loading page

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker-Oldenburg Algorithm.
  • +6
  • Weibo Rao,
  • Nan Yu,
  • Gang Chen,
  • Xinyu Xu,
  • Simin Zhao,
  • Zhaoqi Song,
  • Jiazheng Liu,
  • Longtu Wan,
  • Changhong Hu
Weibo Rao
College of Marine Science and Technology, China University of Geosciences, Wuhan, China
Author Profile
Nan Yu
College of Marine Science and Technology, China University of Geosciences, Wuhan, China; Hubei Key Laboratory of Marine Geological Resources, China University of Geosciences, Wuhan, China

Corresponding Author:yunan@cug.edu.cn

Author Profile
Gang Chen
College of Marine Science and Technology
Author Profile
Xinyu Xu
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Author Profile
Simin Zhao
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Author Profile
Zhaoqi Song
College of Marine Science and Technology, China University of Geosciences, Wuhan, China
Author Profile
Jiazheng Liu
College of Marine Science and Technology, China University of Geosciences, Wuhan, China
Author Profile
Longtu Wan
College of Marine Science and Technology, China University of Geosciences, Wuhan, China
Author Profile
Changhong Hu
College of Marine Science and Technology, China University of Geosciences, Wuhan, China Edit Remove
Author Profile

Abstract

The Moho is the interface between crust and mantle, and accurate location of the Moho is important for both resource exploration and deep earth condition and structural change investigations. The Parker-Oldenburg (P-O) method, is simple and efficient and thus has been extensively applied in the frequency domain and for Moho depth inversion. However, Moho fluctuation simulations using the P-O method are not reliable because of the lack of field geographic data constraints during the inversion process and excessively smoothing of data details caused by using a filter to correct the source data signals. To solve those problems, we propose an improved iteration P-O method with variable density, the iterative process is constrained by geological data in the inversion parameters, and the variable depth of the gravity interface is iterated using an equivalent form of upward continuation in the Fourier domain, which is more stable and convergent than downward continuation term in original P-O method. Synthetic experiments indicate that improved method has the better consistency among the simulations than original method, and our improved method has the smallest RMS of 0.59 km. In a real case, we employed the improved method to invert the Moho depth of the South China Sea, and the RMS between our Moho model and the seismological data is the smallest value of 3.87 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient.