岩石微观结构和岩石物理性质对碳酸盐岩速度-压力关系的影响

A. El-Husseiny
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摘要

研究了碳酸盐岩岩石物理性质对速度-压力关系的影响。提出了一种预测碳酸盐岩地层中压缩速度随压力变化的方法。该方法结合了各种岩石物理性质,包括体积密度、孔隙度、矿物学和孔隙刚度,从而考虑了碳酸盐的复杂性。本研究中使用的数据包括岩石性质(密度、孔隙度、矿物学)和弹性速度(作为围压的函数),这些数据来自已发表的文献中的220个碳酸盐岩心塞样。计算Pearson相关系数,评价各属性在预测速度-压力关系中的显著性。根据给定压力下的初始测量速度,结合所有重要的输入岩石属性,建立了一个简单的回归公式,以预测Vp作为压力的函数。将预测值与测量值进行比较。结果表明,随着孔隙率和孔隙压缩性的增大,Vp对压力变化的敏感性增大。另一方面,具有较高容重和Vp / Vs比的样品(在初始最低压力下),随着压力的增加,Vp的变化很小。高Vp / Vs值在胶结良好、粘土或硅屑含量较少的样品中观察到。这种特性降低了孔隙的可压缩性,导致了非变速度-压力关系。结合岩石性质进行回归分析,可以成功预测Vp随压力的变化,相关系数为0.99,平均绝对误差小于3%。由于所有输入参数(岩石性质)都可以从测井曲线中估计出来,因此所提出的方法有可能用于预测由于压力变化导致的Vp的原位变化。这有助于解释时移地震和地质力学相关的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of Rock Microstructure and Petrophysical Properties on the Velocity-Pressure Relationship of Carbonates
This study investigates the impact of petrophysical rock properties on the velocity-pressure relationship in carbonates. It presents an approach to predict the changes in compressional velocity (Vp) as function of pressure in carbonates. The approach honors the complexity of carbonates by incorporating various petrophysical rock properties including bulk density, porosity, mineralogy and pore stiffness. The data used in this study consists of rock properties (density, porosity, mineralogy) and elastic velocity measured as function of confining pressure for 220 carbonate core plug samples from published literature. Pearson correlation coefficient was calculated to evaluate the significance of each property in predicting velocity-pressure relationship. A simple regression was formulated incorporating all significant input rock properties to predict Vp as function of pressure based on initial measured velocity at a given pressure. The predictions were compared with the measured Vp. The results show that the sensitivity of Vp to changes in pressure increases as the porosity and pore compressiblity increases. On the other hand, samples with higher bulk density and Vp / Vs ratio (at initial lowest pressure) show little Vp variations as function of increasing pressure. High Vp / Vs values are observed in samples that are well cemented and have less clay or silisiclastic fraction. Such characteristics reduce the compressibility of pores leading to non-variable velocity-pressure relationship. Incorporating the rock properties in regression analysis could successfully predict Vp as function of pressure with a correlation coefficient of 0.99 and average absolute error of less than 3%. Since all input parameters (rock properties) can be estimated from well logs, the presented approach can potentially be used to predict in-situ changes in Vp due to pressure changes. This can assist the interpretation of time lapse seismic, and in geomechanics-related applications.
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