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Seismically Driven Reservoir Characterization Using an Innovative Integrated Approach: Syd Arne Field

机译:采用创新综合办法的地震驱动的储层特征:SYD ARNE FIELD

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This paper presents an innovative integrated workflow applied to the characterization of a fractured chalk reservoir in the Danish North Sea. The methodology uses simultaneous integration of geophysical, geological and engineering data to produce an improved reservoir description. Integrating dynamic flow data with the geophysical and geologic information in 3D, reservoir properties - porosity and effective permeability - are generated using artificial intelligence tools. The strength of this technique lies in the fact that property modeling is not constrained to match upscaled well data and consequently these data serve to validate the outcome. This workflow builds upon a methodology that has been used successfully for the characterization of fracture distribution. The technique has been extended to include the generation of seismically derived models of porosity and matrix permeability.The objective of the approach is to improve the ability to capture the heterogeneity of key reservoir properties, and thus use the resulting reservoir model to both provide improved predictive ability and identify previously undiscovered development opportunities. The application and outcome of this integrated workflow to the Syd Arne field is presented in this paper.
机译:本文介绍了一个创新的综合工作流程,适用于丹麦北海的碎屑储层表征。该方法使用地球物理,地质和工程数据的同时集成,以产生改进的储层描述。将动态流量数据与3D,储层性质 - 孔隙度和有效渗透性的地球物理和地质信息集成在一起,使用人工智能工具产生。这种技术的强度在于属性建模并未约束以匹配升高的井数据,因此这些数据用于验证结果。此工作流程构建在成功用于裂缝分布的表征的方法上构建。该技术已经扩展到包括产生孔隙率和矩阵渗透性的地震衍生模型。该方法的目的是提高捕获关键储层性能的异质性的能力,从而使用所得储层模型两者都提供改进的预测性能力并确定以前未被发现的发展机会。本文介绍了这种集成工作流到SYD ARNE领域的应用和结果。

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