Fast evaluation of reservoir performance is one of the main concerns for decision making. Additionally, lack of reservoir data is a big issue in performing numerical simulations and obtaining reasonable history matching results in a short period of time. Asset management tends to question and avoid cost and downtime related to data acquisition. Pressure and rate transient analyses (P&RTA), along extended periods of production, allows the characterization of reservoir and near wellbore features, however, P&RTA alone does not provide pressure and fluid distribution prediction beyond the wellbore, it requires the integration with reservoir simulation.
This paper provides a practical application for integrating well performance models to derive sandface pressure and rate data, that would enable P&RTA and ultimately a full-field integrated reservoir model. P&RTA facilitates the identification of reservoir parameters leading to improve and expedite reservoir history matching, and to perform the evaluation of various production scenarios. Available real-time pressure and rate data is key to achieving these objectives. The applied workflow allows engineers to quickly identify uncertainties and opportunities to evaluate different field development strategies to maximize the ultimate oil recovery.
The methodology was successfully applied in a reservoir study in South America. To achieve the goals, it was necessary to characterize the reservoir in terms of original oil in place, reservoir rock properties, compartmentalization and well performance history by well in each producing reservoir. Unstructured refined grid principles (Voronoi Grid) were applied to build a relatively small and simple model that considers all the required physics of the problem. The estimated reservoir properties from petrophysical analysis were validated against P&RTA thus honoring the near wellbore effects. The resulting model permitted the generation of key field development strategies considering additional well placement and completion technologies and best production operational practices, as well as the characterization of major uncertainties related with the reservoir-well system.
As a result of this application, prediction forecasts in comparison with the base case scenario for all formations showed that optimal production and development strategy results in 16.47 % reduction of water produced, with a simultaneous 13.2 % increase in overall oil recovery and 10 % project profitability. A series of recommendations were also derived including: (i) a data acquisition plan to minimize the impact of uncertainties in the field development plan, (ii) guidelines for generating a more reliable and economically profitable field development plan and (iii) opportunities visualization to improve and enhance oil recovery by conducting by water, gas and polymer injection.