Academic Journal of Architecture and Geotechnical Engineering, 2023, 5(8); doi: 10.25236/AJAGE.2023.050805.
Xindong Wang1, Zhaohui Song1, Guiyi Zhang1, Xin Zhang1, Zhengxin Jiang1, Tao Su1, Haitao Ren2, Bohui Wang1
1Xinjiang Oilfield Company Engineering Technology Research Institute, Karamay, Xinjiang, 834000, China
2Mechanical and Electrical Engineering, Southwest Petroleum University, Chengdu, Sichuan, 610500, China
The drilling strength parameters of formation rocks are important reference basis for drilling engineering design, bit selection, and drilling parameter optimization. Establishing a correlation calculation function between logging data and parameters such as rock compressive strength and drillability level through unit experiments, and obtaining a profile of drilling resistance characteristics that varies with well depth, is a classic technical means in the field of oil and gas well engineering. However, in the case of insufficient core volume, the experimental data obtained is limited, making it difficult to regress and fit the calculation model with high accuracy, which limits the application of this technology to some extent. In this paper, a "correction coefficient method" is proposed to establish a calculation model for parameters such as formation compressive strength and drillability grade based on logging data. First, unit experiment analysis is carried out for the limited core volume of the target block. Secondly, the classical calculation model is modified by using the experimental results. Then, the model is applied to the deep well section of the southern block of the Tarim Basin to analyze the drilling resistance characteristics of formation rock and obtain the change trend conclusions. This method breaks through the limitation of experimental core volume and has good engineering application value and potential.
Rock drillability; Oil and gas drilling; Deep strata; Logging interpretation; Tarim Basin
Xindong Wang, Zhaohui Song, Guiyi Zhang, Xin Zhang, Zhengxin Jiang, Tao Su, Haitao Ren, Bohui Wang. Research on the distribution law of drilling resistance of formation rock based on modified coefficient method. Academic Journal of Architecture and Geotechnical Engineering (2023) Vol. 5, Issue 8: 33-42. https://doi.org/10.25236/AJAGE.2023.050805.
[1] Rollow, A.G: Rock Drillability Index .Colorado. (1969).
[2] Feng K , Liu S J , Qiu Y ,et al.Research on the Modified Calculation Method for Ground Resistance Coefficient of Shield Tunnel[J].Journal of Railway Engineering Society, 2014.
[3] Li, S.B., Li, W., You, H.L. et al.: Classification Methods of Rock Drillability Based on The Fractal Theory [J]. Natural Gas Industry. 27(10), 63-66 (2007). https://doi.org/10.3321/j.issn:1000-0976.2007.10.017.
[4] Andrews, R.J., Hareland, G., Nygaard, R., et al.: Methods of Using Logs to Quantify Drillability. Society of Petroleum Engineers. (2007). https://doi.org/10.2118/106571-ms.
[5] Chen, J.H., Wang, Y., Han, Y.N. et al.: A new method for assessing rock's drillabity for PDC bits via a scratch testing. Journal of China University of Petroleum:Edition of Natural Science. 41(2):95-99 (2017). https://doi.org/10.3969/j.issn.1673-5005.2017.02.011.
[6] SY 5426-91. Rock drillability measurement and its classification. Ministry of Energy, People's Republic of China. 1992-07-01.
[7] Zihan D, Qihua Z, Sheqin P .Research on the Accessor Method of m Value on Slope Site Based on the Modified Calculative Width[J].Chinese Journal of Underground Space and Engineering, 2019.
[8] SY/T 5426-2000. Rock drillability measurement and its classification. Ministry of Energy, People's Republic of China. 2000-10-01.
[9] SY/T 5426-2016. Rock drillability measurement and its classification. Ministry of Energy, People's Republic of China. 2000-06-01.
[10] Shi, X.C., Tao, Z.W., Meng, Y.F. et al.: A Bottomhole Drillability Model in Spherical Symmetric Coordinates. Journal of Southwest PetroleumUniversity(Science & Technology Edition). 38(04):130-135 (2016). https://doi.org/10.11885/j.issn.1674-5086.2014.09.03.05.
[11] Han, L.L.: Drillability of Rock Formations Assessment by Relevance Vector Machine Based on Particle Swarm Optimization. Exploration Engineering (Rock & Soil Drilling and Tunneling). 43(03):23-26 (2016). https://doi.org/10.3969/j.issn.1672-7428.2016.03.005.
[12] Li, C.S., Li, Y.C., Sun, W. et al.: A method to identify lithology using XRF spectrum. Journal of Northwest University (Natural Science Edition). 43(01):8992 (2013). https://doi.org/ 10.16152/j. cnki. xdxbzr.2013.01.014.
[13] Li, C.S., Li, W., He, Y.L.: Study on Rock Drillability Evaluation by Elements' Contents in Cuttings. Drilling & Production Technology. 41(04):25-26+6 (2018). https://doi.org/10.3969/J.ISSN.1006-768X.2018.04.08.
[14] Li, Z.H., Fang, M.Z., Yang, K. et al.: A new method for defining the rock drilling resistance: five-parameter method. Oil Drilling & Production Technology. 40(04):412-416 (2018). https://doi.org/ 10.13639/j.odpt.2018.04.002.
[15] Zhang, H., Wang, H., Miao, X. et al.: The invention relates to a method and device for predicting rock drillability stage value of PDC bit at different temperatures. Beijing China: CN107038300B, 2019-12-31.
[16] Zhou, Q.C., Zhao, T.F., Zhou, W.Q. et al.: Study on Shale Gas Rocks' Drillability Based on Fractal Theory and Neural Network. Drilling & Production Technology. 42(01):1-3+125 (2019). https://doi. org/10.3969/J.ISSN.1006-768X.2019.01.01.
[17] Yang, Y.X., Gao, X., Chen, H. et al.: A New Method for Measuring and Grading of PDC Bit Rock Drillability. Chinese Journal of Underground Space and Engineering. 15(03):811-819 (2019).
[18] Li, Q., Zhang, H.S., Qiu, K. et al.: Research on the rock drillability prediction methods of deep strata in the East China Sea. China Offshore Oil and Gas. 32(02):126-133 (2020). https://doi.org/10. 11935/j. issn. 1673-1506.2020.02.015.
[19] Xie, Z.J., Chang, X., Yang, L. et al.: Classification method of coal and rock drillability based on Mechanical Specific Energy theory. Coal Geology & Exploration. 49(03):236-243 (2021). https://doi. org/10.3969/j.issn.1001-1986.2021.03.030.
[20] Xu, M.G., Liu, H.Y., Wang, P. et al.: Comprehensive Prediciton Study on Rock Drillability Based on RES Theory. Metal Mine. 547(01):113-119 (2022). https://doi.org/10.19614/j.cnki.jsks.202201017.
[21] Zhang, D.J., Wei, W., Liu, M.Y. et al.: Intelligent identification method of formation lithology based on comprehensive logging data. West-China Exploration Engineering. 35(04):54-59 (2023). https://doi. org/ 10.3969/j.issn.1004-5716.2023.04.016.