摘要
火山碎屑岩储层具有岩性复杂、测井数据种类繁多以及区域大、层位多等特点,导致火山碎屑岩储层测井参数难于确定。以海拉尔盆地乌尔逊--贝尔凹陷的火山碎屑岩储层为研究主体,在准确识别岩性的基础上,对测井资料进行预处理,根据岩心分析资料计算其理论骨架参数值。依据孔隙度与中子、密度、声波三者之间的关系,将多元回归方法应用在孔隙度计算中,实现利用多元回归方法计算火山碎屑岩储层孔隙度。其结果与岩心分析孔隙度比较接近,绝对误差仅为1.6%,能满足储量计算要求。
Volcanic clastic rock reservoirs are complex in lithology and logging data, large in distribution regions, and multiple in layers, which lead to the difficulty on logging data determination. On the basis of accurately identification the lithological characters, the authors took the volcanic clastic reservoirs in Wuerxun-Bell depression of Hailar Basin as an example, did pretreatment of the logging data and calculated the theoretical skeleton parameters based on core analysis. Then, the authors applied multivariate-regression method in porosity calculation and returned statistical formula based on the relationship among porosity with neutron, density and sound wave, which realized the porosity calculation of volcanic clastic reservoirs by multivariate regression method. The result was similar with porosity by core analysis ( error = 1.6% ), and met the reservoir calculation requirement.
出处
《世界地质》
CAS
CSCD
2012年第2期377-382,共6页
World Geology
关键词
孔隙度
标准化
多元回归
测井
火山碎屑岩
储层
porosity
standardization
multivariate regression
logging
volcanic clastic rock
reservoir