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Geo-Marine Letters

, Volume 39, Issue 6, pp 447–467 | Cite as

3D seismic-derived bathymetry: a quantitative comparison with multibeam data

  • H. E. PowerEmail author
  • S. L. Clarke
Original
  • 90 Downloads

Abstract

This study compares bathymetry extracted from 3D seismic data at two Australian study sites of differing morphological complexities to two sources of collocated multibeam data: 50-m and 5-m multibeam digital bathymetric models (DBMs). Seafloor horizons are extracted from the 3D seismic data and converted to depth using sound velocity profiles collected during seismic acquisition. The resulting seismic-derived DBMs are independent of the multibeam DBMs and are shown to be highly comparable. For the morphologically simple site, the seismic-derived DBM was within ± 2% of the multibeam DBMs and, at 2σ, 95% of differences are in the range − 1.22 to 0.10% (− 1.02 to 0.48%) for the 50-m (5-m) multibeam DBM. For the morphologically complex site, > 80% (> 99%) of seismic-derived depths were within ± 2% (± 5%) of multibeam DBMs. At 2σ, 94% of differences are in the range − 3.48 to 1.69% (− 2.73% to 2.44%) for the 50-m (5-m) multibeam DBM. Increasing morphological complexity and slope angle were the most important factors affecting DBM comparisons, with seismic-derived depths typically underestimated in canyon thalwegs. Despite these differences, the higher data density, multichannel stacking and migration of the 3D seismic data resulted in seismic-derived DBMs with high resolution and improved feature relief and clarity when compared to multibeam DBMs for the conditions in this study (depths of 120–1900 m), particularly for morphological features such as individual rills and gullies. This method has the potential to expand the spatial coverage of high-resolution DBMs, for example, in Australia, by over 150,000 km2.

Keywords

3D seismic Multibeam Bathymetry Digital bathymetric model Seafloor morphology 

Notes

Acknowledgments

The authors thank Scott Nicholl, Kim Picard, and George Bernadel from Geoscience Australia for comments on an earlier version of this work and Robert Parums from Geoscience Australia for providing bathymetry data. The authors thank Kaya Wilson for constructive comments on an early version of the manuscript as well as Robin Beaman and an anonymous reviewer for their constructive comments.

Authors’ contributions

H.E.P. and S.L.C. analysed the data; H.E.P. obtained the 3D seismic data; H.E.P. and S.L.C. wrote the paper.

Funding information

Funding for this work was provided by a start-up grant to H.E.P. from the University of Newcastle.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 5m CSIRO Multibeam Bathymetry 2015 (2019). Geoscience Australia, CanberraGoogle Scholar
  2. Barnes PM, Lamarche G, Bialas J, Henrys S, Pecher I, Netzeband GL, Greinert J, Mountjoy JJ, Pedley K, Crutchley G (2010) Tectonic and geological framework for gas hydrates and cold seeps on the Hikurangi subduction margin, New Zealand. Mar Geol 272:26–48.  https://doi.org/10.1016/j.margeo.2009.03.012 CrossRefGoogle Scholar
  3. Boyd R, Ruming K, Roberts JJ (2004) Geomorphology and surficial sediments on the southeast Australian continental margin. Aust J Earth Sci 51:743–764CrossRefGoogle Scholar
  4. Brown CJ, Smith SJ, Lawton P, Anderson JT (2011) Benthic habitat mapping: a review of progress towards improved understanding of the spatial ecology of the seafloor using acoustic techniques. Estuar Coast Shelf Sci 92:502–520.  https://doi.org/10.1016/j.ecss.2011.02.007 CrossRefGoogle Scholar
  5. Bulat J (2005) Some considerations on the interpretation of seabed images based on commercial 3D seismic in the Faroe-Shetland Channel. Basin Ress 17:21–42.  https://doi.org/10.1111/j.1365-2117.2005.00253.x CrossRefGoogle Scholar
  6. Bulat J, Long D (2001) Images of the seabed in the Faroe-Shetland Channel from commercial 3D seismic data. Mar Geophys Res 22:345–367.  https://doi.org/10.1023/A:1016343431386 CrossRefGoogle Scholar
  7. Chand S, Rise L, Ottesen D, Dolan MFJ, Bellec V, Bøe R (2009) Pockmark-like depressions near the Goliat hydrocarbon field, Barents Sea: morphology and genesis. Mar Petrol Geol 26:1035–1042.  https://doi.org/10.1016/j.marpetgeo.2008.09.002 CrossRefGoogle Scholar
  8. Chand S et al (2012) Multiple episodes of fluid flow in the SW Barents Sea (Loppa high) evidenced by gas flares, pockmarks and gas hydrate accumulation. Earth Planet Sci Lett 331:305–314CrossRefGoogle Scholar
  9. Clarke S, Hubble T, Webster J, Airey D, de Carli E, Ferraz C, Reimer P, Boyd R, Keene J, Shipboard party SS12/2008 (2016) Sedimentology, structure and age estimate of five continental slope submarine landslides, eastern Australia. Aust J Earth Sci 63:1–22.  https://doi.org/10.1080/08120099.2016.1225600 CrossRefGoogle Scholar
  10. Conti A, D’Emidio M, Macelloni L, Lutken C, Asper V, Woolsey M, Jarnagin R, Diercks A, Highsmith RC (2016) Morpho-acoustic characterization of natural seepage features near the Macondo wellhead (ECOGIG site OC26, Gulf of Mexico). Deep Sea Res Part II: Topical Studies Oceanography 129:53–65.  https://doi.org/10.1016/j.dsr2.2015.11.011 CrossRefGoogle Scholar
  11. Cross V, Twichell D, Foster D, O'Brien T (2012) Apalachicola Bay interpreted seismic horizons and updated IRIS chirp seismic-reflection data. US Geological Survey,Google Scholar
  12. Fatti J, Smith G, Vail P, Strauss P, Levitt P (1994) Detection of gas in sandstone reservoirs using AVO analysis: a 3-D seismic case history using the Geostack technique. GEOPHYSICS 59:1362–1376.  https://doi.org/10.1190/1.1443695 CrossRefGoogle Scholar
  13. Fujiwara T, Kodaira S, No T, Kaiho Y, Takahashi N, Kaneda Y (2011) The 2011 Tohoku-Oki earthquake: displacement reaching the trench Axis. Science 334:1240–1240.  https://doi.org/10.1126/science.1211554 CrossRefGoogle Scholar
  14. Hammerstad E, Pohner F, Parthiot F, Bennett J (1991) Field testing of a new deep water multibeam echo sounder. In: OCEANS'91. Ocean technologies and opportunities in the Pacific for the 90's. Proceedings. IEEE, pp 743–749Google Scholar
  15. Heggland R (1997) Detection of gas migration from a deep source by the use of exploration 3D seismic data. Marine Geology 137:41–47.  https://doi.org/10.1016/S0025-3227(96)00077-1 CrossRefGoogle Scholar
  16. Heggland R (1998) Gas seepage as an indicator of deeper prospective reservoirs. A study based on exploration 3D seismic data. In: Gas seepage as an indicator of deeper prospective reservoirs. A study based on exploration 3D seismic data marine and petroleum geology, vol 15, pp 1–9.  https://doi.org/10.1016/S0264-8172(97)00060-3 CrossRefGoogle Scholar
  17. Hubble T, De Carli E (2015) Mechanisms and processes of the millennium drought river bank failures: lower Murray River, South Australia Goyder Institute for Water Research Technical ReportGoogle Scholar
  18. Jakobsson M, Macnab R, Mayer L, Anderson R, Edwards M, Hatzky J, Schenke HW, Johnson P (2008) An improved bathymetric portrayal of the Arctic Ocean: implications for ocean modeling and geological, geophysical and oceanographic analyses. Geophys Res Lett 35CrossRefGoogle Scholar
  19. Jibrin BW, Reston TJ, Westbrook GK (2013) Seismic-derived seabed topography: insights from the outer fold and thrust belt in the deep-water Niger Delta. Lead Edge 32:420–423CrossRefGoogle Scholar
  20. L’Heureux J-S, Hansen L, Longva O, Emdal A, Grande L (2010) A multidisciplinary study of submarine landslides at the Nidelva fjord delta, Central Norway–implications for geohazards assessments. Nor J Geol 90:1–20Google Scholar
  21. Laberg JS, Kawamura K, Amundsen H, Baeten N, Forwick M, Rydningen TA, Vorren TO (2014) A submarine landslide complex affecting the Jan Mayen ridge, Norwegian–Greenland Sea: slide-scar morphology and processes of sediment evacuation. Geo-Mar Lett 34:51–58.  https://doi.org/10.1007/s00367-013-0345-z CrossRefGoogle Scholar
  22. Lark RM, Marchant BP, Dove D, Green SL, Stewart H, Diesing M (2015) Combining observations with acoustic swath bathymetry and backscatter to map seabed sediment texture classes: the empirical best linear unbiased predictor. Sediment Geol 328:17–32.  https://doi.org/10.1016/j.sedgeo.2015.07.012 CrossRefGoogle Scholar
  23. Masson DG, Wynn RB, Talling PJ (2010) Large Landslides on Passive Continental Margins: Processes, Hypotheses and Outstanding Questions. In: Large landslides on passive continental margins: processes, hypotheses and outstanding questions vol 28. Submarine mass movements and their consequences. Springer, Dordrecht.  https://doi.org/10.1007/978-90-481-3071-9_13 CrossRefGoogle Scholar
  24. Mosher DC, LaPierre AB, Hughes-Clarke JE, Gilbert GR 2002 Theoretical comparison of seafloor surface renders from multibeam sonar and 3D seismic exploration data. In: Offshore Technology Conference, Houstan, Texas, U.S.A., 6–9 May 2002. p OTC 14272Google Scholar
  25. Mosher D, Bigg S, LaPierre A (2006) 3D seismic versus multibeam sonar seafloor surface renderings for geohazard assessment: case examples from the central Scotian slope. Lead Edge 25:1484–1494CrossRefGoogle Scholar
  26. Parums R, Spinoccia M (2018) 50m multibeam dataset of Australia 2018. Geoscience Australia, CanberraGoogle Scholar
  27. Project D3 (2019) Implementing monitoring of AMPs and the status of marine biodiversity assets on the continental shelf. National Environmental Science Programme. https://www.nespmarine.edu.au/project/project-d3-implementing-monitoring-amps-and-status-marine-biodiversity-assets-continental. Accessed 17-Jul 2019
  28. Rutledge A, Leonard D (2001) Role of multibeam sonar in oil and gas exploration and development. In: Offshore technology conference. Offshore Technology Conference, HoustonGoogle Scholar
  29. Schroot BM, Schüttenhelm RTE (2003) Shallow gas and gas seepage: expressions on seismic and otheracoustic data from the Netherlands North Sea. J Geochem Explor 78:305–309.  https://doi.org/10.1016/S0375-6742(03)00112-2 CrossRefGoogle Scholar
  30. Sen A, Ondréas H, Gaillot A, Marcon Y, Augustin J-M, Olu K (2016) The use of multibeam backscatter and bathymetry as a means of identifying faunal assemblages in a deep-sea cold seep. Deep Sea Res Part I: Oceanogr Res Pap 110:33–49.  https://doi.org/10.1016/j.dsr.2016.01.005 CrossRefGoogle Scholar
  31. Talling PJ, Paull CK, Piper DJ (2013) How are subaqueous sediment density flows triggered, what is their internal structure and how does it evolve? Direct observations from monitoring of active flows. Earth-Sci Rev 125:244–287CrossRefGoogle Scholar
  32. Walbridge S, Slocum N, Pobuda M, Wright DJ (2018) Unified geomorphological analysis workflows with benthic terrain modeler. Geosciences 8:94CrossRefGoogle Scholar
  33. Wessel P, Sandwell DT, Kim S-S (2010) The global seamount census. Oceanography 23:24–33CrossRefGoogle Scholar
  34. Wilson O, Buchanan C, Spinoccia M (2012) 50m multibeam dataset of Australia 2012. Geoscience Australia, CanberraGoogle Scholar
  35. Yerramilli SS, Yerramilli RC, Vedanti N, Sen MK, Srivastava RP (2013) Integrated reservoir characterization of an unconventional reservoir using 3D seismic and well log data: a case study of Balol field, India. 2013/1/1/Google Scholar
  36. Zakhour N, Shoemaker M, Lee D (2015) Integrated workflow using 3D seismic and Geomechanical properties with microseismic and stimulation data to optimize completion methodologies: Wolfcamp shale-oil play case study in the Midland Basin. 2015/10/13/Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Environmental and Life SciencesUniversity of NewcastleCallaghanAustralia
  2. 2.School of GeoscienceUniversity of SydneySydneyAustralia

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