.png){kind=icon}
.png){kind=icon}
Return
A GENERALIZED OIL-EXPLORATION PROBLEM
.png){kind=icon}
PRE
AI
DOI：10.1016/0377-2217(94)90235-6.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper we consider a general version of the oil exploration problem model previously investigated by the authors and others. We assume that a region is hypothesized to contain an unknown number of oilfields represented by a prior pi. The discovery of oilfields is governed by a probability law which is a function of the number of undiscovered sources. Drilling a well costs c and the value of a field is fixed at upsilon. Rewards are additive and discounted by a factor theta, 0 less-than-or-equal-to theta < 1. On the basis of the history of successful and unsuccessful drillings, the decision maker is faced with three options: retire with no reward; drill a single well; drill two wells, so as to maximize the total expected return.
Keywords:
EULER DISTRIBUTIONS
OIL EXPLORATION
MARKOV DECISION PROCESS
OPTIMAL STOPPING
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W
Organization
No organization information available