地质统计岩石物理学AVA反演
Geostatistical Rock Physics AVA Inversion
摘要：
储层模型是地下岩石物理性质（如孔隙度、矿物体积和流体饱和度）的数值表示。这些通常是从两步方法中的地震反演推断出的弹性模型导出的：首先，地震反射数据被反演为感兴趣的弹性属性（如密度、P波和S波速度）;然后这些被用作约束属性来模拟地下岩石物理变量。顺序方法不能确保不确定性在整个地质建模工作流程中的适当传播，因为它没有描述观测到的地震资料与所得岩石物理模型之间的直接联系。岩石物理模型将这两个领域联系起来。我们建议将地震和岩石物理建模集成到迭代地质统计地震反演方法中。所提出的方法允许通过同时整合测井、地震反射数据和岩石物理模型预测来直接推断孔隙度、页岩体积和流体饱和度。随机序贯模拟被用作模型参数空间的扰动技术，校准的相相关岩石物理模型将弹性域和岩石物理域联系起来，并且基于交叉基因演算法的全局优化器确保了方法从迭代到迭代的收敛。该方法应用于从北海储层的真实储层数据集提取的3D体积，并与地质统计地震AVA进行比较。
英文摘要：
Reservoir models are numerical representations of the subsurface petrophysical properties such as porosity, volume of minerals and fluid saturations. These are often derived from elastic models inferred from seismic inversion in a two-step approach: first, seismic reflection data are inverted for the elastic properties of interest (such as density, P-wave and S-wave velocities); these are then used as constraining properties to model the subsurface petrophysical variables. The sequential approach does not ensure a proper propagation of uncertainty throughout the entire geo-modelling workflow as it does not describe a direct link between the observed seismic data and the resulting petrophysical models. Rock physics models link the two domains. We propose to integrate seismic and rock physics modelling into an iterative geostatistical seismic inversion methodology. The proposed method allows the direct inference of the porosity, volume of shale and fluid saturations by simultaneously integrating well-logs, seismic reflection data and rock physics model predictions. Stochastic sequential simulation is used as the perturbation technique of the model parameter space, a calibrated facies-dependent rock physics model links the elastic and the petrophysical domains and a global optimizer based on cross-over genetic algorithms ensures the convergence of the methodology from iteration to iteration. The method is applied to a 3D volume extracted from a real reservoir dataset of a North Sea reservoir and compared to a geostatistical seismic AVA.
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