摘要
针对致密砂岩气层与围岩的波阻抗差异较小、气层与围岩区分难度大等问题,研究致密砂岩含气性敏感参数,以准确识别薄层致密砂岩气。根据地层流体对弹性参数的敏感性,提出致密气敏感参数λ/vs(第1拉梅系数与横波速度比值),并根据不同地质条件,提出拓展属性f/vs(Russell流体相与横波速度之比),f/vs在一定条件下可退化为λ/vs。采用Gassmann方程与Brie经验公式进行流体替换,发现λ/vs比常用属性λρ(第1拉梅系数与密度乘积)、vp/vs(纵横波速度比)对含气饱和度更敏感,验证了新敏感参数的有效性。对英台气田营城组营二段进行叠前反演,发现λ/vs比λρ识别气层的精度高,与测井解释结果吻合较好,提高了气层识别能力及预测精度。
Aiming at the difficulty in distinguishing gas-bearing layers and surrounding rocks due to the small differences between their impedance, the gas-bearing sensitivity parameters are studied in tight sandstone to identify thin layer tight gas accurately. According to elastic parameters sensitivity analysis of fluid in tight sandstone, a new combined elastic parameter is proposed, i.e. the ratio of the first Lame coefficient to S-wave velocity. Furthermore, considering different geological conditions, extending attribute(the ratio of Russell fluid phase to S-wave velocity) is deduced, and it can be simplified as the ratio of the first Lame coefficient to S-wave velocity in certain condition. Fluid replacement process is conducted by Gassmann equation and Brie empirical equation, and the new combined elastic parameter is more sensitive to gas saturation than common parameters such as the product of the first Lame coefficient and density, the ratio of P-wave to S-wave velocity, verifying the validity of the new combined elastic parameter. The pre-stack inversion is applied in the second member of Lower Cretaceous Yingcheng Formation in Yingtai gas field. Compared with section of the product of the first Lame coefficient and density, it shows that the new combined elastic parameter improves the accuracy of identifying gas-bearing layers, well conforms to the logging interpretation, and greatly enhances the identification ability and prediction accuracy towards gas-bearing layers.
出处
《石油勘探与开发》
SCIE
EI
CAS
CSCD
北大核心
2014年第6期712-716,共5页
Petroleum Exploration and Development
基金
国家高技术研究发展规划(863计划)(2013AA064902)
关键词
致密砂岩气
含气性
弹性参数
敏感参数
叠前反演
tight sand gas
gas-bearing
elastic parameters
sensitivity parameters
pre-stack inversion