Optimized survey design for the joint use of direct current resistivity and induced polarization: Monitoring of DNAPL source zone evolution at a virtual field site

The combined application of direct current (DC) resistivity and induced polarization (IP) methods, referred to as combined DCIP method, has gained popularity for characterizing the critical zone dynamic processes such as dense non-aqueous phase liquids (DNAPLs) spreading at contaminated sites. Large-scale DCIP surveys typically require considerable durations, necessitating optimized survey designs to enhance survey resolution while controlling time and labor costs. However, to date, approaches to optimize geoelectrical survey design have focused solely on DC applications, and the efficiency of optimized survey designs for combined DCIP is yet to be investigated. Moreover, as subsurface heterogeneity would impact the geophysical observations, most field-scale numerical DCIP studies have still been conducted at artificial sites that lacked realistic aquifer heterogeneity, which could affect the validity of the DCIP survey evaluations. In this work, a virtual geoenvironmental field site based on high-resolution real aquifer analog was created to simulate a DNAPL evolution scenario with simultaneous monitoring by DCIP survey, employing both the optimized survey design and popular non-optimized survey designs (Wenner, Wenner-Schlumberger, Dipole-Dipole arrays). Results show that the optimized survey with prior information improves the monitoring accuracy of DNAPL source zone (SZ) by 8 to 19 % with respect to different DCIP characteristics (conductivity, chargeability, normalized chargeability, and relaxation time). Another ideal numerical test indicates that the optimized survey shows up to an 83 % reduction in measurement time compared to the conventional survey, while maintaining the same subsurface image resolution. Additionally, the optimized surveys designed without or with limited prior information were also shown to be more efficient than conventional survey for imaging the entire subsurface space. The findings in this study highlight the immense potential of optimized survey design methods for enhancing the efficiency of DCIP surveys on subsurface contaminants and hydrological processes.