Skip to main content
Log in

Poromechanics of Fractured/Faulted Reservoirs During Fluid Injection Based on Continuum Damage Modeling and Machine Learning

  • Original Paper
  • Published:
Natural Resources Research Aims and scope Submit manuscript

Abstract

The reactivation of faults is governed by the variation of effective stresses in the fault’s plane. These effective stresses are dependent on the total stresses (solely related to the regional geological stresses and lithology) and pore pressure (strongly affected by rock properties, fluid content, and saturation conditions). Injecting fluids into a reservoir formation may change the distribution of pore pressures, which influences the effective stresses and may cause the reactivation of existing faults, which has a wide range of consequences. This study investigated the reactivation of preexisting faults due to fluid injection into hydrocarbon reservoirs at different pressures and temperatures. A 3D model containing a continuous normal fault that divides the domain into two compartments was used. A user-defined constitutive model based on continuum damage mechanics implemented as a Fortran subroutine to predict the behavior of fractured and faulted reservoirs was used. A parametric analysis was performed to examine the influence of geometric parameters, such as the fault dip angle, reservoir characteristics, and fluid injection parameters. A machine learning approach based on artificial neural networks (ANNs) is incorporated to predict the enhanced oil recovery using fluid injection. The results predicted by the ANN were further confirmed by numerical modeling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12

Similar content being viewed by others

Data availability

The datasets that support the illustrations and/or any other findings of this research are available from the corresponding author upon reasonable request.

References

  • Abbassi, F., Belhadj, T., Mistou, S., & Zghal, A. (2013). Parameter identification of a mechanical ductile damage using artificial neural networks in sheet metal forming. Materials and Design, 45, 605–615.

    Article  Google Scholar 

  • Anderson, E. M. (1905). The dynamics of faulting. Transactions of the Edinburgh Geological Society, 8(3), 387–402.

    Article  Google Scholar 

  • Barthwal, H., & van der Baan, M. (2020). Microseismicity observed in an underground mine: Source mechanisms and possible causes. Geomechanics for Energy and the Environment, 22, 100167.

    Article  Google Scholar 

  • Byerlee, J. (1978). Friction of rocks. Pure and applied geophysics, 116(4–5), 615–626.

    Article  Google Scholar 

  • Chanpura, R. (2001). Fault reactivation as a result of reservoir depletion. Georgia Institute of Technology.

    Google Scholar 

  • Chateau, X., & Dormieux, L. (2002). Micromechanics of saturated and unsaturated porous media. International Journal for Numerical and Analytical Methods in Geomechanics, 26(8), 831–844.

    Article  Google Scholar 

  • Dormieux, L., Kondo, D., & Ulm, F.-J. (2006). Microporomechanics. Wiley.

    Book  Google Scholar 

  • Fang, Z., & Khaksar, A. (2013). Role of Geomechanics in assessing the feasibility of CO2 sequestration in depleted hydrocarbon sandstone reservoirs. Rock Mechanics and Rock Engineering, 46(3), 479–497. https://doi.org/10.1007/s00603-013-0381-z

    Article  Google Scholar 

  • Ghatak, M. D., & Ghatak, A. (2018). Artificial neural network model to predict behavior of biogas production curve from mixed lignocellulosic co-substrates. Fuel, 232, 178–189.

    Article  Google Scholar 

  • Gheibi, S., Holt, R. M., & Vilarrasa, V. (2017). Effect of faults on stress path evolution during reservoir pressurization. International Journal of Greenhouse Gas Control, 63, 412–430.

    Article  Google Scholar 

  • Gheibi, S., Vilarrasa, V., & Holt, R. M. (2018). Numerical analysis of mixed-mode rupture propagation of faults in reservoir-caprock system in CO2 storage. International Journal of Greenhouse Gas Control, 71, 46–61.

    Article  Google Scholar 

  • Haddad, M., & Eichhubl, P. (2020). Poroelastic models for fault reactivation in response to concurrent injection and production in stacked reservoirs. Geomechanics for Energy and the Environment, 24, 100181.

    Article  Google Scholar 

  • Haug, C., Nüchter, J. A., & Henk, A. (2018). Assessment of geological factors potentially affecting production-induced seismicity in North German gas fields. Geomechanics for Energy and the Environment, 16, 15–31.

    Article  Google Scholar 

  • Karrech, A. (2013). Non-equilibrium thermodynamics for fully coupled thermal hydraulic mechanical chemical processes. Journal of the Mechanics and Physics of Solids, 61(3), 819–837.

    Article  Google Scholar 

  • Karrech, A., Poulet, T., & Regenauer-Lieb, K. (2012). A limit analysis approach to derive a thermodynamic damage potential for non-linear geomaterials. Philosophical Magazine, 92(28–30), 3439–3450. https://doi.org/10.1080/14786435.2012.687469

    Article  Google Scholar 

  • Karrech, A., Schrank, C., Freij-Ayoub, R., & Regenauer-Lieb, K. (2014). A multi-scaling approach to predict hydraulic damage of poromaterials. International Journal of Mechanical Sciences, 78, 1–7.

    Article  Google Scholar 

  • Karrech, A., Schrank, C., & Regenauer-Lieb, K. (2015). A parallel computing tool for large-scale simulation of massive fluid injection in thermo-poro-mechanical systems. Philosophical Magazine, 95(28–30), 3078–3102. https://doi.org/10.1080/14786435.2015.1067373

    Article  Google Scholar 

  • Langhi, L., Zhang, Y., Gartrell, A., Underschultz, J., & Dewhurst, D. (2010). Evaluating hydrocarbon trap integrity during fault reactivation using geomechanical three-dimensional modeling: An example from the Timor Sea Australia. AAPG Bulletin, 94(4), 567–591.

    Article  Google Scholar 

  • Leclère, H., & Calais, É. (2019). A parametric analysis of fault reactivation in the New Madrid seismic zone: The role of pore fluid overpressure. Journal of Geophysical Research: Solid Earth, 124(10), 10630–10648. https://doi.org/10.1029/2018JB017181

    Article  Google Scholar 

  • Lee, J., Min, K.-B., & Rutqvist, J. (2012). Probabilistic analysis of fracture reactivation associated with deep underground CO2 injection. Rock Mechanics and Rock Engineering, 46(4), 801–820.

    Article  Google Scholar 

  • Liu, H., Chan, C., Tontiwachwuthikul, P., & Idem, R. (2019). Analysis of CO2 equilibrium solubility of seven tertiary amine solvents using thermodynamic and ANN models. Fuel, 249, 61–72.

    Article  Google Scholar 

  • Mejia Sanchez, E. C., Rueda Cordero, J. A., & Roehl, D. (2020). Numerical simulation of three-dimensional fracture interaction. Computers and Geotechnics, 122, 103528.

    Article  Google Scholar 

  • Mori, T., & Tanaka, K. (1973). Average stress in matrix and average elastic energy of materials with misfitting inclusions. Acta metallurgica, 21(5), 571–574.

    Article  Google Scholar 

  • Morris, A., Ferrill, D. A., & Henderson, D. B. (1996). Slip-tendency analysis and fault reactivation. Geology, 24(3), 275–278.

    Article  Google Scholar 

  • Orlic, B., ter Heege, J., & Wassing, B. (2011). Assessing the integrity of fault-and top seals at CO 2 storage sites. Energy Procedia, 4, 4798–4805.

    Article  Google Scholar 

  • Otchere, D. A., Arbi Ganat, T. O., Gholami, R., & Ridha, S. (2021). Application of supervised machine learning paradigms in the prediction of petroleum reservoir properties: Comparative analysis of ANN and SVM models. Journal of Petroleum Science and Engineering, 200, 108182.

    Article  Google Scholar 

  • Rahrah, M., Lopez-Peña, L. A., Vermolen, F., & Meulenbroek, B. (2020). Network-inspired vs. Kozeny-Carman based permeability-porosity relations applied to Biot’s poroelasticity model. Journal of Mathematics in Industry, 10(1), 19. https://doi.org/10.1186/s13362-020-00087-z

    Article  Google Scholar 

  • Rutqvist, J. (2012). The geomechanics of CO2 storage in deep sedimentary formations. Geotechnical and Geological Engineering, 30(3), 525–551.

    Article  Google Scholar 

  • Rutqvist, J., Birkholzer, J., Cappa, F., & Tsang, C.-F. (2007). Estimating maximum sustainable injection pressure during geological sequestration of CO 2 using coupled fluid flow and geomechanical fault-slip analysis. Energy Conversion and Management, 48(6), 1798–1807.

    Article  Google Scholar 

  • Safari, M. R., Ghassemi, A. (2012). 3D modeling of natural fracture stimulation using a poroelastic displacement discontinuity method with slip weakening. In Paper presented at the Paper ARMA-2012-403, presented at 46th US Rock Mechanics/Geomechanics Symposium.

  • Safari, M. R., Trevor, O., Queena, C., Hamed, C., Blair, N., Uno, M., Hawkes, C. (2013). Effects of depletion/injection induced stress changes on natural fracture reactivation. In Paper presented at the Paper ARMA-2013–395, presented at 47th U.S. Rock Mechanics/Geomechanics Symposium.

  • Shayan Nasr, M., Shayan Nasr, H., Karimian, M., & Esmaeilnezhad, E. (2021). Application of artificial intelligence to predict enhanced oil recovery using silica nanofluids. Natural Resources Research, 30(3), 2529–2542.

    Article  Google Scholar 

  • Sircar, A., Yadav, K., Rayavarapu, K., Bist, N., & Oza, H. (2021). Application of machine learning and artificial intelligence in oil and gas industry. Petroleum Research, 6(4), 379–391.

    Article  Google Scholar 

  • Song, Y., Sung, W., Jang, Y., & Jung, W. (2020). Application of an artificial neural network in predicting the effectiveness of trapping mechanisms on CO2 sequestration in saline aquifers. International Journal of Greenhouse Gas Control, 98, 103042.

    Article  Google Scholar 

  • Streit, J. E., & Hillis, R. R. (2004). Estimating fault stability and sustainable fluid pressures for underground storage of CO 2 in porous rock. Energy, 29(9), 1445–1456.

    Article  Google Scholar 

  • Urpi, L., Rinaldi, A. P., Rutqvist, J., Cappa, F., & Spiers, C. J. (2016). Dynamic simulation of CO2-injection-induced fault rupture with slip-rate dependent friction coefficient. Geomechanics for Energy and the Environment, 7, 47–65.

    Article  Google Scholar 

  • Verdon, J. P., Kendall, J. M., Stork, A. L., Chadwick, R. A., White, D. J., & Bissell, R. C. (2013). Comparison of geomechanical deformation induced by megatonne-scale CO2 storage at Sleipner, Weyburn, and In Salah. Proceedings of the National Academy of Sciences, 110(30), E2762–E2771.

    Article  Google Scholar 

  • Vidal-Gilbert, S., Tenthorey, E., Dewhurst, D., Ennis-King, J., Van Ruth, P., & Hillis, R. (2010). Geomechanical analysis of the Naylor Field, Otway Basin, Australia: Implications for CO 2 injection and storage. International Journal of Greenhouse Gas Control, 4(5), 827–839.

    Article  Google Scholar 

  • Vilarrasa, V., & Laloui, L. (2015). Potential fracture propagation into the caprock induced by cold CO2 injection in normal faulting stress regimes. Geomechanics for Energy and the Environment, 2, 22–31.

    Article  Google Scholar 

  • Vilarrasa, V., Makhnenko, R., & Gheibi, S. (2016). Geomechanical analysis of the influence of CO2 injection location on fault stability. Journal of Rock Mechanics and Geotechnical Engineering, 8(6), 805–818.

    Article  Google Scholar 

  • Wang, G., Mitchell, T. M., Meredith, P. G., Nara, Y., & Wu, Z. (2016). Influence of gouge thickness and grain size on permeability of macrofractured basalt. Journal of Geophysical Research: Solid Earth, 121(12), 8472–8487.

    Article  Google Scholar 

  • Wiprut, D., & Zoback, M. D. (2002). Fault reactivation, leakage potential, and hydrocarbon column heights in the northern North Sea. Norwegian Petroleum Society Special Publications, 11, 203–219.

    Article  Google Scholar 

  • Zaoui, A. (2002). Continuum micromechanics: Survey. Journal of Engineering Mechanics, 128(8), 808–816.

    Article  Google Scholar 

  • Zhang, F., Mukhtar, Y. M. F., Liu, B., & Li, J. (2019). Application of ANN to predict the apparent viscosity of waxy crude oil. Fuel, 254, 115669.

    Article  Google Scholar 

  • Zoback, M. D. (2007). Reservoir geomechanics: ISBN: 978-0-521-77069-9. Cambridge University Press.

    Book  Google Scholar 

Download references

Acknowledgments

This research was supported by the Omani Research Council (Project reference: ORG/DU/EI/14/02) and (BFP/RGP/EI/21/170). The authors gratefully acknowledge these supports.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fethi Abbassi.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abbassi, F., Karrech, A., Islam, M.S. et al. Poromechanics of Fractured/Faulted Reservoirs During Fluid Injection Based on Continuum Damage Modeling and Machine Learning. Nat Resour Res 32, 413–430 (2023). https://doi.org/10.1007/s11053-022-10134-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11053-022-10134-8

Keywords

Navigation