游利军, 刘雄辉, 康毅力, 陈明君, 陈强, 杨斌. 基于统计学方法的页岩孔容预测[J]. 煤田地质与勘探, 2017, 45(1): 45-50,55. DOI: 10.3969/j.issn.1001-1986.2017.01.009
引用本文: 游利军, 刘雄辉, 康毅力, 陈明君, 陈强, 杨斌. 基于统计学方法的页岩孔容预测[J]. 煤田地质与勘探, 2017, 45(1): 45-50,55. DOI: 10.3969/j.issn.1001-1986.2017.01.009
YOU Lijun, LIU Xionghui, KANG Yili, CHEN Mingjun, CHEN Qiang, YANG Bin. Shale pore volume prediction based on statistical method[J]. COAL GEOLOGY & EXPLORATION, 2017, 45(1): 45-50,55. DOI: 10.3969/j.issn.1001-1986.2017.01.009
Citation: YOU Lijun, LIU Xionghui, KANG Yili, CHEN Mingjun, CHEN Qiang, YANG Bin. Shale pore volume prediction based on statistical method[J]. COAL GEOLOGY & EXPLORATION, 2017, 45(1): 45-50,55. DOI: 10.3969/j.issn.1001-1986.2017.01.009

基于统计学方法的页岩孔容预测

Shale pore volume prediction based on statistical method

  • 摘要: 页岩气储集空间与储层矿物特征关系密切,以四川盆地东缘龙马溪组页岩为研究对象,利用矿物组成、微量元素、地球化学等测试结果,结合低温氮气吸附法和高分辨率成像技术,采用多元统计分析方法,建立了页岩孔容预测方程,并分析孔隙分布特征和影响因素。结果表明,龙马溪组中部和底部页岩组分含量差异较大,生物成因的自生石英发育是龙马溪组底部石英含量高的主要原因;页岩纳米级孔隙以2~5 nm为主,对孔容贡献率介于64.2%~70.1%;建立的页岩组分含量与孔容的预测模型高度显著。脆性矿物孔、黏土矿物片间孔及其粒内孔是富黏土矿物页岩的主要孔隙类型,孔隙呈微缝状,小于2 nm孔隙不发育;有机质含量是富有机质页岩孔容大小的主控因素,有机质孔的面孔率介于8.8%~12.5%;有机质含量及成熟度是小于2 nm微孔发育的主控因素,大于50 nm孔隙的发育则受控于黏土矿物、石英及长石含量。

     

    Abstract: The reservoir space of shale gas is closely related to the characteristics of the mineral characteristics of reservoir.The paper, taking the shale in Longmaxi Formation in the eastern margin of Sichuan basin as example, a series of tests were conducted. Based on the results of mineral composition, microelement analysis, and geochemical parameters, as well as the low temperature nitrogen adsorption and high resolution images, a pore volume prediction equation was formulated through multivariate statistical method. Then the pore diameter distribution and its affecting factors were explored with this new model. It is showed that in Longmaxi shale formation the mineral composition has big difference in the middle and the bottom, and the abundant biogenic quartz is the main reason for the high quartz content in the bottom of Longmaxi Formation. The nano pores in shale mainly rank 2~5 nm, and contributes about 64.2%~70.1% of the total pore volume. The formulated equation indicates that pore volume has a strong correlation with shale mineral composition,and standardization of the regression coefficient shows that organic matter, clay minerals and brittle minerals have a diminishing effects on pore volumes. Brittle mineral pores, inter-granular pores in clay pieces and intra-granular pores in clay minerals are the main pore types in clay-rich shale, and silt pores is the most common, usually larger than 2nm in diameter. The pore volume of organic pores is mainly controlled by the value of TOC, and the surface porosity which is primarily contributed by 2~5 nm pores is 8.8%~12.5%.The TOC value and thermal maturity of shale are the primary controlling factors for the pores smaller than 2nm in diameter, while the development of pores larger than 50 nm is mainly controlled by clay minerals, quartz and feldspar.

     

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