期刊文献+

高速通道压裂通道率影响因素实验研究 被引量:5

Research on the influencing factors of channel rate for channel fracturing
下载PDF
导出
摘要 高速通道压裂是近几年在非常规致密油气资源开采中出现的新工艺。通道率是影响高速通道压裂技术的一个重要指标。运用平板裂缝模型研究压裂液黏度、纤维浓度、支撑剂浓度、排量、脉冲时间和孔密6个因素对通道率的影响,以期获得良好的通道率。通过单因素影响实验研究各参数对通道率的影响,并在此基础上,采用正交实验进行多因素组合分析各参数对通道率的影响程度。实验表明,压裂液黏度、纤维浓度以及孔密的增加会使通道率增大;脉冲时间、支撑剂浓度的增加会导致通道率的减小;排量的增加使通道率呈现出先增大后减小的趋势。在黏度大于100 mPa·s实验条件下,6个因素对通道率的影响程度大小为:支撑剂浓度>脉冲时间>纤维浓度>排量>压裂液浓度>孔密。 In the exploitation of unconventional tight oil and gas resources, channel fracturing is a new fracturing technology in re- cent years, and channel rate is a very important factor to influence channel fracturing. In order to gain good channel rate, this paper studies six influential factors of fracturing fluid viscosity, fiber concentration, proppant concentration, discharge rate, pulse time and shooting density by using plate fracture model. In addition, the impact of parameters on channel rate is studied by single factor experiment. Furthermore, the orthogonal experiment is adopted to analyze the effect degree of every parameter on channel rate. The research shows that the increase of fracturing fluid viscosity, fiber concentration and shooting density lead to the increase of chan- nel rate, the increase of pulse time and proppant concentration lead to the decrease of channel rate, and the increase of discharge rate lead to channel rate increase firstly and then decrease. When the viscosity is higher than 100 mPa.s, the effect degree of six pa- rameters from big to small is proppant concentration, pulse time, fiber concentration, discharge rate, fracturing fluid viscosity, and shooting density.
出处 《油气藏评价与开发》 CSCD 2017年第2期58-64,共7页 Petroleum Reservoir Evaluation and Development
关键词 高速通道压裂 参数优化 纤维 脉冲 正交实验 channel fracturing, parameters optimization, fiber, pulse, orthogonal experiment
  • 相关文献

参考文献3

二级参考文献35

  • 1公茂果,焦李成,杜海峰,马文萍.用于约束优化的人工免疫响应进化策略[J].计算机学报,2007,30(1):37-47. 被引量:16
  • 2Coello C C A.Theoretical and numerical constraint-handling techniques used with evolutionary algorithms:A survey of the state of the art.Computation Methods in Applied Mechanics and Engineering,2002,191(11-12):1245-1287.
  • 3Davis L.Handbook of Genetic Algorithm.New York:van Nostrand,Reinhold,1991.
  • 4Zhang Q F,Leung Y W.Orthogonal genetic algorithm for multimedia multicast routing.IEEE Transactions on Evolutionary Computation,1999,3(1):53-62.
  • 5Leung Y W,Wang Yu-Ping.An orthogonal genetic algorithm with quantization for global numerical optimization.IEEE Transactions on Evolutionary Computation,2001,5(1):41-53.
  • 6Wang Yu-Ping,Dang Chuang-Yin.An evolutionary algorithm for global optimization based on level-set evolution and latin squares.IEEE Transactions on Evolutionary Computation,2007,11(5):579-595.
  • 7Hamida S B,Schoenauer M.ASCHEA:New results using adaptive segregational constraint handling//Proceedings of the Congress on Evolutionary Computation.Piscataway,NJ:IEEE Press,2002:884-889.
  • 8Farmani R,Wright J A.Self-adaptive fitness formulation for constrained optimization.IEEE Transactions on Evolutionary Computation,2003,7(5):445-455.
  • 9Yu J X,Yao X,Choi C,Gou G.Materialized view selection as constrained evolutionary optimization.IEEE Transactions on Systems,Man and Cybernetics(C),2003,33(4):458-467.
  • 10Cai Zi-Xing,Wang Yong.A multiobjective optimization-based evolutionary algorithm for constrained optimization.IEEE Transactions on Evolutionary Computation,2006,10 (6):658-675.

共引文献113

同被引文献31

引证文献5

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部