Improvements in the reconstruction of ERT data based on pseudo-pole-pole measurements

Electrical resistivity tomography (ERT) has been successfully applied in a wide range of fields, including geotechnical and environmental engineering. However, conventional measurement protocols often fall short under complex field conditions or when precise imaging is required. Comprehensive datasets, which provide the highest resolution, are better suited to capturing detailed subsurface information. Unfortunately, acquiring such datasets in practice is infeasible due to the vast number of required data points. The pseudo-pole-pole (pdPP) measurement strategy enables the acquisition of comprehensive datasets through superposition, eliminating the need for remote electrodes and allowing data quality evaluation using reconstructed normal and reciprocal datasets. However, noise accumulation during the superposition process can introduce significant errors in the reconstructed data, with differing impacts on normal and reciprocal data.

This study investigates noise accumulation in ERT data reconstructed from pdPP measurements. A linear error model was used to account for measurement errors and derive the error model for reconstructed data. Noise accumulation of different data types were analyzed based on a homogeneous model. Synthetic and field experiments further validated these findings, and practical considerations, such as the optimal placement of reference electrodes, were also explored. The results show that the derived error model can serve as a data filter and weighting tool during inversion to ensure reliable imaging. Reconstructed normal measurements generally exhibit better quality than reciprocal data. Quality control based on normal and reciprocal errors can selectively exclude data with minor errors while retaining data with larger errors. It is recommended to reconstruct normal-type comprehensive datasets from pdPP measurements, with reference electrodes placed approximately 1/5 of the survey line length from the first and last electrodes.