多芳烃参数定量评价烃源岩成熟度的方法——以银额盆地中生界烃源岩为例

芳烃成熟度参数被广泛应用于评价烃源岩或原油成熟度,但实际上生源特征、沉积环境等因素对一些参数的影响可能大于成熟度的控制,导致一些参数在某些研究区的应用效果并不理想,且前人基于单一参数建立的计算视镜质体反射率(R_c)的关系式也并不适用于所有研究区,因此,探索出了一种芳烃参数定量评价烃源岩成熟度的方法。该方法基于研究区一定数量的烃源岩芳烃组分的色谱—质谱(GC-MS)分析数据,通过开展各芳烃成熟度参数与R_o的相关性分析,分别在烷基萘系列、烷基菲系列和烷基二苯并噻吩系列3大类芳烃成熟度参数中找出1个对成熟度最敏感(相关系数最大)的参数,利用数值分析软件对这几个参数和R_o进行多元线性回归,拟合出一个利用多参数定量计算R_c的关系式。该方法在银额盆地哈日凹陷中生界湖相混合型(有机质类型以Ⅱ₁—Ⅱ₂型为主)烃源岩研究中取得了很好的应用效果。用该方法拟合出的关系式计算的R_c与R_o的相关系数R²高达0.96,...

Quantitative assessment of source rock maturity with multiple aromatic parameters:a case study of Mesozoic source rocks in Yingen-Ejinaqi Basin

Aromatic parameters have been widely applied to assess the maturity of organic matters. Some parameters may not only be affected by maturation, but also more affected by organic matter source, sedimentary environment, etc. Therefore, the application effect of some parameters in some study areas were not satisfying, and the previous relational expression to calculate the vitrinite reflectance (R_c) which only based on a single parameter is also not suitable for other areas. In this study, we proposed a method to improve the accuracy of using multiple aromatic parameters to quantitatively evaluate source rock maturity. This method was based on a certain number of GC-MS analysis data of aromatic fractions of source rocks in the study area, to find out a most sensitive parameter to maturity in three categories of aromatics (alkyl naphthalene series, alkyl phenanthrene series and alkyl dibenzothiophene series) respectively. Here the most sensitive parameter meant having the largest correlation coefficient to R_o in certain category. Then a multiple linear regression equation was established among these three parameters and R_o using a numerical analysis software, and with this equation R_c can then be calculated with multiple parameters. This method is applied to the study of Mesozoic lacustrine source rocks in the Hari Sag of Yingen-Ejinaqi Basin, the organic matter types of these source rock are mainly type Ⅱ₁-Ⅱ₂. The results indicated that the correlation coefficient (R_c) between R_o and R_c which was calculated by established formula was as high as 0.96, and compared with the single aromatics parameter, the correlation coefficient has been considerably improved.