| 油气田区承压含水层地下水污染机理及其脆弱性评价 |
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| 引用本文： | 武强,王志强,赵增敏,刘东海. 油气田区承压含水层地下水污染机理及其脆弱性评价[J]. 水利学报, 2006, 37(7): 851-857 |
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| 作者姓名： | 武强 王志强 赵增敏 刘东海 |
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| 作者单位： | 中国矿业大学,资源与安全工程学院,北京,100083;中国矿业大学,资源与安全工程学院,北京,100083;河北工业大学,能源与环境工程学院,天津,300132 |
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| 摘 要： | 根据研究区地质构造及水文地质概况，分析了研究区承压含水层地下水有机污染的机理，建立了针对该地区承压含水层地下水污染脆弱性评价指标体系，并应用神经网络技术作为评价体系中参数的赋权方法；由ANN与GIS耦合技术得到的研究区承压含水层地下水污染脆弱性区划图比较好地符合研究区的实际情况。
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| 关 键 词： | 承压含水层 地下水污染 脆弱性 评价体系 参数权重 神经网络 |
| 文章编号： | 0559-9350（2006）07-0851-07 |
| 收稿时间： | 2005-06-08 |
| 修稿时间： | 2005-06-08 |
Pollution mechanism and vulnerability assessment of confined aquifer groundwater in oil field |
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| WU Qiang. Pollution mechanism and vulnerability assessment of confined aquifer groundwater in oil field[J]. Journal of Hydraulic Engineering, 2006, 37(7): 851-857 |
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| Authors: | WU Qiang |
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| Affiliation: | China University of Mining and Technology, Beijing 100083, China |
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| Abstract: | According to the geological structure and hydrological geology in the area to be studied, the mechanism of confined aquifer groundwater polluted by organic substance is analyzed and the model for assessing the vulnerability of the groundwater is established. The combination of artificial neural networks (ANN) and geographic information system (GIS) technique is adopted to calculate the weight values of indicators in the assessment model, so that the disadvantage of traditional assessment system, in which the weight values are assigned as constant, can be overcome. The confined aquifer groundwater vulnerability mapping by using this method is more precisely accord with the real situation of the studied area. |
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| Keywords: | confined aquifer groundwater groundwater pollution vulnerability assessment method weight of indicator artificial neural networks (ANN) |
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