An iterative workflow introduced to model complex heterogeneous reservoirs: an example from NEAG-2 Field, north Western Desert, Egypt

The challenge in modeling complex-heterogeneous reservoirs is to accurately represent dimensions, trends, and quality for each facies type and to avoid overestimating or underestimating the reservoir elements. NEAG-2 Field has a highly heterogeneous reservoir system of the Albian-Cenomanian age; it is the main reservoir system in the East Abu Gharadig Basin, and it is the main oil contributor in the north Western Desert of Egypt. Therefore, developing a water-tight model for such a complex system can act as an analog for any similar complex-heterogenous system worldwide. In the NEAG-2 Field, a representative reservoir model and dynamic simulation for its reservoir are required to restore the field’s production. The field has an excellent yet unique performance, and it recorded an average production rate of 9000 bbl/d from five producer wells in 2018. Since that peak, production has been declining, with a current total of 1390 bbl/d from four wells. This production behavior was not modeled nor predicted in the previous modeling trials. Therefore, we introduce a mature model to improve production forecasts and optimize recovery while giving an example of how the complex heterogeneous reservoirs should be properly modeled. An object-based geostatistical algorithm was applied in modeling the reservoir facies, and a truncated Gaussian algorithm was applied for the background (non-reservoir) facies. The property models were distributed using Gaussian simulation algorithms, with the guidance of variogram analysis. Three reservoir facies were distinguished, with specific geometry, orientation, and porosity–permeability characteristics to model their flow behavior. The highest-quality facies (type 1) were tidal channels, followed by moderate-quality (type 2) tidal sand bars, which had smaller lateral dimensions compared to the channels. The lowest quality sand facies (type 3) were embodied as mixed tidal flats. Each facies body, reservoir zone, and field segment was modeled distinctly to ensure a representative statistical range for each. The integrated workflow developed a flow-unit-based model that preserved the reservoir heterogeneity and fluid flow complexity, which improved the forecasting for reviving the field production. The final results of this static model were validated by the production data and the history matching of each well.