Hostname: page-component-8448b6f56d-sxzjt Total loading time: 0 Render date: 2024-04-23T09:57:39.773Z Has data issue: false hasContentIssue false

Search models

Published online by Cambridge University Press:  14 July 2016

J. A. Bather*
Affiliation:
University of Sussex
*
Postal address: Mathematics Division, School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton BN1 9QH, UK.

Abstract

Mathematical models have been proposed for oil exploration and other kinds of search. They can be used to estimate the amount of undiscovered resources or to investigate optimal stopping times for the search. Here we consider a continuous search for hidden objects using a model which represents the number and values of the objects by mixtures of Poisson processes. The flexibility of the model and its complexity depend on the number of components in the mixture. In simple cases, optimal stopping rules can be found explicitly and more general qualitative results can sometimes be obtained.

MSC classification

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1992 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baruch, E. and Kaufman, G. M. (1975) Probabilistic modelling of oil and gas discovery. Energy, 132152.Google Scholar
Beale, E. M. L. (1986) Optimization methods in oil and gas exploration. IMA J. Appl. Math. 36, 110.CrossRefGoogle Scholar
Benkherouf, L. and Bather, J. A. (1988) Oil exploration: sequential decisions in the face of uncertainty. J. Appl. Prob. 25, 529543.CrossRefGoogle Scholar
Davis, M. H. A. (1984) Piecewise-deterministic Markov processes: A general class of non-diffusion stochastic models. J. R. Statist. Soc. B46, 353388.Google Scholar
Kramer, M and Starr, N. (1990) Optimal stopping in a size dependent search. Sequential Analysis 9, 5980.CrossRefGoogle Scholar
Rabinowitz, D. (1989) Using exploration history to estimate undiscovered resources. SIMS Technical Report No. 131.Google Scholar
Rao, C. R. and Rubin, H, (1964) On a characterisation of the Poisson distribution. Sankya A32, 265270.Google Scholar
Ross, S. M. (1971) Infinitesimal look-ahead stopping rules. Ann. Math. Statist. 42, 297303.Google Scholar
Shanbhag, D. N. (1974) An elementary proof for the Rao-Rubin characterisation of the Poisson distribution. J. Appl. Prob. 11, 211215.CrossRefGoogle Scholar