Geophysical data integration and its application to seismic tomography

Introduction

In earth sciences, subsurface structures are studied by collecting large and various types of geophysical data. Different geophysical attributes of the subsurface are measured by a variety of geophysical measuring techniques, including but not limited to seismic, magnetic, and well-logs. For many years, different types of data have been used for specific stages of oil exploration and production. However, in recent years, many authors have considered using diverse data in geophysical inversion can reduce uncertainty (Bosch et al., 2005; Colombo and De Stefano, 2007; de Nardis et al., 2005). One of the main challenges of data integration is the difference in physical nature, scale, and frequency contents. All of the collected data, however, while measuring different properties, sample of the same geophysical structures. We can extract mathematical/geophysical properties from a data set that provides structural information. This structural information can be used in geophysical problems as auxiliary data to improve model estimation results by constraining the optimization problem. Geophysical inversion problems can benefit from this method in the form of a regularization misfit term that imposes structural similarity between the main and the auxiliary data fields. It is also applicable to both joint inversion and inversion using the auxiliary data.

Geophysical data integration and its application to seismic tomography