Yingxiongling is located in the western of the Qaidam Basin, with numerous ravines and complex structures. It is known as the "forbidden zone for seismic exploration" by oil and gas exploration experts from all the world. The complex near surface and underground conditions with thrust fractures have led to three major challenges in the area: severe static correction problems, low signal-to-noise ratio of field data and difficulty in imaging, which seriously constrain the progress of oil and gas exploration. On the basis of high-precision intelligent full arrangement of first arrival picking, a technology centered on adaptive weighted tomography and adjoint state tomography is proposed to improve the accuracy of static correction. According to the principle of "first strong then weak, first regular then random" and the idea of "six part method" for denoising, targeted researches on noise suppression strategies will be effectively carried out step by step to improve data fidelity. Combining high-precision grid tomography and multi-information constrained velocity modeling, a true surface full depth domain modeling and imaging technique is proposed to obtain high-quality migration results. The imaging results indicate that the series proposed technologies have improved the imaging accuracy of deep and complex structures, effectively solving the problem of well seismic inconsistency in the target layer, and providing an important guarantee for promoting risk exploration in the Yingxiongling area.