Artificial Intelligence Velocity Pickup in Velocity Modeling for Double Complex Areas: Research and Application

With the continuous deepening of oil and gas exploration and development, exploration targets have become increasingly complex, and the requirements for high-precision processing of massive seismic data have become increasingly demanding. Velocity modeling is one of the core technologies for high-precision imaging, which requires multiple iterations to optimize the velocity model. However, in traditional seismic processing, manual velocity pickup is inefficient, time-consuming, and greatly influenced by human factors. The accuracy and efficiency of manual velocity pickup have been unable to meet the current industrial production demands. This paper adopts an artificial intelligence method combining energy cluster target detection and stacked segment velocity trend prediction, achieving good results in the application of actual seismic data processing in the northeast of the Sichuan Basin, which is characterized by “double complexity”. Application examples demonstrate that the method used in this paper not only improves the efficiency of velocity model pickup, significantly shortens the processing cycle, but also significantly enhances the accuracy of the velocity model, making it widely applicable in industrial production.