Azevedo, L., Huang, X., Pinheiro, L. M., Nunes, R., Caeiro, M. H., Song, H., & Soares, A. (2018). Geostatistical Inversion of Seismic Oceanography Data for Ocean Salinity and Temperature Models. Mathematical Geosciences. https://doi.org/10.1007/s11004-017-9722-x
Conventional multi-channel seismic reflection data, known as seismic oceanography, has recently been used for the qualitative interpretation of meso- to large-scale hydrographic structures of interest. Seismic oceanography has been successfully imaging oceanographic structures in an intermediate scale not sampled by traditional oceanographic tools, such as conductivity, depth and temperature measurements and eXpendable BathyThermograph (XBT) data. However, few attempts have been made for successfully quantifying ocean properties, such as ocean temperature and salinity, directly from the seismic reflection data. This work presents an iterative geostatistical methodology capable of inverting conventional seismic oceanographic data simultaneously for high-resolution temperature and salinity ocean models. The proposed methodology was developed and implemented in a real set of contemporaneous XBT data and two-dimensional seismic profile acquired southwest of Portugal. The resulting high-resolution temperature and salinity models reproduce existing XBT data not used to constrain the geostatistical inversion, which permits reliable quantification of the ocean properties of interest.