocity values using self-organizing maps to aid the interpretation of seismic reflection data from the kevitsa ni-cu-pge deposit in northern finland
publisher MDPI AG
publishDate 2019
url https://doi.org/10.3390/min9090529
https://doaj.org/article/c6cfb8ab5588453ea1d6886bc0b2bc60
genre Northern Finland
genre_facet Northern Finland
op_source Minerals, Vol 9, Iss 9, p 529 (2019)
op_relation https://www.mdpi.com/2075-163X/9/9/529
https://doaj.org/toc/2075-163X
doi:10.3390/min9090529
https://doaj.org/article/c6cfb8ab5588453ea1d6886bc0b2bc60
op_doi https://doi.org/10.3390/min9090529
container_title Minerals
container_volume 9
container_issue 9
container_start_page 529
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