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Hydraulic fracturing optimization framework based on PKN and Cinco-Ley methods

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In an era of decreasing number of discoveries of conventional hydrocarbon reservoirs, in the global oil and gas industry we can observe growing interest in unconventional resources. Conducting effective production from this type of reservoirs is associated with carrying out the intensification processes of production, among which hydraulic fracturing is the most popular. Fracturing project design consist of several technological parameters, i.e. the type of fracturing fluid and quantity of proppant, which have a direct impact on the process effectiveness. The actual shape of the fracture is difficult to predict due to the local heterogeneity of the reservoir and the superposition of the phenomena occurring during stimulation treatment. In this paper optimization model was proposed, which allows for selection appropriate parameters of fracturing technology. Developed optimization algorithm is based on two-dimensional PKN fracture model and Cinco-Ley analytical method. Optimization method used in this paper based on nature - inspired algorithms which were compared with gradient method.
Rocznik
Strony
157--167
Opis fizyczny
Bibliogr. 15 poz., tab., wykr.
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Drilling, Oil and Gas, Krakow, Poland
autor
  • AGH University of Science and Technology, Faculty of Drilling, Oil and Gas, Krakow, Poland
autor
  • AGH University of Science and Technology, Faculty of Drilling, Oil and Gas, Krakow, Poland
  • AGH University of Science and Technology, Faculty of Drilling, Oil and Gas, Krakow, Poland
Bibliografia
  • [1] Economides M.J.: A Practical Companion to Reservoir Stimulation. Elsevier, Leoben, 1992.
  • [2] Economides M.J., Hill A.D., Ehlig-Economides C., Zhu D.: Petroleum Production Systems, 2nd ed. Prentice Hall, New Jersey 2012.
  • [3] Economides M.J., Nolte K.G.: Reservoir Stimulation, 3rd ed. John Wiley & Sons, New York 2000.
  • [4] Eberhart R., Kennedy J.: A new optimizer using particle swarm theory, in: Micro Machine and Human Science, MHS ’95, Proceedings of the Sixth International Symposium on, 1995, pp. 39-43.
  • [5] Floreano D., Mattiussi C.: Bio-inspired artificial intelligence: theories, methods, and technologies. MIT Press, 2008.
  • [6] Guo B., Lyons W.C., Ghalambor A.: Petroleum Production Engineering. Elsevier Science & Technology Books, 2007.
  • [7] Mirjalili S., Mirjalili S.M., Lewis A.: Grey Wolf Optimizer. Advances in Engineering Software, 69, 2014, pp. 46–61, ISSN 0965-9978.
  • [8] Muro C., Escobedo R., Spector L., Coppinger R.: Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations. Behavioural Processes, 88 (3), 2011, pp. 192–197, ISSN 0376-6357.
  • [9] Nordgen R.P.: Propagation of a vertical hydraulic fracture. SPE Journal, August 1972.
  • [10] Perkins T.K., Kern L.R.: Widths of Hydraulic Fractures. JPT, September 1961.
  • [11] Stopa J., Janiga D., Wojnarowski P., Czarnota R.: Optimization of well placement and control to maximize CO2 trapping during geologic sequestration. AGH Drilling, Oil, Gas, vol. 33, No. 1, 2016, pp. 93–104.
  • [12] Sun J., Gamboa E.S., Schechter D., Rui Z.: An integrated workflow for characterization and simulation of complex fracture networks utilizing microseismic and horizontal core data. Journal of Natural Gas Science and Engineering, 34, 2016, pp. 1347-1360.
  • [13] Valko P., Economides M.J.: Hydraulic Fracture Mechanics. John Wiley & Sons, New York 1997.
  • [14] Wojnarowski P.: Metody modelowania i oceny efektywności zabiegów szczelinowania hydraulicznego skał złożowych w odwiertach naftowych. Wydawnictwa AGH, Kraków 2013.
  • [15] Zhang J., Kamenov A., Zhu D., Hill A.D.: Laboratory Measurement of Hydraulic Fracture Conductivities in the Barnett Shale. International Petroleum Technology Conference, Texas A&M University, 2013.
Uwagi
EN
Paper prepared within the statutory research program of the Faculty of Drilling, Oil and Gas, AGH University of Science and Technology No. 11.11.190.555
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8257a2b6-8bd3-4011-acd7-7646d3c7056b
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