预测水驱油藏中油、水流动问题的快速方法

孙宪航; 徐明海; 巩亮; 贾欣鑫; 周辉

doi:10.3879/j.issn.1000-0887.2015.12.002

预测水驱油藏中油、水流动问题的快速方法

doi: 10.3879/j.issn.1000-0887.2015.12.002

¹中国石油大学储运与建筑工程学院能源与动力工程系,山东青岛 266580;²山东省科学院海洋仪器仪表研究所,山东青岛 266001;³辽河油田供水公司,辽宁盘锦 124010

基金项目: 国家自然科学基金(51276199)；国家科技重大专项(2011ZX05017_004_HZ01)

详细信息

作者简介:
孙宪航(1987—)，男，江苏连云港人，博士生(通讯作者. E-mail: sxh19871124@163.com).

中图分类号: TE319
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出版历程
- 收稿日期: 2015-06-11
- 修回日期: 2015-09-30
- 刊出日期: 2015-12-15

A Fast POD-Based Method for Predicting Oil and Water Flow in Water-Drive Reservoir

¹Department of Thermal Energy and Power Engineering, College of Pipeline and Civil Engineering, China University of Petroleum, Qingdao, Shandong 266580, P.R.China;²Institute of Oceanographic Instrumentation, Shandong Academy of Sciences, Qingdao, Shandong 266001, P.R.China;³Water Supply Company of Liaohe Oilfield, Panjin,Liaoning 124010, P.R.China

Funds: The National Natural Science Foundation of China(51276199); The National Science and Technology Major Project of China(2011ZX05017_004_HZ01)

摘要

摘要: 以最佳正交分解(POD)技术为基础提出了一种快速预测油藏中油、水流动问题的方法.采用POD技术建立了水驱油藏中油、水两相流动的低阶模型.通过油藏数值模拟方法获得二维水驱油藏模型在时间0～500 d内的压力和含水饱和度的100个样本，并从样本中提取出一组压力和含水饱和度的POD基函数.当注采参数不断变化后，采用已求得的POD基函数结合低阶模型对新的物理场进行预测.研究结果表明：POD方法能够快速、准确地预测出水驱油藏的压力和含水饱和度场，文中算例给出压力和含水饱和度场的预测误差分别不超过1.2%与1.5%，且计算速度比直接进行油藏数值模拟快50倍以上.
- 最佳正交分解 /
- 低阶模型 /
- 水驱油藏 /
- 油、水流动
Abstract: A fast method based on the proper orthogonal decomposition (POD) technique for predicting oil and water flow in water-drive reservoir was proposed. The reduced order model of oil and water flow in water-drive reservoir was generated with the POD. An ensemble of 100 samples of pressure and water saturation snapshots in the time range of [0 d, 500 d] with an interval step of 5 d for the 2D water-drive reservoir model was obtained through numerical reservoir simulation, and the POD was applied to extract a reduced set of POD basis functions from these snapshots. After the injection and production parameters were changed continuously, the obtained POD basis functions combined with the reduced order model were used to predict the new physical fields. The research results show that fast and accurate predictions can be achieved with the proposed POD-based method, for the given example, the prediction errors of pressure and water saturation are less than 1.2% and 1.5%, respectively. What’s more, this POD-based method is 50 times faster in calculation than the traditional numerical reservoir simulation.
- proper orthogonal decomposition /
- reduced order model /
- water-drive reservoir /
- oil and water flow

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