STOCHASTIC SIMULATION OF SOLUTE TRANSPORT IN HETEROGENEOUS FORMATIONS- A COMPARISON OF PARAMETRIC AND NONPARAMETRIC GEOSTATISTICAL APPROACHES

The Monte Carlo simulation of solute transport in heterogeneous format ions generates equally likely realizations of hydraulic conductivity u sing geostatistical approaches. The available field data on hydraulic conductivity can be classified as hard data (i.e., measurements with a low degree of uncertainty) and soft data (i.e., measurements with a g reater degree of uncertainty). Information on hydraulic conductivity s hould be honored in the generated realizations in order to reduce unce rtainty in the simulation. The traditional parametric approaches, such as the Turning Bands (TUBA) method, are multi-Gaussian and make it di fficult (if not impossible) to include the use of soft data. A recentl y developed nonparametric geostatistical approach, the Sequential Indi cator Simulation (SIS) method, can incorporate soft data easily and ge nerate any distribution functions not limited by multi-Gaussian. The m ain goal of this paper is to investigate the effects of incorporating soft data on solute transport simulations by using SIS. Two synthetic 2-D heterogeneous reference hydraulic conductivity fields, one with an isotropic multi-Gaussian underlying model and the other with an aniso tropic non-Gaussian model, are sampled to obtain limited hard hydrauli c conductivity data and a relatively large number of soft data. Based on the sampled data, realizations of simulated hydraulic conductivity fields are generated by using SIS for different cases depending on whe ther or not the soft data are used. TUBA is also used to generate real izations when only the hard data are used for the comparisons. Solute transport results are calculated by the Monte Carlo method. It is show n that when only limited hard data are available, SIS and TUBA provide similar simulation results which in these cases deviate from the resu lts of the reference fields. The main conclusion of this study is that , by adding a relatively large number of soft data, the statistical fe atures of the reference hydraulic conductivity fields are better chara cterized and transport simulation results are improved significantly. The uncertainties in predictions of both solute arrival time and arriv al position are reduced when soft data are included. More investigatio ns are needed to study the effects on solute transport of high continu ity at extreme hydraulic conductivity values and the effects of incorp orating large amounts of soft data with larger degrees of uncertainty, e.g., the soft data interpreted from seismic lines.