A common effort involved in the remediation of contamination by petroleum hydrocarbons in porous media is the monitoring and volume estimation of the immiscible hydrocarbon fluid. The apparent free product thickness indicated by a standard monitoring well is typically much greater than the actual free product thickness in the surrounding soil. This results in significant errors in estimates of drainable fluid (product) volume, which in turn leads to inaccuracies (i.e., over design, improper pump sizing, etc.) with remediation system design.
An equation to predict actual thickness was developed using heterogeneous fluid flow mechanics and hydrostatics. This equation is: tg= t(l – Sg) - ha, where tg= actual formation free product thickness, t = apparent (well bore product) thickness, Sg= specific gravity of petroleum hydrocarbon (gasoline in this research), and ha= distance between the ground-water table and the free product in the formation.
The developed theory was compared to data collected from a physical model which simulated field conditions. The theory was used to estimate product thickness in the model, and then these estimates were statistically tested for accuracy. The theoretical slope, (1 – Sg), was not statistically different from the regression slope at test levels of α= 0.05 and α= 0.01, while the theoretical intercept (ha) was statistically different at α– 0.05 and α– 0.01. The discrepancy between the theoretical intercept and the regression intercept was probably due to either an incorrect assumption that ha= hc (hc= average wetting capillary rise), or an incorrect laboratory measurement of hc.
The effects of water-table fluctuations were also studied. A rising water table caused a decrease in apparent thickness and an increase in actual thickness, and vice versa. No theoretical equation was developed for the effects of water-table fluctuations, but it was reasoned that hysteresis of the saturation curve and adsorption were the primary factors in the observed trends.
Finally, the developed theoretical equation was compared to the results of previously published predictive methods and experiments. The comparison was made by calculating percent error and using a chi-square statistic. The developed theory was found to be the best predictor of actual product thickness for both laboratory data sets used.
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