The internal cracks of concrete are very important in the safety evaluation of structures, but there is a lack of fine characterization methods at present. Borehole cameras are a piece of in situ borehole detection technology which can measure the structural elements of a borehole wall with high precision. In this paper, borehole camera technology is used to measure the concrete cracks of a tunnel floor, and the morphological characteristics (depth, width, and orientation) of the cracks are analyzed. The results show that the average extension depth of the crack extending from the orifice exceeds 1.195 m, and the width decreases with the increase in depth. The crack orientation is basically stable, with the maximum deviation of 19° at the orifice of different boreholes and 30° at different depths of the same borehole. The crack inside the concrete (not extending to the orifice) usually has a small extension depth and a relatively stable width, but the crack orientation changes greatly. The coarse aggregate and concrete interface have different effects on the extension direction of cracks. This paper also conducted a second measurement on two of the boreholes after an interval of 15 days, and found the difference in crack development in the two measurements. The work of this paper provides a new attempt for the detection and monitoring of concrete crack morphology.

In situ measurement and analysis of pores are helpful to understand the properties of rocks. However, continuous quantitative analysis of pores in whole borehole is still difficult. Borehole camera technology can capture the borehole wall image of the whole well section by going deep into the borehole, which provides technical conditions for the measurement and analysis of pores. In this paper, a continuous measurement method of rock pores based on borehole camera technology is introduced. According to the characteristics of the optical image of borehole wall, a method of pore recognition and analysis is proposed. Specifically, the influence of redundant information on pore recognition is eliminated, and then the pores are accurately recognized by binarization and morphological operation. Based on the results of pore recognition and the coordinate information provided by borehole wall image, the calculation methods of surface porosity and line porosity are proposed, and the statistical analysis of pore distribution is realized according to the calculation results. In addition, the morphological characteristics of pores are also discussed. This method realizes the accurate recognition and quantitative calculation of pore structure based on borehole wall image, and provides a new method for continuous analysis of pore structure in the whole well.

This study proposes a method that uses image processing technology to identify, calculate, and analyze the pore structure in hole wall images. First, the R, B, and G components of a hole wall image are adjusted on the basis of an appropriate threshold to eliminate the effects of drilling fluid attached to the hole wall. Second, the hole wall image is converted into an S component image in the HSV color space to distinguish the pores and dark gray texture of the rock. Third, the best segmentation threshold of the S component image is obtained by the maximum interclass variance method, and the threshold is used to binarize the S component image. Finally, mathematical morphological operations are performed on the binary image to eliminate defects. On the basis of the identified pore structure in the hole wall image, the surface porosity of the rock can be calculated, and the pore distribution characteristics can be further analyzed. The results of this work provide ideas for measuring the porosity of deep rocks and analyzing their pore distribution.

The structural plane is a geological interface of a particular scale, and how to determine the extension of the structural plane in space is an essential issue in the study of rock structure. This paper analyses the structural plane information of multiple boreholes collected by the digital panoramic borehole camera system to determine the structural plane consistency. The discriminative conditions of structural plane consistency in multiple boreholes are deduced through mathematical analysis methods such as spatial geometry and vector. The structural planes that may be connected are quickly screened out. The consistency is further judged by combining the relevant characteristics of the structural planes, thus forming a complete method based on digital borehole images. The method has been validated by a series of indoor tests. Structural planes with specific parameters were presented in the test blocks in these tests, and several boreholes were drilled. The experimental results show that (1) the structural plane consistency discrimination method can be applied to both flat structural planes and structural planes with certain undulation angles and roughness; (2) the tilt of the borehole does not affect the structural plane consistency using the borehole camera, and the structural plane consistency can be judged by this method in any two boreholes in space; and (3) the analysis method proposed in this paper can quickly complete the structural plane consistency discrimination, and is also suitable for the consistency discrimination and screening of a large number of structural planes in deep boreholes. Finally, the method based on the optical borehole images is successfully applied in the slope survey of the Xichang iron ore mine.

Conventional drilling and coring methods are inherently limited to providing one-dimensional geological data, which hinders accurate characterization of the spatial distribution of rock mass structures and properties. Mechanical disturbances during drilling often cause core breakage, further compromising the fidelity of in situ geological representation. This study proposes an integrated approach combining borehole optical imaging and GPR to enhance the characterization of rock mass structures. A dynamic exploration method is introduced, defined as an adaptive drilling layout workflow based on phased information feedback. The fundamental concept, key assumptions, boundary conditions, and field implementation procedures of this dynamic survey are systematically described. The integrated method is applied to a high-speed railway investigation project in the Tengzhou section, Shandong Province, China, where six boreholes were surveyed using both techniques. Results demonstrate that fused analysis of borehole optical images and GPR data effectively reveals rock morphology, fracture distribution, joint systems, and fractured zones. Optical imaging provides high-resolution orientation data at the borehole wall. Borehole GPR extends detection radially into the surrounding rock mass. Together, the two methods enable spatially enhanced characterization and partially mitigate the azimuthal ambiguity inherent in single-borehole radar measurements. A triangular borehole survey scheme is shown to be feasible for locating subsurface anomalies. The proposed method effectively reduces borehole requirements compared to conventional grid layouts. Through the integrated analysis of optical imaging and GPR data, common anomalous features can be successfully identified. The method demonstrates practical applicability for detecting fractures with apertures greater than 1 cm and meter-scale cavities. Good consistency between the two techniques validates the feasibility of this integrated approach. The method’s limitations, including resolution constraints and detection omission risks, are explicitly acknowledged, and risk control strategies are proposed. Overall, the dynamic exploration approach reduces investigation costs and accelerates project timelines. It also provides a practical framework for the spatial characterization of rock mass discontinuities with minimal borehole requirements.