Analysis of well testing data using ant colony optimization

摘要

Well testing analysis is a mature technology in petroleum engineering for obtaining information about a well and a reservoir. It can be the only method to estimate areal permeability, which is a key parameter to perform a reservoir management. Recently, well testing analysis was carried out with the aid of a computational method, which conducts an inverse calculation with time versus pressure data and flow rate. Therefore, it is necessary to apply a global optimization algorithm for accurate inverse calculation. This study presents estimation of the reservoir properties such as permeability, skin factor and wellbore storage coefficient from an insufficient field data by using the ant colony optimization (ACO) method. The reservoir properties are very important input data for a reservoir simulation which is used to perform production optimization and reservoir management. They can be estimated accurately from well testing data analysis. In the study, ACO is applied to solve the optimization problem that is the automatic type curve matching with well test data in homogeneous reservoir with infinite acting boundary. It was found that the results had been good match to these of the genetic algorithm, the non-linear regression method and the modified Levenberg–Marquardt method.