Application of ICEEMDAN to noise reduction of near-seafloor geomagnetic field survey data

Abstract

Submarine geomagnetic field survey is a crucial means of geophysical exploration in the oceans. According to the potential field attenuation, it is preferable to carry out the near-seafloor magnetic survey close to the magnetic sources, for improving the resolution and accuracy of magnetic anomalies. However, due to the complicated marine environments and other factors, the real submarine magnetic data is often distorted by serious noises, which will result in the difficulty and low reliability of subsequent inversion and geological interpretation. Since the excellent adaptability and binary filtering characteristics, the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), revised from Empirical Mode Decomposition (EMD), has become a suitable choice for processing the nonlinear and non-stationary submarine magnetic data. Moreover, to effectively reconstruct the useful signal from the Intrinsic Mode Functions (IMFs) of ICEEMDAN, an improved adaptive shrinkage scheme related to interval extremum based on interval thresholding (IT) function is proposed. In this paper, the ICEEMDAN and adaptive IT techniques are combined and applied to denoise the near-seafloor geomagnetic field survey data. The synthetic tests show that, the proposed method has a better application effect for noise reduction than other methods. Meanwhile, the random noises, ocean wave interferences and gross errors can be effectively removed. The application to the really repeated marine magnetic survey profiles illustrates that the inner coincidence accuracy of the total magnetic intensity anomaly datasets along these two profiles, has been improved from ±16.750 nT to ±1.417 nT via data denoising. Both synthetic test and real data study suggest that proposed method has a good performance for denoising the near-seafloor geomagnetic field survey data.