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Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

机译:合成AVO数据的贝叶斯反演以评估砂页岩介质中的流体和页岩含量

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摘要

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data.
机译:由于页岩晶状体或页岩层形式的各向异性,砂页岩层序的储层表征一直对地球科学家构成挑战。水饱和度和页岩体积是砂页岩层段感兴趣的基本储层属性,并且与流体含量和这种介质的蓄积潜力有关。本文提出了一种综合工作流程,该工作流程基于各向异性岩石物理学(T矩阵近似)和地震反射率建模,使用合成数据来表征页岩砂媒质。贝叶斯反演方案用于根据振幅与偏移量(AVO)数据估算储层参数,以获取有关不确定性及其最可能值的信息。只要已知背景砂孔隙度值和各向同性覆盖层特征,我们的工作流程结果就可以根据AVO数据在很小的不确定性下可靠地估算含水饱和度。对于页岩的体积,即使在AVO数据中存在较大的不确定性时,建议的工作流程也可以提供合理的估算值。

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