| 摘要: |
| 针对油气储域的特点,对油气储楗价值的优劣等级进行划分。选取影响油气储量价值等级的7个闵素,即储量 规模、储量丰度、储层埋深、原油黏度、渗透率、凝固点和采收率,采用最小二乘支持向量机模铟对油气储镇价值等级 划分进行仿真,并运用网格搜索法确定最小二乘支持向量机模型的参数惩罚因子C和核函数参数<7。结果表明，最 小二乘支持向最机是评价油气储域价值等级的有效方法,训练正判率达到95%，检验正判率达到81%。 |
| 关键词: 最小二乘支持向量机 油气储量 价值分级 |
| DOI：10.3969/j.issn.1673-5005.2012.03.033 |
| 分类号:X 196 |
| 基金项目::山东省自然科学基金项目(ZR2009HIW010);中央高校基本科研业务费专项资金资助项目(09CX04085B;09CX05015B) |
|
| Assessing value classification of oil and gas reserve based on support vector machine |
|
YANG Lei1,WANG Hua-zeng2,CHEN Zi-ling3
|
|
(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)
|
| 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
|
| Key words: least square support vector machine oil and gas reserve value degradation |
