Modeling method for automatic grid tomography depth domain velocity

Abstract

The invention discloses a modeling method for an automatic grid tomography depth domain velocity. The method comprises steps: 1) a depth domain migration profile and a common imaging point gather at each grid point are obtained; 2) gamma spectrum scanning is carried out on the common imaging point gather at each grid point to acquire a gamma spectrum value; 3) the inclination angle of each event and the coherence value along the inclination angle are obtained; 4) a depth domain initial velocity model and a reflection point in the depth domain migration profile are determined; 5) the remainingdepth at the reflection point is extracted and converted to a time difference; 6) the ray path of the reflection point is determined; and 7) a velocity perturbation is obtained by solving the tomographic square layer to update the velocity in the depth domain initial velocity model. By automatically interpreting and picking up the reflection point and the time difference deltat, migration velocitymodeling for the automatic grid tomography depth domain is thus realized, the tedious and time-consuming manual interactive pickup process is avoided, and manpower and material resources are saved.

Description

technical field [0001] The invention relates to the field of seismic exploration and development of oil and gas and coalbed methane, and more specifically relates to a modeling method for automatic grid tomography depth domain velocity. Background technique [0002] With the increasing complexity and concealment of oil exploration targets, pre-stack depth migration is more and more applied to production. Prestack depth migration can realize high-precision seismic imaging of complex subsurface structures, and can accurately reflect subsurface structures in areas with severe lateral changes in structural complex velocities. However, establishing an accurate velocity model is the key to prestack migration imaging. The correctness of the velocity model or its accuracy directly affects the success or failure of imaging. [0003] Velocity can be obtained from well logging data, core measurement data, and seismic data. Velocity obtained from seismic data is usually called veloci...

AI Technical Summary

Problems solved by technology

In the current application of tomographic migration velocity analysis, reflection points and time difference Δt are manually picked up interactively, which is a very tedious and time-consuming work, which restricts the practicality of tomographic migration velocity analysis

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