Skip to main content

Advertisement

Log in

Dempster–Shafer Theory Applied to Uncertainty Surrounding Permeability

  • Published:
Mathematical Geosciences Aims and scope Submit manuscript

Abstract

Typically, if uncertainty in subsurface parameters is addressed, it is done so using probability theory. Probability theory is capable of only handling one of the two types of uncertainty (aleatory), hence epistemic uncertainty is neglected. Dempster–Shafer evidence theory (DST) is an approach that allows analysis of both epistemic and aleatory uncertainty. In this paper, DST combination rules are used to combine measured field data on permeability, along with the expert opinions of hydrogeologists (subjective information) to examine uncertainty. Dempster’s rule of combination is chosen as the combination rule of choice primarily due to the theoretical development that exists and the simplicity of the data. Since Dempster’s rule does have some criticisms, two other combination rules (Yager’s rule and the Hau–Kashyap method) were examined which attempt to correct the problems that can be encountered using Dempster’s rule. With the particular data sets used here, there was not a clear superior combination rule. Dempster’s rule appears to suffice when the conflict amongst the evidence is low.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agarwal H, Renaud JE, Preston EL, Padmanabhan D (2004) Uncertainty quantification using evidence theory in multidisciplinary design optimization. Reliab Eng Syst Saf 85:281–294

    Article  Google Scholar 

  • Belitz K, Bredehoeft JD (1988) Hydrodynamics of Denver basin—explanation of subnormal fluid pressures. Am Assoc Petroleum Geol Bull 72(11):1334–1359

    Google Scholar 

  • Binaghi E, Luzi L, Madella P, Pergalani F, Rampini A (1998) Slope instability Zonation: a comparison between certainty factor and fuzzy Dempster-Shafer approaches. Nat Hazards 17:77–97

    Article  Google Scholar 

  • Cayuela L, Golicher JD, Salas Rey J, Rey Benayas JM (2006) Classification of a complex landscape using Dempster–Shafer theory of evidence. Int J Remote Sens 27(10):1951–1971

    Article  Google Scholar 

  • Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38:325–339

    Article  Google Scholar 

  • Dubois D, Prade H (1986) A set-theoretic view on belief functions: logical operations and approximations by fuzzy sets. Int J Gen Syst 12:193–226

    Article  Google Scholar 

  • Dubois D, Prade H (1992) On the combination of evidence in various mathematical frameworks. In: Flamm J, Luisi T (eds) Reliability data collection and analysis. Kluwer Academic, Brussels, pp 213–241

    Google Scholar 

  • Ferson S, Kreinovich V (2002) Representation, propagation, and aggregation of uncertainty: Sandia National Laboratories. Technical report, Albuquerque, New Mexico

  • Ferson S, Kreinovich V, Ginzburg L, Myers DS, Sentz K (2002) Constructing probability boxes and Dempster–Shafer structures: Sandia National Laboratories. Technical report SAND2002-4015, Albuquerque, New Mexico. Available at: http://www.sandia.gov/epistemic/Reports/SAND2002-4015.pdf

  • Hau HY, Kashyap RL (1990) Belief combination and propagation in a lattice-structured inference network. IEEE Trans Syst Man Cybern 20(1):45–57

    Article  Google Scholar 

  • Inagaki T (1991) Interdependence between safety-control policy and multiple-sensor schemes via Dempster–Shafer theory. IEEE Trans Reliab 40(2):182–188

    Article  Google Scholar 

  • Joslyn C, Booker JM (2004) Generalized information theory for engineering modeling and simulation. In: Nikolaidid E, Ghiocel D, Singhal S (eds) Engineering design reliability handbook. CRC Press, Boca Raton, pp 9–1–9–40

    Google Scholar 

  • Joslyn C, Ferson S (2004) Approximate representations of random intervals for hybrid uncertainty quantification in engineering modeling. In: Hanson KM, Hemez FM (eds), Sensitivity analysis of model output (SAMO04), LANL, Los Alamos, pp 453–469. http://library.lanl.gov/cgi-bin/getdoc?event=SAMO2004&document=samo04-83.pdf

  • Klir GJ (2003) Uncertainty. Encycl Inf Syst 4:511–521

    Google Scholar 

  • Kriegler E, Held H (2005) Utilizing belief functions for the estimation of future climate change. Int J Approx Reason 39:185–209

    Article  Google Scholar 

  • Ricciardi KL (2002) Optimal groundwater remediation design subject to uncertainty. PhD dissertation, University of Vermont, USA, pp 50–66

  • Ross J, Ozbek M, Pinder GF (2008) Kalman filter updating of possibilistic hydraulic conductivity. J Hydrol 354:149–159

    Article  Google Scholar 

  • Sentz K, Ferson S (2002) Combination of evidence in Dempster–Shafer theory: Sandia National Laboratories. Technical report SAND2002-0835, Albuquerque, New Mexico. Available at: http://www.sandia.gov/epistemic/Reports/SAND2002-0835.pdf

  • Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton. 312 p

    Google Scholar 

  • Smarandache F (2004) An in-depth look at information fusion rules and the unification of fusion theories: arXiv electronic archives. Available at: http://xxx.lanl.gov/ftp/cs/papers/0410/0410033.pdf

  • Smarandache F, Dezert J (eds) (2004) Applications and advances of DSmT for information fusion. American Research Press, Rehoboth. http://www.gallup.unm.edu/~smarandache/DSmT-book1.pdf

    Google Scholar 

  • Smets P (2005) Analyzing the combination of conflicting belief functions. Available at: http://iridia.ulb.ac.be/%7epsmets/Combi_Confl.pdf

  • Smets P, Kennes R (1994) The transferable belief model. Artif Intell 66:191–234

    Article  Google Scholar 

  • Yager RR (1987) On the Dempster–Shafer framework and new combination rules. Inf Sci 41:93–138

    Article  Google Scholar 

  • Zadeh LA (1984) Review of books: a mathematical theory of evidence. AI Mag 5(3):81–83

    Google Scholar 

  • Zadeh LA (1986) A simple view of the Dempster–Shafer theory of evidence and its implication for the rule of combination. AI Mag 7:85–90

    Google Scholar 

  • Zhang L (1994) Representation, independence, and combination of evidence in the Dempster–Shafer theory. In: Yager RR, Kacprzyk J, Fedrizzi M (eds) Advances in the Dempster–Shafer theory of evidence. Wiley, New York, pp 51–69

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bree R. Mathon.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mathon, B.R., Ozbek, M.M. & Pinder, G.F. Dempster–Shafer Theory Applied to Uncertainty Surrounding Permeability. Math Geosci 42, 293–307 (2010). https://doi.org/10.1007/s11004-009-9246-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11004-009-9246-0

Keywords

Navigation