Utilizing Process-Based Models to Better Incorporate Heterogeneities within Reservoir Modelling

Abstract

Traditional reservoir modelling utilizes a stochastic approach centered around statistics to generate a 3D representation of the reservoir. While the results of a stochastic approach are favorable, they tend to lack the detail that is necessary to fully understand the different aspects of the reservoir, more precisely, the inclusion of heterogeneities. A possible solution to this problem is the use of process-based models. Process-based models utilize the physical processes involved in the transportation, deposition, and erosion of sediments. As a result, the models generated are more complex in nature and better represent what is found within the subsurface. The use of process-based models within reservoir modelling is a a relatively new process that has yet to be fully utilized due to the difficulty in calibrating the models with well data. Before process-based models can be tested on their viability to include the multi-scalar heterogeneities, the model must be calibrated to match the real-world data. To test this, a combination of field work, lab work, and computer simulations is required. In this experiment, the Roda Sandstone Member, a Gilbert-type delta deposit in Northern Spain, was chosen as the unit of focus. The Roda Sandstone consists of multiple prograding sand lobes, with Roda Y being chosen as the focus of this experiment. The Roda Y sandstone exhibits a predominately medium and coarse grain distribution in the central locations of the sand lobe, and a fine and very fine distribution in the distal locations. Five simulations were run within the process-based modelling software "Delft3D", each with varying sediment input parameters, to observe the effects on the results. The results for the simulations show a strong calibration for each of the five simulations for coarse and medium grained sand, with a percent difference between the model results and the field data of 4-8%. The fine and very fine data contain a higher average difference between the two data sets, ranging from 18-23%. The difference for mud averages around 11%, with predominately more mud being deposited within the simulations. The large differences for the fine and very fine grained can be attributed to the difference in the size and shape of the sand lobe produced by the simulations. In locations were the two data points are equivalent in regards to depositional location within the sand lobe, a high correlation is observed. The results indicate that process-based models have the potential to be a very useful took within reservoir modelling. As this is the first step in a series of steps, additional testing is required for the additional aspects involved in utilizing process-based models to better incorporate heterogeneities within reservoir models.