Measurement-while-drilling technique and its scope in design and prediction of rock blasting

Rai, Piyush; Schunnesson, Håkan; Lindqvist, Per-Arne; Kumar, Uday

doi:10.1016/j.ijmst.2016.05.025

Cited by 23 publications

(5 citation statements)

References 13 publications

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“…The flushing medium is used to remove the cuttings from the hole and its pressure (kg/cm 2 ) varies based on the structure of rock mass, such as joints, fracture zones and joint fillings (Mozaffari 2007). It is claimed that the records of flushing pressure variation, and their calibration with changing ground conditions, can be used for detecting discontinuities (Rai et al 2016). Guzek et al (2015) noticed that the vibration can depend on the drill string stiffness and the flushing fluid rheology.…”

Section: Flushing Medium Pressurementioning

confidence: 99%

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

Başarır¹,

Wesseloo²,

Karrech³

et al. 2017

Proceedings of the International Conference on Deep and High Stress Mining

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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.

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Section: Flushing Medium Pressurementioning

confidence: 99%

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

Başarır¹,

Wesseloo²,

Karrech³

et al. 2017

Proceedings of the International Conference on Deep and High Stress Mining

View full text Add to dashboard Cite

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“…With extensive application of nearly-horizontal drilling equipment in the coal mining industry, in for example the gas drainage, the water detection, and the coal bed methane exploitation, directional drilling technology has made a great development [1][2][3][4][5][6]. In particular, the equipment used for monitoring the state of the borehole and measuring the trajectory of the borehole have been an intensive research subject in recent decades [1].…”

Section: Introductionmentioning

confidence: 99%

“…The core of underground in-seam directional drilling technology is exactly this equipment, namely the Measurement-While-Drilling (MWD) instrument. Many scholars have focused on improving the detection function of this instrument to avoid coal mine disasters, such as measuring vibrations to prevent rock bursts [2][3][4][5], while ignoring the measurement of the borehole trajectory itself. Rebuilding the borehole trajectory aims to guide the bottom drilling tool along a predefined line, which is very important during the drilling process [7].…”

Section: Introductionmentioning

confidence: 99%

A Designed Calibration Approach for the Measurement-While-Drilling Instrument

et al. 2022

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The Measurement-While-Drilling (MWD) system, composed of a tri-axial magnetometer and a tri-axial accelerometer, is widely used in the Horizontal Directional Drilling machine in coal mines. This system can provide attitude information of each measuring point in the borehole, which will eventually allow the trajectory of the borehole to be drawn. The attitude information, however, showed a low-level accuracy, due to the sensor’s imperfection and mounting errors. The accuracy worsened when low-cost sensors were employed, as they had higher random noise. Therefore, an exploration of ways to eliminate the sensor imperfection and mounting tolerance as well as to suppress the noise is needed. In this paper, a feasible calibration approach was designed to address these issues. This new approach combined three foundational calibration algorithms, including the ellipsoidal fitting method, the planar fitting method, and the inner product invariance method. The traditional ellipsoidal fitting method and planar fitting method were optimized by using the recursive least square criterion and omitting the steps of sample data acquisition, respectively. In addition, the noise suppression method was involved in our approach to improve the calibration accuracy. The numerical simulation results showed that the number of sampling points decreased significantly, but the accuracy of the azimuthal angle and the pitch angle fully met the engineering requirements. The experimental results showed that the pitch angle error was reduced by less than 0.5°, and the azimuth error was also reduced by less than 2.5°. It should be noted that this new approach could be implemented without the help of other expensive auxiliary equipment.

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“…Measurement-while-drilling (MWD) of blast holes produces data that contain information about the geo-mechanical properties at higher spatial resolution than the exploration data. This may be used for improving the blast plans and for optimizing the subsequent processes [10][11][12]. Drilling and blasting are conducted in cycles, each cycle producing a volume of fragmented rock that is loaded using bucket excavators or load-haul-dump trucks before the next blasting.…”

Section: Introductionmentioning

confidence: 99%

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

2021

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Systems for transport and processing of granular media are challenging to analyse, operate and optimise. In the mining and mineral processing industries, these systems are chains of processes with a complex interplay among the equipment, control and processed material. The material properties have natural variations that are usually only known at certain locations. Therefore, we explored a material-oriented approach to digital twins with a particle representation of the granular media. In digital form, the material is treated as pseudo-particles, each representing a large collection of real particles of various sizes, shapes and mineral properties. Movements and changes in the state of the material are determined by the combined data from control systems, sensors, vehicle telematics and simulation models at locations where no real sensors could see. The particle-based representation enables material tracking along the chain of processes. Each digital particle can act as a carrier of observational data generated by the equipment as it interacts with the real material. This make it possible to better learn the material properties from process observations and to predict the effect on downstream processes. We tested the technique on a mining simulator and demonstrated the analysis that can be performed using data from cross-system material tracking.

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Measurement-while-drilling technique and its scope in design and prediction of rock blasting

Cited by 23 publications

References 13 publications

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

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

A Designed Calibration Approach for the Measurement-While-Drilling Instrument

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

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