Joint inversion of multi-channel surface wave data with vertical electrical sounding data

In the traditional inversion of the Rayleigh Dispersion Curve (RDC), layer thickness, which is the second most sensitive parameter of RDC modeling after S-wave velocity, is assumed as correct and fixed initial parameter. Because the estimation of the layer thickness is typically not precise, keeping as fixed of this information during inversion may result in the traditional RDC inversions getting trapped in non-uniqueness. In this study, we try to avoid this issue by using a joint inversion of the RDC data with Vertical Electric Sounding (VES) data. The key idea of the proposed joint inversion scheme is to link both methods with layer thickness and to combine in a single Jacobian matrix. In the proposed joint inversion algorithm, the non-linear weighted-damped least square method is used with variant damping factor strategy. After successfully tested of the proposed joint method on 6 different and characteristic synthetic models, the field field applications were done on field data from 10 different profiles around Trabzon city center and around. Moreover, on the field data inversion, first breaks of seismic data are implicated in the joint scheme. As a result of studies, the joint inversion allows to reduce the ambiguities depended on layer thickness in RD separate inversion, in this way the dependence to initial model of inversion process is significantly reduced. Consequently, the proposed joint inversion scheme allows providing reliable approximations even in complex and challenging situations and without using any a priori information.