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Development of a refinement criterion for adaptive mesh refinement in steam-assisted gravity drainage simulation

机译:蒸汽辅助重力排水模拟中自适应网格细化的细化准则的发展

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Steam-assisted gravity drainage (SAGD) is an enhanced oil recovery process for heavy oils and bitumens. Numerical simulations of this thermal process allow us to estimate the retrievable volume of oil and to evaluate the benefits of the project. As there exists a thin flow interface (compared to the reservoir dimensions), SAGD simulations are sensitive to the grid size. Thus, to obtain precise forecasts of oil production, very small-sized cells have to be used, which leads to prohibitive CPU times. To reduce these computation times, one can use an adaptive mesh refinement technique, which will only refine the grid in the interface area and use coarser cells outside. To this end, in this work, we introduce new refinement criteria, which are based on the work achieved in Kroener and Ohlberger (Math Comput 69(229):25-39, 2000) on a posteriori error estimators for finite volume schemes for hyperbolic equations. Through numerical experiments, we show that they enable us to decrease in a significant way the number of cells (and then CPU times) while maintaining a good accuracy in the results.
机译:蒸汽辅助重力排水(SAGD)是增强的重油和沥青采油工艺。该热过程的数值模拟使我们能够估计可采油量并评估该项目的收益。由于存在薄的流界面(与储层尺寸相比),因此SAGD模拟对网格尺寸很敏感。因此,为了获得石油产量的精确预测,必须使用非常小的单元格,这会导致CPU时间过长。为了减少这些计算时间,可以使用自适应网格细化技术,该技术只会在界面区域细化网格,而在外部使用较粗的像元。为此,在这项工作中,我们引入了新的细化准则,该准则基于Kroener和Ohlberger(Math Comput 69(229):25-39,2000)中针对双曲有限体积方案的后验误差估计器所完成的工作。方程。通过数值实验,我们表明它们使我们能够显着减少单元数(然后减少CPU时间),同时保持结果的良好准确性。

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