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Delivery Massager: A tool for propagating seismic inversion information into reservoir models

机译:输送按摩器:一种将地震反演信息传播到储层模型中的工具

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摘要

We introduce a new open-source program for transforming inversion data from the open-source Delivery seismic inversion software to industry-standard cornerpoint grid formats suitable for reservoir modelling and flow simulations. The seismic inversion data produced by Delivery is an array of trace-local stochastic samples from a Bayesian posterior distribution of reservoir layer parameters, which contains complex correlations between layers boundaries, rock properties and fluid information, but no transverse correlations. This correlation structure is merged with lateral correlation requirements imposed by geological modelling inputs to the conversion process, thus producing cornerpoint grid models of the reservoir that honour seismic inversion, well data, and the desired lateral continuities. Realisations from the joint 'structural-stochastic', multi-property 3D correlated model can be drawn using a generalised p-field simulation algorithm. Distribution of volumetric quantities of commercial interest (e.g. net-hydrocarbon) can be directly generated. The software can produce both most-likely cornerpoint grids, and stochastic grids, which can be carried forward into production forecast studies for risking and uncertainty studies.
机译:我们引入了一个新的开源程序,用于将反演数据从开源的Delivery地震反演软件转换为适用于储层建模和流量模拟的行业标准角点网格格式。 Delivery产生的地震反演数据是来自储层参数贝叶斯后验分布的痕量局部随机样本数组,其中包含层边界,岩石属性和流体信息之间的复杂相关性,但没有横向相关性。该相关结构与地质模型输入转换过程所施加的横向相关要求合并在一起,从而生成了满足地震反演,井数据和所需横向连续性的储层角点网格模型。可以使用通用的p场模拟算法来绘制联合的“结构随机”,多属性3D相关模型的实现。可以直接生成具有商业意义的体积量(例如,净烃)的分布。该软件既可以生成最有可能的角点网格,也可以生成随机网格,可以将其转入生产预测研究中,以进行风险和不确定性研究。

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