可扩展流动模拟是一项极其有用的油藏工程能力,可应用于模型校准、不确定性估计、油田优化和油藏管理。近期的案例强调将模拟问题构建为孔隙体积/渗透率网络,以开发基于物理的快速代理模型。在完整论文描述的研究中,作者开发了一种基于约束的自适应网格粗化方法,该方法尊重油藏结构和地层,保留流体体积和界面,并保持井附近分辨率。该技术可在商用油藏模拟器中实施。
问题陈述
所使用的商业模拟器在其网格粗化实现中包含几个强大的功能。
可扩展流动模拟是一项极其有用的油藏工程能力,可应用于模型校准、不确定性估计、油田优化和油藏管理。近期的案例强调将模拟问题构建为孔隙体积/渗透率网络,以开发基于物理的快速代理模型。在完整论文描述的研究中,作者开发了一种基于约束的自适应网格粗化方法,该方法尊重油藏结构和地层,保留流体体积和界面,并保持井附近分辨率。该技术可在商用油藏模拟器中实施。
所使用的商业模拟器在其网格粗化实现中包含几个强大的功能。
Scalable flow simulation is an extremely useful reservoir engineering capability with applications to model calibration, uncertainty estimation, field optimization, and reservoir management. Recent examples have emphasized the formulation of simulation problems as pore volume/transmissibility networks to develop fast physics-based proxy models. In the study described in the complete paper, the authors develop an adaptive grid-coarsening approach based on constraints that honor reservoir structure and stratigraphy, preserve fluid volumes and contacts, and retain resolution near wells. The technique may be implemented within commercial reservoir simulators.
The commercial simulator used includes several powerful features within its grid-coarsening implementation.