1887
Volume 40 Number 8
  • E-ISSN: 1365-2478

Abstract

A

We describe an approach to the construction of an engineering geological expert system for identification of sub‐bottom soils in accordance with some predefined nomenclature. The following principles of integrated interpretation of engineering geophysical and geotechnical data are presented: Firstly, the transformation of physical data (compressional‐ and shear‐wave velocities, compressional‐wave attenuation coefficients, electrical conductivity, etc.) for each of the medium points into subjective probabilities for the soil belonging to each type listed in the nomenclature, and secondly, the extrapolation of local geotechnical data (primarily drilling data) to the surrounding space by means of diffusion of the initial membership function distribution, resulting in the same set of probabilities for soil types at each point in the medium under consideration. Aggregation of the fuzzy information obtained, sufficient for reaching a conclusion for most points in the medium, is carried out by means of Bayesian summation. An example is given of integrated interpretation of real data obtained from four different sources (compressional‐ and shear‐wave velocity sections () and (), and two boreholes) related to the same profile.

Loading

Article metrics loading...

/content/journals/10.1111/j.1365-2478.1992.tb00559.x
2006-04-27
2024-04-25
Loading full text...

Full text loading...

References

  1. Belash, V.A.1981. Methods of processing and interpretation of marine VES data [in Russian]. Express-Information (VIEMS): Marine Geology and Geophysics1, 7–20.
    [Google Scholar]
  2. Berzon, I.S., Yepinatieva, A.M., Pariyskaja, G.N. and Starodubrovskaja, S.P.1962. Dynamic Characteristics of Seismic Waves in Real Media [in Russian]. Izdatelstvo AN USSR, Moscow.
  3. Borisov, A.N., Krumberg, O.A. and Fiodorov, I.P.1990. Decision‐Making on the Basis of Fuzzy Models: Examples of Application [in Russian]. Zinatne, Riga.
  4. Code of practice for site investigations. British Standard 5930, 1981.
  5. Doyen, P.M.1988. Porosity from seismic data: A geostatistical approach. Geophysics53, 1263–1275.
    [Google Scholar]
  6. Doyen, P.M., Guidish, T.M. and de Buyl, M.H.1989. Seismic discrimination of lithology in sand/shale reservoirs: A Bayesian approach. 59th SEG meeting, Dallas, Expanded Abstracts , 719–722.
  7. Duda, R.O.1980. The Prospector system for mineral exploration. Stanford Research Institute International, Final Report.
    [Google Scholar]
  8. Fournier, F.1989. Extraction of quantitative geologic information from seismic data with multidimensional statistical analyses: Part 1: Methodology; Part 2: A case history. 59th SEG meeting, Dallas, Expanded Abstracts , 726–733.
  9. Goryainov, N.N. and Lyakhovitsky, F.M.1979. Seismic Methods in Engineering Geophysics [in Russian]. Nedra, Moscow.
  10. Kovalevsky, E.V.1991. Processing and Interpretation of Stoneley waves, registered in engineering studies on aquatories [in Russian]. Ph.D. thesis, Institute of Oceanology of the Academy of Sciences, Moscow.
  11. Kovalevsky, E.V., Yefremov, V.P. and Lumanov, A.A.1990. Application of Stoneley waves in shallow water engineering studies. Proceedings: 6th international congress International Association of Engineering Geology. D. G.Price (ed.), 1095–1100. Balkema, Rotterdam.
    [Google Scholar]
  12. Soils
    Soils : Classification. USSR Standard 25100‐82. 1982. [in Russian].
  13. Thadani, S.G., Alabert, F. and Journel, A.G.1987. An integrated geostatistical/pattern recognition technique for characterization of reservoir spatial variability. 57th SEG meeting, New Orleans, Expanded Abstracts , 372–375.
  14. West, J.1985. Toward an expert system for identification of minerals in thin section. Mathematical Geology17, 743–753.
    [Google Scholar]
  15. Zadeh, L.1965. Fuzzy sets. Information and Control8, 338–353.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/j.1365-2478.1992.tb00559.x
Loading
  • Article Type: Research Article

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