JOINT CONDITIONAL SIMULATIONS AND THE SPECTRAL APPROACH FOR FLOW MODELING

The use of data to condition single random fields has a well-establish ed history. However, the joint use of data from several cross-correlat ed random fields is not as well developed. For example, the use of bot h transmissivity and head data in a steady state 2-d stochastic flow p roblem essentially an inverse problem that is very important for both flow and transport predictions. This problem is addressed here by usin g a combination of numerical simulation and analytical methods and its application illustrated. The type of information conveyed by the diff erent data categories is explored. The results presented are especiall y interesting in that head and transmissivity each give different info rmation: Head values would appear to constrain the geometry of the pat hs while transmissivity data yields information about travel times. Th e linearized model is expanded to an iterative procedure and the ''tru e'' conditional distribution at several locations is compared with the iterative solution. The problem mentioned above is one with a special transfer function specified by the flow equation. In the second part of the paper a Fast Fourier Transform method for generattion and condi tioning of two or more random fields is introduced. This procedure is simple to implement, fast and very flexible.