An automatic RQD analysis method based on borehole image edge threshold segmentation

Rock quality designation (RQD) serves as a key indicator for assessing rock mass integrity. Conventional approaches are significantly influenced by factors such as drilling procedures, core conditions, and run lengths, often leading to results that do not accurately represent actual rock mass quality. To address this limitation, an automated technique for RQD analysis utilizing edge threshold segmentation on borehole imagery is introduced. Initially, borehole images undergo preprocessing followed by edge threshold segmentation to facilitate target identification. Subsequently, the identified target regions are labeled, and adjacent connected areas are combined to isolate the features relevant to RQD evaluation. The final step involves extracting the positions and widths of structural planes and fracture zones, enabling RQD computation for the boreholes. In a case study conducted at the Guxian Water Control Project on the Yellow River, the method is demonstrated on two boreholes, yielding results closely matching both the borehole imagery and the rock mass integrity coefficient. This approach enhances the precision of RQD estimation, expands the data available for RQD determination, and offers a rapid and efficient tool for rock mass integrity assessment.