## 3 Field Test Study on Liquid CO2 Phase-Transition Rock Fracturing
### Fracturing Effects  
#### 3.3.1 Acquisition of the Feature Information of the Rock Masses after Fracturing  
In this research, a \"UAV camera shooting+image processing\" method was used for the fast acquisition of the granular information. The small UAV cameras were flexible and visually controllable, could be combined with self-developed image processing software to acquire the granular information more accurately and comprehensively. The small UAV, which was used in this experiment was \"DJI Phantom 4\". The main technical parameters of the UAV used in this experiment were as follows: A one-inch 20-megapixel camera sensor; 4K/60 fps video; 14 static pictures per second; 5-way environmental sensing; mechanical shutter; double coding; 30-min endurance; 7 km flight distance. While the image acquisition, the overlap rates of the course and side directions were not less than 80% and 60%, respectively. The UAV height was 3 m, and an automatic shooting mode was adopted. The flight speed was 0.3 m/s and the automatic shooting interval was 0.3 m/s. The shooting path diagram is shown in Figure 6.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Item** & **Type 95** & **Type 108** \\ \hline Outer diameter of CO\({}_{2}\) phase-transition fracturing device (mm) & 95 & 108 \\ Length of CO\({}_{2}\) phase-transition fracturing device (mm) & 1300 & 2000 \\ Weight of single CO\({}_{2}\) phase-transition fracturing device (kg) & 44 & 100 \\ Drill size (mm) & 120 & 140 \\ Number of single cracked holes & Several & Single \\ Filling volume of liquid CO\({}_{2}\) & 2.5 & 7 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of CO\({}_{2}\) phase-transition fracturing device.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Item** & **95-Single** & **95-Several** & **108-Single** & **108-Several** \\ \hline Diameter of drilling hole (mm) & 120 & 120 & 140 & 140 \\ Depth of drilling hole (m) & 4 & 4 & 4 & 4 \\ Number of single cracked holes & 2 & 2 & 1 & 1 \\ Number of drilling hole & 1 & 13 & 1 & 13 \\ Distance of drilling hole (Average m) & 0 & 1.5 & 0 & 1.5 \\ Row spacing of drilling hole & 0 & 1.5 & 0 & 1.5 \\ (Average m) & 5 & 5 & 5 & 5 \\ Trigeminal height facing vacancy (m) & 0.3 & 0.3 & 0.3 & 0.3 \\ Minimum distance of resistance line & & & & \\ (Average m) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 2: The pore network parameters of CO\({}_{2}\) phase-transition fracturing device.  
A self-developed digital image processing software system was used to process the UAV images. First, the pre-processing of the images was accomplished using a mean filtering method. The filtering window was 3 \(\times\) 3. Mean filtering is a type of linear spatial filtering, with a simple algorithm and fast calculation speed. The second step was image binarization. The brightness of each pixel in the pre-processed images was expressed by 256 gray levels between 0 and 255. The threshold was selected by an OSTU algorithm. Each of the images was divided into two categories according to the gray characteristics of the images, and the optimal threshold occurred when the separation degree between the within-class variance and the between-class variance was the largest. After the binary images were obtained, manual processing was carried out for the parts with larger interference factors. Then, the images were cut and eliminated in order to improve the accuracy. A processed image is shown in Figure 7 (taking a 108-type several-hole test as an example). Finally, the pixel information is transformed into the actual block feature information using scale transformation.