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A Data-Enable Method for Marcellus Shale Gas Production Data Analysis

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Proceedings of the International Field Exploration and Development Conference 2021 (IFEDC 2021)

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Abstract

Recently shale gas plays have dominated the onshore U.S. natural gas drilling activity with this boom occurring during a time of economic uncertainty. However, skepticism has recently been placed on shale gas production decline trends from consultants and investment firms, where assessing reservoir properties and well productivity of shale plays have been brought into an important place. This paper seeks to find a more accurate methodology on assessing reservoir properties and well productivity of dry shale gas in Marcellus. Based on reservoir properties, an assumption is presented that shale’s thickness and pleasant point’s thickness may be key factors which effect well productivity. A data-enable method which collects hundreds of thousands well’s production data is presented in this article. By dividing Susquehanna into six regions and dividing all wells into three types well group, it was founded that well productivity is mainly affected by shale’s thickness rather than the thickness of point pleasant. Finally, production decline curve has been divided into two periods: rapid decline period with conquered by linear flow in fracture network, and persistent producing period with affected by controlling radius and half-length of fracture. The effects of major parameters on production decline curves are analyzed by using the proposed model and it was found that different parameters have their own influence period and sensitivity intensity. The results of this methodology help engineer easily find which area could be productive in Susquehanna shale plays, or if a better methodology may exist.

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References

  1. Milici, R.C., Swezey, C.S.: Assessment of Appalachian Basin oil and gas resources: Devonian gas shales of the Devonian shale-middle and upper Paleozoic total petroleum system. USGS Professional Paper, vol. 1708, p. 87 (2014)

    Google Scholar 

  2. Carr, T.R., Wang, G., McClain, T.: Petrophysical analysis and sequence stratigraphy of the Utica shale and Marcellus shale, Appalachian Basin, USA. In: IPTC 2013 International Petroleum Technology Conference (2013)

    Google Scholar 

  3. Soeder, D.J.: Porosity and permeability of Eastern Devonian gas shale. SPE Form. Eval. 3(01), 116–124 (1988)

    Article  Google Scholar 

  4. Ward, J.: Kerogen density in the Marcellus shale. In: SPE Unconventional Gas Conference, no. February, pp. 23–25 (2010)

    Google Scholar 

  5. Bruner, K.R., Smosna, R.: A comparative study of the Mississippian Barnett shale, Fort Worth Basin, and Devonian Marcellus shale, Appalachian Basin. US DoE Report, p. 118 (2011)

    Google Scholar 

  6. U. S. E. I. Administration: Annual Energy outlook 2012. An Annual Public United States Department Energy, p. 239 (2012)

    Google Scholar 

  7. Van Cauter, F.: Department of earth science and engineering predicting decline in unconventional reservoirs using analytical and empirical methods by, no. September (2013)

    Google Scholar 

  8. Engineers, P.E.P., Spe, W.: Generalized Hyperbolic Equation S. Ramsey Engineering Inc., Robertson (1988)

    Google Scholar 

  9. Ilk, D., Perego, A.D., Rushing, J.A., Blasingame, T.A.: Exponential vs. hyperbolic decline in tight gas sands — understanding the origin and implications for reserve estimates using Arps’ decline curves. SPE116731 (2008)

    Google Scholar 

  10. Duong, A.N.: Rate-decline analysis for fracture-dominated shale reservoirs. SPE Reserv. Eval. Eng. 14(03), 377–387 (2011)

    Article  Google Scholar 

  11. Kanfar, M.S., Wattenbarger, R.A.: SPE 162648 comparison of empirical decline curve methods for shale wells, no. November, pp. 1–12 (2012)

    Google Scholar 

  12. Joshi, K., Lee, J.: SPE 163870 comparison of various deterministic forecasting techniques in shale gas reservoirs, pp. 1–12 (2013)

    Google Scholar 

  13. Ozkan, E., Raghavan, R., Retd, C., et al.: Modeling of fluid transfer from shale matrix to fracture network. SPE Annu. 18 (2010)

    Google Scholar 

  14. Sang, Y.: A new mathematical model considering adsorption and desorption process for productivity prediction of volume fractured horizontal wells in shale gas reservoirs. J. Nat. Gas Sci. Eng. 19, 228–236 (2014)

    Article  Google Scholar 

  15. Guo, J., Zhang, L., Zhu, Q.: A quadruple-porosity model for transient production analysis of multiple-fractured horizontal wells in shale gas reservoirs. Environ. Earth Sci. 73(10), 5917–5931 (2015). https://doi.org/10.1007/s12665-015-4368-9

    Article  Google Scholar 

  16. Deng, Q., Nie, R.S., Jia, Y.L., et al.: A new analytical model for non-uniformly distributed multi-fractured system in shale gas reservoirs. J. Nat. Gas Sci. Eng. 27, 719–737 (2015)

    Article  Google Scholar 

  17. Zhao, Y.L., Zhang, L.H., Luo, J.X., et al.: Performance of fractured horizontal well with stimulated reservoir volume in unconventional gas reservoir. J. Hydrol. 512, 447–456 (2014)

    Article  Google Scholar 

  18. Wang, H.T.: Performance of multiple fractured horizontal wells in shale gas reservoirs with consideration of multiple mechanisms. J. Hydrol. 510, 299–312 (2014)

    Article  Google Scholar 

  19. Su, Y., Zhang, Q., Wang, W., et al.: Performance analysis of a composite dual-porosity model in multi-scale fractured shale reservoir. J. Nat. Gas Sci. Eng. 26, 1107–1118 (2015)

    Article  Google Scholar 

  20. Lu, T., Li, Z., Lai, F., et al.: Blasingame decline analysis for variable rate/variable pressure drop: a multiple fractured horizontal well case in shale gas reservoirs. J. Pet. Sci. Eng. 178, 193–204 (2019)

    Article  Google Scholar 

  21. Lu, T., Liu, S., Li, Z.: A new approach to model shale gas production behavior by considering coupled multiple flow mechanisms for multiple fractured horizontal well. Fuel 237, 283–297 (2019)

    Article  Google Scholar 

  22. Armstrong, B.L., Park, S.: Sustainable development and design of Marcellus shale play in Susquenanna PA, 149 (2009)

    Google Scholar 

  23. Van Everdingen, A.F., Hurst, W.: The application of the Laplace transformation to flow problems in reservoirs. J. Pet. Technol. 1(12), 305–324 (1949)

    Article  Google Scholar 

  24. Kikani, J., Pedrosa, O.A., Jr.: Perturbation analysis of stress-sensitive reservoirs. SPE Form. Eval. 6(03), 379–386 (1992)

    Article  Google Scholar 

  25. Ozkan, E., Raghavan, R., Apaydin, O.G.: Modeling of fluid transfer from shale matrix to fracture network. In: SPE Annual Technical Conference and Exhibition, p. SPE 134830 (2010)

    Google Scholar 

  26. Kucuk, F., Ayestaran, L.: Analysis of simultaneously measured pressure and sanface flow rate in transient well testing. Soc. Pet. Eng. 37(2), 323–334 (1985)

    Google Scholar 

  27. Von Schroeter, T., Gringarten, A.C.: Superposition principle and reciprocity for pressure transient analysis of data from interfering wells. SPE J. 14(3), 488–495 (2009)

    Article  Google Scholar 

  28. Van Everdingen, A.F.: The skin effect and its influence on the productive capacity of a well. J. Pet. Technol. 5(06), 171–176 (1953)

    Article  Google Scholar 

  29. Clarkson, C.R.: Production data analysis of unconventional gas wells: review of theory and best practices. Int. J. Coal Geol. 109–110, 101–146 (2013)

    Article  Google Scholar 

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Acknowledgements

This article is supported by National Science and Technology Major Project, China (Grant NO. 2016ZX05061) and the Study on Formation Characteristics and Stable Production Technology of Shale Gas and Oil (Grant NO. KL19037) which are gratefully acknowledged.

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Correspondence to Ting Lu .

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Lu, T. et al. (2022). A Data-Enable Method for Marcellus Shale Gas Production Data Analysis. In: Lin, J. (eds) Proceedings of the International Field Exploration and Development Conference 2021. IFEDC 2021. Springer Series in Geomechanics and Geoengineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-2149-0_448

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