Conditioning 3D Stochastic Channels to Pressure Data

Abstract

Summary This work discusses the development and implementation of a procedure to condition a stochastic channel to well-test pressure data and well observations of the channel thickness and the depth of the top of the channel. The stochastic channel is defined by a set of geometric random variables (referred to as geometric model parameters) that describe the location, size, and shape. Channel and nonchannel permeability and porosity are treated as random variables. These four random variables plus the geometric parameters comprise the complete set of model parameters. Multiple conditional realizations of the geometric parameters and rock properties are generated to evaluate the uncertainty in model parameters and the reduction in uncertainty obtained by conditioning to well-test pressure data.