In project management, there is a model known as the quality triangle, which states that a project is constrained by three aspects: quality, time, and cost. Usually, one of these constraints is fixed. For example, if the cost is fixed, the quality of the project will depend heavily on the time available for the conclusion. Of course, this is an idealized and incomplete model of reality, but it has its merits.
In the course of my career, I have had the opportunity to work on several history-matching cases. Every time I think about these cases, the quality triangle comes to mind. Most history-matching studies have fixed resources—that is, the team of engineers and geoscientists is predetermined. (So, the cost vertex of the triangle is settled.) Moreover, the deadlines are always very strict. This constrained scenario often leads to an unfortunate result: The quality of the study suffers. In some cases, this quality reduction comes in the form of a reduction in scope. For example, instead of matching data from all wells of the reservoir, we limit the analysis to the wells near the area of interest of the project. However, we must remember that history matching is never the end of the history. Creeping the quality in a reservoir study can result in very serious consequences for a project by harming the decision-making, which surely can cost a lot of money.
So, what is the way around this problem? The answer is twofold: people and technology. Training is important, and integration is paramount. A talented and engaged team is the main component for success. Technology is the other component. Recent advances in seismic inversion, geostatistics, reservoir simulation, assisted history matching, and high-performance computing (just to mention a few) should always be on the table. In good hands, they can make a difference.
Read theJPTTechnology Focus on History Matching and Forecasting here.
