基于二维经验模式分解的重力资料多尺度分析

Gravity data multi-scale analysis based on two-dimensional empirical mode decomposition

重力资料是从地表到深部所有密度不均匀体引起的重力效应的叠加。针对不同的工作任务,需要利用不同尺度的重力资料进行研究。二维经验模式分解能够自适应地对非线性、非平稳信号实现多尺度分解。文章研究将二维经验模式分解应用于重力资料的多尺度分析,对重力数据进行二维经验模式分解以得到各级固有模态函数和剩余分量,利用径向对数功率谱分析方法估计各级模态函数所反映的地下场源的近似深度,定性地解释不同深度下的场源产生的异常,较好地揭示场源赋存的地质信息。模型数据和实际数据的测试佐证了该方法技术的可行性。

Gravity data embody the superimposed effect of all the bodies with uneven densities from the earth surface to the deep subsurface. And gravity data with different scales are needed for different tasks. The two-dimensional empirical mode decomposition can be adapted to nonlinear or non-stationary signals to achieve the multi-scale decomposition. In this study,the authors applied the two-dimensional empirical mode decomposition to the multi-scale analysis of gravity data. With this method,the gravity data can be decomposed into different intrinsic mode functions and one remaining component. Then,the radial logarithmic power spectrum of various components are computed to get the approximate depth of various sources. Theoretical density model data and real data test support the technical feasibility of the method.