Inversion of ERT data with a priori information using variable weighting factors

In this work we propose a new way of introducing prior information regarding known resistivity distribution within the inversion procedure. Here the prior information is introduced as an extra term into the objective function of the resistivity inverse problem which is minimized via the Lagrangian multiplier technique. The final inversion equation allows the introduction of prior information in a flexible way. The contribution of prior information to the final inversion result can be weighted depending on the reliability of prior information. Further, a variable weighting scheme is proposed in order to avoid erroneous inversion results due to inaccurate prior information. The effectiveness of the new algorithm is demonstrated via synthetic and real data examples. •Variable weighting scheme is proposed to apply a priori information.•The advantage of variable weighting scheme is demonstrated.•The effect erroneous a priori information is studied.•Field data were processed and compared with various a priori constraints.