基于激光诱导击穿光谱的岩屑岩性在线识别试验研究

杨志强, 李光泉, 佘明军

杨志强, 李光泉, 佘明军. 基于激光诱导击穿光谱的岩屑岩性在线识别试验研究[J]. 石油钻探技术, 2019, 47(4): 122-126. DOI: 10.11911/syztjs.2019091
引用本文: 杨志强, 李光泉, 佘明军. 基于激光诱导击穿光谱的岩屑岩性在线识别试验研究[J]. 石油钻探技术, 2019, 47(4): 122-126. DOI: 10.11911/syztjs.2019091
YANG Zhiqiang, LI Guangquan, SHE Mingjun. Test Research of Online Identification of Cuttings Lithology by LIBS Technology[J]. Petroleum Drilling Techniques, 2019, 47(4): 122-126. DOI: 10.11911/syztjs.2019091
Citation: YANG Zhiqiang, LI Guangquan, SHE Mingjun. Test Research of Online Identification of Cuttings Lithology by LIBS Technology[J]. Petroleum Drilling Techniques, 2019, 47(4): 122-126. DOI: 10.11911/syztjs.2019091

基于激光诱导击穿光谱的岩屑岩性在线识别试验研究

基金项目: 中国石化集团科技攻关项目“钻井液地质信息激光在线检测技术研究”(编号:JP16024)、中石化石油工程技术服务有限公司科技攻关项目“激光在线识别岩性技术应用研究”(编号:SG17-45K)资助
详细信息
    作者简介:

    杨志强(1966—),男,吉林镇赉人,1988年毕业于石油大学(华东)地球物理勘探专业,1997年获中国地质大学(北京)石油地质学专业博士学位,主要从事石油工程技术方面的研究与管理工作。E-mail:yangzq.os@sinopec.com

  • 中图分类号: TE142

Test Research of Online Identification of Cuttings Lithology by LIBS Technology

  • 摘要:

    钻井新技术的发展及其推广应用,在提高钻井时效的同时,钻井产生岩屑的粒径变小,给常规岩屑录井带来了困难。近年来,基于激光诱导击穿光谱(LIBS)的岩屑岩性识别技术取得了较好的效果,但该技术仍需要人工采集、清洗岩屑样品,并存在钻遇地层岩屑样品代表性难以准确控制、岩屑岩性识别结果与钻遇地层真实岩性之间具有一定差异等问题。为了解决上述问题,提出了利用LIBS在线识别岩屑岩性的技术构想,在实验室构建了试验平台,探索了激光器光源功率对岩屑样品LIBS信息的影响,通过优选光源功率,提高了岩屑样品LIBS信息的采集精度,进行了干样与湿样、疏松与压实状态下岩屑样品的LIBS检测,发现不同状态下岩屑样品的LIBS特征较为稳定,岩屑样品的LIBS特征与其状态无关。试验结果表明,录井过程中岩屑样品无需处理,可以直接检测,即利用LIBS技术在线识别岩屑岩性可行。

    Abstract:

    With the development and application of new drilling technologies, the drilling time efficiency has effectively improved while producing increasingly small particle sizes of cuttings, which presents challenges to conventional mud logging technologies. In recent years, laser induced breakdown spectroscopy (LIBS) has achieved good application effect in cuttings lithology identification technology, but this technology still needs the manual collection and flushing of cuttings samples, and it faces the problems such as hard to collect the representative cutting samples for the encountered formation. Further, there have been challenges in resolving the difference between the identification results of cuttings lithology and the actual lithology of encountered formation. In order to solve the problems, the idea of using LIBS to identify cuttings lithology was proposed, and an indoor test platform was built, so as to explore the influence of laser source power on LIBS message. Through optimizing the laser source power, the acquisition accuracy of LIBS information was improved, and conducted LIBS measurement for the dry/wet cuttings samples and loose/compacted cuttings samples, respectively. The test found that the LIBS characteristics of cutting samples were stable under different states, and were in essence irrelevant to their states. The test results showed that the cuttings samples could be directly detected without any pre-treatment in the course of mud logging. Therefore, it is feasible to apply LIBS technology to realize the on-line identification of cutting lithology.

  • 图  1   LIBS测量原理示意

    Figure  1.   The principle of LIBS measurement

    图  2   LIBS在线识别岩屑岩性试验平台

    Figure  2.   Test platform for LIBS online identification of cuttings lithology

    图  3   岩屑样品干/湿状态下LIBS特征的相关性

    Figure  3.   Correlation of LIBS characteristics under dry/wet conditions of cutting samples

    图  4   岩屑疏松/压实状态下LIBS特征对比

    Figure  4.   Comparison of LIBS characteristics under the loose/compacted states of cutting samples

    表  1   油基钻井液岩屑样品剥蚀检测结果对比

    Table  1   Comparison of the denudation effects of cutting samples in oil-based drilling fluid

    波长/nm原始状态检测数据/光子
    第1次第2次第3次第4次
    287.30189297332385361
    287.35185237234229222
    287.41273409516344219
    287.47136226324185278
    287.52153218386297184
    287.58159205366236228
    287.64210159198225334
    287.70268205411303368
    287.75232199256284458
    287.81127163205198240
    287.87235191337209257
    287.92232136175341380
    287.98410352405412456
    288.049478691 133 9961 130
    288.103 870 5 917 6 030 6 430 6 934
    288.158 111 12 936 12 372 14 075 15 359
    288.213 334 3 436 3 645 3 767 4 659
    288.278547278808111 166
    288.32532448669646604
    288.38468379467421604
    288.44269283364364269
    288.49101268190232153
    288.55204132337402269
    288.61190189309146355
     注:①为剥蚀次数。
    下载: 导出CSV
  • [1] 田京燕, 徐玉超. 微心PDC钻头设计及现场试验[J]. 石油钻探技术, 2019, 47(1): 65–68. doi: 10.11911/syztjs.2018134

    TIAN Jingyan, XU Yuchao. Design and field application of a micro-coring PDC bit[J]. Petroleum Drilling Techniques, 2019, 47(1): 65–68. doi: 10.11911/syztjs.2018134

    [2] 汪绪刚, 张文华, 李应光, 等. 伊拉克艾哈代布油田快速钻井技术[J]. 石油钻探技术, 2013, 41(1): 35–39. doi: 10.3969/j.issn.1001-0890.2013.01.007

    WANG Xugang, ZHANG Wenhua, LI Yingguang, et al. Rapid drilling technology in Ahdeb Oilfield[J]. Petroleum Drilling Techniques, 2013, 41(1): 35–39. doi: 10.3969/j.issn.1001-0890.2013.01.007

    [3] 路辉, 胡晓军, 曹斌, 等. 普铝中Fe, Si元素的激光诱导击穿光谱测试条件及定量分析研究[J]. 光谱学与光谱分析, 2019, 39(4): 1267–1273.

    LU Hui, HU Xiaojun, CAO Bin, et al. Investigation on experimental conditions and quantitative analysis for Fe and Si elements in general aluminum by laser induced breakdown spectroscopy technique[J]. Spectroscopy and Spectral Analysis, 2019, 39(4): 1267–1273.

    [4] 檀兵. 激光诱导击穿光谱谱峰元素的自动识别[D]. 无锡: 江南大学, 2018.

    TAN Bing. Automatic identification of spectral peaks elements in laser-induced breakdown spectroscopy[D]. Wuxi: Jiangnan University, 2018.

    [5] 檀兵, 黄敏, 朱启兵, 等. 激光诱导击穿光谱谱峰元素自动识别方法研究[J]. 中国激光, 2018, 45(8): 273–279.

    TAN Bing, HUANG Min, ZHU Qibing, et al. Method on elements automatic identification of spectral peaks in laser-induced breakdown spectroscopy[J]. Chinese Journal of Lasers, 2018, 45(8): 273–279.

    [6] 张海滨. 激光诱导击穿光谱定量分析算法研究[D]. 合肥: 中国科学技术大学, 2018.

    ZHANG Haibin. Research on quantitative analysis algorithm of laser-induced breakdown spectroscopy[D]. Hefei: University of Science and Technology of China, 2018.

    [7] 张斌. LIBS在金属元素定量分析中的应用及其影响因素研究[J]. 中国石油石化, 2017(12): 33–34.

    ZHANG Bin. Application and research on its influencing factors of LIBS in quantitative analysis of metal elements[J]. China Petrochem, 2017(12): 33–34.

    [8] 胡志裕. 利用激光诱导击穿光谱定性与定量分析固体中元素方法研究[D]. 太原: 山西大学, 2013.

    HU Zhiyu. Study on qualitative and quantitative analytical method for elements in solid state matter by laser-induced breakdown spectroscopy[D]. Taiyuan: Shanxi University, 2013.

    [9] 郭志卫, 孙兰香, 张鹏, 等. 基于LIBS技术的水泥粉末在线成分分析[J]. 光谱学与光谱分析, 2019, 39(1): 278–285.

    GUO Zhiwei, SUN Lanxiang, ZHANG Peng, et al. On-line component analysis of cement powder using LIBS technology[J]. Spectroscopy and Spectral Analysis, 2019, 39(1): 278–285.

    [10] 辛勇, 李洋, 蔡振荣, 等. 激光诱导击穿光谱液态金属成分在线分析仪在线监测熔融铝液中元素成分[J]. 冶金分析, 2019, 39(1): 15–20.

    XIN Yong, LI Yang, CAI Zhenrong, et al. On-line monitoring of elemental composition in molten aluminum by laser-induced break-down spectroscopy online analyzer for liquid metal composition[J]. Metallurgical Analysis, 2019, 39(1): 15–20.

    [11] 钱燕. 激光诱导击穿光谱技术对于煤中有机元素的测量研究[D]. 杭州: 浙江大学, 2018.

    QIAN Yan. Research on the measurement of organic elements in coal using laser induced breakdown spectroscopy[D]. Hangzhou: Zhejiang University, 2018.

    [12] 于巧玲, 张毅驰. 激光诱导击穿光谱技术在重金属检测中的应用[J]. 化工技术与开发, 2018, 47(10): 26–30, 42. doi: 10.3969/j.issn.1671-9905.2018.10.008

    YU Qiaoling, ZHANG Yichi. Application of laser induced breakdown spectroscopy in heavy metals detections[J]. Technology & Development of Chemical Industry, 2018, 47(10): 26–30, 42. doi: 10.3969/j.issn.1671-9905.2018.10.008

    [13] 姚平, 王阳恩, 程庆华. 基于激光诱导击穿光谱的油菜籽含油量测定研究[J]. 粮食与油脂, 2018, 31(7): 49–51. doi: 10.3969/j.issn.1008-9578.2018.07.015

    YAO Ping, WANG Yang'en, CHENG Qinghua. Study on rapeseed oil content measurement based on laser induced breakdown spectroscopy[J]. Cereals & Oils, 2018, 31(7): 49–51. doi: 10.3969/j.issn.1008-9578.2018.07.015

    [14] 李艳, 翟开华, 李艳丽, 等. 基于激光诱导击穿光谱技术的城市土壤重金属含量检测与分析[J]. 湘潭大学自然科学学报, 2018, 40(3): 86–88, 128.

    LI Yan, ZHAI Kaihua, LI Yanli, et al. Detection and analysis of heavy metal content in urban soil by laser induced breakdown spectroscopy[J]. Journal of Natural Science of Xiangtan University, 2018, 40(3): 86–88, 128.

    [15] 杨文斌. 激光诱导击穿光谱技术在气体检测中的应用研究[D]. 成都: 中国科学院大学(中国科学院光电技术研究所), 2018.

    YANG Wenbin. Research on the application of laser induced breakdown spectroscopy in gas detection[D].Chengdu: University of Chinese Academy of Sciences (Institute of Photoelectric Techno-logy, Chinese Academy of Sciences), 2018.

    [16] 王成皓. 基于LIBS技术的矿石分选装置关键技术研究[D]. 长春: 吉林大学, 2018.

    WANG Chenghao. Research on key technologies of ore separation equipment based on LIBS technology[D]. Changchun: Jilin Univer-sity, 2018.

    [17] 王亚军. 基于激光诱导击穿光谱技术的宝玉石成分分析方法与应用研究[D]. 武汉: 中国地质大学(武汉), 2017.

    WANG Yajun. Study on gemstone component analysis methods and applications using laser induced breakdown spectroscopy[D]. Wuhan: China University of Geosciences(Wuhan), 2017.

    [18] 王鑫. 基于激光诱导击穿光谱煤质分析仪的研制[D]. 太原: 山西大学, 2015.

    WANG Xin. Development of a coal quality analyzer based on laser-induced breakdown spectroscopy[D]. Taiyuan: Shanxi University, 2015.

    [19] 张新华, 佘明军, 王舒, 等. 激光技术在录井工程中的应用进展及展望[J]. 石油钻探技术, 2018, 46(6): 111–117.

    ZHANG Xinhua, SHE Mingjun, WANG Yanshu, et al. The progress and pontential of the application of laser technology in mud logging[J]. Petroleum Drilling Techniques, 2018, 46(6): 111–117.

    [20] 佘明军, 付洪波, 贾军伟, 等. 激光诱导击穿光谱判定岩石陆相和海相沉积[J]. 光子学报, 2018, 47(8): 0847009.

    SHE Mingjun, FU Hongbo, JIA Junwei, et al. Determination of terrestrial and marine sedimentary rocks by laser-induced breakdown spectroscopy[J]. Acta Photonica Sinica, 2018, 47(8): 0847009.

    [21] 贾军伟, 付洪波, 王华东, 等. 基于激光诱导击穿光谱技术的岩性识别方法研究[J]. 量子电子学报, 2018, 35(3): 264–270.

    JIA Junwei, FU Hongbo, WANG Huadong, et al. Lithology identification methods based on laser-induced breakdown spec-troscopy technology[J]. Chinese Journal of Quantum Electronics, 2018, 35(3): 264–270.

    [22] 陈楠, 杨燕婷, 田地, 等. 录井专用型激光诱导击穿光谱仪测定岩屑中的8种元素[J]. 分析化学, 2018, 46(1): 74–80. doi: 10.11895/j.issn.0253-3820.171206

    CHEN Nan, YANG Yanting, TIAN Di, et al. Determination of eight kinds of elements in cuttings by logging special laser-induced breakdown spectrometer[J]. Chinese Journal of Analytical Chemi-stry, 2018, 46(1): 74–80. doi: 10.11895/j.issn.0253-3820.171206

    [23] 陈楠. 基于LIBS技术的录井岩屑定量分析方法及软件研究[D]. 长春: 吉林大学, 2018.

    CHEN Nan. Study on quantitative analysis methods and software of log rock cuttings based on LIBS[D]. Changchun: Jilin University, 2018.

    [24] 佘明军, 李油建, 李胜利, 等. 激光诱导击穿光谱自动识别泥岩颜色试验分析[J]. 录井工程, 2015, 26(1): 5–8. doi: 10.3969/j.issn.1672-9803.2015.01.002

    SHE Mingjun, LI Youjian, LI Shengli, et al. Experimental analysis of automatic identification of mudstone color by laser-induced breakdown spectroscopy[J]. Mud Logging Engineering, 2015, 26(1): 5–8. doi: 10.3969/j.issn.1672-9803.2015.01.002

    [25] 陈兴龙, 董凤忠, 陶国强, 等. 激光诱导击穿光谱在地质录井岩性快速识别中的应用[J]. 中国激光, 2013, 40(12): 1215001.

    CHEN Xinglong, DONG Fengzhong, TAO Guoqiang, et al. Fast lithology identification by laser-induced breakdown spectroscopy[J]. Chinese Journal of Lasers, 2013, 40(12): 1215001.

    [26] 田野, 王振南, 侯华明, 等. 基于激光诱导击穿光谱的岩屑识别方法研究[J]. 光谱学与光谱分析, 2012, 32(8): 2027–2031. doi: 10.3964/j.issn.1000-0593(2012)08-2027-05

    TIAN Ye, WANG Zhennan, HOU Huaming, et al. Study of cuttings identification using laser-induced breakdown spectroscopy[J]. Spec-troscopy and Spectral Analysis, 2012, 32(8): 2027–2031. doi: 10.3964/j.issn.1000-0593(2012)08-2027-05

    [27] 任立辉, 李文东, 慈兴华, 等. 基于LIBSVM的石油录井中岩屑岩性识别方法研究[J]. 中国海洋大学学报, 2010, 40(9): 131–136.

    REN Lihui, LI Wendong, CI Xinghua, et al. A method for identification of cuttings in petroleum logging by LIBSVMs[J]. Periodical of Ocean University of China, 2010, 40(9): 131–136.

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  • 收稿日期:  2019-06-06
  • 修回日期:  2019-06-25
  • 网络出版日期:  2019-07-23
  • 刊出日期:  2019-06-30

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