二类油层聚驱油井模糊分类方法及精细评价研究

综合考虑二类油层的地质特点,以萨尔图油田北二区西部西块为例,利用模糊综合评判法,选择能够反映砂体沉积类型、油层发育状况等因素的静态指标将油井进行分类并评价了相关开发指标.在日常动态分析工程中,该油井分类方法能有针对性、有侧重点的对油井进行分类管理和综合调整挖潜,有助于对油井进行产能评价及改善聚驱开发效果分析,利于提高油田整体开发的经济效益.油井的分类方法同样可以在其他区块中综合应用.     

利用模拟退火算法进行油井流入动态研究

油井流入动态是油井举升优化设计的基础 ,目前国内外研究油井流入动态的方法有多种 ,但是各有其不足和局限性 .为此利用模拟退火方法进行油井流入动态方法研究 .与以往的近似算法相比 ,该方法不需要将单相流和多相流分开讨论 ,且无任何假设条件 ,适用范围广 ;通过实例 ,把模拟退火的预测的产量结果与利用 Vogel方程所预测的产量结果进行比较和误差分析 ,结果表明 ,该算法的误差是非常小的 .因此 ,利用该算法研究油井流入动态非常可行 .     

基于AdaBoost-SVM算法的油井反向压驱效果预测方法

预测油井的反向压驱增油效果是反向压驱选井选层工作的重要环节.针对反向压驱历史数据规模有限的问题,提出一种基于AdaBoost-SVM的油井反向压驱增油效果预测方法.应用SMOTE算法对压驱历史数据进行过采样,并建立AdaBoost-SVM反向压驱增油效果预测模型,以对油井的压驱效果进行预测.在油井上的实际应用结果表明,该预测方法能够有效预测油井应用反向压驱工艺的增油效果,为进一步的选井选层工作提供参考.     

模糊综合评判在油井试挤效果评价中的应用

油井试挤技术是在实践中总结摸索出来的一种简单实用的地层解堵技术.针对传统评价方法只注重累增油指标的片面性和不确定性,应用模糊数学理论评价油井试挤效果,首先选取日增油量、试挤有效期和试挤次数三个评价指标,然后利用层次分析方法确定各指标的合理权重,最后根据模糊综合评价得出评价结果.结果表明,方法可以精确评价油井的试挤效果,具有一定的推广价值.     

应用模糊综合评判方法优选非均质油藏调剖井和层

通过注水保持油层压力的方法开发非均质油藏,不可避免会造成油井含水或部分油井水淹.注入水窜入油井时,不管低渗透层是否受到开发,大部分注入水进入到高渗透层,因而使低渗透层在开发过程中采油速度很慢,或是基本未投入生产.为了降低产水量,保持或提高采油量,必须对已开发的非均质油藏实施相应的堵水调剖措施,防止注入水沿高渗透带水锥突进到油井,影响水驱采收率.本文建立了应用模糊综合评判方法优选非均质油藏调剖井和层的数学模型,通过实例分析表明,运用综合评判方法优选调剖井和层是一种客观有效的方法,该评价方法计算方便,易于操作和推广.     

确定多孔介质储层参数的新方法

§1.问题的陈述 设油井垂直地打开一水平、各相同性,均质的有界封闭油层,边界形状任意(如图1)。则当油井以定压γ,或定产量Q生产时的数学模型分别为     

油井分层注水倍数计算方法

运用水井纵向劈分方法,对B-Z油田3口水井对应5个小层进行劈分,将与油井连通的各水井水量劈分到连通层位上.运用水井平面劈分方法,对上述各区水井劈分到各层的产水量劈分到该层与水井连通的油井上,将各水井水量劈分到同一油井相同层位上的水量累加得到与水井连通油井的注水量.运用劈分结果计算出B-Z油田水井射开层位的累积注水倍数,对油田后续开发调整提供理论依据.     

补孔措施目标井层优选方法

油井补孔措施就是增加射开新的油层,是保证油井高产、油田持续开发的重要增产措施.而补孔措施效果好坏,主要取决于目标井层的选择是否合适.分析了影响油井补孔措施效果的因素,认为主要包括两方面共7个因素,一方面是井因素,包括全井含水率和全井日产油量共2个因素,另一方面是小层因素,包括小层渗透率、小层孔隙度、小层有效厚度、小层含油饱和度和小层地层压力共5个因素.在此基础上,建立了油井补孔措施目标井层优选方法,该方法以模糊数学为基础,通过综合评判对侯选井层打分,从而优选补孔措施目标井层.实际应用结果表明,利用该方法优选补孔措施目标井层,可靠性高,补孔措施实施后效果好.这种方法具有较高的学术与实用价值.     

榆树林油田CO_2吞吐采油目标井优选方法研究

CO_2吞吐是开发低渗透油田的有效方法之一,但进行CO_2吞吐前目标井的优选是关键步骤,它直接关系到CO_2吞吐措施的成败.首先分析了剩余油饱和度、油井含水率、油层厚度、渗透率、孔隙度、井底流压各因素对CO_2吞吐效果的影响,从而建立评价指标,然后利用层次分析方法确定各单因素的合理权重,最后根据模糊综合评判法优选出树11Y68-57和树11Y67-611两口油井适宜CO_2吞吐.优选出的油井具有良好的的油效果,表明该方法是正确可行的,具有一定的推广价值.     

基于示功图理论的有杆泵采油产液量计算

针对油田有杆抽油系统,利用Gibbs一维带阻尼的波动方程数学模型将悬点示功图转化为泵功图,并提出了两个估算油井产液量的数学模型.经实际数据验证表明,泵功图相对于悬点示功图向下平移了一段距离,消除了抽油杆柱对抽油泵工况分析的影响;两种产液量估算模型能较好的估算油井产液量;具有一定的适用性和可靠性.     

环境治理政策的减排、增效与结构优化效果动态评价

为测度环境治理政策波动对产出、减排、要素配置、消费与产业结构的影响及其传导机制,将异质性消费偏好、产出差异性、环境效用和环境损失函数引入E-DSGE模型。政策强度分析发现,技术进步、排污税和消费税政策效果较强,环境控制和治污支出冲击效果较弱。政策效应分析发现,技术进步政策效应最优,能实现增产和减排双重目标,促进要素配置和居民消费、产出与消费结构改进;排污税和政府治污支出政策次优,能实现增产和减排的双赢目标,促进要素供给和产出结构清洁化,不利于消费提升和消费结构优化;环境控制与消费税政策效果最差,以牺牲产出实现减排,不利于要素配置,产出与消费结构改进效果较弱,消费税会抑制居民消费,但消费税政策效果随环境友好型家庭比例提升而加强。     

城市老旧居住小区交通环境评价指标与评价方法

定量的评判城市老旧居住小区整体交通环境质量并进而科学有效的提出老旧小区交通环境更新与改善措施,对城市老旧居住小区交通环境进行了调查,明确了老旧居住小区存在的突出交通问题,并提出了城市老旧居住小区交通环境评价的指标体系,包括行人跨路出行指数、无人行道路段长度占比、停车泊位供需比、路内非法停车占比、平均停车步行距离、泊位数量户数比、人均步行空间、无障碍通道、盲道设置比例、非机动车泊位供需比、地面停放车辆数小区面积比、外部穿行交通周转量小区面积比等。并给出了具体指标的计算方法与获得办法。以长沙市四个典型老旧居住小区为例,对评价方法进行了论证,并得到城市老旧居住小区存在的一般问题,包括人车混杂、人车交织现象严重,停车泊位短缺、车辆乱停乱放,交通设施、特别是弱势群体交通设施缺乏。给出的评价指标、评价方法与结论可为城市老旧小区改造更新,特别是其中很重要的交通环境更新提供决策依据。     

乡村绿色生态旅游适宜等级VIKOR评估方法

针对乡村绿色生态旅游特征,并考虑旅游者个体感受与群体效益,本文从乡村绿色生态旅游开发与适宜评级概念出发,提出乡村绿色生态旅游适宜等级VIKOR评估模型与方法。首先,从等级评估的概念与内涵出发,刻画乡村绿色生态旅游适宜评级问题,避免混淆旅游适宜评级和排序两个本质不同的问题。然后,构建乡村绿色生态旅游适宜等级评估指标及隶属函数,提出评估指标的熵权确定方法。其次,提出乡村绿色生态旅游适宜等级VIKOR评估模型与二元语义等级评估方法。最后,通过案例研究和比较分析,说明本文所提模型与方法的合理性、可行性与实用性。     

Mechanics of Delaminations in Laminate Composite Structures

A survey of the literature and state of the art of the mechanical aspects of delaminations in laminate composite structures is presented. Surface and internal delaminations of various origin, shape, and location are discussed. The origination, stability, and postcritical behavior of delaminations under quasi-static, cyclic, and dynamic loads are analyzed. Some problems for further investigations are discussed.     

Simulating the effect of nepotism on political risk taking and social unrest

Nepotism has been the primary influence on political behavior throughout human history. Despite the spread of democracy in the 20th century, nepotistic regimes have hardly disappeared. Nepotism heavily influences political activity throughout the developing world, Middle East, and central Asia where family ties are essential for gaining access to power, state resources, and privileges. Rebelling against such nepotistic regimes is difficult and risky. RiskTaker is an agent-based model we developed for testing the influences of various social forces on risk taking behavior, including the formulation of rebellious coalitions. We use RiskTaker to examine the influence of nepotism on the distribution of wealth and social status. Nepotism heavily skews the distribution of wealth and status, leading to the formation of opposing coalitions and exacerbating social unrest.This paper was tied for Best Paper, NAACSOS (North American Association for Computational Social and Organizational Science) Annual Conference 2005, June 26–28, Notre Dame. Robert Sedlmeyer, Department of Computer Science, Indiana University – Purdue University, Fort Wayne provided programming for the RiskTaker model. Lawrence A. Kuznar is a professor of anthropology and director of the Decision Sciences and Theory Institute at Indiana University—Purdue University, Fort Wayne. He has conducted fieldwork among Aymara Indians in Andean Peru and the Navajo of the American southwest. His research interests include computer modeling, theories of risk taking and conflict, terrorism, social evolution, and scientific epistemology. He has authored articles in Ecological Economics (with W. Frederick), Current Anthropology, American Anthropologist, Mathematical Anthropology and Culture Theory and Journal of Anthropological Research, and published two books (Awatimarka Harcourt Brace, 1995 and Reclaiming a Scientific Anthropology Altamira Press, 1997) and two edited volumes. William Frederick has served as a faculty member in the departments of mathematical sciences and the department of computer sciences at Indiana University—Purdue University, Fort Wayne since 1979. His primary interests include mathematical modeling, game theory, and genetic algorithms.     

The generalized hierarchical product of graphs

A generalization of both the hierarchical product and the Cartesian product of graphs is introduced and some of its properties are studied. We call it the generalized hierarchical product. In fact, the obtained graphs turn out to be subgraphs of the Cartesian product of the corresponding factors. Thus, some well-known properties of this product, such as a good connectivity, reduced mean distance, radius and diameter, simple routing algorithms and some optimal communication protocols, are inherited by the generalized hierarchical product. Besides some of these properties, in this paper we study the spectrum, the existence of Hamiltonian cycles, the chromatic number and index, and the connectivity of the generalized hierarchical product.     

房地产业对中国经济真的那么重要吗？

为恰当评估房地产业对中国经济的重要性,通过编制2002、2007和2012年中国社会核算矩阵,进行乘数分解和结构化路径分析的结果表明:房地产业对行业总产出、劳动力和资本报酬、居民和企业收入的拉动作用极低。房地产业主要对金融业、租赁和商务服务业、建筑业以及金属冶炼与压延加工业四个行业的产出影响比较显著,对前三个行业主要是直接的一步式影响,与房地产业紧密相关的产业链条并不长。房地产业对要素报酬和机构收入的拉动总效应极小,且主要是开环效应,与此同时,房地产业主要通过自身和金融业影响要素报酬进而影响机构收入,特别是对资本报酬和企业收入的影响简单、直接,高度依赖这两条基础路径。土地出让金和房地产有关税收已成为地方政府的主要收入来源。房地产开发和运营商、金融机构和地方政府已成为房地产业发展过程中最主要的利益相关方。     

Supply chain coordination with downstream operating costs: Coordination and investment to improve downstream operating efficiency

There are many conceptualizations and formalizations of decision making. In this paper we compare classical decision theory with qualitative decision theory, knowledge-based systems and belief–desire–intention models developed in artificial intelligence and agent theory. They all contain representations of information and motivation. Examples of informational attitudes are probability distributions, qualitative abstractions of probabilities, knowledge, and beliefs. Examples of motivational attitudes are utility functions, qualitative abstractions of utilities, goals, and desires. Each of them encodes a set of alternatives to be chosen from. This ranges from a small predetermined set, a set of decision variables, through logical formulas, to branches of a tree representing events through time. Moreover, they have a way of formulating how a decision is made. Classical and qualitative decision theory focus on the optimal decisions represented by a decision rule. Knowledge-based systems and belief–desire–intention models focus on an alternative conceptualization to formalize decision making, inspired by cognitive notions like belief, desire, goal and intention. Relations among these concepts express an agent type, which constrains the deliberation process. We also consider the relation between decision processes and intentions, and the relation between game theory and norms and commitments.     

On the potential of norm-governed behavior in different categories of artificial societies

Based on a classification of artificial societies and the identification of four different types of stakeholders in such societies, we investigate the potential of norm-governed behavior in different types of artificial societies. The basis of the analysis is the preferences of the stakeholders and how they influence the state of the society. A general conclusion drawn is that the more open a society is the more it has to rely on agent owners and designers to achieve norm-governed behavior, whereas in more closed societies the environment designers and owners may control the degree of norm-governed behavior. Paul Davidsson is professor at the Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology, Sweden. He received his Ph.D. in Computer Science in 1996 from Lund University, Sweden. His research interests include the theory and application of multi-agent systems, autonomous agents, and machine learning. Application areas include logistics, transport systems, district heating systems, building automation, and telecommunications systems. The results of this work have been reported in more than 75 peer-reviewed scientific articles published in international journals and conference proceedings. Moreover, he has been the co-editor of three books on Multi Agent Based Simulation and member of program committees of numerous international conferences, such as the International Joint Conference on Autonomous Agents and Multi-Agent Systems Stefan Johansson is an assistant professor at Department of Systems and Software Engineering, Blekinge Institute of Technology, Sweden, where he also finished his PhD in 2002. The main research areas cover coordination issues in multi-agent systems and theories of autonomous agents. Applications of special interests are agents in game ai, robotics, telecommunication networks. On his list of publications are more than 35 peer-reviewed papers published in conference proceedings and scientific journals in the areas of agents, ai, robotics and games. He has also been a member of a variety of programme committees of scientific conferences, including e.g. Intelligent Agent Technology.