Investigating an innovative model for dimensional sedimentary rocks characterization using acoustic frequencies analysis during drilling

Authors

  • Mojtaba Yari Isfahan University of Technology, Department of Mining Engineering
  • Raheb Bagherpour Isfahan University of Technology, Department of Mining Engineering

DOI:

https://doi.org/10.17794/rgn.2018.2.2

Keywords:

Dimensional sedimentary rocks, geomechanical features, acoustic, Fast Fourier Transform (FFT)

Abstract

Determining geomechanical characteristics of rocks plays a significant role in all consequent designing stages of geosciences. On the other hand, drilling is one of the considerable operations in primer phases of extracting rocks. Drilling process produces acoustic signals as by-product during drilling. Then, one possible way for predicting geomechanical properties of rocks, is employing acoustic signal frequencies which are produced during drilling operation. This process helps to geoengineers for determining rock characteristics in short time and by low-cost and satisfying precision. This research tries to develop a novel computational relations between geomechanical characteristics of sedimentary rocks and produced dominant acoustic frequencies by implementing Fast Fourier Transform (FFT). For this purpose, a novel rotary drilling machine is developed by researchers. In order to introducing reliable model, 10 diverse sedimentary rock samples from various sedimentary basins of Iran are gathered in wide range of geomechanical features, and all tests are carried out on them. The results of this research could be used for sedimentary basins' characterization. Results show there are reliable mathematical relations between various characteristics of sedimentary rocks (UCS, TS, porosity and hardness) and diverse dominant frequencies.  

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Published

2018-02-23

How to Cite

Yari, M., & Bagherpour, R. (2018). Investigating an innovative model for dimensional sedimentary rocks characterization using acoustic frequencies analysis during drilling. Rudarsko-geološko-Naftni Zbornik, 33(2), 17–25. https://doi.org/10.17794/rgn.2018.2.2

Issue

Section

Mining