**6. Conclusions**

and percussive control mode are employed for rocks. When penetrating the granular soil from 0 to 22 s, the rotary motor keeps a constant rotary speed 80 r/min and penetrating motor exerts a constant velocity 80 mm/min. In this period, penetrating force is less than 50 N, rotary torque is no more than 0.6 Nm and drilling power is less than 10 W. When penetrating to the formation of limestone, penetrating force booms up meanwhile recognition drilling parameters are adopted to start real-time recognition. When recognizing limestone's drillability level, rotary motor switches rotary speed to 100 r/min and penetrating velocity is maintained a constant value 10 mm/min. In this period, penetrating force maintains a low level of less than 650 N, rotary torque is also no more than 10 Nm and drilling power is controlled no more than 90 W. According to the monitored drilling states, by matching the appropriate drilling parameters with corresponding drillability level, the drilling loads in penetrating five formations keep relatively stable and do not surpass drill tool's load limits. As a result, it takes only 600 s and 10 Wh drilling energy in the 0.5 m drilling process. Overall, this drillability real-time recogni-

tion drilling strategy has been verified by this multi-layered drilling experiments.

Although the proposed non-contact drilling and coring characteristics monitoring method, SVM pattern recognition method, and drillability recognition based drilling strategy in this chapter are more specific to the interplanetary drilling actives, it should point out that these technologies may also be applied to terrestrial oil and gas well drilling operations. Specially speaking, even although by detecting devices applied into terrestrial oil and gas well drilling operations, the in-situ geological information can be acquired before, due to the unpredicted and variable online drilling conditions, there still exists great challenges in drill bits' selection, fluid system monitoring and parameters' optimization, adjustment of drilling parameters,

To solve the above problems, intelligent drilling technologies have been gradually widely employed in oil and gas well drilling activities. However, so far more attention was paid into the drill bit's wearing recognition, drilling faults' identification, formations' lithology evolution, etc. [52–54], few works were conducted to focus on the coring characteristics monitoring and adjustment. Since the ultimate goal of commercial drilling is to extract oil as much as possible, it perhaps is better to apply some facilities to monitor the online coring results into the inner tube. Herein, the proposed non-contact drilling and coring characteristics monitoring method is developed to conduct experimental validations, but once its specific structure parameters and installation conditions can be optimized further it may be employed into

Given suitable drilling parameters in oil and gas well drilling are more dependent on the empirical formula concluded by experts [55], it is also urgently necessary and important to conduct rigorously theoretical calculation and experimental validation works on the soil-machine interaction, wherein the soil or rock's flow monograph can be comprehended more basically and the minimum power of the actuator under specific formation could then be referenced for future

**5. Prospect for future application**

30 Drilling

well drilling faults' diagnosis, etc., [50, 51].

practice to enhance the online coring monitoring performance.

This chapter elaborates the unique challenges in interplanetary drilling and coring mission. To comprehend the specific drilling and coring characteristics, a non-contact drilling and coring characteristics monitoring method has been proposed and verified. By establishing a drillability classification model, different types of drilling formations are evaluated by a combined index. Based on the SVM pattern recognition method, a drillability recognition model has been built up that can accurately identify four different drillability levels after optimization. Experiments under a multi-layered drilling simulant revealed that this intelligent drilling strategy can effectively reduce the drilling loads and can be applied to future interplanetary unmanned drilling and coring exploration.
