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Hydraulic fracturing: New uncertainty based modeling approach for process design using Monte Carlo simulation technique

Author

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  • Awad Ahmed Quosay
  • Dariusz Knez
  • Jan Ziaja

Abstract

Hydraulic fracturing is a key method used in completion of shale gas wells as well as in well stimulation. There are a lot of factors affecting the hydraulic fracturing treatment; i.e. formation in-situ stresses, fracturing fluid properties, proppant, pumping rate, reservoir fluid and rock properties…etc. For predictive modeling, these factors are associated with a lot of uncertainties, since most of them are laboratory measured, calculated or subjectively estimated. Moreover, the precise contribution of each factor on the final fracturing result is unknown for each individual case. Therefore, for better treatment performance and in order to find the best range of designing parameters, a hydraulic fracturing predictive model that involves these uncertainties is required specially for newly exploited shale gas reservoir. In this paper a new uncertainty-based approach is described for hydraulic fracturing processes. It is based on assigning probability distribution for some variables and parameters used in the designing process. These probability distributions are used as input data for analytical equations that describe the fracturing processes. Monte Carlo Simulation technique is used to apply uncertainty-based values on the designing analytical formulas. A hypothetical hydraulic fracturing example is used to simulate the effect of different variables and designing parameters on the entire fracturing process. The simulation results are illustrated into probability distribution curves and variance-based sensitivity analysis is performed to assess the contribution and the correlation between different variables and outcomes. Fracture geometry is almost controlled by the injection fluid’s viscosity, in case of constant injection rate; while rock properties have insignificant effect on the fracture width compares to fracturing fluid’s effect. Therefore more emphases shall be directed to rheological modeling of the fracturing fluid. It is found also that fracture height, which is difficult to be estimated, is the most crucial parameter in the calculation of treatment size or the injected fluid’s volume. Proppant porosity, injected fluid viscosity and formation strength are slightly affecting propped fracture width, while proppant final concentration plays the main role of determining the calculated propped fracture width. It is observed from the simulation results that the initial formation permeability will extremely affect the post fracturing skin factor while other formation rock properties have almost no effect on the skin factor. Throughout the implementation of the uncertainty-based modeling approach for hydraulic fracturing process design, it is found that uncertainties in the value of many variables and parameters are slightly affecting the process outcomes. However, injected fluid viscosity, shale formation permeability and proppant final concentration are found to be the most influencing factors in the entire process. Therefore, it is highly recommended to perform in-depth study for these factors prior conducting any designing process of hydraulic fracturing.

Suggested Citation

  • Awad Ahmed Quosay & Dariusz Knez & Jan Ziaja, 2020. "Hydraulic fracturing: New uncertainty based modeling approach for process design using Monte Carlo simulation technique," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-18, July.
  • Handle: RePEc:plo:pone00:0236726
    DOI: 10.1371/journal.pone.0236726
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    Citations

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    Cited by:

    1. Dariusz Knez & Mohammad Ahmad Mahmoudi Zamani, 2021. "A Review of the Geomechanics Aspects in Space Exploration," Energies, MDPI, vol. 14(22), pages 1-21, November.
    2. Herimitsinjo Rajaoalison & Dariusz Knez & Mohammad Ahmad Mahmoudi Zamani, 2022. "A Multidisciplinary Approach to Evaluate the Environmental Impacts of Hydrocarbon Production in Khuzestan Province, Iran," Energies, MDPI, vol. 15(22), pages 1-19, November.
    3. Dariusz Knez & Mohammad Ahmad Mahmoudi Zamani, 2021. "Empirical Formula for Dynamic Biot Coefficient of Sandstone Samples from South-West of Poland," Energies, MDPI, vol. 14(17), pages 1-17, September.
    4. Honghua Song & Yixin Zhao & Yaodong Jiang & Weisheng Du, 2020. "Experimental Investigation on the Tensile Strength of Coal: Consideration of the Specimen Size and Water Content," Energies, MDPI, vol. 13(24), pages 1-18, December.
    5. Mitra Khalilidermani & Dariusz Knez & Mohammad Ahmad Mahmoudi Zamani, 2021. "Empirical Correlations between the Hydraulic Properties Obtained from the Geoelectrical Methods and Water Well Data of Arak Aquifer," Energies, MDPI, vol. 14(17), pages 1-19, August.
    6. Mohammad Ahmad Mahmoudi Zamani & Dariusz Knez, 2023. "Experimental Investigation on the Relationship between Biot’s Coefficient and Hydrostatic Stress for Enhanced Oil Recovery Projects," Energies, MDPI, vol. 16(13), pages 1-13, June.
    7. Mohammad Ahmad Mahmoudi Zamani & Dariusz Knez, 2021. "A New Mechanical-Hydrodynamic Safety Factor Index for Sand Production Prediction," Energies, MDPI, vol. 14(11), pages 1-14, May.
    8. Ion Pană & Iuliana Veronica Gheţiu & Ioana Gabriela Stan & Florinel Dinu & Gheorghe Brănoiu & Silvian Suditu, 2022. "The Use of Hydraulic Fracturing in Stimulation of the Oil and Gas Wells in Romania," Sustainability, MDPI, vol. 14(9), pages 1-33, May.
    9. Stefan Zelenak & Erika Skvarekova & Andrea Senova & Gabriel Wittenberger, 2021. "The Usage of UCG Technology as Alternative to Reach Low-Carbon Energy," Energies, MDPI, vol. 14(13), pages 1-15, June.

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