# How do we convert the seismic trace wavelet to zero phase which is in mixed phase?

As we know the mixed phase data would not give the "real TWTT" through the medium. We need a zero-phase wavelet that can directly correspond to the time taken to travel in a given media. So my question is how do we convert the seismic trace wavelet to zero phase which is in mixed phase? There must be an important processing procedure to do so.

My preferred way of doing this (I've been working in seismic data processing and analysis for over 20 years now) is:

2. Shape the source wavelet to zero phase (or minimum phase, depending on your application).
3. Design a cross-equalization filter that takes the input from step 1 as the source and step 2 as the target. This can then be globally applied to your data.

There are other ways to do this (like with Wiener deconvolution) that make a statistical estimate of what the wavelet should look like, and this was considered acceptable in the industry for many years. However, such statistical processes are not acceptable for all applications, such as 4D (time lapse seismic) analyses, so I prefer processes that are deterministic rather than processes that rely on a stochastic assumption.

It depends on what your starting information about your seismic data is. For example, if you know that your data contains an impulsive (minimum phase) source wavelet (i.e. the acquisition source was dynamite or a big ol' hammer, or some other impulsive source, and has not been modified) then you can apply the workflow of txpaulm or use spiking deconvolution. But realize that you are making an assumption about the shape of your wavelet's phase spectrum, which is a very good assumption most of the time.

If you don't want to make the minimum phase assumption for your wavelet (i.e. you think you have a mixed phase wavelet), you will need to make some other assumption or incorporate some other piece of information.

A very popular method for estimating a mixed phased wavelet is that of Walden and White (1998). They incorporate additional information from a reflectivity series calculated at a well and then find the impulse response filter that best predicts (in the least squares sense) the seismic data extracted along the well path.