The Reliability of the Predicted Performance of Natural Gas Reservoirs Using Reservoir Parameters From Well Test Data Containing Errors
Authors: Dogru Ali H. , Knapp Roy M. 
Published: December 2007

American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc.
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Abstract
The main purpose of gas reservoir simulation is to predict the future performance of the reservoir under Alternate 1 production policies. The successful prediction of reservoir performance requires accurate parameters such as performance requires accurate parameters such as permeability, porosity and reservoir boundaries. permeability, porosity and reservoir boundaries. These parameters are normally estimated from well tests where the pressure and flow-rate measurements are subject to errors. As a result of the measurement error, the predicted performance will also be subject to error. performance will also be subject to error. This paper shows that statistical limits can be placed on such estimates. placed on such estimates. The parameter estimation procedure from noisy well-test data has been studied. Several drawdown and buildup tests for a radial homogeneous gas reservoir were simulated. "Noise" (measurement error) was superimposed on the test data. Nonlinear least-squares regression was used to estimate the mean values and standard deviations of the reservoir parameters (permeability, porosity and drainage parameters (permeability, porosity and drainage radius) from the "observed" well pressures. At the end of each test statistical confidence limits were established on the estimated parameters. parameters. The estimated parameters and their confidence limits were used to predict the future pressure behavior of the reservoir. Confidence pressure behavior of the reservoir. Confidence limits were also established on the pressure behavior. Several different tests were studied to determine the effect of the well-test method on the confidence limits of the future pressure predictions. predictions. The confidence limits theory (reliability theory) was also applied to gas-in-place estimation from a drawdown test. A Monte-Carlo simulator was used to calculate the standard error in the estimated gas in place.

Introduction
For a natural gas producer or gas transmission company, the accurate prediction of gas well or reservoir performance is of primary importance. Currently, it is likely that the performance of a gas reservoir is predicted by performance of a gas reservoir is predicted by using a mathematical model (simulator) of the reservoir. As an example, the mathematical description of a one-well radial gas reservoir is given by the following nonlinear partial differential equation, initial condition, and boundary conditions.
(1)