1887
Volume 36 Number 9
  • ISSN: 0263-5046
  • E-ISSN: 1365-2397

Abstract

Abstract

The appropriateness of hydraulic fracture stimulation designs can have a significant impact on stimulation effectiveness and the potential productivity of a reservoir. Frac model designs are based on an integration of static (formation geology, velocity structure) and dynamic (bottomhole flowing pressure-normalized oil and gas production, Diagnostic Fracture Injection Testing (DFIT)) data streams. Further constraint on model development can be provided by including additional parameters recorded either prior to or during stimulations. In this regard microseismic monitoring has long been considered as a tool to provide insight into the nature of the stimulation and the effectiveness in developing a well-connected fracture network capable of flow.

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2018-09-01
2024-03-28
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References

  1. Aki, K. and Richards, P.G.
    [2002]. Quantitative Seismology. Second Ed., University Science Books, Mill Valley, California.
    [Google Scholar]
  2. Ardakani, E., Baig, A., Urbancic, T. and Bosman, K.
    [2018]. Microseis-micity-derived fracture network characterization of unconventional reservoirs by topology.Interpretation, 6(2), SE49–SE61. https://doi.org/10.1190/INT-2017-0172.1
    [Google Scholar]
  3. Bour, O. and Davy, P.
    [1997]. Connectivity of random fault networks following a power law fault length distribution.Water Resources Research, 33 (7), 1567–1583. doi: 10.1029/97WR00433.
    https://doi.org/10.1029/97WR00433 [Google Scholar]
  4. Gutenberg, B. and Richter, C.F.
    [1944]. Frequency of earthquakes in California.Bulletin of the Seismological Society of America, 34, 185– 188.
    [Google Scholar]
  5. Ilgen, A.G., Heath, J.E., Akkutlu, I.Y., Bryndzia, L.T., Cole, D.R., Kharaka, Y.K., Kneafsey, T.J., Milliken, K.L., Pyrak-Nolte, L.J. and Suarez-Rivera, R.
    [2017]. Shales at all scales: Exploring coupled processes in mudrocks.Earth Science Reviews, 166, 132–152. https://doi.org/10.1016/j.earscirev.2016.12.013.
    [Google Scholar]
  6. Kagan, Y.Y.
    [2002]. Seismic moment distribution revisited: I. Statistical results.Geophysical Journal International, 148, 520–541. https://doi.org/10.1046/j.1365-246x.2002.01594.x.
    [Google Scholar]
  7. Kostrov, B.V. and Das, S.
    [1988]. Principles of Earthquake Source Mechanics.Cambridge University Press, Cambridge, UK.
    [Google Scholar]
  8. Kwiatek, G., Plenkers, K., Dresen, G.
    and JAGUARS Research Group [2011] Source parameters of picoseismicity recorded at Mponeng deep gold mine, South Africa: Implications for scaling relations.Bulletin of the Seismological Society of America, 101 (6), 2592–2608. https://doi.org/10.1785/0120110094.
    [Google Scholar]
  9. Madariaga, R.
    [1976] Dynamics of an expanding circular fault.Bulletin of the Seismological Society of America, 66 (3), 639–666.
    [Google Scholar]
  10. Odling, N.E., Gillespie, P., Bourgine, B., Castaing, C., Chiles, J.P., Christensen, N.P., Fillion, E., Genter, A., Olsen, C., Thrane, L., Trice, R., Aarseth, E., Walsh, J.J. and Watterson, J.
    [1999]. Variations in fracture system geometry and their implications for fluid flow in fractures hydrocarbon reservoirs.Petroleum Geoscience, 5, 373–384. https://doi.org/10.1144/petgeo.5.4.373.
    [Google Scholar]
  11. OzkanE., BrownM., RaghavanR., and Kazemi, H.
    [2009]. Comparison of Fractured Horizontal-Well Performance in Conventional and Unconventional Reservoirs.Paper SPE 121290 presented at SPE Western Regional Meeting, San Jose, California, 24–26 March.https://doi.org/10.2118/121290-MS.
    [Google Scholar]
  12. Shearer, P.M.
    [2009]. Introduction to Seismology. Second Ed, Cambridge University Press, Cambridge, UK.
    [Google Scholar]
  13. Stalgorova, E. and Mattar, L.
    [2012a]. Practical Analytical Model to Simulate Production of Horizontal Wells with Branch Fractures. Paper SPE 162515 presented at the SPE Canadian Unconventional Resources Conference, Calgary, Alberta, 30 October–1 November. https://doi.org/10.2118/162515-MS.
    [Google Scholar]
  14. [2012b]. Analytical Model for History Matching and Forecasting Production in Multifrac Composite Systems.Paper SPE 162516 presented at the SPE Canadian Unconventional Resources Conference, Calgary, Alberta, 30 October–1 November. https://doi.org/10.2118/162516-PA.
    [Google Scholar]
  15. Urbancic, T., Smith-Boughner, L., Crowley, J.W., Viegas, G., Baig, A. and von Lunen, E.
    [2015]. Characterizing the Dynamic Growth of a Fracture Network, Paper URTEC-2154641 in Proceedings of the Unconventional Resources Technology Conference, San Antonio, Texas, 20–22 July. doi: 10.15530/URTEC‑2015‑2154641.
    https://doi.org/10.15530/URTEC-2015-2154641 [Google Scholar]
  16. Urbancic, T., Baig, A., Viegas, G., Thompson, J.M., Anderson, D., Rice, C. and Martin, L.
    [2017]. Effective Constraint of RTA Models Utilizing Microseismicity Derived Flow Attributes.Proceedings of the Unconventional Resources Technology Conference, doi: 10.15530/urtec‑2017‑2689356.
    https://doi.org/10.15530/urtec-2017-2689356 [Google Scholar]
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