Study on automatic lithology identification method while drilling based on acoustic pressure-rock physics parameters mapping
Wei Jiang, Qingfeng Wang, Baoyong Yan, Yang Liu, Shuhan Shi, Hong Fu
TL;DR
This study introduces a new method for automatically identifying rock types during drilling using the relationship between acoustic pressure and rock properties, improving coal mine exploration.
Contribution
A novel automatic lithology identification method based on acoustic pressure-rock physics mapping is proposed.
Findings
The method achieved recognition accuracies of 47% to 71% for various rock types.
Acoustic pressure is an effective feature for identifying drilling lithology.
The algorithm remains effective even in the presence of a perforated transition zone.
Abstract
The lithology identification while drilling is a critical component of intelligent coal mine exploration. Investigating automatic lithology identification methods is of great significance for enhancing reservoir prediction accuracy and the automation level of drilling exploration. This study proposes a novel method for automatic lithology identification while drilling based on the mapping relationship between acoustic pressure and rock physics parameters. First, core samples were collected from an operational mine borehole to prepare homogeneous (single lithology) and layered (composite lithology) rock specimens, providing reliable materials for drilling experiments. Second, a full-scale laboratory drilling system was designed and constructed, providing a robust dataset for time-frequency analysis with strong engineering applicability. Furthermore, a quantitative fitting model between…
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Taxonomy
TopicsRock Mechanics and Modeling · Hydrocarbon exploration and reservoir analysis · Drilling and Well Engineering