Separation of DC Electrical Method Anomaly By Using Multifractal Modelling

A more accurate method of DC processing data to distinguish the anomalous body is important for the prediction and detection of potential risk such as goaf and water inrush. In this paper, we have performed a DC data processing process, which relies on the theory of aggregation-area(C-A). We investigate the apparent resistant and apparent resistant isograms cumulative area as a function to search the threshold as the boundary value. Comparisons of the conventional data processing method to physical simulation that the C-A identified the higher resistance anomalous body better than the lower resistance because its sensitivity. Scoped the higher resistance area almost identical with the physical model, while the lower approach the nearest boundary. The results are in good agreement with the physical model, validating C-A multifractal theory as an effective way for DC accurate interpretation.