## 4 Case Analysis
### Interpretation of Result
The image data were averaged over the gray scale values in the same depth direction and then converted into values between 0 and 1, and the larger the value, the larger the gray scale, and the closer to the non-weak layer rock. The sound speed value was normalized to the sound speed value of the rock at different depths and converted into values between 0 and 1. The larger the value, the greater the gray scale, and the closer it is to the non-weak layer rock. The smaller the value in Figure 16, the greater the probability of weak layer rock. By comparing the paper method with the traditional optical borehole image method and the rock sound speed method, it can be seen that the results of the method and the traditional two methods in the weak interlayer area is more consistent, and can effectively reflect the geographical depth of the weak interlayer and provide more accurate data for the location of the weak interlayer in the borehole. The image before and after the fusion is curled along the central axis of the borehole to form the image shown in Figure 17. Figure 16a is an image acquired by the optical imaging mode, presenting a virtual core image of the N-S orientation. Figure 17b is an image acquired by an optical imaging mode, presenting a virtual core image of the S-N orientation. Figure 17c shows the image reconstructed using the present method, presenting a virtual core image of the N-S orientation. Figure 17d shows the image reconstructed using the present method, presenting a virtual core image of the S-N orientation. In order to more intuitively present the changes of the stratum with the depth, the 3D stereo diagram of the stratum was reconstructed by the virtual core image, and the stratum map at the depth 28.5-29.5 m is shown in Figure 18. Figure 18a shows the 3D images of the strata before using the method of this paper. Four structural features can be intuitively seen in Figure 18a. Figure 18b shows the 3D images of the strata. One structural feature can be intuitively seen in Figure 18b. Through the comparison, we can see that this method can effectively distinguish the types of structure features, and more effectively identify the weak structure surface from the structure types. This is mainly due to the synthesis of a variety of rock characteristic parameters, and to realize the fusion of multi-source data the results are more specific features. Figure 16: Numerical comparison of different methods. In terms of the verification of the accuracy of the weak structure identification, the present method is compared with the results of the optical imaging acquisition and the rock sound speed test. In terms of the weak structure surface identification of optical imaging, the probability distribution of the weak structure at different depths is shown in Figure 19a. In terms of the structure and weak structure surface identification of this method, the probability distribution of the weak structure at different depths is shown in Figure 19b. In terms of the structure weak structure surface identification of the sound speed test, the probability distribution of the weak structure at different depths is shown in Figure 19c. The abscissa in Figure 19 shows the likelihood that the formation is a weak layer, and the greater the value. The ordinate in Figure 19 indicates the depth of the formation. As can be seen from Figure 19, conventional optical imaging techniques acquire more areas of structural characteristic features, with five areas of concern at hole 28.5-29.5 m when the possibility threshold is set to 0.6. When the possibility threshold is set to 0.8, there are 4 areas of concern at hole 28.5-29.5 m. Traditional acoustic testing techniques acquire smaller areas of structural features, with 1 area of concern at hole 28.5-29.5 m when the possibility threshold is set to 0.6.