Advanced Search
  • 全国中文核心期刊
  • 中国科技核心期刊
  • 美国工程索引（EI）收录期刊
  • Scopus数据库收录期刊
Volume 45 Issue 2
Turn off MathJax
Article Contents
Abstract
References
Related Articles
YAN Hao, ZHANG Jixiong, ZHOU Nan, SHI Peitao. Prediction of SC-CO2 fracturing effects of coal and rock mass based on DA-DE-SVM intelligent model[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(2): 362-368. DOI: 10.11779/CJGE20211287
Citation: YAN Hao, ZHANG Jixiong, ZHOU Nan, SHI Peitao. Prediction of SC-CO2 fracturing effects of coal and rock mass based on DA-DE-SVM intelligent model[J]. Chinese Journal of Geotechnical Engineering, 2023, 45(2): 362-368. DOI: 10.11779/CJGE20211287
shu

Prediction of SC-CO2 fracturing effects of coal and rock mass based on DA-DE-SVM intelligent model

  • State Key Laboratory of Coal Resources and Safe Mining, School of Mines, China University of Mining and Technology, Xuzhou 221116, China

More Information
  • Received Date: November 01, 2021
  • Available Online: February 23, 2023
    Graphical Abstract
    • Abstract
  • The fracturing effect of coal and rock mass is the main basis for the design of supercritical CO2 (SC-CO2) fracturing projects. In order to accurately predict the effects of SC-CO2 fracturing in coal and rock mass, based on the dynamic propagation characteristics between two opposite cracks originating from the adjacent fracturing boreholes, six geological factors and four construction factors that affect the SC-CO2 fracturing effects in coal and rock mass are screened and determined. A hybrid artificial intelligence model that integrates the support vector machine (SVM), dragonfly algorithm (DA) and differential evolution algorithm (DE) is proposed、the relationship between the SC-CO2 fracturing effects and the influencing factors is constructed using the SVM, the hyper-parameters of SVM are optimized using the DA and the differential evolution algorithm, the performance of the hybrid artificial intelligence model is evaluated using the correlation coefficient, root mean square error and average absolute error as the evaluation indices, and the sensitivity of the model input variables is analyzed by the MIV method. The results show that the proposed DA-DE-SVM prediction model can predict the effects of SC-CO2 fracturing well of coal and rock mass. The R value of the training set is 0.9572 and that of the testing set is 0.9316. The importance of factors affecting SC-CO2 fracturing effects is from high to low: horizontal distance between adjacent fracturing boreholes > vertical stress > fracturing fluid injection rate > vertical distance between adjacent fracturing boreholes > tensile strength > horizontal stress > fracturing fluid temperature > coal permeability coefficient > initial pore pressure > coal elastic modulus. The research results may provide important guidance for the parameter optimization design and engineering application of the SC-CO2 fracturing technology.
    • FullText(HTML)
    • References (18)
  • [1]
    卢义玉, 廖引, 汤积仁, 等. 页岩超临界CO2压裂起裂压力与裂缝形态试验研究[J]. 煤炭学报, 2018, 43(1): 175-180. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201801022.htm

    LU Yiyu, LIAO Yin, TANG Jiren, et al. Experimental study on fracture initiation pressure and morphology in shale using supercritical CO2 fracturing[J]. Journal of China Coal Society, 2018, 43(1): 175-180. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201801022.htm
    [2]
    王海柱, 李根生, 郑永, 等. 超临界CO2压裂技术现状与展望[J]. 石油学报, 2020, 41(1): 116-126. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB202001011.htm

    WANG Haizhu, LI Gensheng, ZHENG Yong, et al. Research status and prospects of supercritical CO2 fracturing technology[J]. Acta Petrolei Sinica, 2020, 41(1): 116-126. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB202001011.htm
    [3]
    闫浩. 超临界CO2压裂煤体分阶段致裂机理及裂缝扩展规律[D]. 徐州: 中国矿业大学, 2020.

    YAN Hao. Staged Cracking Mechanism and Crack Propagation Law of Supercritical CO2 Fracturing Coal Mass[D]. Xuzhou: China University of Mining and Technology, 2020. (in Chinese)
    [4]
    ISHIDA T, CHEN Y Q, BENNOUR Z, et al. Features of CO2fracturing deduced from acoustic emission and microscopy in laboratory experiments[J]. Journal of Geophysical Research: Solid Earth, 2016, 121(11): 8080-8098. doi: 10.1002/2016JB013365
    [5]
    侯冰, 武安安, 常智, 等. 页岩油储层多甜点压裂裂缝垂向扩展试验研究[J]. 岩土工程学报, 2021, 43(7): 1322-1330. https://www.cnki.com.cn/Article/CJFDTOTAL-YTGC202107024.htm

    HOU Bing, WU An'an, CHANG Zhi, et al. Experimental study on vertical propagation of fractures of multi-sweet of spots shale oil reservoir[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(7): 1322-1330. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTGC202107024.htm
    [6]
    武男, 陈东, 孙斌, 等. 基于分类方法的煤层气井压裂开发效果评价[J]. 煤炭学报, 2018, 43(6): 1694-1700. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201806025.htm

    WU Nan, CHEN Dong, SUN Bin, et al. Evaluation on fracturing effect based on classification method[J]. Journal of China Coal Society, 2018, 43(6): 1694-1700. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201806025.htm
    [7]
    刘军杰. 官110区块压裂改造效果预测及评价研究[D]. 东营: 中国石油大学(华东), 2016.

    LIU Junjie. Research on the prediction and evaluation of fracturing effect in the Guan 110 block[D]. Dongying: China University of Petroleum (Huadong), 2016. (in Chinese)
    [8]
    曾凡辉, 郭建春, 徐严波, 等. 压裂水平井产能影响因素[J]. 石油勘探与开发, 2007, 34(4): 474-477, 482. doi: 10.3321/j.issn:1000-0747.2007.04.016

    ZENG Fanhui, GUO Jianchun, XU Yanbo, et al. Factors affecting production capacity of fractured horizontal wells[J]. Petroleum Exploration and Development, 2007, 34(4): 474-477, 482. (in Chinese) doi: 10.3321/j.issn:1000-0747.2007.04.016
    [9]
    GENG L D, LI G S, WANG M S, et al. A fractal production prediction model for shale gas reservoirs[J]. Journal of Natural Gas Science and Engineering, 2018, 55: 354-367. doi: 10.1016/j.jngse.2018.04.025
    [10]
    韩斌, 吉坤, 胡亚飞, 等. ANN-PSO-GA模型在湿喷混凝土强度预测及配合比优化中的应用[J]. 采矿与安全工程学报, 2021, 38(3): 584-591. https://www.cnki.com.cn/Article/CJFDTOTAL-KSYL202103018.htm

    HAN Bin, JI Kun, HU Yafei, et al. Application of ANN-PSO-GA model in UCS prediction and mix proportion optimization of wet shotcrete[J]. Journal of Mining & Safety Engineering, 2021, 38(3): 584-591. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KSYL202103018.htm
    [11]
    LIU B, WANG R, ZHAO G, et al. Prediction of rock mass parameters in the TBM tunnel based on BP neural network integrated simulated annealing algorithm[J]. Tunnelling and Underground Space Technology, 2020, 95: 103103.
    [12]
    于永军, 朱万成, 李连崇, 等. 水力压裂裂缝相互干扰应力阴影效应理论分析[J]. 岩石力学与工程学报, 2017, 36(12): 2926-2939. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201712007.htm

    YU Yongjun, ZHU Wancheng, LI Lianchong, et al. Analysis on stress shadow of mutual interference of fractures in hydraulic fracturing engineering[J]. Chinese Journal of Rock Mechanics and Engineering, 2017, 36(12): 2926-2939. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201712007.htm
    [13]
    田伟. 页岩储层水力压裂复杂裂缝网络数值模拟[D]. 合肥: 中国科学技术大学, 2018.

    TIAN Wei. Numerical Simulation of Complex Fracture Network in Shale Gas Reservoir[D]. Hefei: University of Science and Technology of China, 2018. (in Chinese)
    [14]
    张倍宁. 超临界CO2驱替开采煤层气的实验研究[D]. 太原: 太原理工大学, 2015.

    ZHANG Beining. Experimental Study of Coal Bed Methane Displacement and Exploitation by Super Critical Carbon Dioxide Injection[D]. Taiyuan: Taiyuan University of Technology, 2015. (in Chinese)
    [15]
    LI L L, ZHAO X, TSENG M L, et al. Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm[J]. Journal of Cleaner Production, 2020, 242: 118447.
    [16]
    LIU H, WU H P, LI Y F. Multi-step wind speed forecasting model based on wavelet matching analysis and hybrid optimization framework[J]. Sustainable Energy Technologies and Assessments, 2020, 40: 100745.
    [17]
    阮永芬, 余东晓, 吴龙, 等. DE-GWO算法优化SVM反演软土力学参数[J]. 岩土工程学报, 2021, 43(增刊1): 166-170. https://www.cnki.com.cn/Article/CJFDTOTAL-YTGC2021S1032.htm

    RUAN Yongfen, YU Dongxiao, WU Long, et al. DE-GWO algorithm to optimize SVM inversion mechanical parameters of soft soil[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(S1): 166-170. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YTGC2021S1032.htm
    [18]
    QI C C, FOURIE A, CHEN Q S. Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill[J]. Construction and Building Materials, 2018, 159: 473-478.
    • Related Articles

  • Related Articles

    [1]Study on viscosity-temperature effect of petroleum-contaminated soil under synergistic solidification[J]. Chinese Journal of Geotechnical Engineering. DOI: 10.11779/CJGE20240354
    [2]HUANG Ying-hao, DAI Ji-qun, XU Kai. Flowability and viscosity of freshly solidified dredged materials[J]. Chinese Journal of Geotechnical Engineering, 2022, 44(2): 235-244. DOI: 10.11779/CJGE202202004
    [3]LI Pei-xian, WAN Hao-ming, XU Yue, YUAN Xue-qi, ZHAO Yin-peng. Parameter inversion of probability integration method using surface movement vector[J]. Chinese Journal of Geotechnical Engineering, 2018, 40(4): 767-776. DOI: 10.11779/CJGE201804022
    [4]DENG Jian, XIAO Ming, XIE Bing-bing, CHEN Jun-tao. Constitutive relation and integration algorithm for rock discontinuities under cyclic loading[J]. Chinese Journal of Geotechnical Engineering, 2017, 39(6): 1048-1057. DOI: 10.11779/CJGE201706010
    [5]RONG Mian-shui, LI Xiao-jun. Time-domain integral method considering residual strain of soils under irregular loads and its application[J]. Chinese Journal of Geotechnical Engineering, 2013, 35(7): 1239-1245.
    [6]LI Wu, YAO Wenjuan, ZHU Hehua, CAI Yongchang. Application of Monte Carlo numerical integration in natural element method[J]. Chinese Journal of Geotechnical Engineering, 2008, 30(5): 698-704.
    [7]ZHONG Yang, SUN Aiming, ZHOU Fulin, ZHANG Yongshan. Analytical solution for rectangular thin plate on elastic foundation with four edges free by finite cosine integral transform method[J]. Chinese Journal of Geotechnical Engineering, 2006, 28(11): 2019-2022.
    [8]WANG Lizhong, PAN Dongzi, LING Daosheng. Analysis on integral transform of the wave-induced response in seabed and its application[J]. Chinese Journal of Geotechnical Engineering, 2006, 28(7): 847-852.
    [9]Wang Huaizhong, Sun Jun. Local Error Estimator of Energy and Adaptive Time-Stepping Procedure for Direct Integration Method[J]. Chinese Journal of Geotechnical Engineering, 1995, 17(6): 32-41.
    [10]Zhang Wugong. Implicit Time Integration of Elasto-Viscoplastic Multlaminate Model for Jointed Rocks[J]. Chinese Journal of Geotechnical Engineering, 1990, 12(6): 42-54.
    • Supplements (0)

  • Cited by

    Periodical cited type(2)

    1. 刘要来，王堡生，周红波，赵二峰，李章寅. 基于凸集比例因子和WOA-Kriging模型的重力坝非概率可靠性分析. 长江科学院院报. 2025(03): 164-170 .
    2. 魏博文，张升，袁冬阳，徐富刚. 基于概率—模糊—区间混合模型和改进分枝限界法的重力坝可靠性分析方法. 水利学报. 2022(12): 1476-1489 .

    Other cited types(5)

Catalog

    Get Citation
    PDF
    XML
    Article views PDF downloads Cited by(7)
    Related
    Copyright © 2010 Editorial By Chinese Journal of Geotechnical Engineering 苏ICP备05007122号-11公安联网备案号：32010602011255
    Editorial Office address：34 Hujuguan,Nanjing 210024,ChinaPostal Code：210024Tel：025-85829534，85829556E-mail: ge@nhri.cn

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return