Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis

Detalhes bibliográficos
Autor(a) principal: YENICE,HAYATI
Data de Publicação: 2019
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500906
Resumo: Abstract: Drillability is influenced by many factors, including machine parameters and rock properties. The main machine parameters for drilling include rotational speed, thrust force, torque and flush pressure. The specific rock characteristics that affect penetration rate comprise uniaxial compressive strength (UCS), tensile strength, Young’s modulus, hardness and brittleness. In this study, drilling rate index (DRI) is attempted to predict based on UCS and Brazilian tensile strength (BTS) of rocks. Simple and multiple regression analyses have been carried out to determine the best measure of the relation between DRI and two geomechanical properties. The DRI value is strongly related to the uniaxial compressive strength and indirect tensile strength. However, when the uniaxial compressive strength and tensile strength of rock are jointly considered, the correlation coefficient increases. The relationship between the geomechanical properties (UCS, BTS) and the DRI were determined using multiple regression analysis. Strong relationships were obtained from these analyses for the rock strength (UCS) above and below 100 MPa with the correlation coefficients 0.81 and 0.88 respectively.The results of the regression analyses show that for more precise prediction of DRI, rocks should be classified according to their strength.
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spelling Determination of Drilling Rate Index Based on Rock Strength Using Regression AnalysisDrillabilityuniaxial compressive strengthtensile strengthregression analysisAbstract: Drillability is influenced by many factors, including machine parameters and rock properties. The main machine parameters for drilling include rotational speed, thrust force, torque and flush pressure. The specific rock characteristics that affect penetration rate comprise uniaxial compressive strength (UCS), tensile strength, Young’s modulus, hardness and brittleness. In this study, drilling rate index (DRI) is attempted to predict based on UCS and Brazilian tensile strength (BTS) of rocks. Simple and multiple regression analyses have been carried out to determine the best measure of the relation between DRI and two geomechanical properties. The DRI value is strongly related to the uniaxial compressive strength and indirect tensile strength. However, when the uniaxial compressive strength and tensile strength of rock are jointly considered, the correlation coefficient increases. The relationship between the geomechanical properties (UCS, BTS) and the DRI were determined using multiple regression analysis. Strong relationships were obtained from these analyses for the rock strength (UCS) above and below 100 MPa with the correlation coefficients 0.81 and 0.88 respectively.The results of the regression analyses show that for more precise prediction of DRI, rocks should be classified according to their strength.Academia Brasileira de Ciências2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500906Anais da Academia Brasileira de Ciências v.91 n.3 2019reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765201920181095info:eu-repo/semantics/openAccessYENICE,HAYATIeng2019-10-09T00:00:00Zoai:scielo:S0001-37652019000500906Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2019-10-09T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
title Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
spellingShingle Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
YENICE,HAYATI
Drillability
uniaxial compressive strength
tensile strength
regression analysis
title_short Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
title_full Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
title_fullStr Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
title_full_unstemmed Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
title_sort Determination of Drilling Rate Index Based on Rock Strength Using Regression Analysis
author YENICE,HAYATI
author_facet YENICE,HAYATI
author_role author
dc.contributor.author.fl_str_mv YENICE,HAYATI
dc.subject.por.fl_str_mv Drillability
uniaxial compressive strength
tensile strength
regression analysis
topic Drillability
uniaxial compressive strength
tensile strength
regression analysis
description Abstract: Drillability is influenced by many factors, including machine parameters and rock properties. The main machine parameters for drilling include rotational speed, thrust force, torque and flush pressure. The specific rock characteristics that affect penetration rate comprise uniaxial compressive strength (UCS), tensile strength, Young’s modulus, hardness and brittleness. In this study, drilling rate index (DRI) is attempted to predict based on UCS and Brazilian tensile strength (BTS) of rocks. Simple and multiple regression analyses have been carried out to determine the best measure of the relation between DRI and two geomechanical properties. The DRI value is strongly related to the uniaxial compressive strength and indirect tensile strength. However, when the uniaxial compressive strength and tensile strength of rock are jointly considered, the correlation coefficient increases. The relationship between the geomechanical properties (UCS, BTS) and the DRI were determined using multiple regression analysis. Strong relationships were obtained from these analyses for the rock strength (UCS) above and below 100 MPa with the correlation coefficients 0.81 and 0.88 respectively.The results of the regression analyses show that for more precise prediction of DRI, rocks should be classified according to their strength.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500906
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500906
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765201920181095
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.91 n.3 2019
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
instacron_str ABC
institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
repository.name.fl_str_mv Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)
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