Authors : Mehran Azimbagirad, Arash Amiriam and Mohsen Oveisi Moakhar
Abstract: In this study, QR decomposition is utilized for 1D interpretation of Schlumberger sounding data instead of former method to optimize the best fit between the calculated and observed apparent resistivity data. The method is implemented by arbitrary parameters of initial model and uses the damped least-square solution with QR and LU decomposition. The method was tested on three synthetic models comparing with the Singular Value Decomposition (SVD) applicability. Noise also was added to two models. Furthermore, the procedure is employed to interpret real data from Iran and the results are compared with published previous geological information. In all cases, QR and LU Decompositions are quicker than SVD method to determine parameters of models.
Mehran Azimbagirad, Arash Amiriam and Mohsen Oveisi Moakhar, 2016. A New Decomposition to Interpret Curves of Schlumberger Survey. Journal of Engineering and Applied Sciences, 11: 1097-1103.