3D model is a valuable tool in reservoir management, provided its representativeness of reservoir dynamics.Traditional History Match mainly focuses on reproducing reservoir behavior at well scale. A good match is not always representative of fluid movements in the reservoir. The proposed approach for 3D model validation combines and compares the results of integrated production analysis, in particular flow paths identification, with history matching by using streamlines technology. Streamlines speed up the comparison process especially in complex 3D models.
The workflow is based on a massive Production Data Analysis (PDA) where geological and dynamic data are integrated to identify preferential paths followed by the different fluid phases during the producing life of the field. The main result is the Fluid Path Conceptual Model (FPCM) where aquifer and injected water movements are clearly identified. Once the flooded areas are detected, streamlines are traced on the history matched model in order to easily compare the simulated connections with hard information from PDA. Actions to improve the model representativeness are suggested and integrated in an iterative tuning process.
This paper presents the results of the methodology applied on two complex fields with different injection strategies. FPCMs resulting from PDA provided a powerful boost to drive the history match and speed up the whole process. Priority was given in reproducing the identified preferential paths rather than to perfectly match well production data (which can be also affected by allocation uncertainties) by means of local unrealistic adjustments.
Streamlines were run on Intersect simulation, proving to be a fast and powerful tool for the visualization and understanding of fluid movements in the 3D Model. Since streamlines are used as visualization tool and are traced on a corner point geometry grid using fluxes provided by reservoir simulation, the reliability of the simulation output is preserved.
Once the model is representative of the real field behavior, it can be used as predictive tool in Reservoir Management to optimize the current injection strategy, promoting most efficient injectors.
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