四维多波地震在油藏动态监测中的应用

研究区位于加拿大阿萨巴斯卡油砂区，该区目的层埋深极小，地表条件复杂，油藏开发时间短。因此，开发前、后地震数据差异小，四维地震一致性处理、提取可靠的油藏变化信息及二次测井数据难度大，限制了四维地震反演方法的推广、应用。为此，提出了一种基于低频模型驱动的四维多波联合反演方法，在反演模型中考虑了两期转换波的差异信息，在反演过程中加入转换波数据，利用四维三分量（4D3C）地震资料，充分融合“四维”和“多波”两项前沿地震勘探技术，实现了油藏精细描述及动态监测。获得以下认识：①处理与解释实时结合，逐步质控，提高了非油藏信息的一致性，保留并突出了油藏信息真实差异。②岩石物理分析结果表明，纵横波速度比对油藏变化最敏感，可作为油藏动态监测的敏感参数。③充分利用纵波与转换波时移量信息，建立了反映油藏变化趋势的低频模型，规避了缺少二次测井数据的限制，方法简单易行，蒸汽腔预测结果准确、可靠。

Application of 4D multi-component seismic survey in dynamic reservoir monitoring

In the study area located in the Athabasca oil sand region of Canada, the target layers are extremely shallow, the surface conditions are complex, and the time of reservoir development is short. Therefore, the difference of seismic data before and after the reservoir development is small, and it is difficult to do 4D seismic consistency processing, extract reliable reservoir change and record secondary logging data. This limits the popularization and application of 4D seismic inversion. This paper proposes a 4D multi-component joint inversion method based on a low-frequency model. The model takes into account the difference of converted seismic data, adds converted seismic data into the inversion process. By using 4D3C seismic data and fully integrating two frontier seismic exploration technologies (“4D” and “multi-component”), the 4D multi-component joint inversion method realizes fine reservoir characterization and dynamic monitoring. The following understandings are obtained: ①Real-time combination of processing and interpretation and step by step quality control improve the consistency of non-reservoirs, and retains and highlights the real difference of reservoirs; ②rock physics analysis shows that the velocity ratio of compressional and shear wave is most sensitive to reservoir change and can be used as a sensitive parameter for dynamic reservoir monitoring; ③by making full use of time-shift information of compressional seismic data and converted seismic data, the low-frequency model reflecting reservoir variation can be established, which avoids the limitation of secondary logging data. The method is simple and easy to use, and the prediction of steam chamber is accurate and reliable.