| Titre : |
Optimal stopping rules in oil exploration |
| Type de document : |
texte imprimé |
| Auteurs : |
Lakdere Benkherouf, Auteur ; J.A. Bather, Directeur de thèse |
| Editeur : |
London : [s.n.] |
| Année de publication : |
1988 |
| Importance : |
133 f. |
| Présentation : |
ill. |
| Format : |
30 cm. |
| Note générale : |
PhD Thesis: Mathematics : London, Imperial college of science and technology : 1988
Bibliogr. f. 131 - 133 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Optimal -- stopping rules
Oil exploration |
| Index. décimale : |
D000388 |
| Résumé : |
In the thesis, we are concerned with obtaining optimal strategies for drilling in oil exploration.
The criterion for optimality is the maximum expected return.
In the first part of the thesis, a simple bayesian model for oil exploration is introduced.
A condition on the way successes and failures affect the prior distribution implies a certain form of the detection mechanism.
It is shown that the problem reduces to an optimal stopping problem.
Three new families of distributions are obtained with generating functions related to classical work on partitions of integers.
By using such distributions and simple mixtures of them as priors, the stopping problem can be solved explicitly.
This leads to the construction of simple strategies and their effectiveness is demonstrated by evaluating suitable operating characteristics.
Then, the distribution representing the number of undiscovered fields is approximated by one of the new distributions obtained in the first part and the approximate stopping problem is investigated. |
Optimal stopping rules in oil exploration [texte imprimé] / Lakdere Benkherouf, Auteur ; J.A. Bather, Directeur de thèse . - London : [s.n.], 1988 . - 133 f. : ill. ; 30 cm. PhD Thesis: Mathematics : London, Imperial college of science and technology : 1988
Bibliogr. f. 131 - 133 Langues : Anglais ( eng)
| Mots-clés : |
Optimal -- stopping rules
Oil exploration |
| Index. décimale : |
D000388 |
| Résumé : |
In the thesis, we are concerned with obtaining optimal strategies for drilling in oil exploration.
The criterion for optimality is the maximum expected return.
In the first part of the thesis, a simple bayesian model for oil exploration is introduced.
A condition on the way successes and failures affect the prior distribution implies a certain form of the detection mechanism.
It is shown that the problem reduces to an optimal stopping problem.
Three new families of distributions are obtained with generating functions related to classical work on partitions of integers.
By using such distributions and simple mixtures of them as priors, the stopping problem can be solved explicitly.
This leads to the construction of simple strategies and their effectiveness is demonstrated by evaluating suitable operating characteristics.
Then, the distribution representing the number of undiscovered fields is approximated by one of the new distributions obtained in the first part and the approximate stopping problem is investigated. |
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