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Fremgangsmate for optimalisering av produksjon i et oljereservoar med usikkerheter

机译:不确定性条件下优化油藏生产的程序

摘要

An intrinsic parameter of the deposit, and a parameter connected with well development options, are selected. These parameters influence hydrocarbon production from the well. An analytical model is developed expressing the criterion of production over time, as a function of the selected parameters. A finite number of values of production criteria are taken into account, the values being obtained from the production flow simulator. Starting from the analytic model so determined, an uncertainty function is associated with one of the parameters intrinsic to the deposit. A distribution of one of the parameters connected to options of well production development is determined, such that the criterion of production is optimized. Before association of the uncertainty function, the relative mutual influence of parameters is quantified. Parameters having negligible influence on production are removed. The quantification employs a statistical test, either the Student- or the Fisher test. One of the parameter values is fixed and the value of a parameter connected with development options is determined, such that production criteria are optimized. Further variants are proposed, based on the preceding principles. Neural network modeling is employed. At least one intrinsic parameter of the deposit is of discrete, continuous and/or stochastic type.
机译:选择矿床的内在参数以及与井的开发选项相关的参数。这些参数影响井的烃产量。开发了一个分析模型,该模型根据所选参数来表达随时间变化的生产标准。考虑了生产标准的有限数量的值,这些值是从生产流程模拟器中获得的。从如此确定的分析模型开始,不确定性函数与矿床固有参数之一相关联。确定与井生产开发的选项有关的参数之一的分布,从而优化生产标准。在不确定性函数关联之前,先量化参数的相对相互影响。删除对生产影响可忽略的参数。量化采用统计检验,即学生检验或费舍尔检验。参数值之一是固定的,并且确定了与开发选项相关的参数值,从而优化了生产标准。基于前述原理,提出了进一步的变型。采用神经网络建模。沉积物的至少一个固有参数是离散,连续和/或随机类型的。

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