We present lithofacies classifications for a tight gas sandstone reservoir by analyzing hierarchies of heterogeneities. We use principal component analysis (PCA) to overcome the two level of heterogeneities, which results in a better lithofacies classification than the traditional cutoff method. The classical volumetric method is used for estimating oil/gas in-place resources in the petroleum industry since its inception is not accurate because it ignores the heterogeneities of and correlation between the petrophysical properties. We present the importance and methods of accounting for the heterogeneities of and correlation between petrophysical properties for more accurate hydrocarbon volumetric estimations. We also demonstrate the impacts of modeling the heterogeneities and correlation in porosity and hydrocarbon saturation for hydrocarbon volumetric estimations with a tight sandstone gas reservoir. Furthermore, geoscientists have traditionally considered that small-scale heterogeneities only impact subsurface fluid flow, but not impact the hydrocarbon resource volumetric estimation. We show the importance of modeling small-scale heterogeneities using fine cell size in reservoir modeling of unconventional resources for accurate resource assessment.

通过分析非均质性层次，我们提出了致密气砂岩储层的岩相分类。我们使用主成分分析 (PCA) 来克服两个水平的非均质性，这导致比传统的截止方法更好的岩相分类。经典的体积法在石油工业中用于估算石油/天然气的就地资源量，因为它从一开始就不准确，因为它忽略了岩石物理特性的非均质性和相关性。我们介绍了解释岩石物理特性的异质性和相关性的重要性和方法，以实现更准确的碳氢化合物体积估计。我们还展示了对孔隙度和油气饱和度的非均质性和相关性进行建模对致密砂岩气藏油气体积估计的影响。此外，地球科学家传统上认为小规模的非均质性仅影响地下流体流动，而不影响油气资源体积估计。我们展示了在非常规资源储层建模中使用精细单元大小对小规模异质性进行建模以实现准确资源评估的重要性。