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| Assessing value classification of oil and gas reserve based on support vector machine |
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YANG Lei1,WANG Hua-zeng2,CHEN Zi-ling3
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(1. School of Economics & Management in China University of Petroleum, Qingdao 266580, China;2.Shengli Oilfield Dongsheng Group of SINOPEC，Dongying 257091，China;3. Materials Company of PetroCkina, Beijing 100029, China)
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| Abstract: |
| Based on the characteristics of oil and gas reserve, value classification of oil and gas reserve was assessed. Seven factors influencing value classification of oil and gas reserve were chosen, which were reserve scale，reserve abundance, reserve depth, oil viscosity, permeability f freezing point and recovery ratio. Least square support vector machine model was applied to simulate value degradation of oil and gas reserve. The parameters of penalty factor C and kernel function parameter
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| Key words: least square support vector machine oil and gas reserve value degradation |
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