Comparison of Methodologies for Statistical Evaluation of Characteristic Soil Properties for Top Hole Design
- Aline Viana Esteves (Federal University of Alagoas) | Christiano Augusto Ferrario Várady Filho (Federal University of Alagoas) | Eduardo Toledo Lima Junior (Federal University of Alagoas) | João Paulo Lima Santos (Federal University of Alagoas) | Rafael Dias (Petrobras) | Fábio Sawada Cutrim (Petrobras)
- Document ID
- Society of Petroleum Engineers
- SPE Drilling & Completion
- Publication Date
- May 2020
- Document Type
- Journal Paper
- 2020.Society of Petroleum Engineers
- top hole design, conductor casing, characteristic soil
- 2 in the last 30 days
- 30 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 35.00|
Evaluation of characteristic values of geotechnical parameters (used for oil well design) is associated with uncertainties inherent to the geological processes that change soil strata. Statistical analysis of soil data allows one to deal rationally with these uncertainties. This work addresses some normative recommendations and literature models for statistical characterization of undrained shear strength and submerged unit weight in offshore soils, providing more information to conductor casing design. Three methodologies were selected for the analysis. The NORSOK G-001 (2004) standard recommends using mean values computed conservatively. Lacasse et al. (2007b) propose that the characteristic value should be the mean value minus one-half of a standard deviation of the parameter under analysis. DNV-RP-C207 (2012) suggests different methodologies for dependent and independent soil variables, though both methods of calculating the characteristic value involve linear regressions. Using data from geotechnical investigations that characterize eight oil wells located in two Brazilian offshore basins, the selected methodologies were applied to obtain the characteristic values and compared to each other. The analysis is carried out with data from 17 piezocone penetration tests (CPTu) associated with the eight wells mentioned above. It is noted that the NORSOK recommendation leads to the highest characteristic values, which are assumed tending to the mean value of the data set over the well depth. The values obtained using Lacasse et al. (2007a, 2007b) methodology are more conservative than NORSOK methodology and stand as its lower bound. The models suggested by DNV perform differently when applied to the geotechnical parameters. The dependent variables methodology fits both undrained strength and unit weight accurately. Analysis shows that undrained strength is better described using the methodology for standard deviation proportional to the depth, while for the unit weight, accurate results are obtained by using constant standard deviation. The lower bound procedure proposed by DNV provides, in general, higher results in the first meters and more conservative values along the depth when compared with the other methodologies. Regarding all the formulations addressed, differences between them increase for wells whose CPTu data present higher dispersion. This larger dispersion suggests applications of different statistical-based approaches in order to reliably characterize offshore soil data. The data sets analyzed comprise different levels of scattering and soil heterogeneity, and comparing the statistical recommendations brings additive information for the designer to set the characteristic values of soil properties, aiming for the decision-making process on top hole drilling applications (e.g., conductor casing design). To the authors’ knowledge, few papers perform this comparative analysis.
|File Size||2 MB||Number of Pages||8|
API RP-2GEO, Geotechnical and Foundation Design Considerations. 2011. Washington, DC, USA: API.
Cheon, J. and Gilbert, R. 2014. Modeling Spatial Variability in Offshore Geotechnical Properties for Reliability-Based Foundation Design. Struct Saf 49: 18–26. https://doi.org/10.1016/j.strusafe.2013.07.008.
Ching, J., Wu, S. S., and Phoon, K. K. 2015. Statistical Characterization of Random Field Parameters using Frequentist and Bayesian Approaches. Can Geotech J 53 (2): 285–298. https://doi.org/10.1139/cgj-2015-0094.
Clayton, C. and Power, P. 2002. Managing Geotechnical Risk in Deepwater. Presented at Offshore Site Investigation and Geotechnics ‘Diversity and Sustainability’; Proceedings of an International Conference, London, UK, 26–28 November. SUT-OSIG-02-425.
DNV-RP-C207, Statistical Representation of Soil Data. 2012. Høvik, Norway: Det Norske Veritas.
Lacasse, S., Guttormsen, T., Nadim, F. et al. 2007a. Use of Statistical Methods for Selecting Design Soil Parameters. Paper presented at the Offshore Site Investigation and Geotechnics, Confronting New Challenges and Sharing Knowledge, London, UK, 11–13 September. SUT-OSIG-07-449.
Lacasse, S., Nadim, F., Andersen, K. H. et al. 2013. Reliability of API, NGI, ICP and Fugro Axial Pile Capacity Calculation Methods. Paper presented at the Offshore Technology Conference, Houston, Texas, USA, 6–9 May. OTC-24063-MS. https://doi.org/10.4043/24063-MS.
Lacasse, S. Nadim, F., Rahim, A. et al. 2007b. Statistical Description of Characteristic Soil Properties. Paper presented at the Offshore Technology Conference, Houston, Texas, USA, 30 April–3 May. OTC-19117-MS. https://doi.org/10.4043/19117-MS.
NORSOK G-001, Marine Soil Investigations. 2004. Lysaker, Norway: Standards Norway.
NORSOK N-001, Integrity of Offshore Structures, edition 7. 2010. Lysaker, Norway: Standards Norway.
Phoon, K. K. and Kulhawy, F. H. 1999. Characterization of Geotechnical Variability. Can Geotech J 36 (4): 612–624. https://doi.org/10.1139/t99-038.
Silva, P. and Santos, J. 2017. Representação Estatística de Dados de Solo segundo a Norma DNV-RP-C207: A Resistência Não-Drenada como Parâmetro Dependente do Solo. Paper presented at the 9° Congresso Brasileiro de P&D em Petróleo e Gás, Maceió, Brazil.