摘要
在油藏开发中,三维地质模型的精度直接影响油藏模拟的可靠性,而三维地震高分辨率反演的岩性体、物性体等结果在传统地质建模方法中并没有得到充分利用.为此本文将基于Bayesian-MCMC(贝叶斯推理-马尔科夫链蒙特卡罗)算法的地质统计学反演成果直接用于三维地质模型的建立和后续的油藏模拟当中.基于Bayesian-MCMC算法的地质统计学反演技术将约束稀疏脉冲反演和地质统计学模拟技术的优势相结合,以地震数据体、测井曲线和以概率密度函数、变差函数表达的地质信息为基础,反演得到纵、横向均具有高分辨率的三维岩性体、孔隙度体、饱和度体、泥质含量体等.这些结果通过时深转换直接建立高精度的三维岩性模型、物性模型,为后续的油藏模拟提供了高精度的基础数据.基于该方法重新建立的三维地质模型细节更加丰富、重新计算的气田静态储量与动态储量吻合好、生产井的历史拟合效果得到了明显的改善.充分说明重新建立的地质模型具有更高的精度、其增加的细节更符合地下的实际地质情况.文章首先简要介绍了基于Bayesian-MCMC算法的地质统计学反演的方法原理和实现流程,随后通过实例展示了该技术的在三维地质建模和油藏数值模拟中的应用效果.
In the reservoir development, the accuracy of 3 D geological model directly affects the reliability of reservoir simulation. At the mean while,the results of the 3 D seismic highresolution inversion, such as the lithology, physical properties,have not been fully utilized in the traditional geological modeling method. For this purpose,the results of geostatistical inversion based on Bayesian-MCMC algorithm are used to establish 3 D geological model directly and subsequent reservoir simulation. The geostatistical inversion method based on Bayesian-MCMC algorithm can combine the advantages of constrained spare spark inversion with geostatistical simulation. Based on seismic data,log curves and geostatistical information,this method can be used to invert lithologies,porosity,saturation and volume of shale et al. the result has higher vertical resolution and higher horizontal resolution. The results can be used for following geological modeling and reservoir simulation through time to depth conversion. The reconstructed geological model with richer details,static oil reserves recalculated based on new model agree with the dynamic reserves well and history fitting of production wells has been improved significantly. It shows that the re-established geological model has higher accuracy and its added details are more in line with the actual underground geological conditions. This paper introduce the principle and workflow of the method firstly, then apply the method to real geological modeling and reservoir simulation and achieve good application.
作者
孙月成
SUN Yue-cheng(Shenyang Center of China Geological Survey, Shenyang 110034, China)
出处
《地球物理学进展》
CSCD
北大核心
2018年第2期724-729,共6页
Progress in Geophysics
基金
中国地质调查局油气基础地质调查项目(DD20160167)资助