重力梯度特征向量和多尺度分析法在密度异常深度探测中的应用
Application of Density Anomaly Depth Detection Using Gravity Gradient Eigenvectors and Multiscale Analysis Approach
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摘要: 相较于传统的重力测量手段,重力梯度测量能够以更高的灵敏度和分辨率反映出地下密度异常体的结构特征。随着科学技术的不断发展,航空及卫星重力梯度测量系统已经投入使用,并实现了大范围高精度的重力梯度测量。因此,现阶段的主要挑战在于对越来越多的重力梯度数据进行分析、处理和解释。本文根据重力梯度全张量主特征值对应的特征向量,对密度异常体的深度探测进行了研究。由于不同埋深的密度异常体具有不同的波长反映,利用多尺度分析法可以分解出不同频段重力梯度张量,从而增强对更大埋深密度异常体的探测分析能力。通过对模型和实测重力梯度数据的分析解算,结果表明,重力梯度的特征向量和多尺度分析法能够有效地确定密度异常体的深度信息,并且对干扰场源和随机噪声也具有一定的抗干扰能力。Abstract: Compared with the conventional gravity measurements,gravity gradient measurements reflect the structural characteristics of the underground density anomaly with higher sensitivity and spatial resolution. Airborne and satellite gravity gradient survey systems have been put into use on account of continuous technological innovation, whilst wide range and high precision gravity gradient measurements are available.Therefore, the main challenge is analysis,processing and interpretation of extensive gravity gradient data. This paper addresses depth detection of underground density anomalies based on eigenvectors corresponding to the principle eigenvalue of the gravity gradient. As density anomalies of different buried depths have different wavelengths,we can split the gravity gradient tensor into different frequency bands taking advantage of the multiscale analysis approach, thereby enhancing the detection ability to detect deeper density anomalies.Through the analysis of the synthetic and measured gravity gradient data, our results show that the gravity gradient eigenvector and multiscale analysis approach can effectively determine the depth information of density anomalies. The proposed methos is robust to interference sources and random noise.