Investigating the acoustic signs of different rock types based on the values of acoustic signal RMS

Keywords: Acoustic Emission Techniques (AET), Rock Type Recognition, Acoustic signals, Signals RMS, Drilling operation

Abstract

Recent years have seen a vast increase in the use of acoustic waves in real-time and non-destructive detection and monitoring applications in various industries such as mining. Acoustic signal processing methods can provide accurate and reliable estimates of the condition of a process or material in a highly cost-effective way without interrupting the ongoing operations. This paper investigated whether the class of a rock and its strength properties can be estimated based solely on acoustic signals captured during the drilling operation. For this purpose, uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), Schmidt rebound number (SRN), and longitudinal wave velocity (Pw) of a series of samples of sedimentary, metamorphic and igneous rocks were measured in a rock mechanics laboratory. The samples were then subjected to a drilling test and the acoustic signal propagating in the drilling medium was recorded by an acoustic sensor. After obtaining the time spectrum of the captured signals, their RMS values were calculated and compared with the mechanical properties of the corresponding rock samples. For the rocks tested in this study, the obtained RMS values were in the range of 800 to 1,600 and generally increased with the increase of strength and hardness. The RMS values obtained for each class of rocks had their own specific range. For sedimentary rocks, this range was 800 to 1000, for metamorphic rocks, it was 1000 to 1200, and for igneous rocks, it was 1400 to 1600. Given the differences in the range of RMS values obtained from the acoustic signals of drilling, these values can be used in the estimation of rock class and strength properties. These results show that there is significant potential for the future use of this approach in the industry for field identification and classification of rocks, especially in deep drilling operations or when there is little information about the characteristics of the rock being drilled.

Published
2020-04-28
How to Cite
Khoshouei, M., Bagherpour, R., Jalalian, M. H., & Yari, M. (2020). Investigating the acoustic signs of different rock types based on the values of acoustic signal RMS. Rudarsko-geološko-Naftni Zbornik, 35(3). Retrieved from https://hrcak.srce.hr/ojs/index.php/rgn/article/view/10557
Section
Mining