Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy

Measurement while drilling (MWD) data are gathered during drilling operations and can provide information about the strength of the rock penetrated by the boreholes. In this paper MWD data from a marble open-pit operation in northern Norway are studied. The rock types are represented by discrete cla...

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Published in:Minerals
Main Authors: Sajith Vezhapparambu, Veena, Eidsvik, Jo, Ellefmo, Steinar Løve
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2018
Subjects:
Online Access:http://hdl.handle.net/11250/2586946
https://doi.org/10.3390/min8090384
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2586946 2023-05-15T17:43:33+02:00 Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy Sajith Vezhapparambu, Veena Eidsvik, Jo Ellefmo, Steinar Løve 2018 http://hdl.handle.net/11250/2586946 https://doi.org/10.3390/min8090384 eng eng MDPI Norges forskningsråd: 236638 Minerals. 2018, 8 (9), . urn:issn:2075-163X http://hdl.handle.net/11250/2586946 https://doi.org/10.3390/min8090384 cristin:1637312 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no CC-BY 23 8 Minerals 9 Journal article Peer reviewed 2018 ftntnutrondheimi https://doi.org/10.3390/min8090384 2019-09-17T06:54:33Z Measurement while drilling (MWD) data are gathered during drilling operations and can provide information about the strength of the rock penetrated by the boreholes. In this paper MWD data from a marble open-pit operation in northern Norway are studied. The rock types are represented by discrete classes, and the data is then modeled by a hidden Markov model (HMM). Results of using different MWD data variables are studied and presented. These results are compared and co-interpreted with optical televiewer (OTV) images, magnetic susceptibility and spectral gamma values collected in the borehole using down-the-hole sensors. A model with penetration rate, rotation pressure and dampening pressure data show a good visual correlation with OTV image for the studied boreholes. The marble class is characterized by medium penetration rate and medium rotation pressure, whereas the intrusions are characterized by low penetration rate and medium to high rotation pressure. The fractured marble is characterized by high penetration rate, high rotation and low dampening pressure. Future research will use the presented results to develop a heterogeneity index, develop an MWD-based 3D-geology model and an improved sampling strategy and investigate how to implement this in the mine planning process and reconciliation. publishedVersion (C) 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Article in Journal/Newspaper Northern Norway NTNU Open Archive (Norwegian University of Science and Technology) Norway Minerals 8 9 384
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
description Measurement while drilling (MWD) data are gathered during drilling operations and can provide information about the strength of the rock penetrated by the boreholes. In this paper MWD data from a marble open-pit operation in northern Norway are studied. The rock types are represented by discrete classes, and the data is then modeled by a hidden Markov model (HMM). Results of using different MWD data variables are studied and presented. These results are compared and co-interpreted with optical televiewer (OTV) images, magnetic susceptibility and spectral gamma values collected in the borehole using down-the-hole sensors. A model with penetration rate, rotation pressure and dampening pressure data show a good visual correlation with OTV image for the studied boreholes. The marble class is characterized by medium penetration rate and medium rotation pressure, whereas the intrusions are characterized by low penetration rate and medium to high rotation pressure. The fractured marble is characterized by high penetration rate, high rotation and low dampening pressure. Future research will use the presented results to develop a heterogeneity index, develop an MWD-based 3D-geology model and an improved sampling strategy and investigate how to implement this in the mine planning process and reconciliation. publishedVersion (C) 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
format Article in Journal/Newspaper
author Sajith Vezhapparambu, Veena
Eidsvik, Jo
Ellefmo, Steinar Løve
spellingShingle Sajith Vezhapparambu, Veena
Eidsvik, Jo
Ellefmo, Steinar Løve
Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
author_facet Sajith Vezhapparambu, Veena
Eidsvik, Jo
Ellefmo, Steinar Løve
author_sort Sajith Vezhapparambu, Veena
title Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
title_short Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
title_full Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
title_fullStr Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
title_full_unstemmed Rock Classification Using Multivariate Analysis of Measurement While Drilling Data: Towards a Better Sampling Strategy
title_sort rock classification using multivariate analysis of measurement while drilling data: towards a better sampling strategy
publisher MDPI
publishDate 2018
url http://hdl.handle.net/11250/2586946
https://doi.org/10.3390/min8090384
geographic Norway
geographic_facet Norway
genre Northern Norway
genre_facet Northern Norway
op_source 23
8
Minerals
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op_relation Norges forskningsråd: 236638
Minerals. 2018, 8 (9), .
urn:issn:2075-163X
http://hdl.handle.net/11250/2586946
https://doi.org/10.3390/min8090384
cristin:1637312
op_rights Navngivelse 4.0 Internasjonal
http://creativecommons.org/licenses/by/4.0/deed.no
op_rightsnorm CC-BY
op_doi https://doi.org/10.3390/min8090384
container_title Minerals
container_volume 8
container_issue 9
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