In this work, a new automated 3d resistivity inversion algorithm, for parallel 2D ERT lines which is at least two times faster than a standard inversion algorithm, is presented. The basic idea of this algorithm is based on the examination of the Jacobian matrix entries and the fact that due to the 2D arrangement of measuring electrodes there are many 3D parameters for which the calculated Jacobian matrix values are practically zero. These values are automatically identified and excluded from the Jacobian calculation, which is the most time-consuming part of forward modeling. Further, to take full advantage of the sparseness of the resulting Jacobian matrix, inversion is preformed using the LSQR (Least Squares Regression) method which results in faster inversion and has less memory requirements than the conventional approach. The algorithm is compared to a standard 3D inversion routine and proved its efficiency in both synthetic and field data.


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