Modeling production in hydraulically fractured wells with a reservoir simulator

1. Modeling production in hydraulically fractured wells with a reservoir simulator Presented By Wuimin Chang 4/24/2007

2. Content Introduction Background Method Analytical Comparison History matching Results Conclusion

3. Introduction We use commercially available numerical modeling software to model the hydraulically fractured well. Parameters were input into the numerical model (base model). The base model parameters were changed to match the actual history production of a well. The new model is termed �modified�. This �modified� model will have the new geometry of the fracture; and parameters of the reservoirs. The model can be used to generate production forecasts that are necessary for economic analysis.

4. Background The area of research: Bowdoin Field which is located at the Northern Great Plain of the biogenic gas province. These province covers: the eastern margin of Williston Basin in Montana, the sourthern margin of the Aberta basin in Alberta and Saskatchewan, the northern portion of the Powder river Basin in Southern Montana Biogenic gas is natural gas that generated by microbe at a depth generally less than 2,000 feet

5. Background

6. Background

7. Background

8. Background Gas reserves in Bowdoin field are found in �unconventional� reservoirs Which are shallow, low permeability, low formation pressure. The formation is consisting thin lamina of shaly sand, limestone and siltstone that producing natural gas (methane) that interbedded with the shale which acts as seal The wells there have to be be hydraulically fractured in order to producing gas economically. It is common that initial production rate of a wells is 100 to 200 MCFD, and declines to about 50 MCFD within a year.

9. Background Four Bowdoin Field shallow gas wells were selected for facture modeling and production history matching. All four wells are located in the East Loring area. The well names and the formation tops are given below:

10. Background

11. Method Numerical modeling program: Eclipse 2005A We built a base model of single-well reservoir that contain fractures, then modified the model to match the history production of a well. The model are built to accommodate several productive zones and fractures that contain properties (e.g. Permeability, porosity, height, length, conductivity, etc). Properties of the reservoir and the fractures are modified regularly until it matched the actual production. Once the matching is done, the production proportion on each fracture in a well is checked (spinner surveys) Once the matching is achieved, The model will be use to analyze other nearby wells with slight modification

12. Method In the simulator, the fractures are modeled as a discrete connection of notes (DCN). It is a third type of object that interacts with both the well and the gridded reservoir. From the commercial simulator standpoint, the well and the fracture are modeled as �wells�, so no additional code or add-ons to the simulator are required. A �well� is simply connected nodes that are in pressure communication and interacted with surrounding gridblocks Friction factor can be applied to the �wells� which is related to the permeability based on the variant of the Carmen-Kozeny equation

13. Method Model fracture as a �well� Doesn�t produce to surface Allows cross flow to occur 2D plane of connected nodes

14. Well Flow vs. Fracture Flow Flow from reservoir to fracture Flow from fracture to well In a simulator, we control the flow using: Well Productivity Index (PI) Multiplier Well � radial flow Fracture � linear flow WPIfrac = 25 * DZ / DY Flow inside the fracture In a simulator, limit the flow in fracture by changing the diameter of the fracture Wellbore Friction Factor (WFF) Well � pipe flow Fracture � darcy flow ~ kf kf = 1.18x109 * ff * Dp2

15. Analytical Comparison Single phase homogeneous flow FOI vs fracture permeability term

16. Analytical Comparison Three lines correspond to three fracture lengths (xf / re = 0.7, 0.4, and 0.2) Line � Analytical Dots � Simulation

17. SpectraScan Image Log(Tracer Treated Proppant)

18. History Matching

19. History Matching

20. SpectraScan Image Log(Tracer Treated Proppant)

21. History Matching

22. History Matching

24. History Matching

25. History Matching

27. History Matching

28. History Matching

29. History Matching

30. History Matching

31. Results

32. Results

33. Results

34. Results

35. Results

36. Conclusion It is feasible to use the discrete connection of notes (DCN) to model fractures Simulator model is able to capture complex fracture geometry & configuration of multiple fractures Simulator model replicate historical production data and predict future production response. Simulator model capture heterogeneous reservoir properties

37. Future work Compare the fracture geometries with other analytical methods: GDK, PKN model Possible permeability and porosity value changes in Reservoir using sgems Larger scale fracture modeling (between wells)

38. Acknowledgements Dr. Todd Hoffman John G. Evans Ryan Ciolkosz Terry Streit

39. Thank you