A long-standing reservoir simulation problem in petroleum engineering is history matching, where a reservoir simulator is "calibrated" in some way to model the reservoir under study. A correctly calibrated simulator can be used for reservoir characterization and provides a cost-effective way of obtaining essential information about the reservoir. The history matching problem seeks to find a set of suitably adjusted input parameters of the simulator such that the simulator correctly predicts the fluid (oil, gas, water, etc.) outputs of the wells on the reservoir, over the period of time of interest. The history-matching problem is theoretically simple but frequently intractable in practice because of three significant issues: the scale of the problem; lack of reasonably affordable computational resources for many oil operators who need to do the simulation; and the need for human intervention in the process. This paper presents a solution by utilizing soft computing and Web computing techniques.