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储层物性参数的改变伴随着弹性参数某种程度的改变,而这种改变并非简单的线性关系。加上观测信息的缺失、重叠、噪声破坏及模型理想化等原因,致使这种改变关系的获取具有较大的不确定性。针对传统统计岩石物理物性参数反演方法的不足,以利用弹性参数反演储层物性参数为目的,依据贝叶斯反演框架,我们建立了新的储层物性参数目标反演函数。首先,采用兼具确定性与随机性特点的统计岩石物理模型,考虑到不同弹性参数间的精度存在差异,引入权重系数,建立起储层物性参数与弹性参数间的加权统计关系。其次,基于这种加权统计关系,结合马尔科夫链蒙特卡洛随机模拟技术产生储层物性参数、弹性参数随机联合样本空间作为目标函数求解样本空间。最后,建立解的快速求解准则,求取最大后验概率密度对应的储层物性参数取值作为最终解。实际应用表明,该方法具有较高的反演效率,应用前景较好。
Changes in reservoir physical parameters are accompanied by some degree of change in the elastic parameters, which are not simply linear relationships. Coupled with the lack of observation information, overlap, noise damage and idealization of the model and other reasons, resulting in the acquisition of this relationship has a greater change in the uncertainty. In order to overcome the shortcomings of the traditional inversion method of petrophysical parameters, aiming at the inversion of reservoir physical parameters by using elastic parameters, a new inversion function of reservoir physical parameters is established based on Bayesian inversion framework. Firstly, the statistical petrophysical model, which has the characteristics of certainty and randomness, is adopted. Considering the differences in the accuracy of different elastic parameters, the weight coefficient is introduced to establish the weighted statistical relationship between reservoir physical properties and elastic properties. Secondly, based on this weighted statistical relationship, reservoir physical parameters are generated by combining Monte Carlo stochastic simulation with Markov chain, and the elastic parameters are randomly combined with the sample space as the objective function to solve the sample space. Finally, a fast solution criterion of the solution is established, and the value of the reservoir physical property parameter corresponding to the maximum posterior probability density is obtained as the final solution. Practical application shows that this method has high inversion efficiency and good application prospect.