1887
Volume 3, Issue 1
  • E-ISSN:
PDF

Abstract

The emerging technology of synthetic cone penetrometer tests (CPT) offers the potential for profiles of geotechnical resistance to be derived from 2D or 3D geophysical seismic survey data at any location across a site. This avoids the need for interpolation between geotechnical CPTs, alleviating the uncertainty introduced into the design process if a geotechnical CPT is not at the final location of a foundation or anchor. However, synthetic CPTs have a lower vertical resolution than geotechnical CPTs, which may range from a few tens of centimetres to more than a metre, depending on the acquisition equipment, sediment properties, depth and interpretation approach. The reduced resolution of synthetic CPTs can affect geotechnical design outcomes, potentially resulting in under- or over-design. In this study, the effect of CPT resolution on lateral pile resistance is explored to inform on the minimum resolution of synthetic CPTs that would be acceptable for geotechnical design and, in turn, the requirements for geophysical survey equipment and interpretation. Geotechnical CPT profiles from a case study site are systematically reduced in resolution from the field resolution of 0.01 m to a minimum resolution (i.e. maximum data interval) of 2.5 m. Use of artificially reduced-resolution geotechnical CPT data as a proxy for synthetic CPT data enables the comparative assessment of predicted pile volume and capacity in the same deposit at multiple resolutions. Results show an increased variation in predicted pile volume as CPT resolution decreases, and hence data interval increases. In this case study, for all trialled CPTs, a CPT data interval of 0.5 m enables a predicted minimum required pile volume within 3% of, but consistently below, that predicted with the full-resolution geotechnical CPT with a data interval of 0.01 m. This translates to a reduction in pile capacity of the same order of magnitude. Results also show that even the lowest resolution CPT (data interval of 2.5 m) provides a more accurate pile prediction than linear interpolation of full-resolution CPTs (0.01 m) from adjacent boreholes. The method presented here could be applied to preliminary CPTs, or extant knowledge of ground conditions near to or from a prospective site, to inform on the requirements for the geophysical survey or, retrospectively, to assess the confidence of relying on synthetic CPTs derived from acquired geophysical survey data for geotechnical design.

[open-access]

Loading

Article metrics loading...

/content/journals/10.1144/geoenergy2025-022
2025-11-18
2025-12-08
Loading full text...

Full text loading...

/deliver/fulltext/geoenergy/3/1/geoenergy2025-022.html?itemId=/content/journals/10.1144/geoenergy2025-022&mimeType=html&fmt=ahah

References

  1. American Institute of Steel Construction2017. Steel Construction Manual. 15th edn. American Institute of Steel Construction.
    [Google Scholar]
  2. Anastassopoulos, C., Charles, J.A. and Gourvenec, S.2023. Effect of CPT profile resolution on minimum required size of monopile for ultimate limit state design. In:Innovative Geotechnologies for Energy Transition. 9th International SUT Offshore Site Investigation and Geotechnics Conference Proceedings, 12–14 September 2023, London, UK, 393–400, doi: 10.3723/IPLP644910.3723/IPLP6449
    https://doi.org/10.3723/IPLP6449 [Google Scholar]
  3. API2021. RP 2GEO Geotechnical and Foundation Design Considerations. American Petroleum Institute.
    [Google Scholar]
  4. Atkinson, J.H.2007. The Mechanics of Soils and Foundations. 2nd edn. CRC Press, doi: 10.1201/978131527354910.1201/9781315273549
    https://doi.org/10.1201/9781315273549 [Google Scholar]
  5. Bolève, A., Eddies, R., Staring, M., Benboudiaf, Y., Pournaki, H. and Nepveaux, M.2025. Innovative cone resistance and sleeve friction prediction from geophysics based on a coupled geo-statistical and machine learning process. Artificial Intelligence in Geosciences, 6, doi: 10.1016/j.aiig.2025.10011010.1016/j.aiig.2025.100110
    https://doi.org/10.1016/j.aiig.2025.100110 [Google Scholar]
  6. Broms, B.B.1964. Lateral resistance of piles in cohesive soils. Journal of the Soil Mechanics and Foundations Division, 90, 27–63, doi: 10.1061/JSFEAQ.000061110.1061/JSFEAQ.0000611
    https://doi.org/10.1061/JSFEAQ.0000611 [Google Scholar]
  7. Burd, H.J., Taborda, D.M.G. et al.2020. PISA design model for monopiles for offshore wind turbines: application to a marine sand. Géotechnique, 70, 1048–1066, doi: 10.1680/jgeot.18.P.27710.1680/jgeot.18.P.277
    https://doi.org/10.1680/jgeot.18.P.277 [Google Scholar]
  8. Byrne, B., McAdam, R. et al.2015. New design methods for large diameter piles under lateral loading for offshore wind applications. In:Meyer, V. (ed.) Frontiers in Offshore Geotechnics III. CRC Press, 705–710, doi: 10.1201/b18442-910.1201/b18442‑9
    https://doi.org/10.1201/b18442-9 [Google Scholar]
  9. Carpentier, S., Peuchen, J. et al.2021. Generating synthetic CPTs from marine seismic reflection data using a neural network approach. Second EAGE Workshop on Machine Learning, 8–9 March 2021, online, 1–3, doi: 10.3997/2214-4609.20213200810.3997/2214‑4609.202132008
    https://doi.org/10.3997/2214-4609.202132008 [Google Scholar]
  10. Charles, J.A., Axtell, D. and Gourvenec, S.2023. Quantitative analysis approach to assess variability in seabed conditions across a large offshore windfarm site. In:Innovative Geotechnologies for Energy Transition. 9th International SUT Offshore Site Investigation Geotechnics Conference Proceedings, 12–14 September 2023, London, UK, 216–223, doi: 10.3723/GNIE432610.3723/GNIE4326
    https://doi.org/10.3723/GNIE4326 [Google Scholar]
  11. Chen, J., Vissinga, M., Shen, Y., Hu, S., Beal, E. and Newlin, J.2021. Machine learning-based digital integration of geotechnical and ultrahigh-frequency geophysical data for offshore site characterizations. Journal of Geotechnical and Geoenvironmental Engineering, 147, doi: 10.1061/(ASCE)GT.1943-5606.000270210.1061/(ASCE)GT.1943‑5606.0002702
    https://doi.org/10.1061/(ASCE)GT.1943-5606.0002702 [Google Scholar]
  12. Cox, P., Boylan, C. et al.2024. Nederwiek Zuid (NL) integrated ground model: AVO-compliant UHRS processing for elastic pre-stack inversion. First EAGE/SUT Workshop on Integrated Site Characterization for Offshore Renewable Energy, 22–23 May 2024, Boston, USA, 1–6, doi: 10.3997/2214-4609.20248001910.3997/2214‑4609.202480019
    https://doi.org/10.3997/2214-4609.202480019 [Google Scholar]
  13. DNV2021. DNV-RP-C212 Offshore Soil Mechanics and Geotechnical Engineering. Det Norske Veritas.
    [Google Scholar]
  14. DONG Energy2013. Burbo Bank Extension Offshore Wind Farm (BBW02) Substations SSC, Geotechnical Site Investigation, https://www.marinedataexchange.co.uk/details/TCE-217/2012-fugro-engineering-burbo-bank-extension-geotechnical-site-investigation/packages/715?type=Report&directory=%2F#downloads
    [Google Scholar]
  15. DONG Energy2014. Burbo Bank Extension Offshore Wind Farm (BBW02) Geotechnical Site Investigation (2014), Geotechnical Site Investigation Field-Work Report, Part B – Geotechnical Data, https://www.marinedataexchange.co.uk/details/TCE-224/2014-fugro-engineering-services-burbo-bank-extension-geotechnical-site-investigation/packages/756?type=Report&directory=%2F#downloads
    [Google Scholar]
  16. Forsberg, C.F., Lunne, T., Vanneste, M., James, L., Tjelta, T.I., Barwise, A. and Duffy, C.2017. Synthetic CPTS from intelligent ground models based on the integration of geology, geotechnics and geophysics as a tool for conceptual foundation design and soil investigation planning. In: Offshore Site Investigation Geotechnics Conference – Smarter Solutions for Future Offshore Developments. 8th International SUT Offshore Site Investigation Geotechnics Conference Proceedings, 12–14 September 2017, London, UK, 1254–1259, doi: 10.3723/OSIG17.125410.3723/OSIG17.1254
    https://doi.org/10.3723/OSIG17.1254 [Google Scholar]
  17. Gourvenec, S.2024. Offshore geotechnical challenges of the energy transition. Geomechanics for Energy and the Environment, 39, doi: 10.1016/j.gete.2024.10058410.1016/j.gete.2024.100584
    https://doi.org/10.1016/j.gete.2024.100584 [Google Scholar]
  18. GWEC2024. Global Offshore Wind Report 2024. Global Wind Energy Council, https://www.gwec.net/reports/globalofffshorewindreport
    [Google Scholar]
  19. IRENA and GWEC2021. A Next Decade Action Agenda to Advance SDG7 on Sustainable Energy for All, In Line with the Goals of the Paris Agreement on Climate Change. https://www.un.org/sites/un2.un.org/files/2021/09/irena_and_gwec_offshore_wind_energy_compact_-_final_1.pdf
    [Google Scholar]
  20. ISO2025. 19901-4 Specific Requirements for Offshore Structures Part 4: Geotechnical Design Considerations. 3rd edn. International Standardisation Organisation.
    [Google Scholar]
  21. Keaveny, J.1985. In-Situ Determination of Drained and Undrained Soil Strength Using the Cone Penetration Test. PhD dissertation, University of California, Berkeley.
    [Google Scholar]
  22. Klinkvort, R.T., Sauvin, G., Dujardin, J., Griffiths, L., Vardy, M.E. and Vanneste, M.2024. Cone penetration testing prediction using seismo-acoustic data. 85th EAGE Annual Conference & Exhibition, 10–13 June 2024, Oslo, Norway, 1–5, doi: 10.3997/2214-4609.202410143410.3997/2214‑4609.2024101434
    https://doi.org/10.3997/2214-4609.2024101434 [Google Scholar]
  23. Lehane, B.M.2019. E.H. Davis Memorial Lecture (2017): CPT-based design of foundations. Australian Geomechanics, 54(4), 23–48.
    [Google Scholar]
  24. Lesny, K. and Wiemann, J.2005. Design aspects of monopiles in German offshore wind farms. In:Gourvenec,S. and Cassidy, M. (eds) Frontiers in Offshore Geotechnics. CRC Press, 383–389, doi: 10.1201/noe041539063710.1201/noe0415390637
    https://doi.org/10.1201/noe0415390637 [Google Scholar]
  25. Marine Data Exchange2014. 2014, Fugro Engineering Services, Burbo Bank Extension Offshore Wind Farm, Geotechnical Site Investigation. Marine Data Exchange, https://www.marinedataexchange.co.uk/details/224/2014-fugro-engineering-services-burbo-bank-extension-offshore-wind-farm-geotechnical-site-investigation/packages
  26. Mayne, P.W.2007. Cone Penetration Testing State of Practice. NCHRP Project 20-05.
    [Google Scholar]
  27. Moshfeghi, S. and Eslami, A.2016. Study on pile ultimate capacity criteria and CPT-based direct methods. International Journal of Geotechnical Engineering, 12, 28–39, doi: 10.1080/19386362.2016.124415010.1080/19386362.2016.1244150
    https://doi.org/10.1080/19386362.2016.1244150 [Google Scholar]
  28. Myers, D.E.1984. Co-kriging – new developments. In:Verly, G., David, M., Journel, A.G. and Marechal, A. (eds) Geostatistics for Natural Resources Characterization. Springer, 295–305, doi: 10.1007/978-94-009-3699-7_1810.1007/978‑94‑009‑3699‑7_18
    https://doi.org/10.1007/978-94-009-3699-7_18 [Google Scholar]
  29. Ørsted2020. Burbo Bank Extension Offshore Wind Farm. Ørsted, https://orstedcdn.azureedge.net/-/media/www/docs/corp/uk/updated-project-summaries-06-19/sept-2020/200819_ps_burbo-bank-extension_v2_web-aw.pdf?rev=b097516c059f472c993bd8719569e531&hash=81CE5D1E81EE7145FD6F4C110E348EA2
    [Google Scholar]
  30. Peuchen, J., Van Kesteren, W., Vandeweijer, V., Carpentier, S. and Van Erp, F.2022. Upscaling 1 500 000 synthetic CPTs to voxel CPT models of offshore sites. In:Gottardi, G. and Tonni, L. (eds) Cone Penetration Testing 2022. CRC Press, 641–645, doi: 10.1201/9781003308829-9310.1201/9781003308829‑93
    https://doi.org/10.1201/9781003308829-93 [Google Scholar]
  31. Provenzano, G., Vardy, M.E. and Henstock, T.J.2017. Pre-stack full waveform inversion of ultra-high-frequency marine seismic reflection data. Geophysical Journal International, 209, 1593–1611, doi: 10.1093/gji/ggx11410.1093/gji/ggx114
    https://doi.org/10.1093/gji/ggx114 [Google Scholar]
  32. Putuhena, H., White, D.J., Gourvenec, S.M. and Sturt, F.2023. Geospatial assessment of future floating offshore wind challenges: UK case study exploring drag anchor suitability and requirements. In:Innovative Geotechnologies for Energy Transition. 9th International SUT Offshore Site Investigation Geotechnics Conference Proceedings, 12–14 September 2023, London, UK, 257–264, doi: 10.3723/HJMJ565510.3723/HJMJ5655
    https://doi.org/10.3723/HJMJ5655 [Google Scholar]
  33. Randolph, M. and Gourvenec, S.2011. Offshore Geotechnical Engineering. 1st edn. CRC Press, doi: 10.1201/978131527247410.1201/9781315272474
    https://doi.org/10.1201/9781315272474 [Google Scholar]
  34. Robertson, P.K.1990. Soil classification using the cone penetration test. Canadian Geotechnical Journal, 27, 151–158, doi: 10.1139/t90-01410.1139/t90‑014
    https://doi.org/10.1139/t90-014 [Google Scholar]
  35. Robertson, P.K.2009. Performance based earthquake design using the CPT. In:Kokusho, T., Tsukamoto, Y. and Yoshimine, M. (eds) Performance-Based Design in Earthquake Geotechnical Engineering: From Case History to Practice. CRC Press, 3–20, doi: 10.1201/NOE041555614910.1201/NOE0415556149
    https://doi.org/10.1201/NOE0415556149 [Google Scholar]
  36. Robertson, P.K. and Cabal, K.2022. Guide to Cone Penetration Testing. 7th edn. Gregg Drilling & Testing, Inc, https://www.cpt-robertson.com/PublicationsPDF/CPT-Guide-7th-Final-SMALL.pdf
    [Google Scholar]
  37. Robertson, P.K. and Campanella, R.G.1983. Interpretation of cone penetration tests. Part I: sand. Canadian Geotechnical Journal, 20, 718–733, doi: 10.1139/t83-07810.1139/t83‑078
    https://doi.org/10.1139/t83-078 [Google Scholar]
  38. Robertson, P.K. and Wride, C.E.1998. Evaluating cyclic liquefaction potential using the cone penetration test. Canadian Geotechnical Journal, 35, 442–459, doi: 10.1139/t98-01710.1139/t98‑017
    https://doi.org/10.1139/t98-017 [Google Scholar]
  39. Sauvin, G., Vanneste, M., Vardy, M.E., Klinkvort, R.T. and Forsberg, C.F.2019. Machine learning and quantitative ground models for improving offshore wind site characterization. Paper presented at the Offshore Technology Conference, 6–9 May 2019, Houston, Texas, doi: 10.4043/29351-MS10.4043/29351‑MS
    https://doi.org/10.4043/29351-MS [Google Scholar]
  40. Sauvin, G., Vardy, M., Klinkvort, R.T., Vanneste, M., Forsberg, C.F. and Kort, A.2022. State-of-the-art ground model development for offshore renewables – TNW case study. 3rd EAGE Global Energy Transition Conference & Exhibition, 7–9 November 2022, The Hague, Netherlands, 1–5, doi: 10.3997/2214-4609.20222110910.3997/2214‑4609.202221109
    https://doi.org/10.3997/2214-4609.202221109 [Google Scholar]
  41. Sauvin, G., Vanneste, M., Vardy, M., Klinkvort, R.T., Forsberg, C.F. and Kort, D.A.2024. Integration of geoscience data – the TNW offshore wind farm case study. Paper presented at the Offshore Technology Conference, 6–9 May 2024, Houston, Texas, doi: 10.4043/35476-MS10.4043/35476‑MS
    https://doi.org/10.4043/35476-MS [Google Scholar]
  42. Shoukat, G., Michel, G., Coughlan, M., Malekjafarian, A., Thusyanthan, I., Desmond, C. and Pakrashi, V.2023. Generation of synthetic CPTs with access to limited geotechnical data for offshore sites. Energies, 16, 3817, doi: 10.3390/en1609381710.3390/en16093817
    https://doi.org/10.3390/en16093817 [Google Scholar]
  43. Siemann, L., Masoudi, P. et al.2024. Comparison of different prediction methods to derive synthetic CPT profiles – an offshore wind farm case study from the German North Sea. Proceedings of the 7th International Conference on Geotechnical and Geophysical Site Characterization, 18–21 June 2024, Barcelona, Spain, doi: 10.23967/isc.2024.23310.23967/isc.2024.233
    https://doi.org/10.23967/isc.2024.233 [Google Scholar]
  44. Stuyts, B.2024. PLENARY LECTURE – machine learning tools for the treatment of offshore site investigations. Proceedings of the 7th International Conference on Geotechnical and Geophysical Site Characterization, 18–21 June 2024, Barcelona, Spain, doi: 10.23967/isc.2024.30810.23967/isc.2024.308
    https://doi.org/10.23967/isc.2024.308 [Google Scholar]
  45. Suryasentana, S.K. and Lehane, B.M.2014. Numerical derivation of CPT-based p-y curves for piles in sand. Géotechnique, 64, 186–194, doi: 10.1680/geot.13.P.02610.1680/geot.13.P.026
    https://doi.org/10.1680/geot.13.P.026 [Google Scholar]
  46. Tapoglou, E., Tattini, J. et al.2023. Clean Energy Technology Observatory: Wind Energy in the European Union – 2023 Status Report on Technology Development, Trends, Value Chains and Markets. Publications Office of the European Union, Luxembourg, doi: 10.2760/61864410.2760/618644
    https://doi.org/10.2760/618644 [Google Scholar]
  47. Truong, P. and Lehane, B.M.2014. Numerically derived CPT-based p-y curves for a soft clay modeled as an elastic perfectly plastic material. In:Robertson, P.K. and Cabal, K.L. (eds) Proceedings of 3rd International Conference on Cone Penetration Testing, 12–14 May 2014, Las Vegas, USA, 975–982.
    [Google Scholar]
  48. Vardy, M.E.2015. Deriving shallow-water sediment properties using post-stack acoustic impedance inversion. Near Surface Geophysics, 13, 143–154, doi: 10.3997/1873-0604.201404510.3997/1873‑0604.2014045
    https://doi.org/10.3997/1873-0604.2014045 [Google Scholar]
  49. Vardy, M. and Pinson, L.2018. Seismic attenuation – friend or foe. 3rd Applied Shallow Marine Geophysics Conference, 9–12 September 2018, Porto, Portugal, 1–5, doi: 10.3997/2214-4609.20180265810.3997/2214‑4609.201802658
    https://doi.org/10.3997/2214-4609.201802658 [Google Scholar]
  50. Vardy, M.E., Vanneste, M., Henstock, T.J., Clare, M.A., Forsberg, C.F. and Provenzano, G.2017. State-of-the-art remote characterization of shallow marine sediments: the road to a fully integrated solution. Near Surface Geophysics, 15, 387–402, doi: 10.3997/1873-0604.201702410.3997/1873‑0604.2017024
    https://doi.org/10.3997/1873-0604.2017024 [Google Scholar]
  51. Vardy, M.E., Clare, M.A., Vanneste, M., Forsberg, C.F. and Dix, J.K.2018. Seismic inversion for site characterization: when, where and why should we use it?Paper presented at the Offshore Technology Conference, 30 April–3 May 2018, Houston, Texas, doi: 10.4043/28730-MS10.4043/28730‑MS
    https://doi.org/10.4043/28730-MS [Google Scholar]
/content/journals/10.1144/geoenergy2025-022
Loading
/content/journals/10.1144/geoenergy2025-022
Loading

Data & Media loading...

  • Article Type: Research Article
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