基于主成分和支持向量机浓度参量同步荧光光谱油种鉴别

基于浓度参量同步荧光光谱技术,对不同溢油类型不同油源原油样品集、引入外扰相似油源样品集进行光谱数据采集,获取其浓度同步荧光光谱矩阵Concentration-Synchronous-Matrix-Fluorescence(CSMF),利用主成分分析方法对两套不同层次的原油相关样品集进行了多类分类识别。结果表明:主成分载荷图可以很好地反映各个原油相关样品在油源上的相似程度,结合支持向量机可以实现不同溢油类型及不同油源原油的准确分类,对于引入风化和海水外扰相似油源溢油样品集,两类分类区分的结果远远高于多类分类识别的结果。通过详细的主成分分析讨论,为溢油油种鉴别提供了一种利用多类分类识别,逐步缩减嫌疑样本数量,最后通过两两分类实现溢油样品准确识别的新思路。     

结合直观推导式演进特征投影法分析原油中非烃结构和含量

提出一种分析原油非烃结构和含量的方法。用直观推导式演进特征投影法分辨有关二维数据以获得非烃的纯色谱和纯质谱,再将所获质谱在标准质谱库中检索,并结合色谱保留指数分析等来进行单个非烃化合物结构鉴定;利用实验数据,根据分辨获得的纯色谱峰面积所建立的规一化模型,进行非烃化合物定量分析。用本法确定了一原油样品中168个含氮化合物和该油样一个馏分中60个其它非烃化合物的结构和含量。本方法具有系统分析原油非烃结构和含量的通用性;标准化合物加标回收实验表明,其准确度很好。     

综合模拟风化条件下渤海原油中生物标志物及多环芳烃风化规律研究

该文以渤海原油SZ36-1为研究对象进行综合模拟风化实验,探讨了原油中生物标志物及5类多环芳烃(PAHs)组分的分布情况及风化规律。结果表明:经过30 d风化,渤海原油SZ36-1中大部分生物标志物表现出强的稳定性,部分PAHs的分布发生较大改变,其中萘系列化合物损失最严重,相对浓度的损失达80.34%;菲、二苯并噻吩、、芴系列则相对稳定;经t检验分析风化样品测试数据,生物标志物诊断比值表现出良好的稳定性,所选取多环芳烃新诊断比值中,菲和系列、烷基取代二苯并噻吩类、烷基取代芴类的抗风化能力较强,可用于油源鉴别。     

气相色谱结合化学计量学分析4种食用植物油的指纹图谱

运用气相色谱法对4类植物油(橄榄油、花生油、菜籽油和大豆油)的脂肪酸组成进行分析,并构建了植物油的指纹图谱,对4类植物油进行鉴别和分类。采用连续投影算法(SPA)对变量进行筛选,选出11个特征变量。以特征变量作为输入,使用主成分分析(PCA)和有监督模式识别(径向基函数神经网络(RBFANN)、线性判别分析(LDA)和最小二乘-支持向量机(LS-SVM))进行建模分析。结果表明,11个特征变量能够较好地区分4类植物油,PCA获得了较好的分类,RBF-ANN的预报结果最佳,预报率为92.6%,并且能准确预报二组分混合掺杂油样。该方法能够准确区分植物油种类,可用于食用植物油的鉴别和掺杂食用植物油的鉴定。     

碳稳定同位素比质谱法对中东原油的鉴别

采用气相色谱/稳定同位素比质谱法(GC/IRMS)对具有相似化学特征的科威特、阿联酋、沙特以及伊拉克产的原油中正构烷烃(n-C10～n-C24)的碳稳定同位素比δ(13C/12C)进行了分析,通过原油单体烃分布趋势对比、主成分归类、同位素比值与诊断比例(Diagnostic ratio,DR)联用等方法对4种原油进行了鉴别。结果表明,沙特与伊拉克所产原油、科威特与阿联酋所产原油的单体烃分布趋势相似,且主成分相近,采用同位素比值与诊断比例联用法成功地对它们进行溯源。结果表明,沙特与伊拉克所产原油的δ(13C/12C)值以及DR(n-C17/pristane(Pr)、n-C18/phytane(Ph)、Pr/Ph)相近,说明它们具有相同的母质类型及沉积环境,属于同一种原油;科威特与阿联酋所产原油的δ(13C/12C)值相似,而DR明显不同,表明其母质类型及成熟度不同,属于不同种原油。本研究所采用的分析技术也适用于其它原油的溯源研究。     

应用主成分分析SPME/GC-MS法鉴别人体气味的研究

运用SPME/GC-MS法鉴别来自8位个体的16个腋窝部人体气味样品,得出各样品均含有7种共有成分.以7种共有成分为分析变量,运用主成分分析法对16个样品进行鉴别区分,壬酸、环十二醇和5,9-十一烷酸内酯的含量是决定第1主成分的关键因素,庚醛和己醛的含量是决定第2主成分的关键因素.十八烷和1-茨醇的含量是决定第3主成分的关键因素.     

CDJZ稠油降粘剂在吉林油田的应用研究

在本文中,报告了我们针对吉林油田稠油的特点,用成都川大金钟科技有限公司生产的CDJZ稠油降粘剂对该油田油样进行了试验室评价和现场试验的应用研究,结果表明,CDJZ降粘剂对吉林油田的稠油有很高的降粘率,现场采油提高了原油产量,从而极大地降低了生产成本,有较好的经济效益和社会效益。此外,文中还对该降粘剂的降粘机理也进行了初步的讨论。     

基于料酒的三维同步荧光光谱模式识别研究

提出了一种应用同步荧光光谱技术无损快速鉴别料酒品牌的新方法.利用主成分分解法和小波变换法对料酒样品的同步荧光光谱信号进行了压缩处理,分别采用同步荧光光谱数据的第一主成分和小波细节系数为特征变量进行主成分分析和聚类分析,分类结果表明小波系数作为料酒的特征变量对料酒品牌分类正确率更高.利用偏最小二乘和径向基人工神经网络方法...     

能量色散X射线散射结合主成分分析对液体易制毒化学品的探测与鉴别分类

采用能量色散X射线散射(EDXRS)技术探测了8种液体易制毒化学品的X射线散射光谱, 结果显示液体易制毒物质具有各自特征的EDXRS散射图谱. 将液体易制毒化学品的EDXRS散射信息与主成分分析结合, 发现前2个主成分可以表达X射线散射光谱的主要信息, 在PC1～PC2得分分布图上可将液体易制毒化学品进行分类. 研究结果表明, EDXRS光谱技术结合主成分分析法可以实现探测、 鉴别分类液体易制毒化学品, 为隐藏液体易制毒化学品的监管控制提供一个可行的鉴别方法.     

电感耦合等离子体原子发射光谱法测定油田水中金属元素

油田水是指在储集层中与油气伴生的地下水,是烃类运移、聚集、形成油气藏的动力和载体。它和油气之间存在着经常性的物质成分交换,油田水化学成分往往会反映出油气藏与原油、天然气的某些特征,因此研究油田水的性质及其地球化学特征,对于区分油田水和非油田水,分析油气运移、聚集和油     

Surfactants treatment of crude oil contaminated soils

This study reports experimental measurements investigating the ability of a biological (rhamnolipid) and a synthetic (sodium dodecyl sulfate, SDS) surfactant to remove the North Sea Ekofisk crude oil from various soils with different particle size fractions under varying washing conditions. The washing parameters and ranges tested were as follows: temperature (5 to 50 degrees C), time (5 to 20 min), shaking speed (80 to 200 strokes/min), volume (5 to 20 cm3), and surfactant concentration (0.004 to 5 mass%). The contaminated soils were prepared in the laboratory by mixing crude oil and soils using a rotating cylindrical mixer. Two contamination cases were considered: (1) weathered contamination was simulated by keeping freshly contaminated soils in a fan assisted oven at 50 degrees C for 14 days, mimicking the weathering effect in a natural hot environment, and (2) nonweathered contamination which was not subjected to the oven treatment. The surfactants were found to have considerable potential in removing crude oil from different contaminated soils and the results were comparable with those reported in literature for petroleum hydrocarbons. The removal of crude oil with either rhamnolipid or SDS was within the repeatability range of +/-6%. The most influential parameters on oil removal were surfactant concentration and washing temperature. The soil cation exchange capacity and pH also influenced the removal of crude oil from the individual soils. However, due to the binding of crude oil to soil during weathering, low crude oil removal was achieved with the weathered contaminated soil samples.     

FLOW PROPERTIES OF WEATHERED CRUDE OILS AND THEIR EMULSIONS

The present paper proposes the emulsification of weathered crude oils in water as a competitive and cost effective method for reducing their viscosities. Weathered crude oil samples were collected from major Kuwaiti oil lakes. Emulsion preparation involved using, either a nonionic surfactant or alkali, as well as both alkali and fatty acid. The obtained emulsions were characterized by measuring the droplet size distribution of the dispersed phase using optical microscopy. Emulsion stability was also examined in terms of the system breakdown. The rheological properties were measured using a concentric cylinder rotary rheometer. The emulsion rheological behavior has been studied as a function of composition, temperature, and shear rate. A constitutive model was developed to characterize the pseudoplastic behavior of the crude oil and the emulsion systems. The model fitted well the experimental results with a correlation coefficient higher than 95%. Associated with the pseudoplastic behavior, viscoelastic behavior has been observed with emulsions and some oils at high shear rates.

The results of this investigation indicated that the examined weathered crude oils can be transported through pipelines as emulsions of up to 80 vol.% oil concentrations. The proposed method of treatment with NaOH and oleic acid offers several advantages over the surfactant treatment. It exhibited comparable rheological behavior at lower cost and less mixing energy. It also provided higher emulsion stability, which favors oil transportation for longer distances.     

激光解吸电离傅立叶变换离子回旋共振质谱用于食用油的快速分析

利用激光解吸电离傅立叶变换离子回旋共振质谱(Laser desorption ionization,LDI-FTICR-MS)建立了一种快速分析食用油中甘油三酯(TAG)的方法。在激光能量为45%,激光频率100 Hz和辐照次数100shots的条件下,可以获得稳定重复的信号(RSD10%)。通过TAG的一级质谱图和二级碎片信息可以初步区别不同类型的食用油。在置信度为95%条件下,利用主成分分析法和聚类分析法可以有效地将34种食用油归类。此外,利用该方法可直接识别橄榄油中掺杂5%的菜籽油且根据线性公式可初步预测橄榄油中掺杂油品的种类。分析数据表明,LDI-FTICR-MS技术具有快速筛查和识别食用油的潜力。     

模式识别法分析5种植物油脂

通过模式识别方法区分花生油、大豆油、米糠油、棕榈油和菜籽油。采用气相色谱法分析5种植物油脂的脂肪酸,用面积归一化法计算每个植物油脂样品的各脂肪酸相对含量。以每个植物油脂中9个脂肪酸的相对含量为变量,采用SPSS13.0软件的模式识别技术对119个植物油脂样品进行区分。由主成分分析图可知,花生油、大豆油、米糠油、棕榈油和菜籽油被清晰地分为5组。判别分析建立的判别方程能较好地实现样品的判别,自身验证和交互验证的准确率均为100%。另取每种植物油脂各5个样品(共25个)进行验证,识别准确率为100%。对调和有棕榈油的花生油进行主成分分析,在主成分分析图上,调和油的分布点在花生油分布区域与棕榈油分布区域之间。     

Investigation of different crude oils applying thermal analysis/mass spectrometry with soft photoionisation

A variety of crude oil samples have been investigated by the combined methods of thermal analysis and mass spectrometry by means of a newly developed prototype of a thermogravimetry—single photon ionisation time-of-flight mass spectrometer coupling (TG-SPI-TOFMS). Single photon ionisation (SPI) was conducted utilising a novel electron beam pumped argon excimer lamp (EBEL) as photon source, and a TOFMS with orthogonal acceleration has been applied for the detection of the mass to charge signals. The advantage of the soft SPI technique over EI for the analysis of such complex samples could be clearly demonstrated, as the aliphatic hydrocarbons present in crude oil may be detected via their respective molecular ion signals, not showing the intense fragmentation typical for EI spectra of this substance class. The application of SPI revealed furthermore two distinct decomposition regions, dominated by evaporation and pyrolysis processes, respectively. Moreover, different crude oils could be distinguished by TA/SPI mass spectra due to their unique molecular signatures.     

基于化学模式识别的大蒜傅里叶变换红外光谱指纹图谱多样性

以不同地理居群的大蒜为研究对象,采用傅里叶变换红外光谱法获取各样品的红外谱图及不同波数下各样品的透过率数据,运用主成分分析及聚类分析等统计学方法对谱图数据进行了比较分析。结果发现,不同地理居群大蒜的红外指纹图谱存在差异,统计学分析结果显示25个品种大致可分为4大类(其中2个样品,4号及25号与这4类间有较大差异),此现象一定程度上反映了大蒜种植地居群环境对大蒜理化性质的影响。     

Effect of Interfacially Active Fractions of Some Egyptian Crude Oils on Their Emulsion Stability

Four samples from different crude oils were used for this study: light and heavy crude oils from Iran and two crude oils from Egypt, namely, Ras Gharb and Suez mix. The asphaltenes were separated from these crude oils and then the maltene (non‐asphaltenic fraction) was fractionated into waxes, aromatics, and resins. All fractions were characterized using FTIR and UV spectroscopic analyses in addition to gel permeation chromatograph (GPC). These fractions were tested for their emulsion stability. For chemometric analysis different parameters (variables) have been used to study the effect of different fractions (objects) on the emulsion stability. Such variables included the integrated areas under the stretching absorption peaks of CH in the range of 3000–2800 cm^?1, C?O in the range of 1750–1650 cm^?1, and the aromatic C?C in the range of 1650–1550 cm^?1, as well as UV absorption value at 235 nm and average molecular weight (MW). Principal component analysis (PCA) and multiple linear regression (MLR) were conducted for examining the relationship between multiple variables and the stability of water‐in‐crude oil emulsions. The results of PCA explain the interrelationships between the observations and variables in multivariate data. The correlation coefficients between different parameters derived from PCA reveals that the UV absorption value and MW are strongly correlated with emulsion stability. It also reveals that the resins, asphaltenes, and maltene have better emulsion stability than waxes and lower molecular weight aromatics. The linear relationship between the parameters and the stability of water‐in‐crude oil emulsions using MLR was modeled according to the better statistical results. The obtained mathematical model can be used to predict the stability of water‐in‐crude oil emulsions from the chemical groups and functionalities in each crude oil fraction.     

Analysis of petroleum compositional similarity using multiway principal components analysis (MPCA) with comprehensive two-dimensional gas chromatographic data

The accurate establishment of oil similarity is a longstanding problem in petroleum geochemistry and a necessary component for resolving the architecture of an oil reservoir. Past limitations have included the excessive reliance on a relatively small number of biomarkers to characterize such complex fluids as crude oils. Here we use multiway principal components analysis (MPCA) on large numbers of specific chemical components resolved with comprehensive two-dimensional gas chromatography-flame ionization detection (GC×GC-FID) to determine the molecular relatedness of eight different maltene fractions of crude oils. MPCA works such that every compound eluting within the same first and second dimension retention time is quantitatively compared with what elutes at that same retention times within the other maltene fractions. Each maltene fraction and corresponding MPCA analysis contains upwards of 3500 quantified components. Reservoir analysis included crude oil sample pairs from around the world that were collected sequentially at depth within a single well, collected from multiple depths in the same well, and from different depths and different wells but thought to be intersected by the same permeable strata. Furthermore, three different regions of each GC×GC-FID chromatograms were analysed to evaluate the effectiveness of MPCA to resolve compositional changes related to the source of the oil generating sediments and its exposure to biological and/or physical weathering processes. Compositional and instrumental artefacts introduced during sampling and processing were also quantitatively evaluated. We demonstrate that MPCA can resolve multi-molecular differences between oil samples as well as provide insight into the overall molecular relatedness between various crude oils.