1887
Volume 72, Issue 8
  • E-ISSN: 1365-2478

Abstract

Abstract

We present a 3D numerical modelling analysis evaluating the deployment of a borehole electromagnetic measurement tool to detect and image a stimulated zone at the Utah Frontier Observatory for Research in Geothermal Energy geothermal site. As the depth to the geothermal reservoir is several kilometres and the size of the stimulated zone is limited to several 100 m, surface‐based controlled‐source electromagnetic measurements lack the sensitivity for detecting changes in electrical resistivity caused by the stimulation. To overcome the limitation, the study evaluates the feasibility of using a three‐component borehole magnetic receiver system at the Frontier Observatory for Research in Geothermal Energy site. To provide sufficient currents inside and around the enhanced geothermal reservoir, we use an injection well as an energized casing source. To efficiently simulate energizing the injection well in a realistic 3D resistivity model, we introduce a novel modelling workflow that leverages the strengths of both 3D cylindrical‐mesh‐based electromagnetic modelling code and 3D tetrahedral‐mesh‐based electromagnetic modelling code. The former is particularly well‐suited for modelling hollow cylindrical objects like casings, whereas the latter excels at representing more complex 3D geological structures. In this workflow, our initial step involves computing current densities along a vertical steel‐cased well using a 3D cylindrical electromagnetic modelling code. Subsequently, we distribute a series of equivalent current sources along the well's trajectory within a complex 3D resistivity model. We then discretize this model using a tetrahedral mesh and simulate the borehole electromagnetic responses excited by the casing source using a 3D finite‐element electromagnetic code. This multi‐step approach enables us to simulate 3D casing source electromagnetic responses within a complex 3D resistivity model, without the need for explicit discretization of the well using an excessive number of fine cells. We discuss the applicability and limitations of this proposed workflow within an electromagnetic modelling scenario where an energized well is deviated, such as at the Frontier Observatory for Research in Geothermal Energy site. Using the workflow, we demonstrate that the combined use of the energized casing source and the borehole electromagnetic receiver system offer measurable magnetic field amplitudes and sensitivity to the deep localized stimulated zone. The measurements can also distinguish between parallel‐fracture anisotropic reservoirs and isotropic cases, providing valuable insights into the fracture system of the stimulated zone. Besides the magnetic field measurements, vertical electric field measurements in the open well sections are also highly sensitive to the stimulated zone and can be used as additional data for detecting and imaging the target. We can also acquire additional multiple‐source data by grounding the surface electrode at various locations and repeating borehole electromagnetic measurements. This approach can increase the number of monitoring data by several factors, providing a more comprehensive dataset for analysing the deep‐localized stimulated zone. The numerical analysis indicates that it is feasible to use the combination of the energized casing and downhole electromagnetic measurements in monitoring localized stimulated zone at large depths.

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2024-09-15
2026-02-15
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References

  1. Alumbaugh, D., Um, E., Wilt, W., Nichols, E. & Osato, K. (2023) Deep borehole EM deployment for fracture mapping at the FORGE geothermal site. In: Proceedings of the 48th Workshop on Geothermal Reservoir Engineering, 2023, Stanford, California. Stanford University.
  2. Beskardes, G.D., Weiss, C.J., Um, E., Wilt, M. & MacLennan, K. (2021) The effects of well damage and completion designs on geoelectrical responses in mature wellbore environments. Geophysics, 86(6), E355–E366.
    [Google Scholar]
  3. Berryman, J.G. & Hoversten, G.M. (2013) Modelling electrical conductivity for earth media with macroscopic fluid‐filled fractures. Geophysical Prospecting, 61(2), 471–493.
    [Google Scholar]
  4. Blackwell, D.D., Negraru, P.T. & Richards, M.C. (2006) Assessment of the enhanced geothermal system resource base of the United States. Natural Resources Research, 15, 283–308.
    [Google Scholar]
  5. Boitnott, G.N. & Kirkpatrick, A. (1997) Interpretation of field seismic tomography at the Geysers geothermal field, California. In: Proceedings of the 22nd Workshop on Geothermal Reservoir Engineering. Stanford, Stanford University. pp. 391–398.
  6. Breede, K., Dzebisashvili, K., Liu, X. & Falcone, G. (2013) A systematic review of enhanced (or engineered) geothermal systems: past, present and future. Geothermal Energy, 1, 1–27.
    [Google Scholar]
  7. Börner, J.H., Bär, M. & Spitzer, K. (2015) Electromagnetic methods for exploration and monitoring of enhanced geothermal systems–a virtual experiment. Geothermics, 55, 78–87.
    [Google Scholar]
  8. Castillo‐Reyes, O., Queralt, P., Marcuello, A. & Ledo, J. (2021) Land CSEM simulations and experimental test using metallic casing in a geothermal exploration context: Vallès basin (NE Spain) case study. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13.
    [Google Scholar]
  9. Commer, M., Hoversten, G.M., & Um, E.S. (2015) Transient‐electromagnetic finite‐difference time‐domain earth modeling over steel infrastructure. Geophysics, 80(2), E147–E162.
    [Google Scholar]
  10. Cuevas, N.H. (2014) Analytical solutions of EM fields due to a dipolar source inside an infinite casing. Geophysics, 79(5), E231–E241.
    [Google Scholar]
  11. Cuevas, N.H. (2019) Surface‐borehole electromagnetic method‐a review on the technology development and potential for geothermal applications. In: EAGE/BVG/FKPE joint workshop on borehole geophysics and geothermal energy, 2019. Bunnik, The Netherlands, European Association of Geoscientists & Engineers. pp. 1–2.
  12. Dobson, P., Dwivedi, D., Millstein, D., Krishnaswamy, N., Garcia, J. & Kiran, M. (2020) Analysis of curtailment at The Geysers geothermal field, California. Geothermics, 87, 101871.
    [Google Scholar]
  13. Dyer, B.C., Schanz, U., Ladner, F., Haring, M.O. & Spillman, T. (2008) Microseismic imaging of a geothermal reservoir stimulation. The Leading Edge, 27(7), 856–869.
    [Google Scholar]
  14. Finnila, A. & Podgorney, R. (2020) Exploring hydraulic fracture stimulation patterns in the forge reservoir using multiple stochastic DFN realizations and variable stress conditions. In: Proceedings of the 45th Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University.
  15. Gao, G., Alumbaugh, D., Zhang, P., Liu, J., Zhang, H., Levesque, C., Rosthal, R., Abubakar, A. & Habashy, T. (2008) Practical implications of nonlinear inversion for cross‐well electromagnetic data collected in cased‐wells. In: 78Th annual international meeting, SEG annual meeting. Houston, SEG. pp. 299–303.
  16. Gritto, R. & Jarpe, S.P. (2014) Temporal variations of Vp/Vs‐ratio at The Geysers geothermal field, USA. Geothermics, 52, 112–119.
    [Google Scholar]
  17. Gritto, R., Jarpe, S.P. & Alumbaugh, D.L. (2022) New large‐scale passive seismic monitoring at The Geysers geothermal reservoir, CA, USA. In: Proceedings, 47th Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University.
  18. Heagy, L.J., Cockett, R., Kang, S., Rosenkjaer, G.K. & Oldenburg, D.W. (2017) A framework for simulation and inversion in electromagnetics. Computers & Geosciences, 107, 1–19.
    [Google Scholar]
  19. Heagy, L.J. & Oldenburg, D.W. (2019) Modeling electromagnetics on cylindrical meshes with applications to steel‐cased wells. Computers & Geosciences, 125, 115–130.
    [Google Scholar]
  20. Hoversten, G.M., Commer, M., Haber, E. & Schwarzbach, C. (2015), Hydro‐frac monitoring using ground time‐domain electromagnetic. Geophysical Prospecting, 63, 1508–1526.
    [Google Scholar]
  21. Johnston, R. & Shrallow, J. (2011) Ambiguity in microseismic monitoring. In: 81st annual international meeting Society of Exploration Geophysicists, expanded abstracts. Houston, Society of Exploration Geophysicists. pp. 1514–1518.
  22. Kneafsey, T.J., Dobson, P., Blankenship, D., Morris, J., Knox, H., Schwering, P. et al. (2018) An overview of the EGS collab project: field validation of coupled process modeling of fracturing and fluid flow at the Sanford Underground Research Facility, Lead, SD. In: 43Rd Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University.
  23. Kohnke, C., Liu, L., Streich, R. & Swidinsky, A. (2018) A method of moments approach to model the electromagnetic response of multiple steel casings in a layered earth. Geophysics, 83(2), WB81–WB96.
    [Google Scholar]
  24. Kolditz, O., Bauer, S., Bilke, L., Böttcher, N., Delfs, J.O., Fischer, T. et al. (2012) OpenGeoSys: an open‐source initiative for numerical simulation of thermo‐hydro‐mechanical/chemical (THM/C) processes in porous media. Environmental Earth Sciences, 67, 589–599.
    [Google Scholar]
  25. Kordy, M., Wannamaker, P., Maris, V., Cherkaev, E. & Hill, G. (2016) 3‐D magnetotelluric inversion including topography using deformed hexahedral edge finite elements and direct solvers parallelized on SMP computers–part I: forward problem and parameter Jacobians. Geophysical Journal International, 204(1), 74–93.
    [Google Scholar]
  26. Lellouch, A., Lindsey, N.J., Ellsworth, W.L. & Biondi, B.L. (2020) Comparison between distributed acoustic sensing and geophones: downhole microseismic monitoring of the FORGE geothermal experiment. Seismological Society of America, 91(6), 3256–3268.
    [Google Scholar]
  27. Lin, G. & Wu, B. (2018) Seismic velocity structure and characteristics of induced seismicity at The Geysers geothermal field, eastern California. Geothermics, 71, 225–233.
    [Google Scholar]
  28. Lindsey, N.J., Kaven, J.O., Davatzes, N. & Newman, G.A. (2016) Compartmentalization of the Coso East Flank geothermal field imaged by 3‐D full‐tensor MT inversion. Geophysical Journal International, 208(2), 652–662.
    [Google Scholar]
  29. Lu, S.M. (2018) A global review of enhanced geothermal system (EGS). Renewable and Sustainable Energy Reviews, 81, 2902–2921.
    [Google Scholar]
  30. Marsala, A.F., Hibbs, A.D. & Morrison, H.F. (2014) Borehole casing sources for electromagnetic imaging of deep formations. In: SPE annual technical conference and exhibition. Calgary, SPE, pp. SPE–170845
  31. Miura, Y., Osato, K., Takasugi, S., Muraoka, H. & Yasukawa, K. (1996) Development of the vertical electro magnetic profiling (VEMP) method. Journal of applied Geophysics, 35(2–3), 191–197.
    [Google Scholar]
  32. Moore, J., McLennan, J., Allis, R., Pankow, K., Simmons, S., Podgorney, R. et al. (2019) The Utah Frontier Observatory for Research in Geothermal Energy (FORGE): an international laboratory for enhanced geothermal system technology development. In: Proceedings 44th Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University. pp. 11–13.
  33. Moore, J., McLennan, J., Pankow, K., Simmons, S., Podgorney, R., Wannamaker, P. et al. (2020) The Utah Frontier Observatory for Research in Geothermal Energy (Forge): a laboratory for characterizing, creating and sustaining enhanced geothermal systems. In: Proceedings of the 45th Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University.
  34. Moos, D. & Zoback, M.D. (1983) In situ studies of velocity in fractured crystalline rocks. Journal of Geophysical Research: Solid Earth, 88(B3), 2345–2358.
    [Google Scholar]
  35. Muñoz, G. (2014) Exploring for geothermal resources with electromagnetic methods. Surveys in Geophysics, 35, 101–122.
    [Google Scholar]
  36. Newman, G.A., Gasperikova, E., Hoversten, G.M. & Wannamaker, P.E. (2008) Three‐dimensional magnetotelluric characterization of the Coso geothermal field. Geothermics, 37(4), 369–399.
    [Google Scholar]
  37. Orujov, G., Swidinsky, A. & Streich, R. (2022) Do metal infrastructure effects cancel out in time‐lapse electromagnetic measurements?Geophysics, 87(2), E91–E101.
    [Google Scholar]
  38. Oye, V., Langet, N., Hasting, M., Lecomte, I., Messeiller, M. & Reid, P. (2012) Microseismic monitoring of the hydraulic stimulation at the Paralana enhanced geothermal system, South Australia. First Break, 30(7), 91–95.
    [Google Scholar]
  39. Peacock, J., Thiel, S., Reid, P. & Heinson, G. (2012) Magnetotelluric monitoring of a fluid injection: example from an enhanced geothermal system. Geophysical Research Letters, 39(18), L18403.
    [Google Scholar]
  40. Peacock, J., Thiel, S., Heinson, G. & Reid, P. (2013) Time‐lapse magnetotelluric monitoring of an enhanced geothermal system. Geophysics, 78(3), B121–B130.
    [Google Scholar]
  41. Peacock, J., Earney, T., Mangan, M., Schermerhorn, W., Glen, J., Walters, M. et al. (2020) Geophysical characterization of the Northwest Geysers geothermal field, California. Journal of Volcanology and Geothermal Research, 399, 106882.
    [Google Scholar]
  42. Peacock, J., Alumbaugh, D., Mitchell, M. & Hartline, C. (2022) Repeat magnetotelluric measurements to monitor the Geysers steam field in Northern California. In: 47Th Workshop on Geothermal Reservoir Engineering. Stanford, California, Stanford University.
  43. Schlumberger . (2005) Schlumberger log interpretation charts. Houston, TX: Schlumberger.
    [Google Scholar]
  44. Tang, W., Li, Y., Swidinsky, A. & Liu, J. (2015) Three‐dimensional controlled‐source electromagnetic modelling with a well casing as a grounded source: a hybrid method of moments and finite element scheme. Geophysical Prospecting, 63, 1491–1507.
    [Google Scholar]
  45. Tester, J., Anderson, B., Batchelor, A., Blackwell, D., DiPippo, R., Drake, E. et al. (2006) The future of geothermal energy. Cambridge, MA: Massachusetts Institute of Technology.
  46. Um, E.S., Commer, M., Newman, G.A., & Hoversten, G.M. (2015) Finite element modelling of transient electromagnetic fields near steel‐cased wells. Geophysical Journal International, 202(2), 901–913.
    [Google Scholar]
  47. Um, E., Kim, J. & Wilt, M. (2020) 3D borehole‐to‐surface and surface electromagnetic modeling and inversion in the presence of steel infrastructure. Geophysics, 85(5), 139–E152.
    [Google Scholar]
  48. Wannamaker, P., Rose, P., Doerner, W., Berard, B., McCulloch, J. & Nurse, K. (2004) Magnetotelluric surveying and monitoring at the Coso geothermal area, California, in support of the enhanced geothermal systems concept: survey parameters and initial results. In: 29Th Workshop on Geothermal Reservoir Engineering, Stanford, California. Stanford University, pp. 287–294.
  49. Wannamaker, P., Simmons, S., Miller, J., Hardwick, C., Erickson, B., Bowman, S. et al. (2020) Geophysical activities over the Utah FORGE site at the outset of project phase 3. In: Proceedings, 45th Workshop on Geothermal Reservoir Engineering. Stanford, CA: Stanford University, pp. 1–14.
  50. Weiss, C.J. (2017) Finite‐element analysis for model parameters distributed on a hierarchy of geometric simplices. Geophysics, 82(4), E155–E167.
    [Google Scholar]
  51. Wilt, M., Takasugi, S., Uchida, T., Kasameyer, P., Lee, K. & Lippmann, M. (1997) Fracture mapping in geothermal fields with long‐offset induction logging. In: Proceedings: twenty‐second Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University, pp. 2–3 to 2–6.
  52. Wilt, M., Mallan, R., Kasameyer, P. & Kirkendall, B. (2002) 3D extended logging for geothermal resources: field trials with the Geo‐BILT system. In: 27Th Workshop on Geothermal Reservoir Engineering. Stanford, CA, Stanford University, pp. 23–25.
  53. Wu, X. & Habashy, T.M. (1994) Influence of steel casings on electromagnetic signals. Geophysics, 59(3), 378–390.
    [Google Scholar]
  54. Xing, P., Damjanac, B., Radakovic‐Guzina, Z., Torres, M., Finnila, A., Podgorney, R. et al. (2022) Numerical simulation of stimulations at The Utah FORGE site using the designed pumping schedules. In: Proceedings of the Geothermal Rising conference. Davis, CA, Geothermal Rising. pp. 618–628.
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  • Article Type: Research Article
Keyword(s): borehole geophysics; electromagnetics; modelling

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