Simulation On Enhancing Recovery Efficiency In Gao Taizi Reservoir Sa Zhong

Gao taizi reservoir in Sa zhong development area is belong to land facies lake basin—deltaic deposit which has frequent interaction between sand and shale, oil area is 114.79 square kilometer, geologic reserve is 31442 ten-thousand ton, which accounts for 25.61 percent of total geologic reserve of Sa zhong development area. Gao taizi reservoir was developed in 1980. Its well spacing density is increased from 6.5 wells per kilometer to 18.8 wells per kilometer now, cumulative oil production is 11770.74 ten-thousand ton, degree of reserve recovery is 37.4 percent and overall water cut is 87.91 percent, which has developed into high water cut stage later.Gao taizi reservoir is in a serious situation, firstly how to control further increase of water cut, secondly how to control further decrease of production, thirdly how to increase recoverable reserve and weaken contradictory between reservoir and production, last how to further optimize development of Gao taizi reservoir. In order to study remaining oil, it is necessary to increase recovery efficiency with different adjustment and displacement in Gao taizi reservoir, which is important to sustainable development of Sa Zhong reservoir in theory and practice.Four representative geologic models were built basing on geological information and PETREL software was used to build structural model and properties model. The ECLIPSE software was used in the course of numerical simulation and reservoir, pressure, oil production and water cut were matched in the history match. On the basis of fitting the engineering requirement, water drive performances of different adjustment were forecast, best plan was selected and EOR effect of water drive was forecast too. The ECLIPSE software was used to study polymer injection rate, pore volume, polymer molecular and concentration with static data and history match. Those influencing factors and changes in development indicators of polymer flooding were studied, from which influent parameters were optimized and polymer flooding development indicators were forecast.