*5.3. Repair of Failed Gas-Extraction Boreholes*

The study shows that the main reason for the failure of gas-extraction boreholes is air leakage in boreholes [13,14], while the air leakage in boreholes is caused by poor sealing quality. There are mainly two ways to deal with the failed gas-extraction boreholes: closing boreholes and supplementing boreholes, which are passive ways to deal with the failed boreholes. Closing the failed boreholes increases the drainage time of regional coal seams, and extraction effect of supplementary boreholes is also poor. Therefore, in this paper, the repair technology for failure borehole is adopted to realize efficient gas extraction. The process of drilling repair is shown in Figure 8.

**Figure 8.** Repair process of failed gas-extraction boreholes.

As shown in Figure 8, firstly, the hydraulic slotting technology is used to cut and remove the failed sealing material in the borehole. Secondly, an annular slot is cut in front of the working face by a hydraulic slotting device to block the air leakage channel through the crack in the coal–rock mass. In this process, the optimal slotting position and depth need to be determined. Thirdly, secondary sealing is needed for the gas-extraction boreholes. Of course, in this process, the sealing material with high expansion and fluidity is essential, and it is recommended to adopt the "two plugging and one injection" sealing process with pressure. Finally, we need to check the sealing effect of the borehole.

#### **6. Discussion**

Gas drainage in coal mines is a complex process, including drilling design, drilling construction, extraction data management, and other links. With the wide application of information technology in the field of coal mines, professional software has been developed for different methods of gas extraction, which has played a positive role in improving the efficiency of gas extraction. Nowadays, in the context of the development of coal mine intelligence, the deep mining and utilization of data has become the core of coal mine intelligence development. As far as gas drainage is concerned, the intelligent control of gas drainage management based on extraction data, intelligent evaluation of extraction standards, and intelligent design of extraction boreholes have become an important but difficult part of the development of gas-drainage technology. Future studies should focus on building an intelligent decision-making platform for gas drainage based on gas-drainage data by means of big data analysis to achieve intelligent control, thereby realizing the intelligent construction of gas drainage.

#### **7. Conclusions**

(1) Through the accurate prediction of coal seam thickness and gas content, the accurate assessment of coal seam gas reserves is realized. Then, the extraction area is divided into sections, and based on the space–time relationship between mining activities and gas extraction, the calculation model of borehole distance in different sections is established, and the differentiated design of borehole is realized.

(2) The drilling video surveillance system and drilling trajectory measurement device are used to manage the drilling process and effect, respectively, which ensure the precise construction of boreholes.

(3) Based on the monitoring data of gas extraction, the model of extraction data correction and identification of failed borehole are established and the failed borehole caused by air leakage is solved by repair technology of hydraulic slotting and sealing, which improves the gas drainage efficiency.

**Author Contributions:** Conceptualization, X.C.; methodology, X.C. and H.S.; validation, X.C. and H.S.; formal analysis, X.C.; investigation, X.C. and H.S.; resources, X.C.; data curation, H.S.; writing original draft preparation, X.C. and H.S.; writing—review and editing, X.C. and H.S.; visualization, X.C.; supervision, H.S.; project administration, H.S.; funding acquisition, X.C. and H.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by National Natural Science Foundation of China (No. 51874348), Chongqing Science Fund for Distinguished Young Scholars (No.cstc2019jcyjjqX0019), Natural Science Foundation of Chongqing (CSTB2022NSCQ-MSX1080).

**Data Availability Statement:** All data and/or models used in the study appear in the submitted article.

**Conflicts of Interest:** The authors declare no conflict of interest.
