Improving communication between the geomodeler and his team is a topic discussed in all the papers of this series. However, if the geomodeler has to pick one place where improving the communication might have the biggest impact, he should focus on the one with the reservoir engineers. Firstly, the communication between geoscientists and engineers are often challenging, and the communication around a geomodeling project will be no exception, unless attention is given to this challenge. Secondly, transferring the information from the geological model into the flow simulation grid is the moment where considerable knowledge about the reservoir can be corrupted or even lost. If the upscaling is not done properly, the upscaled grid might not reproduce well enough the behavior expected in the geological grid. Also, it is the moment where all the uncertainty identified by the geoscientists might get lost if the wrong realizations, or if not enough realizations, are sent to flow simulation.

For all these reasons, if reservoir engineers are involved in the geomodeling project, it is essential to communicate with them as often as possible.
The next chapter will focus on the use of geomodels as inputs for in-place volume computations.

Many geomodeling packages have tools to create simulation decks, run simulation in the background by calling the flow simulation software and then display the time-dependant results. It might be interesting to discuss about these tools with the engineers.

Similarly, flow simulation software can compute statistics on the properties, as well as run some geostatistics. The geomodeler should get familiar with these. It will give him a better idea of how the engineer will review his model and how he might edit it.

When a field has had some production, running flow simulation starts with history matching. The goal is to validate and edit, if need be, the geomodel and the input dynamic parameters so that the engineers can reproduce the past production in their simulation. Once done, they can move to forecasting how the field’s production will evolve moving forward. For more details about this important topic, the reader can refer to (Gilman and Ozgen, 2013) or (Oliver et al., 2008).

For more details about some techniques of ranking, the reader can refer to (Datta-Gupta and King, 2007) and (Jamshidnezhad, 2015).

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