Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm.

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 theory of the traditional Parker‐Oldenburg (P‐O) method is quite simple and it is widely applied in the frequency domain of 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 the excessively smoothing of data details caused by using filters to correct the source data signals. To solve those problems, we propose an improved iteration P‐O method with a variable density contrast model, 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 root mean square (RMS) of 0.59 km. In a real case, we employed the improved method to invert for the Moho depth of the South China Sea (SCS), and the RMS between our Moho depth model and the seismological data is the smallest value of 2.27 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient. Key Points: We developed an improved Parker‐Oldenburg method using an equivalent form of upward continuation in the Fourier domain instead of applying a low‐pass filter, which achieves a better stable performanceGravity inversion combines the actual density variations between layersMoho inversion in the South China Sea fits well with the seismic data, and our Moho depth model have the smallest root mean square (2.27 km) compared to other gravimetric Moho models [ABSTRACT FROM AUTHOR]