The exploitation strategy of hydrocarbon reservoirs can be technically and economically optimized only if a reliable numerical model of the reservoir under investigation is available to predict the system response for different production scenarios. A numerical model can be reasonably trustworthy after calibration only, which means the model has at least proved its ability to reproduce the historical behavior of the reservoir it represents. The calibration procedure, also known as history matching, is the most time consuming phase in a reservoir study workflow. On the other hand, a new trend on collective computing offers a solution to CPU intensive tasks by distributing the work among several computers located in different places but globally connected through the World Wide Web. In this study, a novel workflow for assisted history matching is proposed. The results proved that this workflow provides better and more representative solutions in a fraction of the time needed by traditional approaches.