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苏里格低渗气田压裂井拟稳态期产量预测方法 被引量:1

Production prediction method for pseudo steady period of fractured well in low-permeability Sulige Gas Field
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摘要 目前气井压裂后产量动态预测的计算模型大多是针对稳态渗流或者是无限大地层的不稳态渗流过程,很少涉及普遍存在的拟稳态流动期间产量动态预测方法。为此,根据压裂气井地层中气体的渗流过程,首先基于边界控制的镜像反映原理所推导出的拟稳态流期间,气层中存在一条有限导流能力垂直裂缝井的无量纲压力解的通用表达式,提出了压裂气井拟稳态流动期的产量动态预测方法,然后给出矩形封闭性气层拟稳态流开始出现时间的确定方法。计算结果表明:苏里格低渗气田压裂井投产2~4个月即进入边界控制的拟稳态流动期,150m合理的裂缝单翼长度所需要的导流能力大约为30D·cm。本文所提出的产量动态预测方法也可用来优化其他低渗气田的压裂裂缝参数和施工规模。 At present, the computing model for dynamic prediction of fractured gas well production is mostly for steady state seep-age or for unsteady state seepage of inifnite formation, and rarely involved in production dynamic prediction method during pseudo steady lfow period. For this reason, according to seeping process of gas in formations of fractured gas well, ifrst based on the fact that, in pseudo steady lfow period derived from mirror relfection principle controlled by boundary, there is a vertical fracture of ifnite conduc-tivity capacity in the gas reservoir in the well, this paper presents a method for dynamic prediction of fractured gas well production in pseudo steady lfow period based on a general expression of dimensionless pressure solution, and then gives the method for determining the time when pseudo steady lfow begins to occur in rectangular bounded gas reservoir. The calculation results show that the fractured wells in Sulige low-permeability gas ifeld are in boundary-controlled pseudo steady seepage period in two to four months after being put into production, and the conductivity capacity required by single wing fracture length of 150 m is about 30D·cm. The method for dynamic prediction of production presented in this paper can also be used to optimize the hydraulic fracture parameters and fracturing size in other low permeability gas ifelds.
出处 《石油钻采工艺》 CAS CSCD 北大核心 2014年第6期65-68,共4页 Oil Drilling & Production Technology
基金 中石油重大科技专项"致密气藏开发重大工程技术研究"(编号:2010E-23)
关键词 压裂气井 封闭气层 拟稳态流 裂缝参数 产量预测 fractured gas well bounded gas reservoir pseudo steadylfow fractureparameters production prediction
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参考文献12

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