中国重点盆地油气资源丰度统计特征及预测模型建立

doi:10.3969/j.issn.1672-7703.2024.03.015

摘要/Abstract

摘要： 油气资源丰度是资源评价的关键参数之一，确定油气资源丰度对油气资源评价具有重要意义。通过对中国重点盆地石油资源丰度和天然气资源丰度进行统计分析，明确了中国各大油气盆地的常规油气总体上以中、低资源丰度为主，且多为特低、低资源丰度，只有少数几个优势区块才具有高资源丰度。在此基础上，分析了影响油气资源丰度的地质因素，筛选了生烃强度、圈闭面积系数、区域不整合次数3个主控因素。分别基于前陆盆地、克拉通盆地和裂谷盆地，建立了以3个主控因素为主，适用于常规油气的资源预测模型，将该模型应用于3类盆地6个凹陷中，计算资源量与第四次油气资源评价结果比较接近，表明该预测方法具有操作简便、结果可靠、便于推广的优点，可以对数据不太丰富、勘探程度不高的地区进行前期常规油气资源预测。

关键词: 油气资源丰度, 统计特征, 预测模型

Abstract: The oil and gas resource abundance is one of the key parameters in resource assessment, and the determination of this parameter is of great significance. The statistical analysis of the abundance of oil and natural gas resources in key basins in China is conducted, which indicates that the conventional oil and gas resources in the major proliferous basins is dominated by medium-low abundance. The resource abundance in most blocks is ultra-low to low, and it is high in only a few dominant blocks. On this basis, the geological factors affecting the abundance of oil and gas resources are determined, including three main controlling factors of hydrocarbon generation intensity, trap area coefficient, and regional unconformities. By using the three main controlling factors, prediction model of conventional oil and gas resource amount is established for foreland basin, cratonic basin and rift basin. Subsequently, the model is applied to six sags in the three types of basins, and relatively consistent results of the calculated resource amount are obtained with those in the fourth round oil and gas resource assessment, indicating advantages of simple operation, reliable results and easy application of this prediction method, which can be used to preliminarily predict the amount of conventional oil and gas resources in areas with less abundant data and low degree of exploration.

中图分类号:

TE16

杨舒越, 姜福杰, 温思远. 中国重点盆地油气资源丰度统计特征及预测模型建立[J]. 中国石油勘探, 2024, 29(3): 170-180.

Yang Shuyue, Jiang Fujie, Wen Siyuan. Statistical characteristics and prediction model of oil and gas resource abundance in key basins in China[J]. China Petroleum Exploration, 2024, 29(3): 170-180.

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