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Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

机译:使用2型模糊逻辑系统对碳酸盐岩储层渗透率进行建模

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In this work, the use of type-2 fuzzy logic systems as a novel approach for predicting permeability fromwell logs has been investigated and implemented. Type-2 fuzzy logic system is good in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crisp value; rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associated with predicting permeability fromwell log data,where uncertainties are very high and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed type-2 fuzzy logic system framework with those earlier used methods, using five different industrial reservoir data.Empirical results fromsimulation showthat type-2 fuzzy logic approach outperformed others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost.
机译:在这项工作中,已经研究并实现了使用2型模糊逻辑系统作为从测井曲线预测渗透率的新方法。 Type-2模糊逻辑系统擅长处理不确定性,包括测量和用于校准参数的数据中的不确定性。在所使用的公式中,对应于特定渗透率值的隶属函数的值不再是清晰的值;相反,它与一系列值相关,这些值可以通过反映不确定性水平的函数来表征。这样,该模型将能够充分考虑与根据测井数据预测渗透率相关的所有形式的不确定性,其中不确定性非常高,非常需要稳定结果。通过使用五个不同的工业油藏数据,进行了比较研究,以将建议的2型模糊逻辑系统框架的性能与较早使用的方法进行比较。仿真的经验结果表明,2型模糊逻辑方法总体上优于其他方法,尤其是在稳定区域和在不确定情况下处理数据的能力,这是测井数据的共同特征。新提出的模型的另一个独特优势是,除了正常目标预测外,它还能够生成作为其副产品的预测间隔,而无需额外的计算成本。

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