Journals →  Gornyi Zhurnal →  2015 →  #10 →  Back

METHODS OF ROCK MASS EXPLORATION IN RADIOACTIVE WASTE ISOLATION
ArticleName Modeling lithologic heterogeneity in bed of sedimentation at deep repository for liquid radioactive waste
DOI 10.17580/gzh.2015.10.04
ArticleAuthor Savelieva E. A., Suskin V. V., Rastorguev A. V., Ponizov A. V.
ArticleAuthorData

Author 1:
Name & Surname: Savelieva E. A.
Company: Institute of Problems of Safe Nuclear Power Development, Russian Academy of Sciences
Work Position: Head of Laboratory, Senior Researcher
Scientific Degree: Candidate of Physico-Mathematical Sciences
Contacts: esav@ibrae.ac.ru


Author 2:
Name & Surname: Suskin V. V.
Company: Institute of Problems of Safe Nuclear Power, Russian Academy of Sciences
Work Position: Engineer-Researcher


Author 3:
Name & Surname: Rastorguev A. V.
Company: Institute of Problems of Safe Nuclear Power, Russian Academy of Sciences
Work Position: Senior Researcher
Scientific Degree: Candidate of Engineering Sciences


Author 4:
Name & Surname: Ponizov A. V.
Company: Zheleznogorsk Division, National Operator for Radioactive Waste Management (NO RAO), Krasnoyarsk Territory
Work Position: Director

Abstract

The presented research is concerned with a series of estimates made to determine applicability of a structure of stratified sedimentary rocks for long-term disposal and safe isolation of liquid radioactive waste. This paper offers two new approaches to parametrization of geo-percolation model to correctly account for heterogeneity of properties of geological medium. In the offered approaches, the heterogeneity of properties is modeled using lithologic heterogeneities of hydrogeological layers in a bed of sedimentation. The both approaches use input data on distribution of lithologic types (hydrofacies) in drill wells and the pumping test data. This paper gives theoretical description of the proposed approaches and exemplifies their application. The first method is construction of a field of local effective permeability factors in cells of analysis grid for a geo-percolation model. The field is constructed based on interpolation of permeability factors at points with the known lithologic structure. The values at these points are assessed by the permeability factors of hydrofacies preliminary calibrated using the pumping test data. The second method constructs, vice versa, the field of hyrofacies first, based on the distribution of lithologic types in drill wells and then calibrates the permeability factors of hydrofacies. The construction of the field of hydrofacies uses the probabilistic classification method based on the kernel probability density estimate of a class (hydrofacies). This method enables natural incorporation of the model of hydrofacies into the process of automated calibration of parameters. The application of the method is discussed in terms of an artificial example and in the framework of parametrization of GEOPOLIS program designed for geo-percolation and geomigration modeling of deep geological repository for liquid radioactive waste—Severny test ground.

keywords Deep liquid RAW repository, sedimentation bed heterogeneity, aquifer, percolation parameters, hydrofacies model, parameter calibration, classification, modeling methods.
References

1. Rybalchenko A. I., Pimenov M. K., Kostin P. P. et al. Glubinnoe zakhoronenie zhidkikh radioaktivnykh otkhodov (Deep disposal of liquid radioactive wastes). Moscow : IzdAT, 1994. 256 p.
2. IAEA Safety Standards Series No. SSR-5. Disposal of Radioactive Waste. Vienna : IAEA, 2011. 104 p. Available at : http://www-pub.iaea.org/MTCD/publications/PDF/Pub1449_web.pdf (accessed: August 17, 2015).
3. Renard P., de Marsily G. Calculating equivalent permeability: a review. Advances in Water Resources. 1997. Vol. 20, No. 5-6. pp. 253–278.
4. Tavassoli Z., Carter J. N., King P. R. Errors in History Matching. SPE Journal. 2004. Vol. 3, No. 9. pp. 352–361.
5. Zimmerman D. A., de Marsily G., Gotway C. A. et al. A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow. Water Resources Research. 1998. Vol. 34, No. 6. pp. 1373–1413.
6. RamaRao B.S., LaVenue A.M., de Marsily G., Marietta M.G. Pilot point methodology for automated calibration of an ensemple of conditionally simulated transmissivity fields, 1. Theory and computational experiments. Water Resources Research. 1995. Vol. 31, No. 3. pp. 475–493.
7. Freedman V. L., Chen X., Finsterle S. et al. A high-performance workflow system for subsurface simulation. Environmental Modelling & Software. 2014. Vol. 55, No. 1. pp. 176–189.
8. Dell’Arciprete D., Bersezio R., Felletti F., Giudici M., Comunian A., Renard P. Comparison of Three Geostatistical Methods for Hydrofacies Simulation: A Test on Alluvial Sediments. Hydrogeology Journal. 2012. Vol. 20, No. 2. pp. 299–311.
9. Guastaldi1 E., Carloni1 A., Pappalardo G., Nevini J. Geostatistical Methods for Lithological Aquifer Characterization and Groundwater Flow Modeling of the Catania Plain Quaternary Aquifer (Italy). Journal of Water Resource and Protection. 2014. Vol. 6, No. 4. pp. 272–296.
10. Allard D., D’Or D., Froidevaux R. An efficient maximum entropy approach for categorical variable prediction. European Journal of Soil Science. 2011. Vol. 62, No. 3. pp. 381–393.
11. Robert C. The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation. New York : Springer, 2007. 602 p.
12. Parzen E. On Estimation of a Probability Density Function and Model. Annals of Mathematical Statistics. 1962. Vol. 33, No. 3. pp. 1065–1076.
13. Efron B. Estimating the error rate of a prediction rule: Improvement on cross-validation. Journal of the American Association. 1983. Vol. 78, Iss. 382. pp. 316–333.
14. Savelyeva E., Rastorguev A. Fuzzy Parameterization of a Filtration Model for a Non-homogeneous Sedimentary Rock. Mathematics of Planet Eather. Seria Lecture Notes in Earth System Sciences. Berlin : Springer, 2014. pp. 131–134.
15. Zimmerman H.-J. Fuzzy Set Theory and its Applications. Dordrecht : Kluwer Academic Publisher, 1996. 315 p.
16. Olsthoorn T. N. Effective parameter optimization for ground-water model calibration. Groundwater. 1995. Vol. 33, No. 1. pp. 42–48.
17. Efron B. Bootstrap methods: Another look at the jackknife. The Annals of Statistics. 1979. Vol. 1, No. 7. pp. 1–26.

Language of full-text russian
Full content Buy
Back