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疏松砂岩油藏出砂状况模拟技术研究
引用本文:蒋官澄,毕彩丰,史源清.疏松砂岩油藏出砂状况模拟技术研究[J].石油大学学报(自然科学版),2005,29(4):64-67,72.
作者姓名:蒋官澄  毕彩丰  史源清
作者单位:[1]中国海洋大学化学化工学院,山东青岛266003 [2]中国石油大学石油工程学院,山东东营257061 [3]中石化胜利化工有限责任公司,山东东营257237
基金项目:中国石油化工集团公司重点资助项目(2001-2-010)
摘    要:在系统研究影响油藏出砂因素的基础上,采用人工神经网络BP模型,首先从理论上研究了引起地层砂粒运移的最低地层流体流速——门限流速预测方法,并建立了实际日产量较大时的地层最大出砂半径计算模型;然后,结合岩石力学、渗流力学等知识,建立了引起岩石结构破坏的临界井底流压的计算模型,并推导了当实际井底流压小于临界井底流压,因岩石结构破坏而引起大量出砂时,出砂半径的计算公式,同时,给出了防砂工艺设计中抑砂剂用量和固体防砂剂用量的计算式,避免了防砂剂量设计的盲目性。现场应用表明,建立的计算模型可明显提高防砂措施的成功率和有效期。

关 键 词:疏松砂岩油藏  出砂  模拟  人工神经网络  门限流速
文章编号:1000-5870(2005)04-0064-04
收稿时间:2005-04-15
修稿时间:2005-04-15

Study on simulating sand production in unconsolidated sandstone reservoir
Jiang GuanCheng;Bi CaiFeng;Shi YuanQing.Study on simulating sand production in unconsolidated sandstone reservoir[J].Journal of the University of Petroleum,China(Edition of Natural Science),2005,29(4):64-67,72.
Authors:Jiang GuanCheng;Bi CaiFeng;Shi YuanQing
Abstract:Based on systematic study on the effects of the reservoir sand production, the minimum formation fluid flow-rate, i.e.threshold flow-rote, which causes formation sand migration, was theoretically studied using the artificial neural network model, and the model was established for calculating maximum formation sand production radius at the higher daily production rate. The model for calculating critical bottom hole flow pressure which causes rock structure failure was also established by adopting theories of rock mechanics and permeation fluid mechanics, and the method for calculating radius of massive sand production caused by rock structure failure at actual bottom hole flow pressure lower than critical bottom hole flow pressure was derived. Meanwhile, the sand production inhibitor amount and solid sand control agent amount were theorectially determined for sand control design to avoid improper use of sand control agents. Field application proved that a series of models established can exhibit significant effects on sand control and prolong sand control life.
Keywords:unconsolidated sandstone reservoir  sand production  simulation  artificial neural network  threshold flow-rate
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