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Identifying The Key Variables for Assessing The Reclamation Success on Early Growth Vegetation in Ex-exploration of Oil and Gas Mining Areas

机译:确定石油和煤气挖掘区前勘探早期成长植被对早期成长植被的关键变量

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摘要

This paper examines the identification of key indicators that could be used to measure the success of reclamation plants in post-exploration oil and gas mining areas. The main objective of this research was to find key indicators or variables for evaluating the level success of reclamation results in the post-mining of oil and gas area. In this study, 44 environmental variables of the physical, biological, soil, water and air indicators were analyzed from 70 field plots of 6 reclamation and 2 natural forest sites. The analysis methods included (1) cluster analysis using the Agglomerative Hierarchical Clustering method with the Ward's method, and (2) quadratic discriminant analysis. The results of the clustering analysis showed that there were some clusters due to variation of biomass, water, soil and air conditions. The three clusters developed based on water and/or air variables provided high cophenetic correlation (0.80) with low within-cluster (14.5%) and high between-cluster variations (85.5%). Based on the multicollinearity analysis, average vector difference test, variance matrix variance test, unidimensional test of each variable and quadratic discriminant function, this study found that there were 3 key indicators determining variations of the quality of the reclamation plantations within the study sites, namely, biological indicator of biomass volume (Bio_B); soil indicator of P content in the soil (Tnh_P), saturation base of soil (Tnh_Kb), Manganese (Mn) content in the soil (Tnh_Mn), Sulfur content in the soil (Tnh_S), percentage of ash in the soil (Tnh_Ab), percentage of clay in the soil (Tnh_Li), and water indicator of chloride content in the surface water (Air_Cl). The examination on four classes of the reclamation quality showed that the classes were successfully classified having excellent cross-validation error matrix with overall accuracy more than 90%.
机译:本文探讨的,可以用来衡量回收厂在勘探后石油和天然气开采地区取得成功的关键指标的确定。这项研究的主要目标是找到关键指标或变量评估填海结果在石油和天然气领域的后采平的佳绩。在这项研究中,44的物理,生物,土壤,水和空气指标的环境变量,从6开垦的70个地块和2名天然林的网站进行分析。包括在分析方法(1)使用凝聚层次聚类方法与Ward的方法,和(2)二次判别分析聚类分析。聚类分析的结果表明,有一些簇由于生物质,水,土壤和空气条件的变化。的三组开发了内群集(14.5%)和高类间变化(85.5%)低基于水和/或提供的高同表象相关(0.80)空气变量。基于所述多重分析,平均矢量差检验,方差矩阵方差测试,每个变量和二次判别函数的一维测试,本研究发现,有确定研究地点内回收种植园的质量的变化3个关键指标,即,生物量的体积(Bio_B)的生物指示器;在土壤中(Tnh_P),饱和土壤(Tnh_Kb)的碱在土壤(Tnh_Mn),锰(Mn)含量,在土壤中(Tnh_S)硫含量,在土壤中的灰分的百分比P含量的土壤指示符(Tnh_Ab) ,粘土在土壤(Tnh_Li),和在表面的水(Air_Cl)氯化物含量水指示器的百分比。上四个类回收质量的检查表明,这些类被成功分类具有整体精度超过90%的优异的交叉验证误差矩阵。

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