Abstract
The limited-memory quasi-Newton optimization method with simple bounds has been applied to develop a novel fully three- dimensional (3-D) magnetotelluric (MT) inversion technique. This nonlinear inversion is based on iterative minimization of a classical Tikhonov-type regularized penalty functional. But instead of the usual model space of log resistivities, the approach iterates in a model space with simple bounds imposed on the conductivities of the 3-D target. The method requires storage that is proportional to ncp×N, where the N is the number of conductivities to be recovered and ncp is the number of the correction pairs (practically, only a few). This is much less than requirements imposed by other Newton type methods (that usually require storage proportional to N ×M ,o rN ×N, where M is the number of data to be inverted). Using an adjoint method to calculate the gradients of the misfit drastically accelerates the inversion. The inversion also involves all four entries of the MTimpedance matrix. The integral equation forward modelling code x3d by Avdeev et al. (1, 2) is employed as an engine for this inversion. Convergence, performance and accuracy of the inversion are demonstrated on a 3D MTsynthetic, but realistic, example.
Published Version (Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.