Identifying the location and distribution of NAPL (Non Aqueous Phase Liquid) in the subsurface constitutes a vital step in the design and implementation of aquifer remediation schemes. In recent years, partitioning interwell tracer tests (PITT) have gained increasing popularity as a means to characterize NAPL distribution in-situ. In this method, a conservative and a partitioning tracer are injected into the contaminated site. The chromatographic separation between the conservative and the partitioning tracer can be used to infer NAPL distribution. The conventional approach to the analysis of the tracer response uses a first-order method of moments to compute average NAPL saturation. Such methods are limited due to the one-dimensional approximation and consequently can not provide detailed spatial distribution of the NAPL.
In this paper we discuss a streamline-based inversion approach for partitioning tracer response to estimate spatial distribution of NAPL saturation in the subsurface. Our approach relies on an analytic sensitivity computation method that yields sensitivities of the partitioning tracer response to subsurface parameters such as porosity, permeability and NAPL saturation in a single streamline simulation. We can then use efficient techniques from geophysical inversion to match the field tracer response and estimate subsurface parameters. For characterizing NAPL saturation we follow a two-step procedure. First, we match the conservative tracer response that provides us with a permeability distribution. Next,the partitioning tracer response is matched by varying the NAPL saturation distribution in the subsurface. The non-uniqueness in the solution is addressed through the use of regularization techniques and/or prior information.
The proposed technique has been applied to synthetic as well as field examples. The synthetic example is used to validate the procedure using tracer response from a 9-spot pattern. The field example is from the Hill Airforce Base, Utah where partitioning tracer tests were conducted in an isolated test cell with 4 injection wells, 3 extraction wells and 12 multi-level samplers. Tracer responses from 51 sampling locations are analyzed to determine permeability variations and NAPL saturation distribution in the test cell. Finally, a performance comparison with another commonly used inversion method viz. simulated annealing, shows that our proposed approach is faster by about three orders of magnitude.