1887

Abstract

Summary

Posiva Oy is responsible for preparation of final disposal of spent nuclear fuel in Olkiluoto and has done extensive research to ensure the over-all safety of the final disposal. Final disposal is scheduled to start in 2020's. Extensive geophysical survey programs have been executed in both deep boreholes and pilot holes located in the vicinity of planned disposal site. Scope of the automated fracture point calculation procedure was to automatically detect the most significant fractures from geophysical data based on known fracture locations and geophysical anomalies. This approach sets high demands for the processing and depth correction accuracy of the data. Automation was implemented using R programming language. Calculation procedure is applied to one hole at the time and processing constants were determined using existing data from pilot holes. Fracture point calculation procedure returns scaled parameter specific points and scaled total points for each fracture. Fractures are then classified based on their total points in order to determine their relevancy. The most relevant ones get the highest total points but in some cases it can also be beneficial to concentrate only on certain methods. Results are used in Rock Suitability Classification process together with geological and hydrogeological data.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201902457
2019-09-08
2020-02-20
Loading full text...

Full text loading...

References

  1. Heikkinen, E., Heinonen, S. and Ravimo, I.
    [2011] Semi-Automated Fracture Classification Procedure Based on Geophysical Drillhole Logging Data. Posiva Working Report 2011-88.
    [Google Scholar]
  2. McEwen, T.
    (ed.), Aro, S., Kosunen, P., Mattila, J., Pere, T. Käpyaho, A. and Hellä, P. [2012] Rock Suitability Classification - RSC 2012. Posiva 2012–24.
    [Google Scholar]
  3. RDocumentation, loess
    RDocumentation, loess. [2019, April 15] Retrieved from https://www.rdocumentation.org/packages/stats/versions/3.5.3/topics/loess
  4. The R Project for Statistical Computing
    The R Project for Statistical Computing. [2019, April 15] Retrieved from https://www.r-project.org/
  5. Tiensuu, K., Heikkinen, E., Kiuru, R. and Ravimo, I.
    [2017a] Geophysical Drillhole Logging and Imaging in Pilot Hole ONK-PH28 at Olkiluoto in Autum 2015. Posiva Working Report 2016-29.
    [Google Scholar]
  6. Tiensuu, K., Heikkinen, E., Ravimo, I. and Kiuru, R.
    [2017b] Geophysical Logging and Imaging of Drillholes OL-KR56, OL-KR57 and OL-KR57B at Olkiluoto in 2012-2015. Posiva Working Report 2016-58.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201902457
Loading
/content/papers/10.3997/2214-4609.201902457
Loading

Data & Media loading...

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