基于激光诱导击穿光谱的岩屑岩性在线识别试验研究

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.

     

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