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Coal Geology & Exploration

Abstract

The advance and accurate identification of coal-rock interfaces is one of the key technologies to realize intelligent mining, improve mining efficiency and reduce cost. Azimuthal electromagnetic wave logging has achieved good results in lithologic interface identification of petroleum logging, but the identification of coal-rock interface is seldom studied. For the purpose of studying the applicability and detection performance of azimuthal electromagnetic wave in the coalfield logging environment, the one-dimensional generalized reflection coefficient method is used to calculate the magnetic field component, and the fast Hankel transform is used to accelerate the integral calculation speed. What is more, the effects of coil system combination mode, frequency, source distance, radius of coil system, resistivity contrast, emission current and resistivity anisotropy on azimuth electromagnetic logging response in the coal field are simulated. The results show that the azimuthal electromagnetic wave logging instrument can distinguish the coal-rock interface and has a great application potential in coal-rock interface recognition. The radius of the coil system and the emission current mainly affect the size of the instrument response signal. In a certain range of resistivity contrast, the amplitude ratio and phase difference near the interface increase with the increase of resistivity contrast, and the resistivity anisotropy has little effect on the amplitude ratio and phase difference in high resistivity formation. The transmitting frequency, source distance and resistivity contrast of the instrument simultaneously affect the maximum edge depth of the azimuth signal.

Keywords

azimuth electromagnetic wave logging, coal-rock interface, horizontal well, forward modeling

DOI

10.12363/issn.1001-1986.21.06.0334

Reference

[1] 葛世荣,郝雪弟,田凯,等. 采煤机自主导航截割原理及关键技术[J]. 煤炭学报,2021,46(3):774−788. GE Shirong,HAO Xuedi,TIAN Kai,et al. Principle and key technology of autonomous navigation cutting for deep coal seam[J]. Journal of China Coal Society,2021,46(3):774−788.

[2] 王海舰,黄梦蝶,高兴宇,等.考虑截齿损耗的多传感信息融合煤岩界面感知识别[J]. 煤炭学报,2021,46(6):1995−2008. WANG Haijian,HUANG Mengdie,GAO Xingyu,et al. Coal-rock interface recognition based on multi-sensor information fusion considering pick wear[J]. Journal of China Coal Society,2021,46(6):1995−2008.

[3] 张强,孙绍安,张坤,等. 基于主动红外激励的煤岩界面识别[J]. 煤炭学报,2020,45(9):3363−3370. ZHANG Qiang,SUN Shaoan,ZHANG Kun,et al. Coal and rock interface identification based on active infrared excitation[J]. Journal of China Coal Society,2020,45(9):3363−3370.

[4] ZHANG Guoxin,WANG Zengcai,ZHAO Lei. Recognition of rock-coal interface in top coal caving through tail beam vibrations by using stacked sparse autoencoders[J]. Journal of Vibroengineering,2016,18(7):4261−4275.

[5] 葛世荣. 采煤机技术发展历程(六):煤岩界面探测[J]. 中国煤炭,2020,46(11):10−24. GE Shirong. The development history of coal shearer technology(Part six):Coal-rock interface detection[J]. China Coal,2020,46(11):10−24.

[6] 王莉,苏波. 综采工作面煤岩界面识别方法研究[J]. 中国设备工程,2020(21):215−216. WANG Li,SU Bo. Study on identification method of coal-rock interface in fully mechanized mining face[J]. China Plant Engineering,2020(21):215−216.

[7] 王文天. 定向钻孔雷达方位识别及三维成像算法研究[D]. 长春:吉林大学,2018.

WANG Wentian. Research on azimuth recognition and 3D imaging algorithm of directional borehole radar[D]. Changchun:Jilin University,2018.

[8] RODNEY P F,WISLER M. Electromagnetic wave resistivity MWD tool[J]. SPE Drilling Engineering,1986,1(5):337−346.

[9] DUPUIS C,DENICHOU J M. Automatic inversion of deep-directional-resistivity measurements for well placement and reservoir description[J]. The Leading Edge,2015,34(5):504−512.

[10] LI Qiming,OMERAGIC D,CHOU L,et al. New directional electromagnetic tool for proactive geosteering and accurate formation evaluation while drilling[C]//SPWLA 46th Annual Logging Symposium. 2005:26–29.

[11] 吴冲. 随钻方位电磁波电阻率测井方法研究[D]. 北京:中国石油大学(北京),2017.

WU Chong. Study on azimuthal electromagnetic resistivity logging while drilling[D]. Beijing:China University of Petroleum(Beijing),2017.

[12] WU Zhenguan,WANG Lei,FAN Yiren,et al. Detection performance of azimuthal electromagnetic logging while drilling tool in anisotropic media[J]. Applied Geophysics,2020,17:1−12.

[13] 王磊,范宜仁,操应长,等. 大斜度井/水平井随钻方位电磁波测井资料实时反演方法[J]. 地球物理学报,2020,63(4):1715−1724. WANG Lei,FAN Yiren,CAO Yingchang,et al. Real-time inversion of logging-while-drilling azimuthal electromagnetic measurements acquired in high-angle and horizontal wells[J]. Chinese Journal of Geophysics,2020,63(4):1715−1724.

[14] CONSTABLE M V,ANTONSEN F,STALHEIM S O,et al. Looking ahead of the bit while drilling:From vision to reality[C]// SPWLA 57th Annual Logging Symposium,2016, 57(5):426–446.

[15] 柴斌,许小凯,张川,等. 六种不同变质程度煤的电阻率研究[J/OL]. 地球物理学进展,2021:1–13[2021-04-19]. http://kns.cnki.net/kcms/detail/11.2982.p.20201109.1440.134.html.

CHAI Bin,XU Xiaokai,ZHANG Chuan,et al. Characteristics of resistivity and its anisotropy of six kinds of metamorphic coals[J/OL].Progress in Geophysics(in Chinese),2021:1–13[2021-04-19]. http://kns.cnki.net/kcms/detail/11.2982.p.20201109.1440.134.html.

[16] CHEN Gang,FAN Yiren,LI Quanxin. A study of coalbed methane(CBM) reservoir boundary detections based on azimuth electromagnetic waves[J]. Journal of Petroleum Science and Engineering,2019,179:432−443.

[17] 陈刚,范宜仁,李泉新. 顺煤层钻进随钻方位电磁波顶底板探测影响因素[J]. 煤田地质与勘探,2019,47(6):201−206. CHEN Gang,FAN Yiren,LI Quanxin. Influencing factors of azimuth electromagnetic wave roof and floor detection while drilling along coal seam[J]. Coal Geology & Exploration,2019,47(6):201−206.

[18] CHEN Gang,FAN Yiren,LI Quanxin. Using an azimuth electromagnetic wave imaging method to detect and characterize coal–seam interfaces and low–resistivity anomalies[J]. Journal of Environmental and Engineering Geophysics,2020,25(1):75−87.

[19] 王磊. 深探测多分量随钻电磁波测井理论与正反演研究[D]. 青岛:中国石油大学(华东),2018.

WANG Lei. Deep-detection multi-component logging-while-drilling electromagnetic logging:Theory,forward modeling and inversion/data processing[D]. Qingdao:China University of Petroleum(East China),2018.

[20] 倪尧. 三分量感应测井响应分析及反演研究[D]. 成都:电子科技大学,2016.

NI Yao. Response analysis and inversion of multicomponent induction logging[D]. Chengdu:University of Electronic Science and Technology of China,2016.

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