1887
Volume 74, Issue 1
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Accurately detecting the locations of fractures and the permeability structure within a subsurface reservoir can significantly improve the optimization of production performance. Achieving peak performance in subsurface groundwater or hydrocarbon reservoirs depends on creating an accurate map that details the reservoir's characteristics derived from the history‐matching process. However, this process involves repeated forward modelling simulations until the results align with historical production data, often consuming significant resources and potentially yielding non‐unique reservoir models. An integration approach between bottom‐hole pressure data and surface self‐potential measurements was used to perform simultaneous inversion for the permeability structure. The self‐potential method, a cost‐effective geophysical technique, allows for the inversion of subsurface self‐potential sources based on the underlying resistivity structure. Through a series of synthetic experiments, we demonstrate that combining borehole pressure data with surface self‐potential measurements significantly enhances reservoir characterization, providing more robust and accurate subsurface models. By using the resolution matrix, we further confirm that the solution achieves higher accuracy when both data sets are integrated. This approach not only improves the precision of reservoir mapping but also reduces the uncertainty typically associated with traditional methods, offering a more efficient and reliable tool for optimizing production performance.

© 2026 European Association of Geoscientists & Engineers. © 2026 European Association of Geoscientists & Engineers.
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2026-01-26
2026-02-18

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References

  1. Abdelrahman, E. M., K. S.Essa, E. R.Abo‐Ezz, and K. S.Soliman. 2006. “Self‐Potential Data Interpretation Using Standard Deviations of Depths Computed From Moving‐Average Residual Anomalies.” Geophysical Prospecting54, no. 4: 409–423.
     [Google Scholar]
  2. Abdelrahman, E. M., H. S.Saber, K. S.Essa, and M. A.Fouda. 2004. “A Least‐Squares Approach to Depth Determination From Numerical Horizontal Self‐Potential Gradients.” Pure and Applied Geophysics161: 399–411.
     [Google Scholar]
  3. Ahmad, M. U.1964. “A Laboratory Study of Streaming Potentials.” Geophysical Prospecting12, no. 1: 49–64.
     [Google Scholar]
  4. Ai, H., H.Li, K. S.Essa, et al. 2024. “Global Optimization of Self‐Potential Anomalies Using Hunger Games Search Algorithm.” Pure and Applied Geophysics181: 1303–1336. https://doi.org/10.1007/s00024‐024‐03457‐5.
     [Google Scholar]
  5. Alkafeef, S., R. J.Gochin, and A. L.Smith. 2001. “The Effect of Double Layer Overlap on Measured Streaming Currents for Toluene Flowing Through Sandstone Cores.” Colloids and Surfaces A: Physicochemical and Engineering Aspects195, no. 1–3: 77–80.
     [Google Scholar]
  6. Al Nasser, S.2023. “Mitigating the Problem of Non‐Uniqueness in Fluid‐Flow Modeling.” PhD thesis, Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences.
  7. Backus, G., and F.Gilbert. 1968. “The resolving power of gross earth data.” Geophysical Journal International, 16, no. 2: 169–205.
     [Google Scholar]
  8. Backus, G. E., and J. F.Gilbert. 1967. “Numerical applications of a formalism for geophysical inverse problems.” Geophysical Journal International, 13, no. 1‐3: pp.247–276.
     [Google Scholar]
  9. Bear, J.1988. Dynamics of Fluids in Porous Media. Courier Corporation.
     [Google Scholar]
  10. Burns, D. R., M. E.Willis, M. N.Toksöz, and L.Vetri. 2007. “Fracture Properties From Seismic Scattering.” Leading Edge26, no. 9: 1186–1196.
     [Google Scholar]
  11. Chapman, D. L.1913. “LI. A Contribution to the Theory of Electrocapillarity.” London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science25, no. 148: 475–481.
     [Google Scholar]
  12. Colombo, D., M.Mantovani, S.Hallinan, and M.Virgilio. 2008. “Sub‐Basalt Depth Imaging Using Simultaneous Joint Inversion of Seismic and Electromagnetic (MT) Data: A CRB Field Study.” In Proceeding of the SEG Technical Program Expanded Abstracts 2008. Society of Exploration Geophysicists‏.
  13. Cueto‐Felgueroso, L., and R.Juanes. 2013. “Forecasting Long‐Term Gas Production From Shale.” Proceedings of the National Academy of Sciences110, no. 49: 19660–19661.
     [Google Scholar]
  14. Davis, S. M., D. A.Landgrebe, T. L.Phillips, et al. 1978. Remote Sensing: The Quantitative Approach. McGraw‐Hill.
     [Google Scholar]
  15. DesRoches, A. J., K. E.Butler, and K. T.MacQuarrie. 2018. “Surface Self‐Potential Patterns Related to Transmissive Fracture Trends During a Water Injection Test.” Geophysical Journal International212, no. 3: 2047–2060.
     [Google Scholar]
  16. Essa, K. S.2019. “A Particle Swarm Optimization Method for Interpreting Self‐Potential Anomalies.” Journal of Geophysics and Engineering16, no. 2: 463–477.
     [Google Scholar]
  17. Essa, K. S.2020. “Self Potential Data Interpretation Utilizing the Particle Swarm Method for the Finite 2D Inclined Dike: Mineralized Zones Delineation.” Acta Geodaetica et Geophysica55: 203–221. https://doi.org/10.1007/s40328‐020‐00289‐2.
     [Google Scholar]
  18. Fagerlund, F., and G.Heinson. 2003. “Detecting Subsurface Groundwater Flow in Fractured Rock Using Self‐Potential (SP) Methods.” Environmental Geology43, no. 7: 782–794.
     [Google Scholar]
  19. Greenberg, M. D.2015. Applications of Green's Functions in Science and Engineering. Courier Dover Publications.
  20. Hajibeygi, H., D.Karvounis, and P.Jenny. 2011. “A Hierarchical Fracture Model for the Iterative Multiscale Finite Volume Method.” Journal of Computational Physics230, no. 24: 8729–8743.
     [Google Scholar]
  21. Hu, H., A.Alali, A.Almomin, and Y.Zheng. 2021. “3D Seismic Characterization of Fractures Using Elastic P‐to‐S Double Beams.” Geophysics86, no. 6: R927–R937.
     [Google Scholar]
  22. Hu, H., and Y.Zheng. 2017. “3D Seismic Characterization of Fractures in a Dipping Reservoir Layer by Double Beams.” In Proceeding of the 2017 SEG International Exposition and Annual Meeting. OnePetro.
  23. Hyndman, D. W., J. M.Harris, and S. M.Gorelick. 1994. “Coupled Seismic and Tracer Test Inversion for Aquifer Property Characterization.” Water Resources Research30, no. 7: 1965–1977.
     [Google Scholar]
  24. Irving, J., and K.Singha. 2010. “Stochastic Inversion of Tracer Test and Electrical Geophysical Data to Estimate Hydraulic Conductivities.” Water Resources Research46, no. 11.
     [Google Scholar]
  25. Jardani, A., J. P.Dupont, and A.Revil. 2006. “Self‐Potential Signals Associated With Preferential Groundwater Flow Pathways in Sinkholes.” Journal of Geophysical Research: Solid Earth111, no. B9: B09204.
     [Google Scholar]
  26. Jardani, A., A.Revil, W.Barrash, et al. 2009. “Reconstruction of the Water Table From Self‐Potential Data: A Bayesian Approach.” Groundwater47, no. 2: 213–227.
     [Google Scholar]
  27. Jardani, A., A.Revil, A.Bolève, J. P.Dupont, W.Barrash, and B.Malama. 2007. “Tomography of the Darcy Velocity From Self‐Potential Measurements.” Geophysical Research Letters34, no. 24: L24403.
     [Google Scholar]
  28. Jougnot, D., D.Roubinet, L.Guarracino, and A.Maineult. 2020. “Modeling Streaming Potential in Porous and Fractured Media, Description and Benefits of the Effective Excess Charge Density Approach.” In Advances in Modeling and Interpretation in Near Surface Geophysics. Springer International Publishing.
     [Google Scholar]
  29. Kang, P. K., Y.Zheng, X.Fang, et al. 2016. “Sequential Approach to Joint Flow‐Seismic Inversion for Improved Characterization of Fractured Media.” Water Resources Research52, no. 2: 903–919.
     [Google Scholar]
  30. Kormiltsev, V. V., A. N.Ratushnyak, and V. A.Shapiro. 1998. “Three‐Dimensional Modeling of Electric and Magnetic Fields Induced by the Fluid Flow Movement in Porous Media.” Physics of the Earth and Planetary Interiors105, no. 3–4: 109–118.
     [Google Scholar]
  31. Lacazette, A., J.Vermilye, S.Fereja, and C.Sicking. 2013. “Ambient Fracture Imaging: A New Passive Seismic Method.” In Proceeding of the Unconventional Resources Technology Conference. Society of Exploration Geophysicists, American Association of Petroleum Geologists, Society of Petroleum Engineers.
  32. Lie, K. A.2019. An Introduction to Reservoir Simulation Using MATLAB/GNU Octave: User Guide for the MATLAB Reservoir Simulation Toolbox (MRST). Cambridge University Press.
     [Google Scholar]
  33. Linde, N., A.Binley, A.Tryggvason, L. B.Pedersen, and A.Revil. 2006. “Improved Hydrogeophysical Characterization Using Joint Inversion of Cross‐Hole Electrical Resistance and Ground‐Penetrating Radar Traveltime Data.” Water Resources Research42, no. 12: W04410.
     [Google Scholar]
  34. Maineult, A., B.Thomas, C.Nussbaum, et al. 2013. “Anomalies of Noble Gases and Self‐Potential Associated With Fractures and Fluid Dynamics in a Horizontal Borehole Mont Terri Underground Rock Laboratory.” Engineering Geology156: 46–57.
     [Google Scholar]
  35. McKenna, S. A., and E. P.Poeter. 1995. “Field Example of Data Fusion in Site Characterization.” Water Resources Research31, no. 12: 3229–3240.
     [Google Scholar]
  36. Mehanee, S. A., K. S.Essa, K. S.Soliman, et al. 2023. “A Fast Imaging Method for the Interpretation of Self‐Potential Data With Application to Geothermal Systems and Mineral Investigation.” Scientific Reports13: 13548.
     [Google Scholar]
  37. Menke, W.2018. “Geophysical data analysis: Discrete inverse theory.” Academic press.
     [Google Scholar]
  38. Morgan, F. D.1989. “Fundamentals of Streaming Potentials in Geophysics: Laboratory Methods.” In Detection of Subsurface Flow Phenomena. Springer.
     [Google Scholar]
  39. Morgan, F. D., S.Al Nasser, R.Jerry, and A.Verneuil. 2019. “Investigations in Groundwater Flow Toward a Spring in the Saphire Area, Soufriere, Saint Lucia, West Indies.” Leading Edge38, no. 6: 460–464.
     [Google Scholar]
  40. Revil, A., and A.Jardani. 2010. “Stochastic Inversion of Permeability and Dispersivities From Time Lapse Self‐Potential Measurements: A Controlled Sandbox Study.” Geophysical Research Letters37: L11404. https://doi.org/10.1029/2010GL043257.
     [Google Scholar]
  41. Revil, A., and A.Jardani. 2013. The Self‐Potential Method: Theory and Applications in Environmental Geosciences. Cambridge University Press.
     [Google Scholar]
  42. Revil, A., and H.Mahardika. 2013. “Coupled Hydromechanical and Electromagnetic Disturbances in Unsaturated Porous Materials.” Water Resources Research49, no. 2: 744–766.
     [Google Scholar]
  43. Revil, A., V.Naudet, J.Nouzaret, and M.Pessel. 2003. “Principles of Electrography Applied to Self‐Potential Electrokinetic Sources and Hydrogeological Applications.” Water Resources Research39, no. 5: 1114.
     [Google Scholar]
  44. Revil, A., K.Titov, C.Doussan, and V.Lapenna. 2006. “Applications of the Self‐Potential Method to Hydrological Problems.” In Applied Hydrogeophysics. Springer.
     [Google Scholar]
  45. Riley, K. F., M. P.Hobson, and S. J.Bence. 1998. Mathematical Methods for Physics and Engineering: A Comprehensive Guide. Cambridge University Press.
     [Google Scholar]
  46. Revil, A., A.Jardani, and J.Dupont. 2012, December. “Stochastic joint inversion of geoelectrical cross-well data for salt tracer test monitoring to image the hydraulic conductivity field of heterogenous aquifers.” In AGU Fall Meeting Abstracts (Vol. 2012, pp. H11K‐01).
     [Google Scholar]
  47. Rizzo, E., B.Suski, A.Revil, S.Straface, and S.Troisi. 2004. “Self‐Potential Signals Associated With Pumping Tests Experiments.” Journal of Geophysical Research: Solid Earth109, no. B10: B10203.
     [Google Scholar]
  48. Sheffer, M. R., and D. W.Oldenburg. 2007. “Three‐Dimensional Modelling of Streaming Potential.” Geophysical Journal International169, no. 3: 839–848.
     [Google Scholar]
  49. Sill, W. R.1983. “Self‐Potential Modeling From Primary Flows.” Geophysics48, no. 1: 76–86.
     [Google Scholar]
  50. Soueid Ahmed, A., A.Jardani, A.Revil, and J. P.Dupont. 2016. “Joint Inversion of Hydraulic Head and Self‐Potential Data Associated With Harmonic Pumping Tests.” Water Resources Research52, no. 9: 6769–6791.
     [Google Scholar]
  51. Straface, S., F.Chidichimo, E.Rizzo, et al. 2011. “Joint Inversion of Steady‐State Hydrologic and Self‐Potential Data for 3D Hydraulic Conductivity Distribution at the Boise Hydrogeophysical Research Site.” Journal of Hydrology407, no. 1–4: 115–128.
     [Google Scholar]
  52. Suski, B., A.Revil, K.Titov, et al. 2006. “Monitoring of an Infiltration Experiment Using the Self‐Potential Method.” Water Resources Research42, no. 8: WO8418.
     [Google Scholar]
  53. Tikhonov, A. N.1943. “On the Stability of Inverse Problems.” Doklady Akademii Nauk SSSR39: 195–198.
     [Google Scholar]
  54. Vichabian, Y., and F. D.Morgan. 2002. “Self Potentials in Cave Detection.” Leading Edge21, no. 9: 866–871.
     [Google Scholar]
  55. Vinogradov, J., and M. D.Jackson. 2011. “Multiphase Streaming Potential in Sandstones Saturated With Gas/Brine and Oil/Brine During Drainage and Imbibition.” Geophysical Research Letters38, no. 1: 1–7.
     [Google Scholar]
  56. Wiggins, R. A.1972. “The General Linear Inverse Problem: Implication of Surface Waves and Free Oscillations for Earth Structure.” Reviews of Geophysics10, no. 1: 251–285.
     [Google Scholar]
  57. Wishart, D. N., L. D.Slater, and A. E.Gates. 2006. “Self Potential Improves Characterization of Hydraulically‐Active Fractures From Azimuthal Geoelectrical Measurements.” Geophysical Research Letters33, no. 17: L17314.
     [Google Scholar]
  58. Wishart, D. N., L. D.Slater, and A. E.Gates. 2008. “Fracture Anisotropy Characterization in Crystalline Bedrock Using Field‐Scale Azimuthal Self Potential Gradient.” Journal of Hydrology358, no. 1–2: 35–45.
     [Google Scholar]
  59. Wurmstich, B., and F. D.Morgan. 1994. “Modeling of Streaming Potential Responses Caused by Oil Well Pumping.” Geophysics59, no. 1: 46–56.
     [Google Scholar]
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Joint Self‐Potential and Fluid Flow Inversion for Imaging Permeability Structure and Detecting Fractures
Geophysical Prospecting 74, e70118 (2026); https://doi.org/10.1111/1365-2478.70118
/content/journals/10.1111/1365-2478.70118
/content/journals/10.1111/1365-2478.70118
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  • Article Type: Research Article
Keyword(s): fracture detection; joint Inversion; self‐potential

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