• journal_title：Bulletin of Canadian Petroleum Geology
• Contributor：Pang Xiongqi ; Jiang Zhenxue ; Li Zhuo ; Wu Li ; Jiang Fujie ; Zhou Jingjing ; Zhou Xiaohui ; Li Xiaolei
• Publisher：Canadian Society of Petroleum Geologists
• Date：2012-09-01
• Format：text/html
• Language：en
• Identifier：10.2113/gscpgbull.60.3.200
• journal_abbrev：Bulletin of Canadian Petroleum Geology
• issn：0007-4802
• volume：60
• issue：3
• firstpage：200

Hydrocarbon Accumulation Coefficient (HAC) is an important parameter in the genetic method of hydrocarbon resource assessment. This parameter is usually derived from a simple geological analogy or from expert judgment based on experience, which can lead to large uncertainties in hydrocarbon resource assessment results. In this article, we introduce a new method for determining the HAC, based on Single Factor Correlation Analysis and Multivariate Regression Analysis, using data collected from basins with a high degree of exploration maturity and large amounts of proven reserves. Firstly, the principal factors that control the hydrocarbon accumulation coefficient, such as the time ratio of peak expulsion and caprock formation, the ratio of maximum fault throw and caprock thickness, and the rate of fault displacement, are determined by Single Factor Correlation Analyses. A quantitative model can then be established between HAC and the principal controlling factors using the Multivariate Regression Analysis. The proposed method was applied to the Huanghekou Sag in Bohai Bay Basin, eastern China. The results show that the HAC is 29% in the Huanghekou Sag, with a total resource of 1435 × 10⁶ m³ oil equivalent, which is consistent with geological observations of this basin and suggests that the proposed method improves the applicability of the generic method in resource assessment.