摘要
定量荧光样品分析时,需要确定油层及刻度曲线,这需要分析人员具备地层识别能力,而且对于区域地层构造了解不清晰或地层复杂时,其确定难度较大。通过分析待测样品与原油谱图形态相似程度,实现智能判断原油层位及进行刻度曲线选择,提高了定量荧光分析的准确性。该方法实现了油层的智能识别,不需要人工判断原油层位及进行刻度曲线选择,便于在油田现场录井作业中推广和应用。
Quantitative fluorescence sample analysis requires determination of reservoir and calibration curves.This requires the analyst to have the ability of formation identification,moreover,it is difficult to determine the formation when the regional stratigraphic structure is complex or not clear.By analyzing the similarity degree between the testing sample andcrude oil spectrogram,the intelligent judgment of crude oil horizon and calibration curve selection can be realized,improving the accuracy of quantitative fluorescence analysis.The method realizes the intelligent identification of oil layers,no artificial judgment of crude oil horizon and calibration curve selection are required,it is easy to popularize and apply in field logging operation.
出处
《录井工程》
2017年第2期39-41,55,共4页
Mud Logging Engineering
关键词
定量荧光
谱图形态
油层识别
刻度曲线识别
quantitative fluorescence
spectrogram morpholo-gy
oil layer identification
calibration curve recognition
