Development of an intelligent drilling cuttings method drill rig for addressing suction and sticking phenomena: Field experiment

Abstract

During the operation of the drilling cuttings method, frequent occurrences of suction and sticking phenomena lead to the loss of drilling tools and failure to achieve the designed borehole depth. resulting in inaccurate risk assessment for coal seam rockbursts. To address these challenges, a mechanical analysis of cuttings transport via the spiral drill pipe was conducted. This analysis identified the primary factors contributing to suction and sticking phenomena in spiral drill pipes and proposed a targeted approach for mitigating these issues. Based on this analysis, an intelligent drilling cuttings method drill rig (IDCMDR) was developed, and field experiments were conducted. The experimental results demonstrate that when suction occurs, adjusting the rotational and drilling speeds of the IDCMDR effectively controls the phenomenon. When sticking occurs, the stuck drill pipe can be addressed by injecting high-pressure gas into the borehole bottom through the hollow structure of the spiral drill pipe or by reversing its rotation. During operation, characteristic patterns in the needle movements of the thrust and torque hydraulic gauges on the IDCMDR enable the identification of suction and sticking phenomena. The development and field validation of the IDCMDR confirm the feasibility of the theoretically proposed mitigation methods.

Keywords

Rockburst / Drilling cuttings method / Intelligent drilling cuttings method drill rig (IDCMDR) / Spiral drill pipe / Suction and sticking phenomena

References

[1] Lyu JG, Xue ZP, Pan YS, Dai LP, Tang Z, Wang XB. Quantitative correlation between stress variation and charge signals of loaded coal and its implication for dynamic fracturing of surrounding rock. Int J Min Sci Technol 2026; 36(2):313-31.

[2] Zhang SC, Li YY, Shen BT, Sun XZ, Gao LQ. Effective evaluation of pressure relief drilling for reducing rock bursts and its application in underground coal mines. Int J Rock Mech Min Sci 2019; 114:7-16.

[3] Zheng YH, Zhao ZG, Zhao TB, Ma CF, Zhang K, Qi YS. A new method for monitoring coal stress while drilling process: Theoretical and experimental study. Energy Sources Part A 2023; 45(2):3980—93.

[4] Dai LP, Pan YS, Li ZH, Wang AW, Xiao YH, Liu FY, et al. Quantitative mechanism of roadway rockbursts in deep extra—thick coal seams: Theory and case histories. Tunn Undergr Space Technol 2021; 111:103861.

[5] Xu HC, Li K, Shan PF, Wu XF, Zhang S, Wang ZY, et al. Automatic picking method for the first arrival time of microseismic signals based on fractal theory and feature fusion. Fractal Fract 2025; 9(11):679.

[6] Dai LP, Zhao X, Pan YS, Wang AW, Gao YN, Zhu CQ, et al. Revisiting the strainburst intensity of roadways in coal mines: Theory and case study. J Rock Mech Geotech Eng 2026.

[7] Wang W, Pan YS, Zhao HR, Xiao YH, Li XL, Bao XY, et al. Electric charge induction monitoring of deformation and failure behavior of igneous rock: Laboratory test and field application. J Rock Mech Geotech Eng 2026; 18(2):861-86.

[8] Xu HC, Li K, Lai XP, Shan PF, Zhang B, Dai LP, et al. Intelligent prediction method of rockburst driven by microseismic temporal features in deep near—vertical coal seams. Int J Miner Metall Mate 2026.

[9] Xu HC, Lai XP, Shan PF, Yang YB, Zhang S, Yan BX, et al. Energy dissimilation characteristics and shock mechanism of coal—rock mass induced in steeply—inclined mining: Comparison based on physical simulation and numerical calculation. Acta Geotech 2023; 18(2):843-64.

[10] Dai LP, Feng DJ, Pan YS, Wang AW, Ma Y, Xiao YH, et al. Quantitative principles of dynamic interaction between rock support and surrounding rock in rockburst roadways. Int J Min Sci Technol 2025; 35(1):41-55.

[11] Tan YL, Tan Y, Guo WY, Li B, He SD, Zhang L, et al. Calculation model for kinetic energy and rock burst risk evaluation method during roadway excavation. Int J Min Sci Technol 2025; 35(5):677—90.

[12] Qin ZC, Li T, Li QH, Chen GB, Cao B. Combined early warning method for rock burst and its engineering application. Adv Civ Eng 2019; 2019(1):1269537.

[13] Wang GH, Wang XY, Zhao JX, Zhang FT, Wei HL, Bai JB. Research on inversion method for stress characteristics of roadway surrounding rock based on real—time weight measurement of drill cuttings. Simul Model Pract Theory 2025; 139:103064.

[14] Petukhov HM. Coal mine rock burst. Beijing: Coal Industry Press; 1980. p. 35-49.

[15] Brona G. Ultimate stress of coal seam. Min Transl 1983;1(1):20-8.

[16] Zhao YS, Liang CS, Liu CD. Exploration of measuring surrounding rock pressure by drilling cuttings method. Chin J Geotech Eng 1987; 9(2):104—10. in Chinese.

[17] Pan YS. Research on the theory of drilling cuttings method for measuring coal body drilling powder. J Fuxin Min Inst 1985;S1:91—7.

[18] Wang ZH, Tan J, Tan YL, Wu YH. Theoretical study and experiment validation on drilling cutting weight during the whole process of drilling. Shock Vib 2021; 2021(1):4487280.

[19] Yin YC, Zhang QZ, Guo L, Wang CW, He SD, Zhang DD. Drill cuttings test of coal under different stresses and characteristics of coal particle distribution during borehole collapse. Processes 2025; 13(2):499.

[20] Zhan K, Wen XT, Wang XB, Kong C. A method for characterization of stress concentration degree of coal mine roadway surrounding rock. J Geophys Eng 2023; 20:699-711.

[21] Zhu GA, Han JP. Experimental research into the drilling cutting method of rockburst—prone coal under water—rich conditions. Geomech Geophys Geo Energy Geo Resour 2023; 9(1):167.

[22] Li HR, Qiao YF, Shen RX, He MC. Electromagnetic radiation signal monitoring and multi—fractal analysis during uniaxial compression of water—bearing sandstone. Measurement 2022; 196:111245.

[23] Shen F, He SQ, Song DZ, He XQ, Kang ZQ, Meng YF. Rockburst monitoring in high—water—content coal seams using the drill cuttings method. J Appl Geophys 2026; 247:106138.

[24] Gao HK, Wu WR, Jiang B, Liu GJ. Research on rockburst proneness evaluation based on interpretation of drilling parameters. Eng Fail Anal 2024; 163:108421.

[25] Hao ZY, Wang SL, Pan YS. Experimental study on prediction of rock burst risk by multi—parameter indexes of borehole. Coal Geol Explor 2018; 46(6):203—11. in Chinese.

[26] Pan YS, Xu LM. Experimental investigation on temperature of drilling cuttings to predict rock burst. Chin J Geotech Eng 2012; 34(12):2228—32. in Chinese.

[27] Zheng WH, Pan YS, Shi TW. Study on the phenomenon of the ultra—large drilling cuttings quantity in rockburst coal seam. Sci Rep 2025; 15(1):11686.

[28] Gu ST, Wang CQ, Jiang BY. Field test of rock burst danger based on drilling pulverized coal parameters. DISASTER ADV 2012; 5(4):237—40.

[29] Zou XY, Luo LJ, Wang ZB, Tao PF, Wu HL, Pan J. Refined sticking monitoring of drilling tool for drilling rig in underground coal mine: from mechanism analysis to data mining. Mech Syst Sig Process 2025; 228:112467.

[30] Geng YF, Tan J, Yin YC, Tan YL. Theoretical analysis of drilling cuttings considering stress zoning of surrounding rock and its application in stress detection. Energy Sci Eng 2023; 11(5):1662-70.

[31] Lu QH, Kong LF, Peng GY, Jia W, Jin S, Dai CY, et al. Algorithm for automatic rod feeding and positioning error compensation for underground drilling robots in coal mines. Sensors 2023; 23(17):7530.

[32] Tang JP, Chen S, Li WJ. Theoretical and experimental studies on drilling cutting weight considering effective stress. Chin J Geotech Eng 2018; 40(1):130—8. in Chinese.