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Estimation of Oil Land Area by Using Bayes’ Theorem

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dc.contributor.author Shwe, Myo Myat
dc.contributor.author Thein, Naychi Lai Lai
dc.date.accessioned 2019-07-24T15:07:13Z
dc.date.available 2019-07-24T15:07:13Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1242
dc.description.abstract Petroleum exploration is a high risk business. Consulting geologists predicts the probable existence of oil based on the geological evidence such as reservoir rocks, source rocks, sealed rocks, trap, recovery factor and generation timing to obtain a better estimation of oil. To predict the probable existence of oil, it is very hard decisions because exploration of hydrocarbons is a high-risk venture and geological concepts are uncertain with respect to structure, reservoir seal, etc., . Bayes’ theorem is used to compute the prior probability to make the decision of drill the oil or sell the land upon the given user facts. This system also presents the method of computing posterior probabilities from prior probabilities using Bayes’ theorem to get decision tree. By using this system, people in petroleum-exploration field will get the knowledge of the essential factors for them. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject decision support system en_US
dc.subject Bayes’ theorem en_US
dc.subject prior probabilities en_US
dc.subject posterior probabilities en_US
dc.subject decision tree en_US
dc.title Estimation of Oil Land Area by Using Bayes’ Theorem en_US
dc.type Article en_US

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