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苏里格致密砂岩气藏岩性致密,具有非均质性强、微观孔隙结构复杂、低阻气层和高低阻水层并存的特点.其测井响应关系复杂,微电极电阻率曲线在低渗透层上无明显幅度差,常规测井技术系列和解释方法已呈现出新的不适性.本文综合分析苏里格致密砂岩气藏不同层位下高分辨率阵列感应测井(HDIL)电阻率曲线的差异,应用累积法建立电阻率曲线总差异参数.另外,在无阵列感应测井条件下,通过有高分辨率阵列感应测井(HDIL)数据的井点建立与常规测井之间的关系,进而可以使得常规测井也具备高分辨率阵列感应测井的优势.并在此基础上,将基于遗传算法GA优化的SVM算法(GASVM)引入到测井解释当中,建立了流体识别的非线性模型,解决了常规测井技术系列和解释方法在致密砂岩储层上无法准确识别流体的问题.
Sulige tight sandstone gas reservoirs are characterized by tight lithology, high heterogeneity, complex microscopic pore structure and coexistence of low-resistivity gas reservoirs and high and low water-resistance reservoirs. The logging response is complex and the resistivity curves of microelectrodes are low There is no significant difference between the permeable layers and conventional series of well logging techniques and interpretation methods have shown new discomfort.This paper comprehensively analyzes the resistivity of high resolution arrayed induction logging (HDIL) at different layers of the tight sandstone gas reservoir in the Sulige area And the total difference of the resistivity curve is established by using the cumulative method.In addition, under the condition of no array induction logging, through the well point established with high resolution array induction logging (HDIL) data and the conventional logging Which can make the conventional logging have the advantages of high resolution array induction logging.On this basis, the genetic algorithm GA-based SVM algorithm (GASVM) is introduced into well logging interpretation, and the fluid identification The nonlinear model solves the problem that conventional logging technology series and interpretation methods can not accurately identify fluids on tight sandstone reservoirs.