Geostatistical seismic inversion is an important method for establishing high‐resolution reservoir parameter models. There is no accurate representation method for reservoir structural features, and prior information about structural features cannot be incorporated into geostatistical inversion. Based on the assumption of the sparsity of stratigraphic sedimentary features, the same type of structural feature is used to represent the sedimentary pattern of reservoirs within the same facies. Different sparse representation patterns are used to represent the differences in sedimentary patterns between facies. Although changes in depositional environment might result in the multi‐scale characteristics of geological structures for varying sedimentary rhythms, this paper proposes a facies‐constrained geostatistical inversion method based on multi‐scale sparse representation to better accommodate such situation. Using the method of sparse representation combined with wavelet transform, the multi‐scale sedimentary structural features of reservoirs are learned from well‐logging data. Seismic facies and multi‐scale features are used as prior information for geostatistical inversion. Further, the likelihood function is constructed using seismic data to obtain the posterior probability distribution of reservoir parameters. Finally, the accurate inversion result is obtained by using multi‐scale sparse representation as a constraint in the posterior probability distribution of reservoir parameters. Compared with conventional geostatistical methods, this algorithm can better match the structural features of reservoir parameters with varying geological conditions. Field data tests have shown the effectiveness of this method in improving the accuracy and resolution of reservoir parameter structural features.

中文翻译：

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基于多尺度稀疏表示的相约束地统计地震反演方法

地统计地震反演是建立高分辨率储层参数模型的重要方法。储层结构特征尚无准确的表征方法，构造特征先验信息无法纳入地质统计反演中。基于地层沉积特征稀疏性的假设，用同一类型的构造特征来表征同一相内储层的沉积格局。采用不同的稀疏表示模式来表示相间沉积模式的差异。尽管沉积环境的变化可能导致不同沉积韵律的地质构造呈现多尺度特征，但为了更好地适应这种情况，本文提出了一种基于多尺度稀疏表示的相约束地质统计反演方法。采用稀疏表示结合小波变换的方法，从测井数据中了解储层多尺度沉积结构特征。地震相和多尺度特征被用作地质统计反演的先验信息。此外，利用地震数据构造似然函数以获得储层参数的后验概率分布。最后，利用多尺度稀疏表示作为储层参数后验概率分布的约束，得到准确的反演结果。与常规地质统计方法相比，该算法能够更好地匹配不同地质条件下储层参数的结构特征。现场数据测试表明，该方法在提高储层参数结构特征精度和分辨率方面是有效的。