Title of article :
Automatic estimation of regularization parameter by active constraint balancing method for 3D inversion of gravity data
Author/Authors :
Moghadasi, M Faculty of Mining - Petroleum & Geophysics Engineering - Shahrood University of Technology - Shahrood, Iran , Nejati Kalateh, A Faculty of Mining - Petroleum & Geophysics Engineering - Shahrood University of Technology - Shahrood, Iran , Rezaie, M Faculty of Engineering - Malayer University - Malayer, Iran
Abstract :
Gravity data inversion is one of the important steps in the interpretation of practical
gravity data. The inversion result can be obtained by minimization of the Tikhonov
objective function. The determination of an optimal regularization parameter is highly
important in the gravity data inversion. In this work, an attempt was made to use the
active constrain balancing (ACB) method to select the best regularization parameter for
a 3D inversion of the gravity data using the Lanczos bidiagonalization (LSQR)
algorithm. In order to achieve this goal, an algorithm was developed to estimate this
parameter. The validity of the proposed algorithm was evaluated by the gravity data
acquired from a synthetic model. The results of the synthetic data confirmed the correct
performance of the proposed algorithm. The results of the 3D gravity data inversion
from this chromite deposit from Cuba showed that the LSQR algorithm could provide an
adequate estimate of the density and geometry of sub-surface structures of mineral
deposits. A comparison of the inversion results with the geologic information clearly
indicated that the proposed algorithm could be used for the 3D gravity data inversion to
estimate precisely the density and geometry of ore bodies. All the programs used in this
work were provided in the MATLAB software environment.
Keywords :
Inverse Problem , Regularization Parameter , Active Constrain Balancing , Gravity Data , Holguin Ore Deposit
Journal title :
Astroparticle Physics