基于重力全张量数据的Parker-Oldenburg算法研究

相比重力数据,重力张量数据通常包含更多的异常信息。本文根据重力数据与重力张量数据的关系,利用位场转化技术,将重力张量数据应用于传统的Parker-Oldenburg密度界面反演算法中。通过模型试验,证明了在网格间距较大或者数据存在一定噪音时,使用本文算法进行反演能得到更好的效果。实验结果说明利用重力张量数据可以有效地提高密度界面反演的分辨率。

Parker-Oldenburg algorithm based on full tensor gravity data

Compared with gravity data， gravity tensor data usually contains more information about the anomaly． Based on the relationship between gravity data and gravity tensor data，we apply gravity tensor data to the traditional Parker-Oldenburg density interface inverse algorithm by using transformation techniques in potential field． The model tests show that when the grid spacing is larger or there is a certain noise in the data，using the proposed algorithm can get better inversion results． The experimental results prove that using gravity tensor data can improve the inversion resolution of density interfaces effectively．