Abstract:
Solving the inversion of ultra-deep electromagnetic measurements is a challenging task in directional resistivity logging while drilling (LWD) service. The target is to r...Show MoreMetadata
Abstract:
Solving the inversion of ultra-deep electromagnetic measurements is a challenging task in directional resistivity logging while drilling (LWD) service. The target is to reconstruct the subsurface formation structure around the borehole in the real-time drilling job. Due to the complexity of ultra-deep measurements, the inverse modeling is highly nonlinear and ill-posed. Hence, the conventional methods are insufficient to resolve this problem. In this paper, a statistical data-driven approach is proposed, which combines Bayesian inference and parallel tempering techniques.
Published in: 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
Date of Conference: 07-12 July 2019
Date Added to IEEE Xplore: 31 October 2019
ISBN Information: