Sun Xianhang, Li Bingfan, Ma Xu, Pan Yi, Yang Shuangchun, Huang Weiqiu
Jiangsu Key Laboratory of Oil and Gas Storage and Transportation Technology, Changzhou University, Changzhou 213164, China e-mail:
Shandong Key Laboratory of Oil & Gas Storage and Transportation Safety, China University of Petroleum (East China), Qingdao 266580, China e-mail:
J Energy Resour Technol. 2020 Jan;142(1):0124011-1240110. doi: 10.1115/1.4044192. Epub 2019 Jul 18.
Calculation process of some reservoir engineering problems involves several passes of full-order numerical reservoir simulations, and this makes it a time-consuming process. In this study, a fast method based on proper orthogonal decomposition (POD) was developed to predict flow and heat transfer of oil and water in a reservoir. The reduced order model for flow and heat transfer of oil and water in the hot water-drive reservoir was generated. Then, POD was used to extract a reduced set of POD basis functions from a series of "snapshots" obtained by a finite difference method (FDM), and these POD basis functions most efficiently represent the dynamic characteristics of the original physical system. After injection and production parameters are changed constantly, the POD basis functions combined with the reduced order model were used to predict the new physical fields. The POD-based method was approved on a two-dimensional hot water-drive reservoir model. For the example of this paper, compared with FDM, the prediction error of water saturation and temperature fields were less than 1.3% and 1.5%, respectively; what is more, it was quite fast, where the increase in calculation speed was more than 70 times.
一些油藏工程问题的计算过程涉及多次全阶油藏数值模拟，这使得该过程耗时较长。在本研究中，开发了一种基于本征正交分解（POD）的快速方法来预测油藏中油水的流动和传热。生成了热水驱油藏中油水流动和传热的降阶模型。然后，利用POD从有限差分法（FDM）获得的一系列“快照”中提取一组降阶的POD基函数，这些POD基函数能最有效地表示原始物理系统的动态特性。在注入和生产参数不断变化后，将POD基函数与降阶模型相结合来预测新的物理场。基于POD的方法在二维热水驱油藏模型上得到了验证。对于本文的例子，与FDM相比，水饱和度和温度场的预测误差分别小于1.3%和1.5%；此外，该方法速度非常快，计算速度提高了70多倍。
