Using Gassmann Equation Predict Marine Sediment Porosity
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摘要: 孔隙度对于石油勘探和海底测量等领域是一个重要的参数，但是海洋沉积物孔隙度的预测一直是个难点.对Gassmann方程进行变换，利用孔隙度和纵波声速的相关关系求解出孔隙度预测公式，并将该公式应用于南海南部海底沉积物孔隙度预测中.沉积物声速是根据南海采集的柱状样品在甲板上测量的，孔隙度是在实验室测量的.将Gassmann方程预测结果与沉积物柱状样品实验室测量结果进行对比研究.结果表明Gassmann方程能够较好的预测海底沉积物的孔隙度，对浅海地区的孔隙度预测尤为准确.利用误差范数分析法对Gassmann方程各输入参数进行敏感性分析，发现沉积物纵波声速对孔隙度预测精度影响最大.Abstract: Porosity is one of the most important parameters for oil exploration and ocean topographic survey. The prediction of porosity in marine sediments has always been a difficulty. In this paper, the Gassmann equation was rearranged and utilized to estimate porosity based on the relationship between porosity and compressional wave velocity. The compressional wave velocity was measured on the deck based on the core samples collected in the southern South China Sea, and the porosity was measured in the laboratory. Porosity calculated using Gassmann equation was compared with that measured in laboratory. The results show that Gassmann equation can better predict the seafloor sediment porosity, and that is particularly accurate at shallow water areas. The sensitivity of Gassmann equation was studied by error norm method, and the results show that compressional wave velocity is the most influential parameter for porosity prediction.
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Key words:
- porosity /
- Gassmann equation /
- seafloor sediment /
- compressional wave velocity /
- petroleum geology /
- marine geology
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图 4 Gassmann方程孔隙度在不同深度上与实测孔隙度对比结果
Fig. 4. Comparisons between the measured porosities and porosities calculated by Gassmann equation in different depth
图 5 Gassmann方程各参数误差分析
Fig. 5. The error norm of each parameters based on Gassmann equation
表 1 Gassmann方程参数
Table 1. Gassmann equation parameters
方法 参数 数值 Gassmann方程 纵波声速Vp(m/s) 实测 密度ρ(kg/m3) 实测 颗粒体积模量Kg(Pa) 1.50×1010 孔隙水体积模量Kw(pa) 2.18×109 框架体积模量Kf(pa) 7.78×107 沉积物剪切模量μ(pa) 2.22×107 
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