@inproceedings{scholars12255,
       publisher = {Society of Exploration Geophysicists},
         journal = {2018 SEG International Exposition and Annual Meeting, SEG 2018},
           title = {Petro Elastic Modeling for enhancement of hydrocarbon prediction: Case study in SE Asia},
           pages = {3141--3145},
            note = {cited By 5; Conference of 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 ; Conference Date: 14 October 2018 Through 19 October 2018; Conference Code:143290},
            year = {2019},
             doi = {10.1190/segam2018-2968514.1},
        abstract = {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. {\^A}{\copyright} 2018 SEG.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059431247&doi=10.1190\%2fsegam2018-2968514.1&partnerID=40&md5=04b153898e29cc435714c7c0d8a7c8ed},
        keywords = {Acoustic fields; Acoustic impedance; Elasticity; Forecasting; Gas industry; Geophysical prospecting; Hydrocarbons; Lithography; Seismology, Bayesian probabilities; Elastic modeling; Elastic properties; High confidence; Hydrocarbon predictions; Oil and gas fields; Pre-stack seismic data; Well location, Petroleum prospecting},
          author = {Babasafari, A. A. and Ghosh, D. P. and Salim, A. M. A. and Ratnam, T. and Sambo, C. and Rezaee, S.}
}