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Simulation of Silica Nanoparticle Flooding for Enhancing Oil Recovery

机译:纳米二氧化硅驱提高油采收率的模拟

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Obtaining accurate relative permeability curves from coreflood experiments is imperative for characterizing a reservoir and estimating its production capability. As the relative permeabilities are not directly measurable, they are inferred from the measured data utilizing some mathematical model of the physical process. This procedure is referred to as inverse modelling. The inverse problem is to obtain estimates of the relative permeability functions using the data measured during displacement experiments. It concerns on the unsteady state relative permeabilities that are obtained from waterflood and suspension of silica nanoparticle flood experiments. For each experiment, recovery and pressure drop data were collected and used in a coreflood simulator. The coreflood simulator used in this study is the Sendra. As the relative permeability is a function of saturation, the authors required the estimates of the entire function. The results show that it is possible to determine one set of relative permeability curves that reconcile several nanosilica flooding experiments simultaneously using the history match method.
机译:必须通过岩心驱油实验获得准确的相对渗透率曲线,以表征储层特征并估算其生产能力。由于不能直接测量相对渗透率,因此可以使用物理过程的一些数学模型从测量数据中推断出它们的相对渗透率。此过程称为逆建模。反问题是要使用在位移实验中测得的数据来获得相对渗透率函数的估计值。它涉及从注水和二氧化硅纳米颗粒注水实验的悬浮获得的非稳态相对渗透率。对于每个实验,均会收集采收率和压降数据,并将其用于岩心驱油模拟器中。本研究中使用的核心洪水模拟器是Sendra。由于相对渗透率是饱和度的函数,因此作者需要对整个函数进行估算。结果表明,可以使用历史匹配方法来确定一组相对渗透率曲线,以同时协调多个纳米二氧化硅驱替实验。

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