Application of transdimensional Markov chain Monte Carlo inversion to seismic oceanography study

Abstract

The information of the sea water structure and physical properties is essential to analyze the oceanographic feature of the sea water. However, observing the detail feature of the complex water structure by using conventional physical oceanographic instruments is difficult because of the low horizontal resolution. The Seismic Oceanography (SO) is a method to obtain the location of the water layer boundaries and/or the physical properties of water by using seismic exploration. The SO can generate the information with high horizontal resolution because the horizontal resolution of the seismic data is usually below 10 m. However, it is difficult to calculate the properties of sea water by using the conventional seismic inversion methods. In this study, we apply transdimensional Markov chain Monte Carlo (McMC) inversion method to invert the location of water layer boundaries and sound speed of sea water simultaneously. The transdimensional McMC inversion assumes both the location of water layer boundary and the properties of sea water as inversion parameters and performs stochastic inversion, thus it can overcome the local minima problem. Moreover, it is less influenced by the problems from the insufficient low frequency information and the limitation of the offset range because it uses the post-stack data instead of the pre-stack data. We apply transdimensional McMC inversion to the field seismic data and invert the lay1