Our previous publication Biondi and Sava (1999) introduced the concept of wave-equation migration velocity analysis (WEMVA) as the natural counterpart of wave-equation migration. The objective of our method is to exploit in the velocity analysis context the main strengths of processing based on the wave-equation: accuracy, multipathing, and stability.
In addition to its wave-equation nature, another important concept exploited by our method is that of velocity analysis by image enhancement, in contrast to other methods that also use wave-equation techniques but aim at fitting the recorded data. Our method operates by recursively and simultaneously improving both the migrated image and the velocity model. The advantage of doing so is that the users have an opportunity to quality control the results at every step.
In this paper, we briefly review the theory of WEMVA and show a complete synthetic example in which we start with simulated data, create an image with an approximate velocity model, and then improve both the velocity and the image using WEMVA.
The WEMVA puzzle relies on several key ingredients, among which some of the most important are image enhancement by residual migration, image quality control in the angle-domain and inversion that uses model constraints. All these are briefly discussed in this paper and are demonstrated with our example.