国际原油价格波动对我国外贸收支的冲击效应

本文以2001年1月至2012年12月外贸收支差额、国际原油价格、实际汇率、贸易条件和产出缺口等内生变量和加入WTO、金融危机两个外生变量的月度数据为样本,采用受限向量自回归（cvaR）模型,实证分析国际原油价格波动对我国外贸收支平衡的动态冲击效应。结果表明,油价冲击是造成我国外贸收支失衡的一个重要影响因素。其作用大于实际汇率、贸易条件和产出缺口。油价上涨将对外贸收支差额产生负向影响,但从长期看,新能源和替代能源的开发利用以及中国出口产品能源密集度的降低,将使油价变动对外贸收支失衡的影响逐渐消失。     

中国油港低碳绿色化发展的影响因素分析

构建低碳绿色油港应首先明确影响中国油港低碳绿色化发展的因素。运用系统分析的方法,提出中国油港低碳绿色化发展的8个因素、21个子因素,以帮助识别油港发展的＂非低碳、非绿色＂因素并找出其薄弱环节,同时在国内低碳绿色油港的建设方面为主管部门和相关企业提供决策参考。     

权力游戏与产业制度变迁——以中国石油产业外部合作战略转型为例（1988-2008）

1988-2008年间，中国石油产业外部合作战略实现了从早期以引进外国资本与技术为主要内容的“引进来”战略，向1998年后以输出资本与技术为主要特征的“走出去”战略的重要转型。本文以组织社会学决策分析的推论方式研究发现，作为一种产业制度变迁现象，中国石油产油产业外部合作战略的转型除了受到国家及其产业政策和市场机制的重要影响外，更深刻地受到一种复杂权力关系互动或权力游戏机制的作用。即中国石油产业外部合作战略转型深层的动力来源主要是国家和国有石油公司之间特定的权力游戏，这种权力游戏是基于各自行动能力与资源控制，和各自对特定的互动组织环境以及对方可能的行动策略的权衡与判断而建构起来的。     

改进FMEA法的石油钻探设备HSE风险识别

针对石油钻探设备的特点，围绕HSE体系的基本框架，从安全、健康、环境三个方面将石油钻探设备HSE风险分为两级。通过改进的故障模型及影响分析（FMEA）法对石油钻探设备HSE风险进行识别，并将识别出的风险因素加以归类，为石油钻探设备风险评价和控制提供依据。     

基于小波神经网络的油泵故障诊断

依据小波神经网络技术的各种优点，提出采用三层BP小波神经网络构造故障诊断模型，对油泵进行故障监测和诊断。该故障诊断方法对神经网络训练、故障特征参数提取和对应神经网络状态输出等均实现了数据库管理，对油泵多种常见故障取得了满意的诊断效果，不仅具有特征自动提取以及较强的自学习和自适应功能，而且操作维护简便。研究结果表明：信号的小波分析和神经网络识别的融合将为油泵状态监测与故障诊断系统的建立提供新的方法和更简便的途径；对油库安全维护与故障诊断具有重要意义。     

低渗透储层可动剩余油核磁共振分析

针对有代表性密闭取芯岩芯平行样，分别进行油水饱和度和油水高速离心驱替实验核磁共振分析，定量获得 储层目前剩余油饱和度、采出油相对量、可动油饱和度及驱油效率上限等参数，对比各参数建立储层可动剩余油饱和 度核磁共振分析方法。研究表明，建立岩芯饱和油束缚水状态和水驱油的最佳离心力分别为2.250 MPa 和0.220 MPa， 4 个渗透率级别（>50、[10，50）、[1，10）和<1 mD）储层采出油饱和度分别为23.49%、16.81%、8.70% 和9.99%，可动油 饱和度分别为50.34%、43.76%、29.67% 和22.89%，可动剩余油饱和度分别为26.85%、26.95%、20.97% 和12.90%，由 于储层非均质性影响，大于10 mD 储层采出油明显高于10 mD 以下储层，但大于10 mD 储层可动油饱和度较高，故可 动剩余油饱和度也较高，小于1 mD 的储层可动剩余油明显低于其他储层。     

Who Lives Near Coke Plants and Oil Refineries? An Exploration of the Environmental Inequity Hypothesis

Facility-specific information on pollution was obtained for 36 coke plants and 46 oil refineries in the United States and matched with information on populations surrounding these 82 facilities. These data were analyzed to determine whether environmental inequities were present, whether they were more economic or racial in nature, and whether the racial composition of nearby communities has changed significantly since plants began operations.The Census tracts near coke plants have a disproportionate share of poor and nonwhite residents. Multivariate analyses suggest that existing inequities are primarily economic in nature. The findings for oil refineries are not strongly supportive of the environmental inequity hypothesis. Rank ordering of facilities by race, poverty, and pollution produces limited (although not consistent) evidence that the more risky facilities tend to be operating in communities with above-median proportions of nonwhite residents (near coke plants) and Hispanic residents (near oil refineries). Over time, the racial makeup of many communities near facilities has changed significantly, particularly in the case of coke plants sited in the early 1900s. Further risk-oriented studies of multiple manufacturing facilities in various industrial sectors of the economy are recommended.The authors are all affiliated with the Harvard Center for Risk Analysis     

英国石油天然气监管法律制度探析

英国拥有丰富的油气资源,为西欧重要的油气资源国和生产国。本文对英国石油天然气资源进行了概述,阐述了英国石油天然气监管的立法及其特点,探讨了英国石油天然气监管法律制度的基本框架,并指出了英国石油天然气监管法律制度对我国的启示。     

亲水性膜的研制和亲水性研究

为了消除小片距、复杂片型高效表冷器在湿工况下运行时产生的“水塞”问题和进一步提高这类表冷器的热工性能,本文从凝结方式的理论分析出发,介绍了在表冷器上制作亲水性膜的方法,从理论上分析了这种亲水性膜的结构与亲水性的关系,从实践上给出了这种亲水性膜对表冷器的热工性能的新贡献,为研制高效紧凑式表冷器提供了可喜的前景。     

Probabilistic Reliability Modeling for Oil Exploration & Production (E&P) Facilities in the Tallgrass Prairie Preserve

The aging domestic oil production infrastructure represents a high risk to the environment because of the type of fluids being handled (oil and brine) and the potential for accidental release of these fluids into sensitive ecosystems. Currently, there is not a quantitative risk model directly applicable to onshore oil exploration and production (E&P) facilities. We report on a probabilistic reliability model created for onshore exploration and production (E&P) facilities. Reliability theory, failure modes and effects analysis (FMEA), and event trees were used to develop the model estimates of the failure probability of typical oil production equipment. Monte Carlo simulation was used to translate uncertainty in input parameter values to uncertainty in the model output. The predicted failure rates were calibrated to available failure rate information by adjusting probability density function parameters used as random variates in the Monte Carlo simulations. The mean and standard deviation of normal variate distributions from which the Weibull distribution characteristic life was chosen were used as adjustable parameters in the model calibration. The model was applied to oil production leases in the Tallgrass Prairie Preserve, Oklahoma. We present the estimated failure probability due to the combination of the most significant failure modes associated with each type of equipment (pumps, tanks, and pipes). The results show that the estimated probability of failure for tanks is about the same as that for pipes, but that pumps have much lower failure probability. The model can provide necessary equipment reliability information for proactive risk management at the lease level by providing quantitative information to base allocation of maintenance resources to high-risk equipment that will minimize both lost production and ecosystem damage.