The use of soft computing methods for the prediction of rock properties based on measurement while drilling data

Research output: Chapter in Book/Conference paperConference paper

Abstract

Due to recent technological advancements drilling operations conducted for different purposes such as exploration, blasting and even grouting are not considered as auxiliary operations any longer. On the contrary, nowadays onsite drilling operations are considered as important resources for getting more information about rock properties. Many researchers have been working on measurement while drilling (MWD) techniques and their possible use for the prediction of rock mass properties. This paper presents a literature survey on the use of MWD technology for the prediction of rock mass properties. The survey indicates that the analysis and interpretation of MWD data is as important as recording the data. Both blackbox modelling such as regression and soft computing or grey-box modelling techniques are used as a tool for the analysis and interpretation of MWD data. This paper presents a case study showing the integration of soft computing methods such as adaptive fuzzy inference system (ANFIS) with MWD data for the prediction of rock mass properties such as rock quality designation (RQD). The results indicated that such soft computing methods can successfully be used as an analysis and interpretation tool. Keywords: measurement while drilling (MWD), adaptive neuro fuzzy inference system (ANFIS), rock quality designation (RQD), soft computing
Original languageEnglish
Title of host publicationProceedings of the Eighth International Conference on Deep and High Stress Mining
EditorsJ Wesseloo
Place of PublicationAustralia
PublisherAustralian Centre for Geomechanics
Pages537-551
Number of pages15
ISBN (Print)9780992481063
Publication statusPublished - 2017
Event8th International Conference on Deep and High Stress Mining - Perth, Australia
Duration: 28 Mar 201730 Mar 2017

Conference

Conference8th International Conference on Deep and High Stress Mining
CountryAustralia
CityPerth
Period28/03/1730/03/17

Fingerprint

Soft computing
Drilling
Rocks
Fuzzy inference
Grouting
Adaptive systems
Blasting

Cite this

Basarir, H., Wesseloo, J., Karrech, A., Pasternak, E., & Dyskin, A. (2017). The use of soft computing methods for the prediction of rock properties based on measurement while drilling data. In J. Wesseloo (Ed.), Proceedings of the Eighth International Conference on Deep and High Stress Mining (pp. 537-551). Australia: Australian Centre for Geomechanics.
Basarir, H ; Wesseloo, J ; Karrech, A ; Pasternak, E ; Dyskin, A. / The use of soft computing methods for the prediction of rock properties based on measurement while drilling data. Proceedings of the Eighth International Conference on Deep and High Stress Mining. editor / J Wesseloo. Australia : Australian Centre for Geomechanics, 2017. pp. 537-551
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Basarir, H, Wesseloo, J, Karrech, A, Pasternak, E & Dyskin, A 2017, The use of soft computing methods for the prediction of rock properties based on measurement while drilling data. in J Wesseloo (ed.), Proceedings of the Eighth International Conference on Deep and High Stress Mining. Australian Centre for Geomechanics, Australia, pp. 537-551, 8th International Conference on Deep and High Stress Mining, Perth, Australia, 28/03/17.

The use of soft computing methods for the prediction of rock properties based on measurement while drilling data. / Basarir, H; Wesseloo, J; Karrech, A; Pasternak, E; Dyskin, A.

Proceedings of the Eighth International Conference on Deep and High Stress Mining. ed. / J Wesseloo. Australia : Australian Centre for Geomechanics, 2017. p. 537-551.

Research output: Chapter in Book/Conference paperConference paper

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AB - Due to recent technological advancements drilling operations conducted for different purposes such as exploration, blasting and even grouting are not considered as auxiliary operations any longer. On the contrary, nowadays onsite drilling operations are considered as important resources for getting more information about rock properties. Many researchers have been working on measurement while drilling (MWD) techniques and their possible use for the prediction of rock mass properties. This paper presents a literature survey on the use of MWD technology for the prediction of rock mass properties. The survey indicates that the analysis and interpretation of MWD data is as important as recording the data. Both blackbox modelling such as regression and soft computing or grey-box modelling techniques are used as a tool for the analysis and interpretation of MWD data. This paper presents a case study showing the integration of soft computing methods such as adaptive fuzzy inference system (ANFIS) with MWD data for the prediction of rock mass properties such as rock quality designation (RQD). The results indicated that such soft computing methods can successfully be used as an analysis and interpretation tool. Keywords: measurement while drilling (MWD), adaptive neuro fuzzy inference system (ANFIS), rock quality designation (RQD), soft computing

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Basarir H, Wesseloo J, Karrech A, Pasternak E, Dyskin A. The use of soft computing methods for the prediction of rock properties based on measurement while drilling data. In Wesseloo J, editor, Proceedings of the Eighth International Conference on Deep and High Stress Mining. Australia: Australian Centre for Geomechanics. 2017. p. 537-551