The advent of fast digital computer has made numerical modeling of petroleum reservoirs very attractive, starting with a landmark paper published in 1953 by G.H. Bruce, et al. Reservoir simulation, a major numerical modeling technique, has now become an important tool used to study the performance of oil and gas reservoirs of various complexity where several variables are involved, and therefore, analytical solution may not be appropriate and/or closed form solution is not feasible. A number of sources of error in reservoir simulation application has been identified and documented in literature. One major source of error is frequent use of inaccurate reservoir description data. Therefore, model validation and calibration, meant to ascertain the correctness of the simulator and the applied description data, are essential parts of reservoir performance numerical modeling. Model validation and calibration are usually done by history matching of the field performance data and simulator calculated performance responses. In the last couple of decades, there has been considerable interest in the development of automatic history matching algorithms. Automatic history matching is preferred to the traditional trial-and-error approaches despite the fact that the automatic routines require some additional iterative optimization routines to the basic simulator because the investment of additional optimization code development time and computational CPU time is worth the effort.