1887
Volume 71, Issue 8
  • E-ISSN: 1365-2478
PDF

Abstract

Abstract

This study complements two earlier papers on the interpretation and estimation of post‐stack time‐shifts that detail the most popular measurement methods to date. In this current work, the focus is on describing the magnitude and identifying the origin of the uncertainty present in these time‐shift values. We also consider how the underlying assumptions behind conventional time‐shift estimation methods can contribute to the inadequate resolution of the subsurface time‐lapse changes. The various errors fall into three broad categories: (1) those related to intrinsic data limits that cannot be avoided; (2) those associated with seismic measurement methods that can be corrected with some effort; and finally (3) those that arise due to approximations to the wave physics made during the design or implementation of the methods. In the first category are limitations due to sampling rate and signal‐to‐noise ratio, and wavelet interferences resulting from the narrow band nature of the seismic data and the heterogeneous nature of the geology itself. The effects produce errors of typically a fraction of a millisecond, but exceptionally in 4D data with poor repeatability up to 1 ms. In the second category are acquisition and processing errors. These are usually of the order of a few milliseconds but can reach up to 10s of milliseconds and are, therefore, essential to correct. It is possible to correct the effects of tides and seawater variations in marine acquisition if these changes are monitored and measured. Navigation and timing are identified as issues to consider carefully. For land data, daily and seasonal near‐surface variations are still problematic, and source and sensors must be buried to deliver interpretable time‐shifts. The impact of choices made during processing can be significant but is specific to the workflow and dataset and thus cannot be generically assessed. However, the effects from residual multiples can be identified and treated. Of moderate importance is the third category of errors, which consists of four items. Of these, the effect of lateral image shifts and amplitude effects are judged to play a minor role. Deviation from the assumption of vertical ray‐paths during post‐stack analysis appears to be of concern only for reservoirs with noticeably dipping structures and strong contrasts. The effect of pre‐stack variations on the post‐stack measurements remains a topic to be more thoroughly examined, and the conclusion is unclear. Finally, it is apparent that uncertainties in all categories are strongly dependent on the field setting and geographical location.

© 2023 European Association of Geoscientists & Engineers. © 2023 The Authors. Geophysical Prospecting published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.13391
2023-09-22
2026-02-18

  • From This Site

    /content/journals/10.1111/1365-2478.13391
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

/deliver/fulltext/gpr/71/8/gpr13391.html?itemId=/content/journals/10.1111/1365-2478.13391&mimeType=html&fmt=ahah

References

  1. Andersen, T., Sinke, K., Wilcox, L. & Kelly, I. (2011) 4D interpretation of the Terra Nova field, a structural and stratigraphical complex field with small 4D signals [Extended abstracts]. 73rd EAGE annual meeting, Vienna, Austria.
  2. Audebert, F.A. & Agut, C.A. (2014) Retrieval of 4D perturbations by application of warping in depth imaging contexts. 76th EAGE annual conference & exhibition, Amsterdam, The Netherlands.
  3. Baek, H. & Keho, T.H. (2015) A model‐based warping method for 4D event characterization [Extended abstracts]. 85th SEG annual meeting, New Orleans. SEG. pp. 5409–5413.
  4. Bakulin, A., Burnstad, R., Jervis, M. & Kelamis, P. (2012) Evaluating permanent seismic monitoring with shallow buried sensors in a desert environment [Extended abstracts]. 82nd annual international meeting. SEG. pp. 1–5. https://doi.org/10.1190/segam2012‐0951.1
  5. Bakulin, A., Smith, R. & Jervis, M. (2018) Permanent buried receiver monitoring of a carbonate reservoir in a desert environment. 80th EAGE conference and exhibition 2018. European Association of Geoscientists & Engineers. Vol. 2018, pp. 1–5.
  6. Barker, R., Wood, T. & Ørpen, O. (2003) Decimeter accuracy differential GPS for real time tidal monitoring in seismic applications. SEG technical program expanded abstracts 2003. Society of Exploration Geophysicists. pp. 11–14.
  7. Barley, B. (1999) Deepwater problems around the world. The Leading Edge, 18(4), 488–493.
     [Google Scholar]
  8. Berron, C., Michou, L., Cacqueray, B.D., Duret, F., Cotton, J. & Forgues, E. (2015) Permanent, continuous & unmanned 4D seismic monitoring: Peace River case study. SEG technical program expanded abstracts 2015. Society of Exploration Geophysicists. pp. 5419–5423.
  9. Bertrand, A. & MacBeth, C. (2003) Seawater velocity variations and real‐time reservoir monitoring. The Leading Edge, 22(4), pp. 351–355.
     [Google Scholar]
  10. Bertrand, A. & MacBeth, C. (2005) Repeatability enhancement in deep‐water permanent seismic installations: a dynamic correction for seawater velocity variations. Geophysical Prospecting, 53(2), 229–242.
     [Google Scholar]
  11. Bertrand, A. (2005) The impact of seawater velocity variations on time‐lapse seismic monitoring (Doctoral dissertation). Heriot‐Watt University.
     [Google Scholar]
  12. Hatchell, P. & Bourne, S. (2005) Rocks under strain: strain‐induced time‐lapse time‐shifts are observed for depleting reservoirs. The Leading Edge, 24(12), 1222–1225.
     [Google Scholar]
  13. Brain, J. (2017) Results from a 4D seismic campaign to unlock the remaining potential from the Rotliegend gas fields of the Southern North Sea [Extended abstracts]. 1st EAGE workshop on practical reservoir monitoring, Amsterdam, The Netherlands.
  14. Brain, J., Lassagne, T., Darnet, M. & van Loevezijn, P. (2017) Unlocking 4D seismic technology to maximize recovery from the pre‐salt Rotliegend gas fields of the Southern North Sea [Extended abstracts]. 8th Petroleum geology conference series, London, UK. Geological Society. pp. 1–7.
  15. Buland, A. & El Quair, Y. (2006), Bayesian time‐lapse inversion. Geophysics, 71(3), R43–R48.
     [Google Scholar]
  16. Burren, J. & Lecerf, D. (2015) Repeatability measure for broadband 4D seismic. 77th EAGE conference and exhibition 2015. European Association of Geoscientists & Engineers. Vol. 2015, pp. 1–5.
  17. Calvert, R. (2005a) Insights and methods for 4D reservoir monitoring and characterization. Society of Exploration Geophysicists and European Association of Geoscientists and Engineers.
     [Google Scholar]
  18. Calvert, R. (2005b) 4D technology: where are we, and where are we going?Geophysical Prospecting, 53(2), 161–171.
     [Google Scholar]
  19. Campbell, S., Lacombe, C., Brooymans, R., Hoeber, H. & White, S. (2011) Foinaven: 4D processing comes up trumps. The Leading Edge, 30(9), 1034–1040.
     [Google Scholar]
  20. Campbell, S., Schons, M., Mathew, S., Khalil, A., Riley, D., Hill, C., Allan, P., Gubbala, E., Alexe, M., Dervish‐Uman, C. & Deschizeaux, B. (2015) Optimising value through improved 4D seismic processing on 10 vintages‐Foinaven‐Schiehallion‐Loyal case history. 77th EAGE conference and exhibition 2015. European Association of Geoscientists & Engineers. Vol. 2015, pp. 1–5.
  21. Carter, G.C. (1987) Coherence and time delay estimation. Proceedings of the IEEE, 75, 236–255.
     [Google Scholar]
  22. Ceragioli, E., Bovet, L., Guilbot, J. & Toinet, S. (2010) The Dalia OBN project. 72nd EAGE conference and exhibition incorporating SPE EUROPEC 2010. European Association of Geoscientists & Engineers. pp. cp–161.
  23. Cox, B. & Hatchell, P. (2008) Straightening out lateral shifts in time‐lapse seismic data. First Break, 26, 93–98.
     [Google Scholar]
  24. Di, M., Zhang, A., Guo, B., Zhang, J., Liu, R. & Li, M. (2020) Evaluation of real‐time PPP‐based tide measurement using IGS real‐time service. Sensors, 20(10), 2968.
     [Google Scholar]
  25. Druzhinin, A. & MacBeth, C. (2001) Robust cross‐equalization of 4D‐4C PZ migrated data at Teal South. 71st annual international SEG meeting 2001, San Antonio, Texas, United States. Society of Exploration Geophysicists. pp. 1670–1673.
  26. Duan, Y., Yuan, S., Hatchell, P., Vila, J. & Wang, K. (2020) Estimation of time‐lapse timeshifts using machine learning. SEG technical program expanded abstracts 2020. Society of Exploration Geophysicists. pp. 3724–3728.
  27. Dvorak, I., MacBeth, C. & Amini, H. (2018) Evaluating 4D overburden velocity perturbation for the shearwater field via pre‐stack time‐shift inversion [Expanded abstracts]. 80th EAGE Conference & Exhibition 2018.
  28. Dvorak, I. & MacBeth, C. (2019) Deriving 4D velocity effects for the shearwater field with least squares pre‐stack time‐shift tomography. 81st EAGE conference and exhibition 2019. European Association of Geoscientists & Engineers. Vol. 2019, pp. 1–5.
  29. Dyce, M., Whitcombe, D., McKenzie, C. & Hodgson, L. (2004) The quantification of 4D noise. 66th EAGE conference & exhibition. European Association of Geoscientists & Engineers. pp. cp–133.
  30. Falahat, R. (2012) Quantitative monitoring of gas injection, exsolution and dissolution using 4D seismic (PhD thesis). Heriot‐Watt University, UK.
  31. Edgar, J.A. & Blanchard, T.D. (2015) Estimating overburden velocity changes from pre‐stack time‐shifts using linear tomography. 77th EAGE conference and exhibition‐workshops. European Association of Geoscientists & Engineers. Vol. 2015, pp. 1–5.
  32. Fehmers, G.C., Hunt, K., Brain, J.P., Bergler, S., Kaestner, U., Schutjens, P.M. & Burrell, R.V. (2007) Curlew D – Pushing the boundaries of 4D depletion signal in a gas condensate field, UK Central North Sea [Expanded abstracts]. 69th EAGE annual meeting, London.
  33. Fehmers, G. (2010) How compaction causes misalignment of multiples and false time‐shifts in time‐lapse seismic data. First Break, 28(7), 35–40. https://doi.org/10.3997/1365‐2397.2010018
     [Google Scholar]
  34. Grandi, A., Raymond, B. & Yuriza, N. (2010) Multi‐monitor warping inversion on Ekofisk field [Expanded abstracts]. 80th SEG annual meeting, Denver. Society of Exploration Geophysicists. pp. 4237–4241.
  35. Grubb, H., Tura, A. & Hanitzsch, C. (2001) Estimating and interpreting velocity uncertainty in migrated images and AVO attributes. Geophysics, 66, 1208–1216. doi: https://doi.org/10.1190/1.1487067
     [Google Scholar]
  36. Hall, S.A., MacBeth, C., Barkved, O.I. & Wild, P. (2002) Time‐lapse seismic monitoring of compaction and subsidence at Valhall through cross‐matching and interpreted warping of 3D streamer and OBC data [Expanded abstracts]. 72nd SEG annual meeting, Barcelona. pp. 1696–1699.
  37. Hall, S.A., MacBeth, C., Barkved, O.I. & Wild, P. (2005) Cross‐matching with interpreted warping of 3D streamer and 3D ocean‐bottom‐cable data at Valhall for time‐lapse assessment. Geophysical Prospecting, 53(2), 283–297.
     [Google Scholar]
  38. Hall, S.A., MacBeth, C., Stammeijer, J. & Omerod, M. (2006) Timelapse seismic analysis of pressure depletion in the Southern Gas Basin. Geophysical Prospecting, 54, 63–73.
     [Google Scholar]
  39. Hansen, O., Aronsen, H.A. & Østmo, S. (2009) 4D time‐shifts caused by depleting a HPHT reservoir – an example from the Kristin Field. In 71st EAGE conference and exhibition incorporating SPE EUROPEC 2009. European Association of Geoscientists & Engineers. pp. cp–127.
  40. Harris, P. (2005) Prestack repeatability of time‐lapse seismic data. SEG technical program expanded abstracts 2005. Society of Exploration Geophysicists. pp. 2410–2413.
  41. Hatab, M. & MacBeth, C. (2021) The impact of a multi‐realisation processing approach on the 4D interpretability. 82nd EAGE annual conference & exhibition. European Association of Geoscientists & Engineers. Vol. 2021, pp. 1–5.
  42. Hatab, M. & MacBeth, C. (2023) A pre‐stack time‐shift correction to improve amplitude fidelity post‐stack. 85th EAGE conference, Vienna.
  43. Hatchell, P., Wills, P. & Didraga, C. (2008) Identifying and removing effects of multiples on time‐lapse interpretation at Valhall. First Break, 26(5), 69–76.
     [Google Scholar]
  44. Helgerud, M.B., Miller, A.C., Johnston, D.H., Udoh, M.S., Jardine, B.G., Harris, C. & Aubuchon, N. (2011) 4D in the deepwater Gulf of Mexico: hoover, Madison, and Marshall fields. The Leading Edge, 30(9), 1008–1018.
     [Google Scholar]
  45. Hicks, E., Hoeber, H., Houbiers, M., Lescoffit, S.P., Ratcliffe, A. & Vinje, V. (2016) Time‐lapse full‐waveform inversion as a reservoir‐monitoring tool—a North Sea case study. The Leading Edge, 35(10), 850–858.
     [Google Scholar]
  46. Hoeber, H., Khalil, A., de Pierrepont, S., Dobo, Z., Neal, H., Purcell, C., Ubik, K., Singh, B. & Singh, Y. (2016) Application of Image Consistent Time‐strain Analysis to the 4D Baobab Data. 78th EAGE conference and exhibition 2016. European Association of Geoscientists & Engineers. Vol. 2016, pp. 1–5.
  47. Horman, K., Wills, P.B. & Didraga, C. (2011) Near‐surface variations and onshore time‐lapse seismic. 73rd EAGE conference and exhibition‐workshops 2011. European Association of Geoscientists & Engineers. pp. cp–239.
  48. Hubans, C. (2016) 4D noise understanding to validate 4D anomalies. 78th EAGE conference and exhibition 2016. European Association of Geoscientists & Engineers. Vol. 2016, pp. 1–5.
  49. Izadian, S. & MacBeth, C. (2021) Exploring value in pre‐stack time‐shifts with Ekofisk PRM data. 82nd EAGE annual conference & exhibition. European Association of Geoscientists & Engineers. Vol. 2021, pp. 1–5.
  50. Izadian, S. & MacBeth, C. (2022a) Measurement, interpretation and value of pre‐stack time‐shifts in a North Sea dataset. EAGE expanded abstracts, Madrid 2022.
  51. Izadian, S. & MacBeth, C. (2022b) Application of a new 4D time‐shift tomographic solution to a North Sea dataset. EAGE expanded abstracts, Madrid 2022.
  52. Jaramillo, A. (2020) Dynamic characterisation of non‐reservoir rocks from time‐lapse seismic data (PhD thesis). Heriot‐Watt University, Edinburgh.
  53. Jervis, M., Bakulin, A., Burnstad, R., Berron, C. & Forgues, E. (2012) Suitability of vibrators for time‐lapse monitoring in the Middle East. In SEG technical program expanded abstracts 2012. Society of Exploration Geophysicists. pp. 1–5.
  54. Jervis, M., Bakulin, A. & Smith, R. (2018) Making time‐lapse seismic work in a complex desert environment for CO2 EOR monitoring—design and acquisition. The Leading Edge, 37(8), 598–606.
     [Google Scholar]
  55. Ji, L. (2017) Integrating 4D seismic data into dynamic characterization of an HPHT reservoir (PhD thesis). Heriot‐Watt University, UK.
  56. Johnston, D.H. (2013) Practical applications of time‐lapse seismic data. Bunnik: Society of Exploration Geophysicists.
     [Google Scholar]
  57. Karimi, P. & Fomel, S. (2015) Stratigraphic coordinates: a coordinate system tailored to seismic interpretation. Geophysical Prospecting, 63(5), 1246–1255.
     [Google Scholar]
  58. Karimi, P., Fomel, S. & Zhang, R. (2016) Time‐lapse image registration using the stratigraphic coordinate system [Expanded abstracts]. 86th SEG annual meeting, Dallas. pp. 5500–5505.
  59. Khalil, A. & Hoeber, H. (2016) Wave‐equation‐based image warping. Geophysics, 81(1), V1–V6.
     [Google Scholar]
  60. Kiyashchenko, D., Wong, W.F., Cherief, D., Clarke, D., Duan, Y. & Hatchell, P. (2020) Unlocking seismic monitoring of stiff reservoirs with 4D OBN: a case study from Brazil pre‐salt. SEG technical program expanded abstracts 2020. Society of Exploration Geophysicists. pp. 3759–3763.
  61. Kragh, E.D. & Christie, P. (2002) Seismic repeatability, normalized RMS, and predictability. The Leading Edge, 21(7), 640–647.
     [Google Scholar]
  62. Kudarova, A., Hatchell, P., Brain, J. & MacBeth, C. (2016) Offset‐dependence of production‐related 4D time‐shifts: real data examples and modelling [Expanded abstracts]. 86th SEG annual meeting, Denver, USA. pp. 5395–5399.
  63. La Follet, J.R., Wills, P., Lopez, J.L., Przybysz‐Jarnut, J.K. & van Lokven, M. (2015) Continuous seismic reservoir monitoring at Peace River: initial results and interpretation [Expanded abstracts]. 85th SEG annual meeting, New Orleans, USA. pp. 5440–5444.
  64. Lacombe, C., Schultzen, J., Butt, S. & Lecerf, D. (2006) Correction for water velocity variations and tidal statics [Expanded abstracts]. SEG annual meeting, New Orleans. pp. 2881–2885.
  65. Landrø, M. & Stammeijer, J. (2004) Quantitative estimation of compaction and velocity changes using 4D impedance and traveltime changes. Geophysics, 69(4), 949–957.
     [Google Scholar]
  66. Lecerf, D., Boelle, J.L., Lafram, A. & Cantillo, J. (2011) Ocean bottom node processing in deep offshore environment for reservoir monitoring. 12th international congress of the Brazilian Geophysical Society. European Association of Geoscientists & Engineers. pp. 2095–2098.
  67. Lecerf, D., Burren, J., Hodges, E. & Barros, C. (2015) Repeatability measure for broadband 4D seismic [Expanded abstracts]. 85th SEG annual meeting, New Orleans. pp. 5483–5487.
  68. Leggott, R., Williams, R.G. & Skinner, M. (2000) Collocation of 4‐D seismic data in the presence of systematic navigational errors. The Leading Edge, 19(3), 303–307.
     [Google Scholar]
  69. Leguijt, J. & Jenkins, G. (2013) A 4D noise model used in probabilistic seismic inversion. SEG technical program expanded abstracts 2013. Society of Exploration Geophysicists. pp. 3262–3266.
  70. Li, C., Meadows, M. & Dygert, T. (2017) Chevron warping least‐squares inversion for 4D velocity change: gulf of Mexico case study [Expanded abstracts]. 87th SEG annual meeting, Anaheim. pp. 5829–5833.
  71. MacBeth, C., Mangriotis, M.D. & Hatchell, P. (2016) Evaluation of the spurious time‐shift problem [Expanded abstracts]. 86th SEG annual meeting, Dallas. pp. 5457–5462.
  72. MacBeth, C., Kudarova, A. & Hatchell, P. (2018) A semi‐empirical model of strain sensitivity for 4D seismic interpretation. Geophysical Prospecting, 66(7), 1327–1348.
     [Google Scholar]
  73. MacBeth, C., Mangriotis, M.‐D. & Amini, H. (2019) A review of post‐stack 4D seismic time‐shifts, Part 1: values and interpretation. Geophysical Prospecting, 67, 3–31.
     [Google Scholar]
  74. MacBeth, C., Amini, H. & Izadian, S. (2020) Methods of measurement for 4D seismic post‐stack time‐shifts. Geophysical Prospecting, 68(9), 2637–2664.
     [Google Scholar]
  75. MacKay, S., Fried, J. & Carvill, C. (2003) The impact of water‐velocity variations on deepwater seismic data. The Leading Edge, 22(4), 344–350.
     [Google Scholar]
  76. Medwin, H. (1975) Speed of sound in water: a simple equation for realistic parameters. The Journal of the Acoustical Society of America, 58(6), 1318–1319.
     [Google Scholar]
  77. Micksch, U., Klemm, H., Cherrett, A.J. & Christian, P.J. (2018) Integrated 4D processing and inversion workflow using multi‐well wavelet extraction. 80th EAGE conference and exhibition 2018. European Association of Geoscientists & Engineers. Vol. 2018, pp. 1–5.
  78. Ng, H.T., Bentley, L.R. & Krebes, E.S. (2005) Monitoring fluid injection in a carbonate pool using time‐lapse analysis: rainbow Lake case study. The Leading Edge, 24, 530–534.
     [Google Scholar]
  79. Narongsirikul, S. (2019) Ekofisk time‐lapse seismic monitoring of injection in shale. Sixth EAGE shale workshop. European Association of Geoscientists & Engineers. Vol. 2019, pp. 1–3.
  80. Omofoma, V. (2017) The quantification of pressure and saturation changes in clastic reservoirs using 4D seismic data (PhD thesis). Heriot‐Watt University, UK.
  81. Omofoma, V., MacBeth, C. & Amini, H. (2019) Intra‐survey reservoir fluctuations–implications for quantitative 4D seismic analysis. Geophysical Prospecting, 67(2), 282–297.
     [Google Scholar]
  82. Ong, B.S., Hembd, J., Srinivasan, A., Chu, D. & Johnston, D.H. (2015) Estimation of water layer correction in shallow time‐lapse streamer data sets. SEG technical program expanded abstracts 2015. Society of Exploration Geophysicists. pp. 5394–5398.
  83. Qu, S. & Verschuur, D.J. (2020) Simultaneous joint migration inversion for high‐resolution imaging/inversion of time‐lapse seismic datasets. Geophysical Prospecting, 68(4), 1167–1188.
     [Google Scholar]
  84. Rappin, D., Doukoure‐Tchissassa, F., Hubans, C. & Shchukina, N. (2019) Time‐lapse noise modeling for enhanced 4D interpretation. 81st EAGE conference and exhibition 2019. European Association of Geoscientists & Engineers. Vol. 2019, pp. 1–5.
  85. Reiser, C., Webb, B., Bertarini, M., Lecerf, D., Milluzzo, V. & Rizzetto, C. (2018) 4D analysis, combining shallow hydrophone and multi‐component streamer: the Cinguvu Field Offshore Angola example. SEG international exposition and annual meeting, October 2018, Anaheim, California, USA. doi: https://doi.org/10.1190/segam2018‐2996121.1
  86. Rickett, J.E. & Lumley, D.E. (2001) Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: a case study from the Gulf of Mexico. Geophysics, 66, 1015–1025.
     [Google Scholar]
  87. Røste, T., Stovas, A. & Landrø, M. (2005) Estimation of layer thickness and velocity changes using 4D prestack seismic data [Extended abstracts]. 67th EAGE annual meeting, Madrid, Spain. p. C010.
  88. Røste, T., Landrø, M. & Hatchell, P. (2007) Monitoring overburden layer changes and fault movements from time‐lapse seismic data on the Valhall Field. Geophysical Journal International, 170(3), 1100–1118.
     [Google Scholar]
  89. Røste, T. & Ke, G. (2017) Overburden 4D time‐shifts – indicating undrained areas and fault transmissibility in the reservoir. The Leading Edge, 36(5), 423–430.
     [Google Scholar]
  90. Ross, P. & Altan, M.S. (1997) Time‐lapse seismic monitoring some shortcomings in nonuniform processing. The Leading Edge, 16, 931–937.
     [Google Scholar]
  91. Saint Andre, C., Blanco, B., Hubans, C. & Paternoster, B. (2012) Innovative QCs for more effective 4D processing. 2012 SEG annual meeting. OnePetro.
  92. Sarkar, S., Gouveia, W.P. & Johnston, D.H. (2003) On the inversion of time‐lapse seismic data. SEG technical program expanded abstracts 2003. Society of Exploration Geophysicists. pp. 1489–1492.
  93. Silver, P.G., Daley, T.M., Niu, F. & Majer, E.L. (2007) Active source monitoring of cross‐well seismic travel time for stress‐induced changes. Bulletin of the Seismological Society of America, 97(1B), 281–293.
     [Google Scholar]
  94. Smith, P., Glenister, P., Yanez, M., Sundøy, K. & Kvam, Ø. (2021) Reprocessed time‐lapse seismic data provides new reservoir information on the Njord field. First Break, 39(2), 87–93.
     [Google Scholar]
  95. Staples, R., Nash, R., Hague, P. & Burrell, R. (2007) Using 4D seismic data and geomechanical modelling to understand pressure depletion in HPHT fields of the Central N. Sea [Extended abstracts]. 69th EAGE annual meeting, London, UK.
  96. Teien, O.M. (2017) Estimation of water velocity and tidal changes between 4D seismic vintages (Master's thesis). NTNU.
  97. Thore, P., Allouche, H., Lys, P.O. & Tarrass, I. (2010) Retrieving 4D signal in complex media using the full waveform inversion paradigm. 72nd EAGE conference and exhibition incorporating SPE EUROPEC 2010. European Association of Geoscientists & Engineers. pp. cp–161.
  98. Thore, P., de Verdiere, C.C. & McManus, E. (2012) Estimation of 4D signal in complex media: a fast track approach. SEG technical program expanded abstracts 2012. Society of Exploration Geophysicists. pp. 1–5.
  99. van Gestel, J.P. (2021) Ten years of time‐lapse seismic on Atlantis Field. The Leading Edge, 40(7), 494–501.
     [Google Scholar]
  100. van Gestel, J.P., Steiner, C. & Doré, T. (2019) Atlantis—finding a field within a field. GeoGulf Transactions, 69, 653–654.
     [Google Scholar]
  101. Vasco, D.W., Alfi, M., Hosseini, S.A., Zhang, R., Daley, T., Ajo‐Franklin, J.B. & Hovorka, S.D. (2019) The seismic response to injected carbon dioxide: comparing observations to estimates based upon fluid flow modeling. Journal of Geophysical Research: Solid Earth, 124(7), 6880–6907.
     [Google Scholar]
  102. Verschuur, D.J. (2013) Seismic multiple removal techniques: past, present and future. Houten, The Netherlands: EAGE Publications.
     [Google Scholar]
  103. Walker, W.F. & Trahey, G.E. (1995) A fundamental limit on delay estimation using partially correlated speckle signals. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 42(2), 301–308.
     [Google Scholar]
  104. Wang, K., Hatchell, P.J., Udengaard, C., Craft, K. & Dunn, S. (2013) Water velocity and tide measurement in marine seismic acquisition. 75th EAGE conference & exhibition incorporating SPE EUROPEC 2013. European Association of Geoscientists & Engineers. pp. cp–348.
  105. Wang, K. & Hatchell, P.J. (2013) Impact of receiver decimation and mispositioning on time‐lapse OBN data. 75th EAGE conference & exhibition incorporating SPE EUROPEC 2013. European Association of Geoscientists & Engineers. pp. 4890–4894.
  106. Williamson, P.R., Cherrett, A.J. & Sexton, P.A. (2007) A new approach to warping for quantitative time–lapse characterisation [Expanded abstracts]. 69th EAGE annual meeting, London. p. P056.
  107. Wong, M. (2017) Pressure and saturation estimation from PRM time‐lapse seismic data for a compacting reservoir (PhD thesis). Heriot‐Watt University, UK.
  108. Zadeh, M.H. & Landrø, M. (2011) Monitoring a shallow subsurface gas flow by time‐lapse refraction analysis. Geophysics, 76(6), O35–O43.
     [Google Scholar]
  109. Zadeh, H.M., Srivastava, R.P., Vedanti, N. & Landrø, M. (2010) Seismic monitoring of in situ combustion process in a heavy oil field. Journal of Geophysics and Engineering, 7(1), 16–29.
     [Google Scholar]
  110. Zhan, X., Chu, D., Wheelock, B., Johnston, D., Bandyopadhyay, K. & McAdow, D. (2017) 4D time‐shift and amplitude versus offset joint (AVO) inversion. SEG technical program expanded abstracts 2017. Society of Exploration Geophysicists. pp. 5855–5859.
/content/journals/10.1111/1365-2478.13391
Loading
A review and analysis of errors in post‐stack time‐shift interpretation
Geophysical Prospecting 71, 1497 (2023); https://doi.org/10.1111/1365-2478.13391
/content/journals/10.1111/1365-2478.13391
/content/journals/10.1111/1365-2478.13391
Loading

Data & Media loading...

  • Article Type: Review Article
Keyword(s): interpretation; monitoring; time lapse

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