Prediction of multi-reservoir production for water injection well by using temperature logging data

被引:2
作者
Zheng, Lei [1 ]
Nian, Yong-Le [1 ]
Zhao, Rui [1 ]
Cheng, Wen-Long [1 ]
机构
[1] Univ Sci & Technol China, Dept Thermal Sci & Energy Engn, Hefei 230027, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-reservoir production; Water injection well; Heat transfer model; Temperature logging data; Stochastic approximation method; HEAVY OIL; NUMERICAL-SIMULATION; PRODUCTION FORECAST; POROUS-MEDIA; FLOW-RATE; RECOVERY; MODEL; EXTRACTION; SYSTEMS;
D O I
10.1016/j.petrol.2020.107989
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In most cases, oil wells are completed and perforated to produce from multiple reservoirs. Thus, it is crucial to monitor production from each individual reservoir. Therefore, a new prediction method for multi-reservoir production by using temperature logging data is presented in this paper. Firstly, by coupling the wellbore and formation heat transfer with reservoirs heat transfer, a new comprehensive heat transfer model for the oil well with multiple reservoirs is established in this paper. Both the heat convection of two-phase flow in reservoir and vertical heat transfer between different reservoirs was considered in the model, and the relationship between flow rate distribution and temperature distribution could be specified by the model. Then based on the model, the stochastic approximation method was proposed to predict the multi-reservoir production through the temperature logging data. Lastly for a water injection well with five layered reservoirs and depth of 3500m, the production of each reservoir was predicted by the presented method. The results show that the temperature distribution simulated by the built model has a good agreement with the reference data. The estimation error of the total flow rate is less than 9% compared with the reference data, and the production of the five reservoirs accounted for 36%, 35%, 17%, 7% and 5% of the total production respectively.
引用
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页数:10
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