重力异常的相关分析及其应用

Correlation analysis of gravity anomaly and its application,

利用随机过程的理论进行重磁资料的解释有独特的效果,它能克服一些传统方法难以克服的困难。本文提出利用自相关函数来表征随机过程。因为,当随机重力异常变换为自桐关函数过程中包含了异常向上廷拓的效果,故自相关函数能够起到压制高频随机干扰、测量误差,突出场源主异常的作用。随机重力异常的自相关函数通常有如下类型:单位脉冲型;三角型;马尔科夫型;高斯型;余弦指数型。利用这些形状的模型,可给出相应的规范自相关函数,再求出相应地质体的形状函数和计算地质体的中心深度的评估函数。应用上述理论处理两条实测重力剖面,将其结果与地震、地质资料进行对比表明,利用深度评估函数算出主密度层的平均深度和构造地质—地球物理模型进行正、反演计算,可以较可靠地研究地层分组和起伏。值得特别指出的是,主密度层平均深度的评估是由重力资料独立完成的,并不依赖密度资料的有无。

Interpreting gravimetric and magnetic data by random process theory brings unique effect because it can well overcome the difficulty conventional methods can hardly do. It is proposed that the random process can be expressed by autocorrelation function. The transformation of random gravity anomaly into autocorrelation function also brings upward continuation effect of gravity anomaly,so that the auto- correlation function can remove high-frequency noise and observation error, and enhance the major anomaly caused by gravity-field source. The autocorrelation functions of random gravity anomaly can be classed into five types, namely, unit impulsive,triangular, Markovian, Gaussian and cosine-exponential types. Using the models of these types, we can obtain corresponding normalized autocorrelation function, then derive both the shape functions of corresponding geological bodies and the estimation functions for calculating center depths of the geological bodies. Two real gravity profiles were processed by using above theory, then the processed results were compared with seismic and geological profiles. The comparison shows that using the estimation function to calculate average depth of major density layer and to constr ct geological-geophysical model for forward and inverse calculations favours analysing the formation classification and bed-surface undulation. It must be particularly pointed out that the average depth of major density layer is derived from gravimetric data, without the dependence of density data.