3 results about "Receiver function" patented technology

The present invention discloses a method for inverting the density anomaly of the lithospheric mantle in the orogenic belt adjacent to the craton. The gravity anomaly caused by the stripping of the crust and the Moho surface is removed by the empirical relationship between crustal velocity and density and the gravity forward modeling method. The gravity anomaly forward test of the lithospheric mantle plate in the orogenic belt adjacent to the craton is jointly constrained by the residual gravity anomaly of the lithospheric mantle and the accumulated mass anomaly of the residual lithospheric mantle, and a series of qualified model sets are obtained. Finally, the depth, thickness and residual density of the optimal plate model are selected by the interface constraint obtained by the receiver function. The method of the present invention makes maximum use of known geophysical information and adopts a stable estimation strategy to obtain reliable lithospheric mantle density anomaly information of the orogenic belt adjacent to the craton, thereby improving the research level of the lithospheric mantle density anomaly in the orogenic belt adjacent to the craton, and playing an important role in promoting the study of continental lithosphere evolution and mineral resource exploration.

This invention provides a physics- and data-driven receiver function inversion method. By determining the model parameters to be optimized, an objective function for the inversion problem is constructed. This objective function includes a data fitting term, a model regularization term, and a coupling term combining data-driven and physics-driven approaches. During inversion, iterative optimization is performed by introducing the objective function and the coupling term combining data-driven and physics-driven approaches to determine the inversion model. By combining the advantages of the BFGS optimization algorithm and the UNet deep learning algorithm, a more robust receiver function inversion is achieved, outperforming single physics-driven or data-driven inversion methods. Compared to receiver function linearization inversion methods, it no longer relies on the initial model, reducing the possibility of the inversion solution getting trapped in local minima. Compared to deep learning inversion methods, it can better fit observational data and more closely approximate the true inversion solution.

This invention relates to the field of seismic data imaging technology, and proposes a seismic data imaging method, apparatus, device, medium, and program, comprising: acquiring seismic data; performing deconvolution processing on the seismic data using a preset algorithm to obtain receiver function data; calculating the source travel time, station travel time, and scattering point travel time based on preset sources, preset scattering points, and preset stations; storing and statistically analyzing the source travel time and the scattering point travel time to obtain source travel time fields and scattering point travel time fields; performing central difference calculation on the source travel time fields and scattering point travel time fields to obtain propagation data; performing imaging calculations on the receiver function data, source travel time, station travel time, scattering point travel time, and propagation data to obtain data migration imaging; performing weighted average imaging on the data migration imaging to obtain an imaging profile; and realizing migration imaging using methods for processing natural earthquake data.