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A Mathematical Calculation Model Using Biomarkers to Quantitatively Determine the Relative Source Proportion of Mixed Oils 被引量:3
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作者 CHEN Jianping DENG Chunping +1 位作者 SONG Fuqing ZHANG Dajiang 《Acta Geologica Sinica(English Edition)》 SCIE CAS CSCD 2007年第5期817-826,共10页
It is difficult to identify the source(s) of mixed oils from multiple source rocks, and in particular the relative contribution of each source rock. Artificial mixing experiments using typical crude oils and ratios ... It is difficult to identify the source(s) of mixed oils from multiple source rocks, and in particular the relative contribution of each source rock. Artificial mixing experiments using typical crude oils and ratios of different biomarkers show that the relative contribution changes are non-linear when two oils with different concentrations of biomarkers mix with each other. This may result in an incorrect conclusion if ratios of biomarkers and a simple binary linear equation are used to calculate the contribution proportion of each end-member to the mixed oil. The changes of biomarker ratios with the mixing proportion of end-member oils in the trinal mixing model are more complex than in the binary mixing model. When four or more oils mix, the contribution proportion of each end-member oil to the mixed oil cannot be calculated using biomarker ratios and a simple formula. Artificial mixing experiments on typical oils reveal that the absolute concentrations of biomarkers in the mixed oil cause a linear change with mixing proportion of each end-member. Mathematical inferences verify such linear changes. Some of the mathematical calculation methods using the absolute concentrations or ratios of biomarkers to quantitatively determine the proportion of each end-member in the mixed oils are deduced from the results of artificial experiments and by theoretical inference. Ratio of two biomarker compounds changes as a hyperbola with the mixing proportion in the binary mixing model, as a hyperboloid in the trinal mixing model, and as a hypersurface when mixing more than three end- members. The mixing proportion of each end-member can be quantitatively determined with these mathematical models, using the absolute concentrations and the ratios of biomarkers. The mathematical calculation model is more economical, convenient, accurate and reliable than conventional artificial mixing methods. 展开更多
关键词 mixed oil biomarker oil source correlation quantitative determination mathematical model
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用生物标志物定量计算混合原油油源的数学模型 被引量:24
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作者 陈建平 邓春萍 +1 位作者 宋孚庆 张大江 《地球化学》 CAS CSCD 北大核心 2007年第2期205-214,共10页
多烃源层叠合盆地混源油油源的定量计算是十分困难的问题。典型原油的人工混合配比实验显示,当两个生物标志物浓度不同的原油相混合时,各类生物标志物的比值参数随端元原油混入量呈非线性变化,以生物标志物比值参数和简单的二元线性关... 多烃源层叠合盆地混源油油源的定量计算是十分困难的问题。典型原油的人工混合配比实验显示,当两个生物标志物浓度不同的原油相混合时,各类生物标志物的比值参数随端元原油混入量呈非线性变化,以生物标志物比值参数和简单的二元线性关系方程定量计算混源油的混合比例将导致错误的结论。三个或者三个以上原油相混合时,各类生物标志物比值参数的变化更加复杂,各端元原油的贡献更加难以判识。但是,人工混合模拟实验表明混合油中生物标志物绝对含量与端元油的混入量呈线性关系,数学推导证明了这种线性关系,由此推导出相应的数学计算模型,其中:二元混合时比值参数与混入量呈双曲线关系,三元混合呈双曲面关系,四元及其以上的多元混合呈多维曲面,可以矩阵的方式定量计算各端元油的比例。依据这些数学模型,应用生物标志物的绝对含量和(或)生物标志物比值参数均可以定量计算出混源原油中各类原油的贡献比例。数学模型比通常的人工模拟实验方法更加经济、方便、精确和可靠。 展开更多
关键词 混源油 生物标志物 油源对比 定量计算 数学模型
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胜坨油田多源多期成藏混源油的定量判析 被引量:14
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作者 吕慧 张林晔 +1 位作者 刘庆 王忠 《石油学报》 EI CAS CSCD 北大核心 2009年第1期68-74,79,共8页
精细的原油组群划分、油源对比及成藏分析表明,东营凹陷胜坨油田主要含油层系沙二段的原油是由沙四上亚段烃源岩提供的早期降解原油与沙三下亚段、沙四上亚段两套烃源岩提供的晚期成藏原油形成的三元混合原油。选择两期成藏三个端元典... 精细的原油组群划分、油源对比及成藏分析表明,东营凹陷胜坨油田主要含油层系沙二段的原油是由沙四上亚段烃源岩提供的早期降解原油与沙三下亚段、沙四上亚段两套烃源岩提供的晚期成藏原油形成的三元混合原油。选择两期成藏三个端元典型的原油样品,建立三角形判识图版,运用生物标志物绝对定量分析方法对胜坨油田的混源油进行了油源比例确定。结果表明:坨二区沙二段原油中,沙四上亚段源岩早期贡献为39%,晚期贡献为30%,沙三下亚段源岩的贡献为31%;坨三区沙二段原油中,沙四上亚段源岩早期贡献为41%,晚期贡献为33%,沙三下亚段源岩贡献为26%,即从坨二区到坨三区沙三下亚段烃源岩的贡献有减小的趋势。另外,坨二区沙一段原油中,沙四上亚段源岩早期贡献为8%,晚期贡献为24%,沙三下亚段源岩贡献为68%,混源比例不同于本区主要含油层系原油。 展开更多
关键词 胜坨油田 混源油 生物标志物 油源对比 成藏期次 端元油 定量计算
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