Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications

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Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications. / Navarro, Juan; Seidl, Thomas; Hartlieb, Philipp; Sanchidrián, José A.; Segarra, Pablo; Couceiro, Paulo; Schimek, Peter; Godoy, Clara.

In: Rock mechanics and rock engineering, Vol. 54.2021, No. June, 17.04.2021, p. 3209-3228.

Research output: Contribution to journalArticleResearchpeer-review

Harvard

Navarro, J, Seidl, T, Hartlieb, P, Sanchidrián, JA, Segarra, P, Couceiro, P, Schimek, P & Godoy, C 2021, 'Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications', Rock mechanics and rock engineering, vol. 54.2021, no. June, pp. 3209-3228. https://doi.org/10.1007/s00603-020-02354-2

APA

Author

Navarro, Juan ; Seidl, Thomas ; Hartlieb, Philipp ; Sanchidrián, José A. ; Segarra, Pablo ; Couceiro, Paulo ; Schimek, Peter ; Godoy, Clara. / Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications. In: Rock mechanics and rock engineering. 2021 ; Vol. 54.2021, No. June. pp. 3209-3228.

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@article{5acd459cf21f4a7ea26f0e7a9b5095b3,
title = "Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications",
abstract = "Blasting performance is influenced by mechanical and structural properties of the rock, on one side, and blast design parameterson the other. This paper describes a new methodology to assess rock mass quality from drill-monitoring data to guideblasting in open pit operations. Principal component analysis has been used to combine measurement while drilling (MWD)information from two drill rigs; corrections of the MWD parameters to minimize external influences other than the rockmass have been applied. First, a Structural factor has been developed to classify the rock condition in three classes (massive,fractured and heavily fractured). From it, a structural block model has been developed to simplify the recognition ofrock classes. Video recording of the inner wall of 256 blastholes has been used to calibrate the results obtained. Secondly, acombined strength-grade factor has been obtained based on the analysis of the rock type description and strength propertiesfrom geology reports, assaying of drilling chips (ore/waste identification) and 3D unmanned aerial vehicle reconstructionsof the post-blast bench face. Data from 302 blastholes, comprised of 26 blasts, have been used for this analysis. From theresults, four categories have been identified: soft-waste, hard-waste, transition zone and hard-ore. The model determineszones of soft and hard waste rock (schisted sandstone and limestone, respectively), and hard ore zones (siderite rock type).Finally, the structural block model has been combined with the strength-grade factor in an overall rock factor. This factor,exclusively obtained from drill monitoring data, can provide an automatic assessment of rock structure, strength, and waste/ore identification.",
author = "Juan Navarro and Thomas Seidl and Philipp Hartlieb and Sanchidri{\'a}n, {Jos{\'e} A.} and Pablo Segarra and Paulo Couceiro and Peter Schimek and Clara Godoy",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = apr,
day = "17",
doi = "10.1007/s00603-020-02354-2",
language = "English",
volume = "54.2021",
pages = "3209--3228",
journal = "Rock mechanics and rock engineering",
issn = "0723-2632",
publisher = "Springer Wien",
number = "June",

}

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TY - JOUR

T1 - Blastability and Ore Grade Assessment from Drill Monitoring for Open Pit Applications

AU - Navarro, Juan

AU - Seidl, Thomas

AU - Hartlieb, Philipp

AU - Sanchidrián, José A.

AU - Segarra, Pablo

AU - Couceiro, Paulo

AU - Schimek, Peter

AU - Godoy, Clara

N1 - Publisher Copyright: © 2021, The Author(s).

PY - 2021/4/17

Y1 - 2021/4/17

N2 - Blasting performance is influenced by mechanical and structural properties of the rock, on one side, and blast design parameterson the other. This paper describes a new methodology to assess rock mass quality from drill-monitoring data to guideblasting in open pit operations. Principal component analysis has been used to combine measurement while drilling (MWD)information from two drill rigs; corrections of the MWD parameters to minimize external influences other than the rockmass have been applied. First, a Structural factor has been developed to classify the rock condition in three classes (massive,fractured and heavily fractured). From it, a structural block model has been developed to simplify the recognition ofrock classes. Video recording of the inner wall of 256 blastholes has been used to calibrate the results obtained. Secondly, acombined strength-grade factor has been obtained based on the analysis of the rock type description and strength propertiesfrom geology reports, assaying of drilling chips (ore/waste identification) and 3D unmanned aerial vehicle reconstructionsof the post-blast bench face. Data from 302 blastholes, comprised of 26 blasts, have been used for this analysis. From theresults, four categories have been identified: soft-waste, hard-waste, transition zone and hard-ore. The model determineszones of soft and hard waste rock (schisted sandstone and limestone, respectively), and hard ore zones (siderite rock type).Finally, the structural block model has been combined with the strength-grade factor in an overall rock factor. This factor,exclusively obtained from drill monitoring data, can provide an automatic assessment of rock structure, strength, and waste/ore identification.

AB - Blasting performance is influenced by mechanical and structural properties of the rock, on one side, and blast design parameterson the other. This paper describes a new methodology to assess rock mass quality from drill-monitoring data to guideblasting in open pit operations. Principal component analysis has been used to combine measurement while drilling (MWD)information from two drill rigs; corrections of the MWD parameters to minimize external influences other than the rockmass have been applied. First, a Structural factor has been developed to classify the rock condition in three classes (massive,fractured and heavily fractured). From it, a structural block model has been developed to simplify the recognition ofrock classes. Video recording of the inner wall of 256 blastholes has been used to calibrate the results obtained. Secondly, acombined strength-grade factor has been obtained based on the analysis of the rock type description and strength propertiesfrom geology reports, assaying of drilling chips (ore/waste identification) and 3D unmanned aerial vehicle reconstructionsof the post-blast bench face. Data from 302 blastholes, comprised of 26 blasts, have been used for this analysis. From theresults, four categories have been identified: soft-waste, hard-waste, transition zone and hard-ore. The model determineszones of soft and hard waste rock (schisted sandstone and limestone, respectively), and hard ore zones (siderite rock type).Finally, the structural block model has been combined with the strength-grade factor in an overall rock factor. This factor,exclusively obtained from drill monitoring data, can provide an automatic assessment of rock structure, strength, and waste/ore identification.

U2 - 10.1007/s00603-020-02354-2

DO - 10.1007/s00603-020-02354-2

M3 - Article

VL - 54.2021

SP - 3209

EP - 3228

JO - Rock mechanics and rock engineering

JF - Rock mechanics and rock engineering

SN - 0723-2632

IS - June

ER -