1887
  1. Home
  2. A-Z Publications
  3. Geophysical Prospecting
  4. Volume 73, Issue 4
  5. Article
Volume 73, Issue 4
  • E-ISSN: 1365-2478
PDF

Abstract

Abstract

Reducing the uncertainty of reservoir characterization requires to better identify the small‐scale structures of the subsurface from the available data. Studying the seismic response of meter‐scale, stratigraphic heterogeneities typically relies on the generation of reservoir models based on outcrop examples and their forward seismic modelling. To bridge geological information and seismic modelling, these methods allocate values of acoustic properties, such as mass‐density and P‐wave velocity, according to discretized properties like layer‐type lithology or facies units. This strategy matches the current workflow in seismic data inversion in industry, where modelling workflows are based on lithofacies distributions. However, from stratigraphic modelling, we know that meter‐scale heterogeneities occur within certain facies and lithologies. Here, we evaluate the difference on the seismic response between allocating acoustic properties in a grain size–based, semi‐continuous manner versus discretized manners based on lithology and facies classifications. To do so, we generate a reference geological simulation that we populate with acoustic properties, mass‐density and P‐wave velocity, using three different strategies: (1) based on grain size distribution; (2) based on facies distribution; and (3) based on lithology. The method we propose includes the generation of realistic geological simulations based on stratigraphic modelling and the transformation of its output into acoustic properties, honouring the intra‐lithology and intra‐facies, small‐scale structures. We, then, generate seismic data by applying a forward seismic modelling workflow. The synthetic data show that the grain size–based simulation allows the identification of small‐scale, stratigraphic heterogeneities, such as beds with strong density and velocity contrasts. These stratigraphic structures are smoothened or may completely disappear in the facies and lithology discretized simulations and, therefore, are not (well) represented in the synthetic seismic data. Recognizing meter‐scale, stratigraphic heterogeneities is relevant for the characterization of the fluid flow in the reservoir. However, current discrete and lithology‐based strategies in seismic inversion are not able to resolve such heterogeneities because real subsurface properties are not discrete properties but continuous, unless there are stratigraphic discontinuities such as erosional surfaces or faults. This research works towards a better understanding of the relationship between changes in these continuous properties and the observed seismic data by introducing greater complexity into the discretized geological simulations. Here, we use synthetic seismic images with the goal of eventually aiding in fine‐tuning seismic inversion methodologies applied to real seismic data. One pathway is to foster the development of inversion approaches that can leverage stratigraphic modelling to get stronger geological priors and replace the standard but inadequate multi‐Gaussian prior.

© 2025 European Association of Geoscientists & Engineers. © 2025 The Author(s). Geophysical Prospecting published by John Wiley & Sons Ltd on behalf of European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.70015
2025-04-17
2025-05-19

  • From This Site

    /content/journals/10.1111/1365-2478.70015
    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/73/4/gpr70015.html?itemId=/content/journals/10.1111/1365-2478.70015&mimeType=html&fmt=ahah

References

  1. Abolhassani, S. & Verschuur, D.J. (2024) Efficient preconditioned least‐squares wave‐equation migration. Geophysics, 89(3), S275–S288. Available from: https://doi.org/10.1190/geo2023‐0048.1
     [Google Scholar]
  2. Aki, K., & Paul, G. R. (2002). Quantitative Seismology. Vol. 2. CA: Univ. Sci. Books. Sausalito. 700.
  3. Allen, P.A. & Allen, J.R. (1990) Basin analysis: Principles and applications. Oxford: Blackwell Scientific Publications.
     [Google Scholar]
  4. Anell, I., Lecomte, I., Braathen, A. & Buckley, S.J. (2016) Synthetic seismic illumination of small‐scale growth faults, paralic deposits and low‐angle clinoforms: a case study of the Triassic successions on Edgeøya, NW Barents Shelf. Marine and Petroleum Geology, 77, 625–639. Available from: https://doi.org/10.1016/j.marpetgeo.2016.07.005
     [Google Scholar]
  5. Anthony, E.J. (2013) Storms, shoreface morphodynamics, sand supply, and the accretion and erosion of coastal dune barriers in the southern North Sea. Geomorphology (Amsterdam, Netherlands), 199, 8–21. Available from: https://doi.org/10.1016/J.GEOMORPH.2012.06.007
     [Google Scholar]
  6. Anthony, E.J. & Aagaard, T. (2020) The lower shoreface: morphodynamics and sediment connectivity with the upper shoreface and beach. Earth‐Science Reviews, 210, 103334. Available from: https://doi.org/10.1016/J.EARSCIREV.2020.103334
     [Google Scholar]
  7. Armitage, D.A. & Stright, L. (2010) Modeling and interpreting the seismic‐reflection expression of sandstone in an ancient mass‐transport deposit dominated deep‐water slope environment. Marine and Petroleum Geology, 27(1), 1–12. Available from: https://doi.org/10.1016/J.MARPETGEO.2009.08.013
     [Google Scholar]
  8. Backstrom, J., Jackson, D., Cooper, A. & Loureiro, C. (2015) Contrasting geomorphological storm response from two adjacent shorefaces. Earth Surface Processes and Landforms, 40(15), 2112–2120. Available from: https://doi.org/10.1002/ESP.3788
     [Google Scholar]
  9. Bailly, C., Fortin, J., Adelinet, M. & Hamon, Y. (2019) Upscaling of elastic properties in carbonates: a modeling approach based on a multiscale geophysical data set. Journal of Geophysical Research: Solid Earth, 124(12), 13021–13038. Available from: https://doi.org/10.1029/2019JB018391
     [Google Scholar]
  10. Bakke, K., Gjelberg, J. & Agerlin Petersen, S. (2008) Compound seismic modelling of the Ainsa II turbidite system, Spain: application to deep‐water channel systems offshore Angola. Marine and Petroleum Geology, 25(10), 1058–1073. Available from: https://doi.org/10.1016/j.marpetgeo.2007.10.009
     [Google Scholar]
  11. Bakke, K., Kane, I.A., Martinsen, O.J., Petersen, S.A., Johansen, T.A., Hustoft, S. et al. (2013) Seismic modeling in the analysis of deep‐water sandstone termination styles. AAPG Bulletin, 97(9), 1395–1419. Available from: https://doi.org/10.1306/03041312069
     [Google Scholar]
  12. Baldwin, B. & Butler, C.O. (1985) Compaction curves. AAPG Bulletin, 69(4), 622–626.
     [Google Scholar]
  13. Barajas‐Olalde, C., Mur, A., Adams, D.C., Jin, L., He, J., Hamling, J.A. et al. (2021) Joint impedance and facies inversion of time‐lapse seismic data for improving monitoring of CO2 incidentally stored from CO2 EOR. International Journal of Greenhouse Gas Control, 112, 103501. Available from: https://doi.org/10.1016/j.ijggc.2021.103501
     [Google Scholar]
  14. Beard, D.C. & Weyl, P.K. (1973) Influence of texture on porosity and permeability of unconsolidated sand. AAPG Bulletin, 57(2), 349–369. Available from: https://doi.org/10.1306/819A4272‐16C5‐11D7‐8645000102C1865D
     [Google Scholar]
  15. Berkhout, A.J. (Guus). (2014) Review paper: an outlook on the future of seismic imaging, Part I: forward and reverse modelling. Geophysical Prospecting, 62(5), 911–930. Available from: https://doi.org/10.1111/1365‐2478.12161
     [Google Scholar]
  16. Bhattacharya, J. & Walker, R.G. (1991) River‐ and wave‐dominated depositional systems of the upper cretaceous dunvegan formation, northwestern Alberta. Bulleting of Canadian Petroleum Geology, 39(2), 165–191.
     [Google Scholar]
  17. Bjørlykke, K. & Høeg, K. (1997) Effects of burial diagenesis on stresses, compaction and fluid flow in sedimentary basins. Marine and Petroleum Geology, 14(3), 267–276. Available from: https://doi.org/10.1016/S0264‐8172(96)00051‐7
     [Google Scholar]
  18. Boisvert, J.B., Manchuk, J.G. & Deutsch, C.V. (2009) Kriging in the presence of locally varying anisotropy using non‐euclidean distances. Mathematical Geosciences, 41(5), 585–601. Available from: https://doi.org/10.1007/s11004‐009‐9229‐1
     [Google Scholar]
  19. Bourgeois, A., Joseph, P. & Lecomte, J.C. (2004) Three‐dimensional full wave seismic modelling versus one‐dimensional convolution: the seismic appearance of the Grès d'Annot turbidite system. Geological Society Special Publication, 221, 401–417. Available from: https://doi.org/10.1144/GSL.SP.2004.221.01.22
     [Google Scholar]
  20. Cardiff, M. & Kitanidis, P.K. (2009) Bayesian inversion for facies detection: an extensible level set framework. Water Resources Research, 45(10). 1–15. Available from: https://doi.org/10.1029/2008WR007675
     [Google Scholar]
  21. Červený, V. (2001) Seismic ray theory. Cambridge: Cambridge University Press.
     [Google Scholar]
  22. Červený, V., Klimeš, L. & Pšenčík, I. (2007) Seismic ray method: Recent developments. Advances in Geophysics, 48, 1–126. Available from: https://doi.org/10.1016/S0065‐2687(06)48001‐8
     [Google Scholar]
  23. Charvin, K., Hampson, G.J., Gallagher, K.L., Storms, J.E.A. & Labourdette, R. (2011) Characterization of controls on high‐resolution stratigraphic architecture in wave‐dominated shoreface–shelf parasequences using inverse numerical modeling. Journal of Sedimentary Research, 81(8), 562–578. Available from: https://doi.org/10.2110/JSR.2011.48
     [Google Scholar]
  24. Chhoa, J.F. (2020) An adaptive approach to Gibbs’ Phenomenon. Hattiesburg: University of Southern Mississippi.
     [Google Scholar]
  25. Chilingar, G.V. (1964) Relationship between porosity, permeability, and grain‐size distribution of sands and sandstones. Developments in Sedimentology, 1, 71–75. Available from: https://doi.org/10.1016/S0070‐4571(08)70469‐2
     [Google Scholar]
  26. Cho, G.‐C., Dodds, J. & Santamarina, J.C. (2006) Particle shape effects on packing density, stiffness, and strength: natural and crushed sands. Journal of Geotechnical and Geoenvironmental Engineering, 132(5), 591–602. Available from: https://doi.org/10.1061/(ASCE)1090‐0241(2006)132:5(591)
     [Google Scholar]
  27. Chopra, S., Castagna, J.P. & Portniaguine, O. (2006) Seismic resolution and thin‐bed reflectivity inversion. CSEG Recorder, 31, 19–25. Available from: https://doi.org/10.1190/1.2369941
     [Google Scholar]
  28. Cordua, K.S., Hansen, T.M. & Mosegaard, K. (2012) Monte Carlo full‐waveform inversion of crosshole GPR data using multiple‐point geostatistical a priori information. Geophysics, 77(2), H19–H31. Available from: https://doi.org/10.1190/geo2011‐0170.1
     [Google Scholar]
  29. Cox, D.R., Newton, A.M.W. & Huuse, M. (2020) An introduction to seismic reflection data: acquisition, processing and interpretation. In Regional geology and tectonics: principles of geologic analysis. Academic Press: Elsevier, pp. 571–603 Available from: https://doi.org/10.1016/B978‐0‐444‐64134‐2.00020‐1
     [Google Scholar]
  30. Crepaldi, J.L., de Figueiredo, L.P., Zerilli, A., Oliveira, I.S. & Sinnecker, J.P. (2024) Bayesian joint inversion of seismic and electromagnetic data for reservoir lithofluid facies, including geophysical and petrophysical rock properties. Geophysics, 89(3), K1–K16. Available from: https://doi.org/10.1190/geo2022‐0546.1
     [Google Scholar]
  31. Davydenko, M. (2016) Full wavefield migration: seismic imaging using multiple scattering effects. Delft: TU Delft. Available from: https://doi.org/10.4233/uuid:1cda75d5‐8998‐49fe‐997e‐b38c9b7f8b8b
     [Google Scholar]
  32. Davydenko, M., & Verschuur, D. J. (2017). Full‐wavefield estimation of angle‐dependent reflectivity and migration velocity. Proceedings of the 87th Annual International Meeting SEG. 5631–5635.
     [Google Scholar]
  33. de Jager, J. (2021) Handbook: Risk and Volume Assessment. Self‐published.
  34. Eberhart‐Phillips, D., Han, D.H. & Zoback, M.D. (1989) Empirical relationships among seismic velocity, effective pressure, porosity, and clay content in sandstone. 54(1), 82–89. Available from: https://doi.org/10.1190/1.1442580
  35. Fagin, S.W. (1991) Seismic Modeling of Geologic Structures. Society of Exploration Geophysicists. Available from: https://doi.org/10.1190/1.9781560802754
     [Google Scholar]
  36. Falivene, O., Arbués, P., Ledo, J., Benjumea, B., Muñoz, J.A., Fernández, O. et al. (2010) Synthetic seismic models from outcrop‐derived reservoir‐scale three‐dimensional facies models: the Eocene Ainsa turbidite system (southern Pyrenees). AAPG Bulletin, 94(3), 317–343. Available from: https://doi.org/10.1306/08030908157
     [Google Scholar]
  37. Feng, R., Luthi, S.M., Gisolf, D. & Sharma, S. (2017) Obtaining a high‐resolution geological and petrophysical model from the results of reservoir‐orientated elastic wave‐equation‐based seismic inversion. Petroleum Geoscience, 23(3), 376–385. Available from: https://doi.org/10.1144/petgeo2015‐076
     [Google Scholar]
  38. Field, M.E. & Roy, P.S. (1984) Offshore transport and sand‐body formation; evidence from a steep, high‐energy shoreface, southeastern Australia. Journal of Sedimentary Research, 54(4), 1292–1302. Available from: https://doi.org/10.1306/212F85C1‐2B24‐11D7‐8648000102C1865D
     [Google Scholar]
  39. Folk, R.L. (1954) The distinction between grain size and mineral composition in sedimentary‐rock nomenclature. The Journal of Geology, 62, 344–359.
     [Google Scholar]
  40. Folk, R.L. & Ward, W.C. (1957) Brazos river bar [Texas]; a study in the significance of grain size parameters. Journal of Sedimentary Research, 27(1), 3–26. Available from: https://doi.org/10.1306/74D70646‐2B21‐11D7‐8648000102C1865D
     [Google Scholar]
  41. Fouedjio, F. (2017) Second‐order non‐stationary modeling approaches for univariate geostatistical data. Stochastic Environmental Research and Risk Assessment, 31(8), 1887–1906. Available from: https://doi.org/10.1007/s00477‐016‐1274‐y
     [Google Scholar]
  42. Friedman, G.M. (1962) On sorting, sorting coefficients, and the lognormality of the grain‐size distribution of sandstones. The Journal of Geology, 70(6), 737–753. http://www.journals.uchicago.edu/t‐and‐c
     [Google Scholar]
  43. Giles, M.R. (1997) Diagenesis: a quantitative perspective. Implications for basin modelling and rock property prediction. Berlin: Springer.
  44. Gonzalez, E.F., Gesbert, S. & Hofmann, R. (2016) Adding geologic prior knowledge to Bayesian lithofluid facies estimation from seismic data. Interpretation, 4(3), SL1–SL8. Available from: https://doi.org/10.1190/INT‐2015‐0220.1
     [Google Scholar]
  45. González, E.F., Mukerji, T. & Mavko, G. (2008) Seismic inversion combining rock physics and multiple‐point geostatistics. Geophysics, 73(1), R11–R21. Available from: https://doi.org/10.1190/1.2803748
     [Google Scholar]
  46. Grana, D. (2018) Joint facies and reservoir properties inversion. Geophysics, 83(3), M15–M24. Available from: https://doi.org/10.1190/geo2017‐0670.1
     [Google Scholar]
  47. Grana, D. (2019) Joint inversion of facies and reservoir properties. In 81st EAGE conference and exhibition, European Association of Geoscientists & Engineers.pp. 1–5. Available from: https://doi.org/10.3997/2214‐4609.201901298
  48. Granjeon, D. (2019) Use of high‐performance stratigraphic forward modelling to improve siliciclastic and carbonate reservoir depositional architecture description. Journal of the Japanese Association for Petroleum Technology, 84(1), 59–70. Available from: https://doi.org/10.3720/japt.84.59
     [Google Scholar]
  49. Granjeon, D. & Joseph, P. (1999) Concepts and applications of A 3‐D multiple lithology, diffusive model in stratigraphic modeling. In Numerical experiments in stratigraphy: recent advances in stratigraphic and sedimentologic computer simulations. SEPM Society for Sedimentary Geology, Available from: https://doi.org/10.2110/PEC.99.62.0197
     [Google Scholar]
  50. Grasseau, N., Grélaud, C., López‐Blanco, M. & Razin, P. (2019) Forward seismic modeling as a guide improving detailed seismic interpretation of deltaic systems: example of the Eocene Sobrarbe delta outcrop (South‐Pyrenean foreland basin, Spain), as a reference to the analogous subsurface Albian‐Cenomanian Torok‐Nanushuk Delta of the Colville Basin (NPRA, USA). Marine and Petroleum Geology, 100, 225–245. Available from: https://doi.org/10.1016/J.MARPETGEO.2018.11.010
     [Google Scholar]
  51. Grippa, A., Hurst, A., Palladino, G., Iacopini, D., Lecomte, I. & Huuse, M. (2019) Seismic imaging of complex geometry: forward modeling of sandstone intrusions. Earth and Planetary Science Letters, 513, 51–63. Available from: https://doi.org/10.1016/j.epsl.2019.02.011
     [Google Scholar]
  52. Hampson, G.J. & Storms, J.E.A. (2003) Geomorphological and sequence stratigraphic variability in wave‐dominated, shoreface‐shelf parasequences. Sedimentology, 50(4), 667–701. Available from: https://doi.org/10.1046/j.1365‐3091.2003.00570.x
     [Google Scholar]
  53. Han, D.H., Nur, A. & Morgan, D. (1986) Effects of porosity and clay content on wave velocities in sandstones. Geophysics, 51(11), 2093–2107. Available from: https://doi.org/10.1190/1.1442062
     [Google Scholar]
  54. Harbaugh, J.W. (1993) Simulating sedimentary basins: an Overview of the SEDSIM model and its relevance to sequence stratigraphy. Geoinformatics, 4(3), 123–126.
     [Google Scholar]
  55. Hodgetts, D. & Howell, J.A. (2000) Synthetic seismic modelling of a large‐scale geological cross‐section from the Book Cliffs, Utah, USA. Petroleum Geoscience, 6(3), 221–229. Available from: https://doi.org/10.1144/PETGEO.6.3.221
     [Google Scholar]
  56. Holberg, O., Pajchel, J., Riste, P. & Helle, H.B. (1990) Comparison of ray tracing and finite‐difference modeling. SEG Technical Program Expanded Abstracts, 1990, 1037–1041. Available from: https://doi.org/10.1190/1.1889901
     [Google Scholar]
  57. Holgate, N.E., Hampson, G.J., Jackson, C.A.‐L. & Petersen, S.A. (2014) Constraining uncertainty in interpretation of seismically imaged clinoforms in deltaic reservoirs, Troll field, Norwegian North Sea: insights from forward seismic models of outcrop analogs. AAPG Bulletin, 98(12), 2629–2663. Available from: https://doi.org/10.1306/05281413152
     [Google Scholar]
  58. Holgate, N.E., Jackson, C.A.‐L., Hampson, G.J. & Dreyer, T. (2015) Seismic stratigraphic analysis of the Middle Jurassic Krossfjord and Fensfjord formations, troll oil and gas field, northern North Sea. Marine and Petroleum Geology, 68, 352–380. Available from: https://doi.org/10.1016/j.marpetgeo.2015.08.036
     [Google Scholar]
  59. Howell, J.A., Skorstad, A., MacDonald, A., Fordham, A., Flint, S., Fjellvoll, B. et al. (2008) Sedimentological parameterization of shallow‐marine reservoirs. Petroleum Geoscience, 14(1), 17–34. Available from: https://doi.org/10.1144/1354‐079307‐787
     [Google Scholar]
  60. Hubbert, M.K. & Rubey, W.W. (1959) Role of fluid pressure in mechanics of overthrust faulting: I. Mechanics of fluid‐filled porous solids and its application to overthrust faulting. GSA Bulletin, 70(2), 115–166.
     [Google Scholar]
  61. Jackson, A., Jackson, A., Stright, L., Hubbard, S.M. & Romans, B.W. (2019) Static connectivity of stacked deep‐water channel elements constrained by high‐resolution digital outcrop models. AAPG Bulletin, 103(12), 2943–2973. Available from: https://doi.org/10.1306/03061917346
     [Google Scholar]
  62. Jackson, M.D., Hampson, G.J. & Sech, R.P. (2009) Three‐dimensional modeling of a shoreface‐shelf parasequence reservoir analog: part 2. Geologic controls on fluid flow and hydrocarbon recovery. American Association of Petroleum Geologists Bulletin, 93(9), 1183–1208. Available from: https://doi.org/10.1306/05110908145
     [Google Scholar]
  63. Journel, A.G. (2005) Beyond covariance: the advent of multiple‐point geostatistics. In Geostatistics banff 2004. Berlin: Springer, pp. 225–233. Available from: https://doi.org/10.1007/978‐1‐4020‐3610‐1_23
     [Google Scholar]
  64. Jullum, M. & Kolbjørnsen, O. (2016) A Gaussian‐based framework for local Bayesian inversion of geophysical data to rock properties. Geophysics, 81(3), R75–R87. Available from: https://doi.org/10.1190/geo2015‐0314.1
     [Google Scholar]
  65. Keen, T.R., Slingerland, R.L., Bentley, S.J., Furukawa, Y., Teague, W.J. & Dykes, J.D. (2012) Sediment transport on continental shelves: storm bed formation and preservation in heterogeneous sediments. Sediments, morphology and sedimentary processes on continental shelves: advances in technologies, research, and applications. Hoboken, NJ: Wiley, pp. 295–310. Available from: https://doi.org/10.1002/9781118311172.CH14
     [Google Scholar]
  66. Kelly, K.R., Ward, R.W., Treitel, S. & Alford, R.M. (1976) Synthetic seismograms—a finite difference approach. Geophysics, 41(1), 2–27. Available from: https://doi.org/10.1190/1.1440605
     [Google Scholar]
  67. Kemper, M. & Gunning, J. (2014) Joint impedance and facies inversion—seismic inversion redefined. First Break, 32(9), 89–95. Available from: https://doi.org/10.3997/1365‐2397.32.9.77968
     [Google Scholar]
  68. Ketzer, J.M., Morad, S., Evans, R. & Al‐Aasm, I.S. (2002) Distribution of diagenetic alterations in fluvial, deltaic, and shallow marine sandstones within a sequence stratigraphic framework: evidence from the Mullaghmore formation (Carboniferous), NW Ireland. Journal of Sedimentary Research, 72(6), 760–774. Available from: https://doi.org/10.1306/042202720760
     [Google Scholar]
  69. Klausen, T.G., Torland, J.A., Eide, C.H., Alaei, B., Olaussen, S. & Chiarella, D. (2018) Clinoform development and topset evolution in a mud‐rich delta—the Middle Triassic Kobbe Formation, Norwegian Barents Sea. Sedimentology, 65(4), 1132–1169. Available from: https://doi.org/10.1111/sed.12417
     [Google Scholar]
  70. Kumar, N. & Sanders, J.E. (1976) Characteristics of shoreface storm deposits; modern and ancient examples. Journal of Sedimentary Research, 46(1), 145–162. Available from: https://doi.org/10.1306/212F6EDD‐2B24‐11D7‐8648000102C1865D
     [Google Scholar]
  71. Laigle, L., Joseph, P., De Marsily, G. & Violette, S. (2013) 3‐D process modelling of ancient storm‐dominated deposits by an event‐based approach: Application to Pleistocene‐to‐modern Gulf of Lions deposits. Marine Geology, 335, 177–199. Available from: https://doi.org/10.1016/j.margeo.2012.11.007
     [Google Scholar]
  72. Lis, P. & Wysocka, A. (2012) Middle miocene deposits in carpathian foredeep: facies analysis and implications for hydrocarbon reservoir prospecting. Annales Societatis Geologorum Poloniae, 82, 239–253.
     [Google Scholar]
  73. Liu, Y., Harding, A., Abriel, W. & Strebelle, S. (2004) Multiple‐point simulation integrating wells, three‐dimensional seismic data, and geology. AAPG Bulletin, 88(7), 905–921. Available from: https://doi.org/10.1306/02170403078
     [Google Scholar]
  74. Liu, Y. & Sen, M.K. (2009) Advanced finite‐difference methods for seismic modeling. Geohorizons, 14, 5–16.
     [Google Scholar]
  75. Machuca‐Mory, D.F. & Deutsch, C.V. (2013) Non‐stationary geostatistical modeling based on distance weighted statistics and distributions. Mathematical Geosciences, 45(1), 31–48. Available from: https://doi.org/10.1007/s11004‐012‐9428‐z
     [Google Scholar]
  76. Madsen, O. (1991) Mechanics of cohesionless sediment transport in coastal waters. In Proceedings of the Coastal Sediments, ASCE. pp. 15–27.
  77. Merletti, G.D. & Torres‐Verdín, C. (2006) Accurate detection and spatial delineation of thin‐sand sedimentary sequences via joint stochastic inversion of well logs and 3D Prestack seismic amplitude data. In Paper presented at the SPE annual technical conference and exhibition, San Antonio, Texas, USA. OnePetro. Available from: https://doi.org/10.2118/102444‐MS
  78. Merriman, R.J., Highley, D.E. & Cameron, D.G. (2003) Definition and characteristics of very‐fine grained sedimentary rocks : clay, mudstone, shale and slate. Nottingham: British Geological Survey.
  79. Mitchell, N.C. & Zhao, Z. (2023) Effects of currents and waves on the morphologies of coastal sandy clinoforms: sediment mobility calculations based on current meter and wave data from Southern California, U.S.A. Journal of Sedimentary Research, 93(7), 488–501. Available from: https://doi.org/10.2110/JSR.2023.002
     [Google Scholar]
  80. Mur, A. & Waters, K. (2018) Play scale seismic characterization: using basin models as an input to seismic characterization in new and emerging plays. SEG Technical Program Expanded Abstracts, 2018, 555–559. Available from: https://doi.org/10.1190/segam2018‐2992809.1
     [Google Scholar]
  81. Neidell, N. S. (1986). Amplitude variation with offset. The Leading Edge, 5(3), 47–51.
     [Google Scholar]
  82. Ostrander, W. J. (1984). Plane‐wave reflection coefficients for gas sands at nonnormal angles of incidence. Geophysics, 49, 1637–1648.
     [Google Scholar]
  83. Paola, C. (2000) Quantitative models of sedimentary basin filling. Sedimentology, 47, (Supplement 1), 121–178. Available from: https://doi.org/10.1046/J.1365‐3091.2000.00006.X
     [Google Scholar]
  84. Patro, B.C. & Sahu, B.K. (1974) Factor analysis of sphericity and roundness data of clastic quartz grains: environmental significance. Sedimentary Geology, 11(1), 59–78. Available from: https://doi.org/10.1016/0037‐0738(74)90005‐0
     [Google Scholar]
  85. Pemberton, E.A.L., Stright, L., Fletcher, S. & Hubbard, S.M. (2018) The influence of stratigraphic architecture on seismic response: reflectivity modeling of outcropping deepwater channel units. Interpretation, 6(3), T783–T808. Available from: https://doi.org/10.1190/INT‐2017‐0170.1
     [Google Scholar]
  86. Pendrel, J. & Schouten, H. (2020) Facies— the drivers for modern inversions. The Leading Edge, 39(2), 102–109. Available from: https://doi.org/10.1190/tle39020102.1
     [Google Scholar]
  87. Picard, M.D. (1971) Classification of fine‐grained sedimentary rocks. Journal of Sedimentary Research, 41(1), 179–195. Available from: https://doi.org/10.1306/74D7221B‐2B21‐11D7‐8648000102C1865D
     [Google Scholar]
  88. Pyrcz, M.J., McHargue, T., Clark, J., Sullivan, M. & Strebelle, S. (2012) Event‐based geostatistical modeling: description and applications. In: Abrahamsen, P., Hauge, R., Kolbjørnsen, O. (Eds.) Geostatistics oslo 2012. Quantitative geology and geostatistics. Dordrecht: Springer, pp. 27–38. Available from: https://doi.org/10.1007/978‐94‐007‐4153‐9_3
     [Google Scholar]
  89. Pyrcz, M.J., Sech, R.P., Covault, J.A., Willis, B.J., Sylvester, Z. & Sun, T. (2015) Stratigraphic rule‐based reservoir modeling. Bulletin of Canadian Petroleum Geology, 63(4), 287–303. Available from: https://doi.org/10.2113/GSCPGBULL.63.4.287
     [Google Scholar]
  90. Shuey, R. T. (1985). A simplification of the Zoeppritz equations. Geophysics, 50, 609–614.
     [Google Scholar]
  91. Quiquerez, A., Allemand, P., Dromart, G. & Garcia, J. (2004) Impact of storms on mixed carbonate and siliciclastic shelves: insights from combined diffusive and fluid‐flow transport stratigraphic forward model. Basin Research, 16(4), 431–449. Available from: https://www.academia.edu/23222459/Impact_of_storms_on_mixed_carbonate_and_siliciclastic_shelves_insights_from_combined_diffusive_and_fluid_flow_transport_stratigraphic_forward_model
     [Google Scholar]
  92. Rabbel, O., Galland, O., Mair, K., Lecomte, I., Senger, K., Spacapan, J.B. et al. (2018) From field analogues to realistic seismic modelling: a case study of an oil‐producing andesitic sill complex in the Neuquén Basin, Argentina. Journal of the Geological Society, 175(4), 580–593. Available from: https://doi.org/10.1144/JGS2017‐116
     [Google Scholar]
  93. Rawlinson, N., Hauser, J. & Sambridge, M. (2008) Seismic ray tracing and wavefront tracking in laterally heterogeneous media. Advances in Geophysics, 49, 203–273. Available from: https://doi.org/10.1016/S0065‐2687(07)49003‐3
     [Google Scholar]
  94. Ringrose, P. & Bentley, M. (2015) Reservoir model design: a practitioner's guide. Berlin: Springer.
     [Google Scholar]
  95. Rogers, J.J.W. & Head, W.B. (1961) Relationships between porosity, median size, and sorting coefficients of synthetic sands. Journal of Sedimentary Petrology, 31(3), 467–470.
     [Google Scholar]
  96. Roncarolo, F. & Grana, D. (2010) Improved reservoir characterization integrating seismic inversion, rock physics model, and petroelastic log facies classification: a real case application. In: Proceedings of the SPE annual technical conference and exhibition, Florence, Italy, OnePetro. Available from: https://doi.org/10.2118/134919‐MS
  97. Rongier, G., Storms, J.E.A. & Cuesta Cano, A. (2023) pyBarSim (Version 1). 4TU. ResearchData. Software: https://github.com/grongier/pybarsim
  98. Roy, P.S., Cowell, P.J., Ferland, M.A., Thom, B.G. & van de Plassche, O. (1995) Wave‐dominated coasts. In Coastal evolution: late quaternary shoreline morphodynamics. Cambridge: Cambridge University Press, pp. 121–186.
     [Google Scholar]
  99. Schön, J.H. (2011) Chapter 1–Rocks—their classification and general properties. In Handbook of petroleum exploration and production, vol. 8, Random Publications, pp. 1–16. Available from: https://doi.org/10.1016/S1567‐8032(11)08001‐3
     [Google Scholar]
  100. Sclater, J.G. & Christie, P.A.F. (1980) Continental stretching: an explanation of the Post‐Mid‐Cretaceous subsidence of the central North Sea Basin. Journal of Geophysical Research: Solid Earth, 85(B7), 3711–3739. Available from: https://doi.org/10.1029/JB085iB07p03711
     [Google Scholar]
  101. Sech, R.P., Jackson, M.D. & Hampson, G.J. (2009) Three‐dimensional modeling of a shoreface‐shelf parasequence reservoir analog: part 1. surface‐based modeling to capture high‐resolution fades architecture. American Association of Petroleum Geologists Bulletin, 93(9), 1155–1181. Available from: https://doi.org/10.1306/05110908144
     [Google Scholar]
  102. Sheriff, R. E., & Geldart, L. P. (1995). Exploration Seismology. Cambridge University Press.
  103. Shuster, M.W. & Aigner, T. (1994) Two‐dimensional synthetic seismic and log cross sections from stratigraphic forward models. AAPG Bulletin, 78(3), 409–431. Available from: https://doi.org/10.1306/BDFF90C8‐1718‐11D7‐8645000102C1865D
     [Google Scholar]
  104. Simmons, M., Davies, A. & Cowliff, L. (2023) Plausible characterisation of subsurface geology is essential for the energy transition. First Break, 41(6), 69–74. Available from: https://doi.org/10.3997/1365‐2397.fb2023045
     [Google Scholar]
  105. Sømme, T.O., Howell, J.A., Hampson, G.J. & Storms, J.E.A. (2008) Genesis, architecture, and numerical modeling of intra‐parasequence discontinuity surfaces in wave‐dominated deltaic deposits: upper cretaceous sunnyside member, blackhawk formation, Book Cliffs, Utah, U.S.A. In Recent advances in models of siliciclastic shallow‐marine stratigraphy. SEPM (Society for Sedimentary Geology), pp. 421–441. Available from: https://doi.org/10.2110/PEC.08.90.0421
     [Google Scholar]
  106. Storms, J.E.A. (2003) Event‐based stratigraphic simulation of wave‐dominated shallow‐marine environments. Marine Geology, 199(1–2), 83–100. Available from: https://doi.org/10.1016/S0025‐3227(03)00144‐0
     [Google Scholar]
  107. Storms, J.E.A. & Hampson, G.J. (2005) Mechanisms for forming discontinuity surfaces within shoreface‐shelf parasequences: sea level, sediment supply, or wave regime?Journal of Sedimentary Research, 75(1), 67–81. Available from: https://doi.org/10.2110/jsr.2005.007
     [Google Scholar]
  108. Storms, J.E.A. & Swift, D.J.P. (2003) Shallow‐marine sequences as the building blocks of stratigraphy: insights from numerical modelling. Basin Research, 15(3), 287–303. Available from: https://doi.org/10.1046/j.1365‐2117.2003.00207.x
     [Google Scholar]
  109. Storms, J.E.A., Weltje, G.J., Van Duke, J.J., Geel, C.R. & Kroonenberg, S.B. (2002) Process‐response modeling of wave‐dominated coastal systems: simulating evolution and stratigraphy on geological timescales. Journal of Sedimentary Research, 72(2), 226–239. Available from: https://doi.org/10.1306/052501720226
     [Google Scholar]
  110. Suh, H.S., Kim, K.Y., Lee, J. & Yun, T.S. (2017) Quantification of bulk form and angularity of particle with correlation of shear strength and packing density in sands. Engineering Geology, 220, 256–265. Available from: https://doi.org/10.1016/j.enggeo.2017.02.015
     [Google Scholar]
  111. Swift, D.J.P., Phillips, S. & Thorne, J.A. (1991) Sedimentation on continental margins, IV. Lithofacies and depositional systems. In Swift, D. J. P., Oertel, G. F., Tillman, R. W. & Thorne, J. A. (Eds.), Shelf sand and sandstone bodies: geometry, facies and sequence stratigraphy. vol. 14. Hoboken, NJ: Wiley, pp. 89–152
     [Google Scholar]
  112. Tahir, S., Musta, B., Asis, J. & Hanis, F. (2018) Wave and tide influence in Neogene paralic hydrocarbon potential reservoirs in Sabah. ASM Science Journal, 11(2), 278–292.
     [Google Scholar]
  113. Taylor, K.G., Gawthorpe, R.L., Curtis, C.D., Marshall, J.D. & Awwiller, D.N. (2000) Carbonate cementation in a sequence‐stratigraphic framework: upper cretaceous sstones, book cliffs, Utah‐Colorado. Journal of Sedimentary Research, 70(2), 360–372. Available from: https://doi.org/10.1306/2DC40916‐0E47‐11D7‐8643000102C1865D
     [Google Scholar]
  114. Tetzlaff, D.M. (2005) Modelling coastal sedimentation through geologic time. Journal of Coastal Research, 21((3), 610–617. Available from: https://doi.org/10.2112/04‐704A.1
     [Google Scholar]
  115. Tetzlaff, D.M. & Harbaugh, J.W. (1989) Simulating clastic sedimentation (computer methods in the geosciences) In: Tetzlaff, D. M. & Harbaugh, W. (Eds.). London: Van Nostrand Reinhold.
     [Google Scholar]
  116. Tomasso, M., Bouroullec, R. & Pyles, D.R. (2010) The use of spectral recomposition in tailored forward seismic modeling of outcrop analogs. AAPG Bulletin, 94(4), 457–474. Available from: https://doi.org/10.1306/08240909051
     [Google Scholar]
  117. Trask, P.D. (1930) Mechanical analysis of sediments by centrifuge. Economic Geology, 25(6), 581–599.
     [Google Scholar]
  118. Tyler, N. & Finley, R.J. (1991) Architectural controls on the recovery of hydrocarbons from sandstone reservoers. In The three‐dimensional facies architecture of terrigenous clastic sediments and its implications for hydrocarbon discovery and recovery. Tulsa: SEPM Society for Sedimentary Geology, pp. 1–5. Available from: https://doi.org/10.2110/csp.91.03.0001
     [Google Scholar]
  119. Wan, L., Hurter, S., Bianchi, V., Li, P., Wang, J. & Salles, T. (2022) The roles and seismic expressions of turbidites and mass transport deposits using stratigraphic forward modeling and seismic forward modeling. Journal of Asian Earth Sciences, 232, 105110. Available from: https://doi.org/10.1016/j.jseaes.2022.105110
     [Google Scholar]
  120. Wang, R., Jia, X. & Hu, T. (2004) The precise finite difference method for seismic modeling. Applied Geophysics, 1(2), 69–74. Available from: https://doi.org/10.1007/s11770‐004‐0001‐5
     [Google Scholar]
  121. Wendebourg, J. & Harbaugh, J.W. (1997) Chapter 4 Endowing simulated sequences with petrophysical flow properties. In Wendebourg, J. & Arbaugh, J.W. (Eds.) Computer methods in the geosciences vol. 16. Oxford: Pergamon, p. 81. Available from: https://doi.org/10.1016/S1874‐561X(97)80005‐3
     [Google Scholar]
  122. Willis, B.J. & Tang, H. (2010) Three‐dimensional connectivity of point‐bar deposits. Journal of Sedimentary Research, 80(5), 440–454. Available from: https://archives.datapages.com/data/sepm/journals/080/080005/440_gsjsedres800440.htm
     [Google Scholar]
  123. Yilmaz, Ö. (2001) Seismic data analysis. Houston, TX: Society of Exploration Geophysicists.
     [Google Scholar]
  124. Zeng, H., Zhu, X. & Zhu, R. (2013) New insights into seismic stratigraphy of shallow‐water progradational sequences: subseismic clinoforms. Interpretation, 1(1), SA35–SA51. Available from: https://doi.org/10.1190/INT‐2013‐0017.1
     [Google Scholar]
/content/journals/10.1111/1365-2478.70015
Loading
Discretization of small‐scale, stratigraphic heterogeneities and its impact on the seismic response: Lessons from the application of process‐based modelling
Geophysical Prospecting 73, 1280 (2025); https://doi.org/10.1111/1365-2478.70015
/content/journals/10.1111/1365-2478.70015
/content/journals/10.1111/1365-2478.70015
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): imaging; interpretation; petrophysics; reservoir geophysics; seismics

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