Abstract

Geophysical logs can be used not only for qualitative interpretation such as strata correlation but also for geotechnical assessment through quantitative data analysis. In an emerging digital mining age, such a use of geophysical logs helps to establish reliable geological and geotechnical models, which reduces safety and financial risks due to geological and geotechnical uncertainty for new and existing coal mining projects. This paper presents some examples of geological and geotechnical characterizations from geophysical logs at various coal mines in Australia and India. The applications include rock strength and coal quality estimations, automated lithological/geotechnical interpretation and geophysical strata rating, all based on geophysical logs. These derived parameters could provide input to modelling, control, even ‘digital twin’ generation in a form of geological and geotechnical models as part of the future digital mining. The outcomes can be visualized in 3D space and used for identifying the key geotechnical strata units that are responsible for caving behaviors during longwall mining. This could assist site geologists and planning and production engineers predict and manage mining conditions on an ongoing basis. Both conventional logs such as density, natural gamma and sonic and less common logging data, such as full waveform sonic, televiewer and SIROLOG spectrometric natural gamma logging data are examined for their potential applications. The geotechnical strata classification and rock strengths predicted from the geophysical logs match the laboratory tests, drill core geotechnical strata classification, core photos and the mining condition/behavior observed. These illustrate the usefulness and effectiveness of using geophysical logs for geological and geotechnical characterizations.

Highlights

  • The geotechnical strata classification and rock strengths predicted from the geophysical logs match the laboratory tests, drill core geotechnical strata classification, core photos and the mining condition/behavior observed

  • Geophysical borehole logging can play an important role in the digital mining age as it can help to establish reliable geological and geotechnical models required for safe and productive mining operations

  • Conclusions paper presents various waystotouse usegeophysical geophysical borehole and their derived parameters. This This paper presents various ways boreholelogs logs and their derived parameters as input to digital mine to generate better geological and geotechnical models for safe, productive as input to digital mine to generate better geological and geotechnical models for safe, productive and beneficial mining operation

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Summary

Introduction

Geophysical borehole logging can play an important role in the digital mining age as it can help to establish reliable geological and geotechnical models required for safe and productive mining operations. We will demonstrate various applications of geophysical logs such as the estimation of the strength of intact rock or the unconfined (or uniaxial) compressive strength (UCS), geophysical strata rating and coal quality parameters. These derived parameters could provide input to modelling, control, even ‘digital twin’ generation in a form of geological and geotechnical models as part of the future digital mining. Both conventional logs such as density, natural gamma and sonic and less common logging data such as full waveform sonic, televiewer and the SIROLOG spectrometric natural gamma logging data are examined for different applications. The examples used in this paper are derived directly from research conducted in Australia and India by the authors and their collaborators

Geotechnical Characterization from Geophysical Logs
UCS Estimation from Acoustic Logs–the McNally Method
Rock Strength Evaluation from Acoustic Scanner Logs
Rock Integrity Assessment from Full-Waveform Sonic Data
Geophysical
Geophysical Strata Rating
10. The estimated porosity fromdensity densityand and clay
Automated
14. LogTrans
Coal Quality Estimation from Geophysical Logs
Findings
Conclusions
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