GENESIS AND PETROPHYSICAL IDENTIFICATION OF RELATIVE HIGH PERMEABILITY OF SANDBODY IN SULIGE GAS FIELD, ORDOS BASIN
-
摘要: 研究苏里格低效气藏中相对高渗砂体的成因、特征及其相应的岩石物理测井响应机理和解释模型,从而得到相对高渗砂体识别的有效方法是苏里格气田高效开发的关键。苏里格气田具有典型的煤系地层特征,因强烈的成岩作用使原生孔隙损失较多,表现出粗岩相和次生孔隙发育是相对高渗砂体最主要的特征。在此地质成因分析的基础上,分析其岩石物理测井响应机理、建立响应的测井解释模型是识别相对高渗砂体的主要途径之一。不同的测井系列对孔隙结构和岩石相具有不同的岩石物理响应机理。地层密度测井与声波测井虽然同为孔隙度测井系列,但是它们响应的是不同的孔隙结构,由此可以得到储层次生孔隙度指数测井解释模型。在关键井岩性标定下,选择自然伽马、光电截面和地层密度等一组对岩性响应敏感的测井曲线进行聚类分析,是岩石相识别的有效方法。基于这种次生孔隙和岩石相测井解释模型所识别的相对高渗砂体,与岩心分析和气井产能测试具有很好的一致性。Abstract: The key problem for developing the Sulige gas field with high efficiency is the identification of the relatively high permeability of sandbodies in low efficient gas reservoirs.In Sulige gas field,with the characteristics of typical coal measure strata,many primary pores have disappeared due to severe diagenesis.As a result,the relatively high permeable sandbodies are mainly developed in coarse sandstone facies with secondary pores.It is known that different log curves,such as density log and acoustic log,reflect different pore structure and lithofacies.Based on this,an interpretation model of secondary porosity index for the reservoir is established.After the calibration with the core lithology of key wells,the sensitive logs to lithology,such as GR,PE,and DEN are used to identify lithofacies by utilizing cluster analysis.The results show that the relatively high permeable sandbodies identified by this log interpretation model of secondary pores and lithofacies are consistent with core analysis and production capacity tests of gas wells.
-
[1] 席胜利,王怀厂,秦伯平.鄂尔多斯盆地北部山西组、下石盒子组物源分析[J].天然气工业,2002,22(2):21~24. [2] 于兴河,郑俊茂,王德发等.华北地区二叠系砂岩沉积体系、成岩特点基础层特征和预测[A].见:地质矿产部石油地质研究所编.石油与天然气地质文集(第4集)——中国天然气地质研究[C].北京:地质出版社,1994. [3] O Serra.Fundamentals of well-log interpretation:the acquistition of logging data[J].Development in Petroleum Science 15A,1984,117~320. [4] 郭余峰.石油测井中的核物理基础[M].北京:石油工业出版社,1990.166~189. [5] 段康,谭廷栋.测井学[M].北京:石油工业出版社,1998.198~199. [6] 王碧泉,陈祖荫.模式识别理论方法和应用[J].北京:地震出版社,1989.7~18,69~73. [7] 唐萍.多井条件下进行测井神经网络储层参数计算[J].石油实验地质,2003,25(4):413~416
计量
- 文章访问数: 962
- HTML全文浏览量: 114
- PDF下载量: 464
- 被引次数: 0