Dynamic imaging of metallic contamination plume based on self-potential data

A dynamic imaging method for monitoring self-potential data was proposed. Based on the Darcy's law and Archie's formulas, a dynamic model was built as a state model to simulate the transportation of metallic ions in porous medium, and the Nernst equation was used to calculate the redox potential of metallic ions for observation modeling. Then, the state model and observation model form an extended Kalman filter cycle to perform dynamic imaging. The noise added synthetic data imaging test shows that the extended Kalman filter can effectively fuse the model evolution and observed self-potential data. The further sandbox monitoring experiment also demonstrates that the self-potential can be used to monitor the activities of metallic ions and exactly retrieve the dynamic process of metallic contamination.