Petro Elastic Modeling for enhancement of hydrocarbon prediction: Case study in SE Asia
One of the widely used methods for litho-facies classification in oil and gas fields is conducted through cross plotting elastic properties e.g. Acoustic Impedance vs. Vp/Vs ratio. First at well locations the cross plot is color coded by litho-facies classes. Afterwards, to predict litho-facies away...
| Main Authors: | Babasafari, A.A., Ghosh, D.P., Salim, A.M.A., Ratnam, T., Sambo, C., Rezaee, S. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.22201 / |
| Published: |
2019
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059431247&doi=10.1190%2fsegam2018-2968514.1&partnerID=40&md5=04b153898e29cc435714c7c0d8a7c8ed http://eprints.utp.edu.my/22201/ |
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| Summary: |
One of the widely used methods for litho-facies classification in oil and gas fields is conducted through cross plotting elastic properties e.g. Acoustic Impedance vs. Vp/Vs ratio. First at well locations the cross plot is color coded by litho-facies classes. Afterwards, to predict litho-facies away from the wells, pre-stack seismic data inversion is performed. Cross plot of predicted elastic properties between the wells aid to discriminate each class. However, discrimination of defined litho-facies classes represents uncertainty particularly at overlapped zones between classes. This study reveals how Petro Elastic Modeling (PEM) generates a more suitable differentiation of litho-facies classification through elastic properties estimation. This process allows predicting the hydrocarbon zones more precisely and rational continuity of pay-zone layers is obtained due to high confidence value of each class in Bayesian probability classification. © 2018 SEG. |
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