← Back to Gallery

Three-dimensional Least-squares Migration of Teleseismic Receiver Functions and Its Application to the Qaidam Basin

The receiver function (RF) method has been widely applied to resolve seismic discontinuities in the Earth's crust and mantle. The advent of dense seismic arrays enables wavefield sampling at unprecedented spatial resolution, providing new opportunities to develop advanced RF imaging techniques for improved subsurface characterization. In this study, we develop a high-resolution RF imaging technique based on three-dimensional least-square migration (LSM). The Split-step Fourier algorithm is employed to construct the forward and adjoint operators, reformulating the migration process as a least-squares optimization problem. This approach facilitates the easy incorporation of model constraints to suppress strong acquisition footprints and compensate for inadequate illumination.
The application of the LSM method to a dense linear array deployed in the Qaidam basin, northeastern Tibetan Plateau, reveals high-resolution crustal structures. Pronounced sedimentary layer-generated conversions and reverberations enable us to conduct waveform modeling that accurately constrains the basin structure and refines the migration velocity model. The modeling results indicate that a 12-km thick sedimentary sequence can adequately explain the converted phase near 3 seconds, which aligns well with the sedimentary base identified in high-resolution seismic reflection data for hydrocarbon exploration. The final migration image reveals that the Moho is relatively shallow (~50 km) beneath the basin margins adjacent to the Eastern Kunlun and Qilian orogenic belts, but deepens to ~55 km towards the basin center. These improved seismic constraints from LSM provide new insights into the deep structure and evolution of the Qaidam basin, contributing to a better understanding of intracontinental tectonics in Central Asia.

Session: Earth’s Structure from the Crust to the Core - II

Type: Oral

Room: Key Ballroom 9

Date: 4/16/2025

Presentation Time: 11:30 AM (local time)

Presenting Author: Pengfei Zuo

Student Presenter: Yes

Invited Presentation: 

Poster Number:

Additional Authors