Oil sands are the most important of the oil and gas resources in Canada. So the distribution and evaluation of oil sands form a critical basis for risk investment in Canada. Distribution of oil sands resources is seve...Oil sands are the most important of the oil and gas resources in Canada. So the distribution and evaluation of oil sands form a critical basis for risk investment in Canada. Distribution of oil sands resources is severely controlled by the reservoir heterogeneity. Deterministic modeling is commonly used to solve the heterogeneity problems in the reservoir, but rarely used to evaluate hydrocarbon resources. In this paper, a lithofacies based deterministic method is employed to assess the oil sands resources for a part of a mining project in northern Alberta. The statistical analysis of Dean Stark water and oil saturation data and study of the core description data, regional geology and geophysical logs reveal that the lithofacies in the study area can be classified into reservoir facies, possible reservoir facies and non-reservoir facies. The indicator krigging method is used to build a 3D lithofacies model based on the classification of sedimentary facies and the ordinary krigging method is applied to petrophysical property modeling. The results show that the krigging estimation is one of the good choices in oil sand resources modeling in Alberta. Lithofacies-grade based modeling may have advantages over the grade-only based modeling.展开更多
文摘Oil sands are the most important of the oil and gas resources in Canada. So the distribution and evaluation of oil sands form a critical basis for risk investment in Canada. Distribution of oil sands resources is severely controlled by the reservoir heterogeneity. Deterministic modeling is commonly used to solve the heterogeneity problems in the reservoir, but rarely used to evaluate hydrocarbon resources. In this paper, a lithofacies based deterministic method is employed to assess the oil sands resources for a part of a mining project in northern Alberta. The statistical analysis of Dean Stark water and oil saturation data and study of the core description data, regional geology and geophysical logs reveal that the lithofacies in the study area can be classified into reservoir facies, possible reservoir facies and non-reservoir facies. The indicator krigging method is used to build a 3D lithofacies model based on the classification of sedimentary facies and the ordinary krigging method is applied to petrophysical property modeling. The results show that the krigging estimation is one of the good choices in oil sand resources modeling in Alberta. Lithofacies-grade based modeling may have advantages over the grade-only based modeling.
