Optimization of injection method for viscosity reduction chemical flooding in heavy oil reservoirs
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TE357.46

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    Abstract:

    The viscosity reduction chemical flooding is an effective alternative production method after steam stimulation in heavy oil reservoirs,and its injection method has a great influence on the development effect. Based on the oil displacement mechanism of viscosity reduction chemical flooding,a reservoir numerical simulation model was established. The numerical simulation technology was used to analyze the characteristics of the viscosity reduction chemical flooding after steam stimulation. The injection slug sequence was optimized based on the injection and production capacity and the development effect. Based on the net present value method,an optimized model of injection parameters of the viscosity reduction chemical flooding after steam stimulation was established. The reservoir numerical simulation technology and particle swarm optimization algorithm were integrated to obtain the optimal injection parameters. The research results show that the viscosity reduction chemical flooding after steam stimulation can effectively reduce the viscosity of crude oil in the formation,and the water cut declines significantly after a rapid increase;the sequence of injecting viscosity reducer first and then polymer slug is the best;based on the optimization,the optimal mass fractions and injection volumes of the viscosity reducer and polymer in the target reservoir are 0.28%,0.32%,0.40 PV and 0.36 PV respectively. The optimization results can effectively improve the development effect of heavy oil reservoirs,and the method of injection optimization proposed in this paper is of great significance to guide the development practice of viscosity reduction chemical flooding after steam stimulation in heavy oil reservoir.

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HU Bo, ZHENG Wenqian, ZHU Yangwen, CUI Chuanzhi, YUAN Fuqing, WANG Meng. Optimization of injection method for viscosity reduction chemical flooding in heavy oil reservoirs[J]. Petroleum Geology and Recovery Efficiency,2020,27(6):91~99

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  • Online: December 24,2020
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