A program to create permeability fields that honor single-phase flow rate and pressure data

Abstract

Accurate prediction (or simulation) of reservoir performance or contaminant transport in groundwater requires a realistic geological model representative of the reservoir/aquifer heterogeneity. Geostatistics provides tools for constructing such complex geological models constrained by different types of available (hard and soft) data and providing an assessment of related uncertainty. Permeability and flow data are nonlinearly related through the flow equations. Derivation of permeability models that honor flow response data is typically an inverse problem. This paper presents a FORTRAN program for generating permeability fields conditional to multiple-well single-phase flow rate and pressure data through an iterative inverse technique, called the sequential self-calibration (SSC) method. The SSC method is geostatistically-based, that is, it generates multiple equiprobable realizations that honor the input geostatistics of permeability and match pressure data for the given flow rate, under the given boundary conditions. The unique aspects of SSC are: (1) the master point concept that reduces the amount of computation, (2) a propagation mechanism based on kriging that accounts for spatial correlations of perturbations and (3) a fast method for computing all sensitivity coefficients within a single flow simulation run. Results from running the SSC code using an example data set are presented.