钻井液中的烃能够显示出地层的含油气情况，地层含油气浓度的检测对识别真假油气显示，特别是准确解释和评价油气层具有重要意义。基于激光拉曼光谱技术具有连续、快速、直接检测样品的独特优势，开展了激光拉曼光谱技术应用于钻井液中含烃浓度定量识别的研究。实验室条件下搭建的激光拉曼在线检测系统对C7～C14正构烷烃及苯进行了检测与振动模式指认，在水基钻井液中优选正辛烷作为标志烃，基于最小二乘法建立了水基钻井液中正辛烷不同特征峰数学模型，在1 298 cm-1频移处振动强度与正辛烷含量具有良好的线性关系；在柴油基钻井液中优选苯作为标志烃，基于最小二乘法建立了油基钻井液中苯的不同特征峰数学模型，在986 m-1频移处振动强度与添加苯含量具有良好线性关系。实验结果表明：激光拉曼光谱技术可用于钻井液中含烃浓度的检测，为反演地层含油气浓度，提高油气层判识精度提供了一种新的途径。

The hydrocarbons in the drilling fluid can indicate the hydrocarbon content of the formation.The detection of oil and gas concentration in the stratum is of great significance for the identification of true and false oil and gas,especially for the accurate interpretation and evaluation of oil and gas layers.Based on the unique advantages of continuous,rapid and direct detection of samples by laser Raman spectroscopy,we carried out researches on quantitative Raman detection of hydrocarbon concentration in drilling fluid.The laser Raman online detection system was built under laboratory conditions which was used to detect C7-C14 normal paraffin and benzene.The n-octane was selected as the marker of alkanes in water-based drilling fluid and the mathematical models of different characteristic peaks of n-octane in water-based drilling fluid were established based on the least square method.The vibration intensity at the frequency shift of 1 298 cm-1 has a good linear relationship with n-octane content.The benzene was selected as the marker hydrocarbon in the diesel oil drilling fluid and the mathematical model of different characteristic peaks of benzene in oil drilling fluid were established based on the least square method.The vibration intensity at the frequency shift of 986 m-1 has a good linear relationship between the vibration intensity and the content of added benzene.The experimental results show that the laser Raman spectroscopy can be used for in-situ detection of hydrocarbon concentration in drilling fluid and has good stability and repeatability in order to provide a new way for the inversion of oil and gas concentration and improving the accuracy of oil and gas reservoir identification.