PhD Research:
My primary area of research is to analyze subsurface anisotropy using seismic, well and core data. It is now established from several geophysical and electrical measurements that subsurface commonly exhibit seismic anisotropy, caused for example by changes in lithology or stratigraphy, the intensity and pattern of fracturing, preferred mineral alignment or mechanical or fluid processes. So analyzing anisotropy and keeping that in account have become a necessity to avoid errors while developing a reservoir model.
Conventionally, convolution based AVO inversion methods are used for anisotropic inversion, but it has certain limitations, such as, they are not valid for far and ultra-offsets (> 30°). Therefore, I propose to use a different approach of inversion, of anisotropic P-wave data, which is based on using genetic algorithm (GA). As opposed to convolution based conventional AVO inversion methods, this new approach uses waveform-based technique and therefore is valid for far-offsets (> 30°) where traditional AVO inversion methods fail. The benefit of this kind of inversion is that we can utilize the far and ultra-far offsets to see the variations in geophysical properties from the near-offsets and then can quantify these variations in studying the anisotropic nature of the subsurface more effectively.
Masters Research:
The topic of my masters thesis was “Modelling Seismic Response of Thin Beds”. This involved generation and analysis of P and S-wave synthetic seismograms at several offsets for different subsurface models when we have below tuning bed thicknesses. All the programming for developing synthetic seismograms was done in C++.