STOCHASTIC SIMULATION OF TRANSMISSIVITY FIELDS CONDITIONAL TO BOTH TRANSMISSIVITY AND PIEZOMETRIC DATA 2 - DEMONSTRATION ON A SYNTHETIC AQUIFER

In the first paper of this series a methodology for the generation of transmissivity fields conditional to both transmissivity and piezometr ic head data was presented. This methodology, termed the self-calibrat ed approach, consists of two steps: first, the generation of a seed tr ansmissivity field conditioned only to transmissivity data, and second , the perturbation of the seed field up until the piezometric head dat a are reproduced. The methodology is now demonstrated on a set of cont rolled numerical experiments carried out on synthetic aquifers. The ob jective of these experiments is not just to show that the methodology works, but also to explore its robustness under different situations. A total of 12 experiments have analyzed the performance of the method as a function of: (i) the log(10) T transmissivity variance (from 0.2 to 2.0); (ii) the number of log(10) T conditioning data (from 10 to 30 ); (iii) the number of piezometric head data (from 30 to 90); (iv) the number of master points (from 25 to 1000); (v) the magnitude of allow ed departure of the final T field from the seed field (up to four time s the kriging standard deviation). In all cases, the method was able t o generate transmissivity fields conditional to both transmissivity an d head measurements, at the same time preserving the spatial variabili ty of the transmissivity field. It was found that the performance of t he method increases with both the number of log(10) T data and the num ber of master points, whereas it decreases as either the log(10) T var iance or the number of piezometric head data increases. (C) 1997 Elsev ier Science B.V.