1887
  1. Home
  2. A-Z Publications
  3. Geophysical Prospecting
  4. Volume 70, Issue 6
  5. Article
Volume 70, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Steam‐assisted gravity drainage reservoirs require an immense amount of energy and water resources, and proper monitoring of steam evolution and depletion patterns is integral to the economic and environmental efficiency of the operation. Muon tomography is a passive sensing technique, which has proven to successfully model density anomalies in a variety of applications but has not yet been applied to the oil and gas field. A previous study simulated muon intensity data to model density changes in a realistic steam‐assisted gravity drainage reservoir at 1.25 and 5 years after initial production. The results showed that muon tomography is a promising technique for monitoring steam‐assisted gravity drainage reservoirs with high spatial resolution and over short time intervals of weeks to months. Here we demonstrate the advantage of using vertical gravity gradient data and muon tomography data in a joint inversion to improve the muon‐only inverse models. Forward models for simulated muon and gravity gradient data are jointly inverted for a realistic steam‐assisted gravity drainage reservoir at 230 and 130 m total vertical depth at 1.25 years after initial production. Results show that the addition of gravity gradient data helps to constrain the density change models mainly in depth and to a smaller extent laterally. For a sparse muon sensor array of 48 sensors over a reservoir at depth, the joint inversion using gravity gradient data reduces the difference between the inverse and true model by 12% compared to a muon‐only inversion. The improvement is smaller at depth with 6%. The improvement in resolvability metrics is summarized, and limitations are discussed. The addition of multiple data types in a joint inversion improves the resulting models leading to an overall decrease in model uncertainty which can be used for improved operational efficiency in steam‐assisted gravity drainage operations.

© 2022 European Association of Geoscientists & Engineers. © 2022 European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.13205
2022-06-16
2024-04-27

  • From This Site

    /content/journals/10.1111/1365-2478.13205
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Alvarez, L.W., Anderson, J.A., El Bedwei, F., Burkhard, J., Fakhry, A., Girgis, A., Goneid, A., Hassan, F., Iverson, D., Lynch, G., Miligy, Z., Moussa, A.H., Mohammed‐Sharkawi & Yazolino, L. (1970) Search for hidden chambers in the pyramids. Science, 167(3919), 832–839.
     [Google Scholar]
  2. Ambrosi, G., Ambrosino, F., Battiston, R., Bross, A., Callier, S., Cassese, F., Castellini, G., Ciaranfi, R., Cozzolino, F., D'Alessandro, R., Taille, C.d.L., Iacobucci, G., Marotta, A., Masone, V., Martini, M., Nishiyama, R., Noli, P., Orazi, M., Parascandolo, L., Parascandolo, P., Passeggio, G., Peluso, R., Pla‐Dalmau, A., Raux, L., Rocco, R., Rubinov, P., Saracino, G., Scarpato, G., Sekhniaidze, G., Strolin, P., Tanaka, H. K.M., Tanaka, M., Trattino, P., Uchida, T. & Yokoyamao, I. (2011) The MU‐RAY project: volcano radiography with cosmic‐ray muons. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 628(1), 120–123.
     [Google Scholar]
  3. Barnoud, A., Cayol, V., Leliévre, P.G., Portal, A., Labazuy, P., Boivin, P. & Gailler, L. (2021) Robust Bayesian joint inversion of gravimetric and muographic data for the density imaging of the Puy de Doôme volcano (France). Frontiers in Earth Science, 8, 510.
     [Google Scholar]
  4. Barnoud, A., Cayol, V., Niess, V., Carloganu, C., Leliévre, P., Labazuy, P. & Le Ménédeu, E. (2019) Bayesian joint muographic and gravimetric inversion applied to volcanoes. Geophysical Journal International, 218(3), 2179–2194.
     [Google Scholar]
  5. Beringer, J., Arguin, J.F., Barnett, R.M., Copic, K., Dahl, O., Groom, D.E., Lin, C.J., Lys, J., Murayama, H., Wohl, C.G., Yao, W.M., Zyla, P.A., Amsler, C., Antonelli, M., Asner, D.M., Baer, H., Band, H.R., Basaglia, T., Bauer, C.W., Beatty, J.J., Belousov, V.I., Bergren, E., Bernardi, G., Bertl, W., Bethke, S., Bichsel, H., Biebel, O., Blucher, E., Blusk, S.R., Brooijmans, G., Buchmueller, O., Cahn, R.N., Carena, M., Ceccucci, A., Chakraborty, D., Chen, M.C., Chivukula, R.S., Cowan, G., D'ambrosio, G., Damour, T., De Florian, D., De Gouvêa, A., Degrand, T., De Jong, P., Dissertori, G., Dobrescu, B., Doser, M., Drees, M., Edwards, D.A., Eidelman, S., Erler, J., Ezhela, V.V., Fetscher, W., Fields, B.D., Foster, B., Gaisser, T.K., Garren, L., Gerber, H.J., Gerbier, G., Gherghetta, T., Golwala, S., Goodman, M., Grab, C., Gritsan, A.V., Grivaz, J.F., Grünewald, M., Gurtu, A., Gutsche, T., Haber, H.E., Hagiwara, K., Hagmann, C., Hanhart, C., Hashimoto, S., Hayes, K.G., Heffner, M., Heltsley, B., Hernández‐Rey, J.J., Hikasa, K., Höcker, A., Holder, J., Holtkamp, A., Huston, J., Jackson, J.D., Johnson, K.F., Junk, T., Karlen, D., Kirkby, D., Klein, S.R., Klempt, E., Kowalewski, R.V., Krauss, F., Kreps, M., Krusche, B., Kuyanov, Y.V., Kwon, Y., Lahav, O., Laiho, J.W., Langacker, P., Liddle, A., Ligeti, Z., Liss, T.M., Littenberg, L., Lugovsky, K.S., Lugovsky, S.B., Mannel, T., Manohar, A.V., Marciano, W.J., Martin, A.D., Masoni, A., Matthews, J., Milstead, D., Miquel, R., Mönig, K., Moortgat, F., Nakamura, K., Narain, M., Nason, P., Navas, S., Neubert, M., Nevski, P., Nir, Y., Olive, K.A., Pape, L., Parsons, J., Patrignani, C., Peacock, J.A., Petcov, S.T., Piepke, A., Pomarol, A., Punzi, G., Quadt, A., Raby, S., Raffelt, G., Ratcliff, B.N., Richardson, P., Roesler, S., Rolli, S., Romaniouk, A., Rosenberg, L.J., Rosner, J.L., Sachrajda, C.T., Sakai, Y., Salam, G.P., Sarkar, S., Sauli, F., Schneider, O., Scholberg, K., Scott, D., Seligman, W.G., Shaevitz, M.H., Sharpe, S.R., Silari, M., Sjöstrand, T., Skands, P., Smith, J.G., Smoot, G.F., Spanier, S., Spieler, H., Stahl, A., Stanev, T., Stone, S., Sumiyoshi, T., Syphers, M.J., Takahashi, F., Tanabashi, M., Terning, J., Titov, M., Tkachenko, N.P., Törnqvist, N.A., Tovey, D., Valencia, G., Van Bibber, K., Venanzoni, G., Vincter, M.G., Vogel, P., Vogt, A., Walkowiak, W., Walter, C.W., Ward, D.R., Watari, T., Weiglein, G., Weinberg, E.J., Wiencke, L.R., Wolfenstein, L., Womersley, J., Woody, C.L., Workman, R.L., Yamamoto, A., Zeller, G.P., Zenin, O.V., Zhang, J., Zhu, R.Y., Harper, G., Lugovsky, V.S. & Schaffner, P. (2012) Review of particle physics. Physical Review D ‐ Particles, Fields, Gravitation and Cosmology, 86(1), 010001.
     [Google Scholar]
  6. Bessel, F. (1813) Auszug aus einem Schreiben des Herrn Prof. Bessel. Zach's Monatliche Correspondenz zur Beförderung der Erd‐und Himmelskunde, 27, 80–85.
     [Google Scholar]
  7. Blakely, R.J. (1995) Potential Theory in Gravity and Magnetic Applications. Cambridge University Press.
     [Google Scholar]
  8. Bonomi, G., Caccia, M., Donzella, A., Pagano, D., Villa, V. & Zenoni, A. (2019) Cosmic ray tracking to monitor the stability of historical buildings: a feasibility study. Measurement Science and Technology, 30(4), 045901.
     [Google Scholar]
  9. Bouman, J., Ebbing, J., Fuchs, M., Sebera, J., Lieb, V., Szwillus, W., Haagmans, R. & Novak, P. (2016) Satellite gravity gradient grids for geophysics. Scientific Reports, 6(1), 21050.
     [Google Scholar]
  10. Capriotti, J. & Li, Y. (2014) Gravity and gravity gradient data: Understanding their information content through joint inversions. In SEG Technical Program Expanded Abstracts 2014. Society of Exploration Geophysicists, pp. 1329–1333.
     [Google Scholar]
  11. Carbone, D., Cannavó, F., Greco, F., Reineman, R. & Warburton, R.J. (2019) The benefits of using a network of superconducting gravimeters to monitor and study active volcanoes. Journal of Geophysical Research: Solid Earth, 124(4), 4035–4050.
     [Google Scholar]
  12. Cosburn, K., Roy, M., Guardincerri, E. & Rowe, C. (2019) Joint inversion of gravity with cosmic ray muon data at a well‐characterized site for shallow subsurface density prediction. Geophysical Journal International, 217(3), 1988–2002.
     [Google Scholar]
  13. Davis, K. & Oldenburg, D.W. (2012) Joint 3D of muon tomography and gravity data to recover density. ASEG Extended Abstracts, 2012(1), 1–4.
     [Google Scholar]
  14. Dusseault, M.B. (2001) Comparing Venezuelan and Canadian heavy oil and tar sands. In The 2nd Annual Canadian International Petroleum Conference of the Petroleum Society of CIM. Petroleum Society of CIM, pp. 1–20.
     [Google Scholar]
  15. Elliott, E. & Braun, A. (2017) On the resolvability of steam assisted gravity drainage reservoirs using time‐lapse gravity gradiometry. Pure and Applied Geophysics, 174(11), 4119–4136.
     [Google Scholar]
  16. Elliott, E.J. & Braun, A. (2016) Gravity Monitoring of 4D Fluid Migration in SAGD Reservoirs – Forward Modelling. CSEG Recorder, Vol 41, No 1, 16–21.
     [Google Scholar]
  17. Geng, M., Yang, Q. & Huang, D. (2017) 3D joint inversion of gravity‐gradient and borehole gravity data. Exploration Geophysics, 48(2), 151–165.
     [Google Scholar]
  18. George, E.P. (1955) Cosmic rays measure overburden of tunnel. Commonwealth Engineer, pp. 455–457.
     [Google Scholar]
  19. Gharti, H.N., Tromp, J. & Zampini, S. (2018) Spectral‐infinite‐element simulations of gravity anomalies. Geophysical Journal International, 215(2), 1098–1117.
     [Google Scholar]
  20. Groom, D.E., Mokhov, N.V. & Striganov, S.I. (2001) Muon stopping power and range tables 10 MeV–100 TeV. Atomic Data and Nuclear Data Tables, 78(2), 183–356.
     [Google Scholar]
  21. Jourde, K., Marteau, J. & Gibert, D. (2015) Improvement of density models of geological structures by fusion of gravity data and cosmic muon radiographies. Geoscientific Instrumentation, Methods and Data Systems, 4, 177–188.
     [Google Scholar]
  22. Leliévre, P.G., Barnoud, A., Niess, V., Carloganu, C., Cayol, V. & Farquharson, C.G. (2019) Joint inversion methods with relative density offset correction for muon tomography and gravity data, with application to volcano imaging. Geophysical Journal International, 218(3), 1685–1701.
     [Google Scholar]
  23. Lesparre, N., Gibert, D., Marteau, J., Komorowski, J.‐C., Nicollin, F. & Coutant, O. (2012) Density muon radiography of La Soufriére of Guadeloupe volcano: comparison with geological, electrical resistivity and gravity data. Geophysical Journal International, 190(2), 1008–1019.
     [Google Scholar]
  24. Li, Y. & Oldenburg, D.W. (1998) 3‐D inversion of gravity data. Geophysics, 63(1), 109–119.
     [Google Scholar]
  25. Marteau, J., Gibert, D., Lesparre, N., Nicollin, F., Noli, P. & Giacoppo, F. (2012) Muons tomography applied to geosciences and volcanology. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 695, 23–28.
     [Google Scholar]
  26. Menke, W. (1989) Geophysical Data Analysis: Discrete Inverse Theory (revised ed.). Elsevier.
     [Google Scholar]
  27. Mollweide, K. (1813) Auflösung einiger die Anziehing von Linien Flächen und Köpern betreffenden Aufgaben unter denen auch die in der Monatl Corresp Bd XXIV. S, 522, 26–38.
     [Google Scholar]
  28. Morishima, K., Kuno, M., Nishio, A., Kitagawa, N., Manabe, Y., Moto, M., Takasaki, F., Fujii, H., Satoh, K., Kodama, H., Hayashi, K., Odaka, S., Procureur, S., Attié, D., Bouteille, S., Calvet, D., Filosa, C., Magnier, P., Mandjavidze, I., Riallot, M., Marini, B., Gable, P., Date, Y., Sugiura, M., Elshayeb, Y., Elnady, T., Ezzy, M., Guerriero, E., Steiger, V., Serikoff, N., Mouret, J.B., Charlés, B., Helal, H. & Tayoubi, M. (2017) Discovery of a big void in Khufu's Pyramid by observation of cosmic‐ray muons. Nature, 552(7685), 386–390.
     [Google Scholar]
  29. Mossop, G.D. (1980) Geology of the Athabasca Oil Sands. Science, 207(4427), 145–152.
     [Google Scholar]
  30. Nagamine, K., Iwasaki, M., Shimomura, K. & Ishida, K. (1995) Method of probing inner‐structure of geophysical substance with the horizontal cosmic‐ray muons and possible application to volcanic eruption prediction. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 356(2), 585–595.
     [Google Scholar]
  31. Nagy, D. (1966) The gravitational attraction of a right rectangular prism. Geophysics, 31(2), 362–371.
     [Google Scholar]
  32. Nishiyama, R., Miyamoto, S., Okubo, S., Oshima, H. & Maekawa, T. (2017) 3D density modeling with gravity and muon‐radiographic observations in Showa‐Shinzan Lava Dome, Usu, Japan. Pure and Applied Geophysics, 174(3), 1061–1070.
     [Google Scholar]
  33. Nishiyama, R., Tanaka, Y., Okubo, S., Oshima, H., Tanaka, H. K.M. & Maekawa, T. (2014) Integrated processing of muon radiography and gravity anomaly data toward the realization of high‐resolution 3‐D density structural analysis of volcanoes: case study of Showa‐Shinzan lava dome, Usu, Japan. Journal of Geophysical Research: Solid Earth, 119(1), 699–710.
     [Google Scholar]
  34. Okabe, M. (1979) Analytical expressions for gravity anomalies due to homogeneous polyhedral bodies and translations into magnetic anomalies. Geophysics, 44(4), 730–741.
     [Google Scholar]
  35. Oláh, L., Tanaka, H.K.M., Ohminato, T., Hamar, G. & Varga, D. (2019) Plug formation imaged beneath the active craters of Sakurajima volcano with muography. Geophysical Research Letters, 46(17‐18), 10417–10424.
     [Google Scholar]
  36. Pieczonka, S., Schouten, D., Dabboor, O., Osler, D. & Braun, A. (2020) On the detectability of density change in steam‐assisted gravity drainage reservoirs using muon tomography. The Leading Edge, 39(7), 497–504.
     [Google Scholar]
  37. Plouff, D. (1976) Gravity and magnetic fields of polygonal prisms and application to magnetic terrain corrections. Geophysics, 41(4), 727–741.
     [Google Scholar]
  38. Rosas‐Carbajal, M., Jourde, K., Marteau, J., Deroussi, S., Komorowski, J.‐C. & Gibert, D. (2017) Three‐dimensional density structure of La Soufriére de Guadeloupe lava dome from simultaneous muon radiographies and gravity data. Geophysical Research Letters, 44(13), 6743–6751.
     [Google Scholar]
  39. Schouten, D. (2019) Muon geotomography: selected case studies. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 377(2137), 20180061.
     [Google Scholar]
  40. Schouten, D. & Ledru, P. (2018) Muon tomography applied to a dense uranium deposit at the McArthur River mine. Journal of Geophysical Research: Solid Earth, 123(10), 8637–8652.
     [Google Scholar]
  41. Tanaka, H.K.M., Nakano, T., Takahashi, S., Yoshida, J., Takeo, M., Oikawa, J., Ohminato, T., Aoki, Y., Koyama, E., Tsuji, H. & Niwa, K. (2007) High resolution imaging in the inhomogeneous crust with cosmic‐ray muon radiography: the density structure below the volcanic crater floor of Mt. Asama, Japan. Earth and Planetary Science Letters, 263(1), 104–113.
     [Google Scholar]
  42. Torrence, B. (2020) Seeing the symmetric difference. In Yackel, C., Bosch, R., Torrence, E. & Fenyvesi, K. (Eds.), Proceedings of Bridges 2020: Mathematics, Art, Music, Architecture, Education, Culture. Phoenix, Arizona: Tessellations Publishing, pp. 387–390.
     [Google Scholar]
  43. Yao, L. & Changli, Y. (2007) Forward modeling of gravity, gravity gradients, and magnetic anomalies due to complex bodies. Journal of China University of Geosciences, 18(3), 280–286.
     [Google Scholar]
  44. Zhang, R. & Li, T. (2019) Joint inversion of 2D gravity gradiometry and magnetotelluric data in mineral exploration. Minerals, 9, 541.
     [Google Scholar]
  45. Zhu, Y., Zhdanov, M.S. & Cuma, M. (2013) Gramian constraints in the joint inversion of airborne gravity gradiometry and magnetic data. In SEG Technical Program Expanded Abstracts 2013Society of Exploration Geophysicists, pp. 1166–1170.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.13205
Loading
Joint inversion of muon tomography and gravity gradiometry for improved monitoring of steam‐assisted gravity drainage reservoirs
Geophysical Prospecting 70, 1033 (2022); https://doi.org/10.1111/1365-2478.13205
/content/journals/10.1111/1365-2478.13205
/content/journals/10.1111/1365-2478.13205
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): gravity gradiometry; joint inversion; Muon tomography; Steam Assisted Gravity Drainage (SAGD)

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error