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Multiple attributes fusion based on fuzzy logic in oil-gas prediction

机译:基于油气预测模糊逻辑的多个属性融合

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There is no obviously corresponding relationship between seismic attributes and reservoir parameters, which inevitably gives rise to uncertainty of reservoir characterization when rely upon single attribute. During the process of reservoir prediction, it is fuzzy whether single or integral attributes are capable of indicating oil and gas or not. To solve the problems above, we propose a multi-attributes fusion method based on fuzzy logic, applying fuzzy theory to attributes fuzzy, with the help of membership function to quantify the fuzzy problem, calculating weight factor through fuzzy nearness matrix, eventually obtaining a quantitative comprehensive result. During the process of fusion, the calculation of weight factor of each attributes is completely data driven which could reduce the subjectivity. This method has been tested on synthetic and real data in order to prove its feasibility and effectiveness. Results of the test show that, the fusion results are in accordance with well data. Consequently, the proposed multi-attributes fusion method based on fuzzy logic used for oil and gas prediction is effective and available.
机译:没有明显的地震属性与储层参数之间的对应关系,当依赖于单个属性这不可避免地产生了油藏描述的不确定性。在储层预测的过程中,它是模糊单一或一体的属性是否能够指示油气与否。为了解决上述问题,我们提出了一个多属性基于模糊逻辑,模糊理论在模糊属性,与隶属函数的帮助,以量化的模糊问题,通过模糊贴近度矩阵计算权重因子,最终获得定量的融合方法综合作用的结果。在融合过程中的过程中,每个属性的权重因子的计算是完全驱动,可以减少主观性数据。这种方法已经被以证明其可行性和有效性上合成和真实数据进行测试。的测试的结果显示,该融合的结果是根据公数据。因此,所提出基于用于石油和天然气的预测是有效的和可用的模糊逻辑多属性融合方法。

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