Abstract：Due to the presence of low-velocity anomalies such as gas clouds, seismic data in complex offshore exploration areas are seriously affected by stratum absorption and attenuation. The amplitude energy of gas cloud data is weak, and the reflected signals are difficult to identify. The traditional velocity modeling methods of depth migration such as grid tomography inversion and horizon velocity analysis rely on residual picking up and are difficult to be carried out. Therefore, this paper proposes a new velocity modeling method based on Q tomography inversion technology. The core of this method is to employ Q tomography inversion based on peak frequency to build a Q model. Meanwhile, under the constraint of the model, a targeted local velocity update is conducted for efficient and accurate velocity modeling of local low-velocity anomalies. During the modeling, the built Q model and velocity model ultimately improve the imaging quality of pre-stack depth migration through mutual promotion and iterative update and optimization. The experimental analysis of the theoretical model proves the correctness of this method, which yields significant application effects in complex 3D exploration areas of southwest China. Finally, this method is verified to have advantages and feasibility in practical production applications.
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