An analysis of spatial resolution is incorporated into an efficient model calibration approach with multi-scale data integration to examine the reliability of the estimated solution. The resolution is a measure of the degree of averaging of the local-scale (grid block) permeabilities during parameter estimation via inverse modeling. For a given set of data, it indicates the regions where our estimate is well constrained. By examining the spatial resolution in time-lapse seismic data integration, we can quantitatively evaluate the relative contribution of pressure and saturation changes on the calibrated permeability field. We illustrate this concept using synthetic and field applications. The synthetic example is a 5 spot pattern, where the time-lapse seismic data are incorporated as inferred pressure and saturation changes. The field example involves waterflooding of a North Sea reservoir with multiple seismic surveys. The results demonstrate that the analysis of spatial resolution provides quantitative information on our ability to estimate the subsurface heterogeneity. It is found that integration of seismic data based on inferred pressure changes better determine the barriers to the flow (e.g., low permeability areas), while calibrating the model based on saturation changes provides complementary information to identify the channels (e.g., high permeability regions).

中文翻译：

---

时移地震和生产数据的整合：空间分辨率分析

空间分辨率的分析被纳入具有多尺度数据集成的有效模型校准方法中，以检查估计解的可靠性。分辨率是通过逆向建模进行参数估计期间局部尺度（网格块）渗透率平均程度的度量。对于给定的数据集，它表示我们的估计受到良好约束的区域。通过检查时移地震数据集成中的空间分辨率，我们可以定量评估压力和饱和度变化对校准渗透率场的相对贡献。我们使用合成和现场应用来说明这个概念。合成示例是一个 5 点模式，其中将延时地震数据合并为推断的压力和饱和度变化。现场示例涉及通过多次地震勘测对北海水库进行注水。结果表明，空间分辨率的分析为我们估计地下非均质性的能力提供了定量信息。发现基于推断压力变化的地震数据的整合可以更好地确定流动障碍（例如，低渗透率区域），而基于饱和度变化校准模型提供补充信息来识别通道（例如，高渗透率区域） .