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Improve impedance inversion by adopting seismic sedimentary-guided a priori model

机译:通过地震沉积引导的先验模型改善阻抗反演

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We have developed an innovative procedure for model-based seismic inversion in areas with sparse or clustered and biased well control, where lithofacies and geobodies cannot be adequately sampled in wells and correctly represented in a priori acoustic impedance (AI) models constructed with conventional kriging methods. We have applied seismic sedimentology for facies mapping before the model building process. Lithology- calibrated seismic stratal slices contain rich information for analyzing sedimentary geomorphology and dispersal patterns of depositional systems, providing independent geologic knowledge to constrain a priori models. The new information can be incorporated by directional kriging that properly addresses facies types, orientations, and facies boundary conditions. Finally, the improved a priori model can be applied in Bayesian inversion for an updated inverted AI volume. This procedure was applied in a 3D project in Saidong Depression, Erlian Basin, China, with promising results, achieving inverted AI maps with a more complete facies representation, a more reasonable sediment dispersal pattern (orientation), and clearer facies boundaries.
机译:我们开发了一种创新的程序,用于在稀疏或集群和偏向井控区域中的基于模型的地震反演,在这些区域中,岩相和地质体无法在井中进行充分采样,并且无法正确地表示为使用传统克里金法构造的先验声阻抗(AI)模型。在建立模型之前,我们已将地震沉积学应用于相图绘制。岩性校准的地震地层切片包含丰富的信息,可用于分析沉积地貌和沉积系统的扩散模式,提供独立的地质知识以约束先验模型。可以通过定向克里金法合并新信息,该方法可以正确处理相类型,方向和相边界条件。最后,可以将改进的先验模型应用于贝叶斯反演,以获取更新的反演AI量。该程序已在中国二连盆地赛义登凹陷的3D项目中得到了应用,并获得了可喜的成果,获得了具有更完整的相表示,更合理的沉积物分散模式(方向)和更清晰的相界的倒置AI图。

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