激光诱导击穿光谱技术对火成岩岩性的高精度识别

摘要

在石油勘探领域，细碎岩屑样品的岩性识别，特别是物性接近的火成岩的高精度识别是地质学的难题之一。针对这一问题，提出了一种基于激光诱导击穿光谱技术（LIBS）元素分析和全碱-硅（TAS）图版的新方法。利用自主搭建的 LIBS 系统，首先通过对比实验，系统的研究了脉冲能量、采集延时、采集方式、预燃对光谱信号的影响，确定了对火成岩样品元素分析的最佳条件：脉冲能量50 mJ，采集延时2μs，采集同一样品表面20个不同点的光谱积分平均，并通过实验证明了预燃的样品处理方式不适合火成岩样品，有效提高了样品检测光谱数据的重复性。随后确定了火成岩岩性识别常用7种元素（钠镁铝硅钾钙铁）的特征谱线，定性分析和比较了不同岩性的火成岩样品；利用已知元素含量的国标系列岩石样品信息，生成了钠、硅、钾的定标曲线，线性相关系数均大于0．9，并利用国标岩石样品考察了定量分析的准确性；利用定标曲线法定量分析了火成岩样品的元素含量，并采用 TAS 图版法识别火成岩的岩性，准确率达90．7％。研究表明，LIBS 技术能够有效实现火成岩岩性的高精度识别。%In the field of petroleum exploration,lithology identification of finely cuttings sample,especially high precision identi-fication of igneous rock with similar property,has become one of the geological problems.In order to solve this problem,a new method is proposed based on element analysis of Laser-Induced Breakdown Spectroscopy (LIBS)and Total Alkali versus Silica (TAS)diagram.Using independent LIBS system,factors influencing spectral signal,such as pulse energy,acquisition time de-lay,spectrum acquisition method and pre-ablation are researched through contrast experiments systematically.The best analysis conditions of igneous rock are determined:pulse energy is 50 mJ,acquisition time delay is 2 μs,the analysis result is integral av-erage of 20 different points of sample’s surface,and pre-ablation has been proved not suitable for igneous rock sample by experi-ment.The repeatability of spectral data is improved effectively.Characteristic lines of 7 elements (Na,Mg,Al,Si,K,Ca,Fe) commonly used for lithology identification of igneous rock are determined,and igneous rock samples of different lithology are an-alyzed and compared.Calibration curves of Na,K,Si are generated by using national standard series of rock samples,and all the linearly dependent coefficients are greater than 0.9.The accuracy of quantitative analysis is investigated by national standard samples.Element content of igneous rock is analyzed quantitatively by calibration curve,and its lithology is identified accurately by the method of TAS diagram,whose accuracy rate is 90.7%.The study indicates that LIBS can effectively achieve the high precision identification of the lithology of igneous rock.