2010 SPWLA Topical Conference

1. 2010 SPWLA Topical Conference Integration of Reservoir Rock Types in Simulation Models Shawket Ghedan, PhD Petroleum Institute Integration of RRTs in Sim Models

2. Development and Identification of RRTs Reservoir Rock Types, RTTs developed by integrating: • Petrophysical Lab data, • Pore system information, and • Capillary Pressure Data. RRTs can be identified by the following parameters: • Rock Fabric: texture, grain size, packing & pore geometry • Proportion of primary porosity and secondary porosity. • Porosity/ permeability relationships • Range of, and similarity in pore throat size distribution, • Similar Pc curves and saturation end points. Integration of RRTs in Sim Models

3. RRTs in Static and Dynamic Models Static RRTs are routinely employed for: • Modeling of reservoir petrophysical attributes, as well as • Building & assigning the required water/ oil and Gas/ oil Kr curves to the different cells of the simulation models. There is a problem with the second application: • Static RRT schemes do not consider the reservoir multiphase flow properties of wettability, fluids IT, etc… Integration of RRTs in Sim Models

4. Static vs Kr-Defined RRTs • Hamon introduced the Kr-defined rock types (SPE 84035, 2003 ATCE). • Definition of Kr-Defined Rock Types: • Kr-defined rock types are defined as units of rock characterized by similar ranges of pore geometry and wettability indicators resulting in a unique relative permeability saturation relationships. Integration of RRTs in Sim Models

5. Kr-Defined RRTs or Dynamic RRTs • For the same saturation history cycle in a reservoir, the rock multiphase flow properties would only be a function of wettability only for any static RRT. • In a reservoir with a wettability profile, each RRT would have many Wettability Driven Dynamic RRTs. • Therefore, imposing the effect of reservoir wettability on the RRTs is essential in developing and assigning the Kr curves to the cells of simulation models. • Each would have unique relative permeability curves and saturation endpoints. Integration of RRTs in Sim Models

6. USBM WI vs Depth from Well A of Hawiyah area SPE 105114 SPE 105114 Integration of RRTs in Sim Models

7. USBM WI versus Depth from Well B of Hawiyah area SPE 105114 SPE 105114 Integration of RRTs in Sim Models

8. USBM WI versus Depth for Uthmaniyah area SPE 105114 Integration of RRTs in Sim Models

9. Reservoir Wettability Profile • Wells perforations Producers down to X000 ftssInjectors up to X150 ftss • WettabilityOil Wet at Top structure Water Wet Below DOL. Integration of RRTs in Sim Models

10. Transition Zone? • Transition zones in Carbonate reservoirs could be fairly thick. depending on reservoir characteristics. • Transition zone is conventionally defined as that part of the reservoir where water saturation start to deviate from irreducible saturation down to 100% saturation. Integration of RRTs in Sim Models

11. Dry Oil Limit 300 oil producers, screened to identify • Deepest perforations of dry oil producers, and • Static RRTs of their producing layers. From Which Identified the Dry Oil Limit of the reservoir RRTs. Integration of RRTs in Sim Models

12. Alternative Definition of TZ • DOL for any rock type was found to be always appreciably deeper than the top of the conventional transition zone. • The difference depends on the rock types encountered and profile of rock wettability changes. • Transition zone is better defined as the reservoir part where both phases of oil and water are mobile. Integration of RRTs in Sim Models

13. Requirements of Saturation Tables • Log-derived W/O Pc curves. • Swirr at top of structure, Swc at Dry Oil Limit Integration of RRTs in Sim Models

14. History Matching of Available Exp Kr Data • Use Corey Model for history matching • For various RTs determined No and Nw with Depth Integration of RRTs in Sim Models

15. History matching of Available Exp Data • Exp Kr data for RT1 • No and Nw variation with Depth Integration of RRTs in Sim Models

16. Variation of Corey Exponents Poorer RTsIncreasing DepthPorosityNo Increase Decrease ConstantNw Increase Increase Constant No = (2.8 to 5.0) Nw = (1.3 to 2.6) Integration of RRTs in Sim Models

17. Correlation of Sorw vs. Swi or Swc Integration of RRTs in Sim Models

18. Effect of Wettability on Krwmax and Sorw It is well established that Sorw as well as Krwmax at Sorw would be lower for more water wet rock. From Dave Bowen of Core Lab Integration of RRTs in Sim Models

19. Krwmax versus Sorw The available data did not yield clear relationship between Krw(Sorw) Vs Sorw But a straight line relationship was forced that fits the general trend of the data. Integration of RRTs in Sim Models

20. Number of DRRTs Per Static RRT The number of DRRTs generated per each SRRT is decided by the number of the Sw increment employed to go from Swirr down to Swc at the DOL of each drainage Pc curve of each static RRT. For instance, using a 5% Sw increment with seven maximum steps would produce up to 21 DRRTs (Kr sets) for each static RRT. Integration of RRTs in Sim Models

21. Generation of DRRTs (Kr Curves) 1. For each depth, Swc is picked from any drainage Pc curve, ranging from Swirr up to Swc at DOL, then: 2. Use Swc to determine Sorw from the proposed correlations, similar to Land correlation 3. Use depth and rock type to determine Corey’s exponents, Nw and No, using a table look up. 4. Use Sorw to determine Krwmax from the proposed correlation (Kromax is taken as 1.0): Integration of RRTs in Sim Models

22. Generation of Kr Curves 5. Use the Corey Krw and Kro models to determine Krw and Kro for any water saturation between any Swc and its Sorw. Integration of RRTs in Sim Models

23. Generation of Kr Curves Set of Kr curves for Limestone RRT 4 of 15% porosity. Integration of RRTs in Sim Models

24. 2010 SPWLA Topical Conference ? Integration of RRTs in Sim Models