Dense nonaqueous phase liquids (DNAPL) are prevalent at a large number of sites throughout the world. The variable release history, unstable flow, and geologic heterogeneity make the spatial distribution of DNAPLs complex. This causes difficulties in site remediation contributing to long-term groundwater contamination for decades to centuries. We present laboratory experiments to demonstrate the efficacy of Sequential Successive Linear Estimator (SSLE) algorithm that images DNAPL source zones. The algorithm relies on the fusion of hydraulic and partitioning tracer tomography (HPTT) to derive the best estimate of the K heterogeneity, DNAPL saturation (S(N)) distribution, and their uncertainty. The approach is nondestructive and can be applied repeatedly. Results from our laboratory experiments show that S(N) distributions compare favorably with DNAPL distributions observed in the sandbox but not so with local saturation estimates from core samples. We also found that the delineation of K heterogeneity can have a large impact on computed S(N) distributions emphasizing the importance of accurate delineation of hydraulic heterogeneity.