石油储量动态经济评价研究
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摘要
众所周知，石油是重要的战略性资源，石油工业是国民经济和社会发展的支柱性产业。随着我国“两种资源，两种市场”的战略格局的形成，以及中石油等三大石油公司在海外的成功上市，如何对石油储量进行经济评价并使评价结果符合国际通行的规则，已成为摆在我们面前的重要和紧迫的问题。科学的石油储量动态经济评价，是加强与国际石油市场接轨的前提；是石油企业实施科学决策，加强风险防范的保证；是进一步深化石油企业改革的基础；是彻底改变若干年来我国“重技术储量轻经济储量”观念的需要。因此，本论文的选题既具有较好的理论研究价值，又具有很强的实践可操作意义。
根据国际权威机构对石油储量评价主要集中于探明储量的经济评价，而探明储量包括了探明已开发储量和探明未开发储量。因此，本文对石油储量动态经济评价研究的重点也放在探明未开发储量和探明已开发储量上。
论文采用的主要研究方法有：第一，定性分析与定量分析相结合的研究方法，以体现决策的科学性和石油资源的复杂性等特点；第二，规范分析与实证分析相结合的研究方法。论文以数量经济学、技术经济学、数学、复杂系统分析等学科知识为基础建立理论模型，将模型与实际案例结合作实证分析，使得建立的模型既具有理论性又具有实用性；第三，比较分析法。文中既注重理论方法的比较，又注重实证结果的比较。如对拓展的DCF-NPV模型和传统方法在同一油区的NPV值大小的比较、软计算方法和硬计算方法的比较等；第四，宏观与微观相结合的研究方法。论文主体关于石油储量动态分析部分总体思路是进行微观经济评价和宏观产量预测，微观经济评价侧重于油田的某一具体区块或某几个具体区块的研究，而宏观产量预测侧重于整个油田的研究；第五，系统分析法。本文的石油储量动态经济评价研究，既注重某具体油区的微观经济分析，又兼顾油田企业宏观发展规划，因而文章的主体构架就是宏观预测和微观评价。同时在具体的研究中，特别是模型的构建过程中，不是孤立地分析问题解决问题，而是将研究对象放在一个系统中，从系统的角度进行指标的构建、参数的选取，既体现了油田自身的特点以及非人为因子对经济指标的影响，又客观反映油田自身因子之外的社会因素的影响，这二类因子客观存在且共同影响经济指标。
论文的创新点主要体现在以下几方面：
第一，构建了探明未开发储量动态经济评价的DCF-NPV拓展模型，该拓展模型将项目经济寿命期分为勘探开发期、产量上升期、稳产期、减产期几个阶段，体现了石油价格以固定比率变化，石油产量稳产期保持不变，递减期成指数递减，开发成本在稳产期维持不变，在减产期以固定比率递增等特点，以客观地评价项目寿命期内资金的时间价值以及因素的变化对储量价值的影响情况。
第二，构建了探明已开发储量的动态经济下限产量(储量)分析模型，该模型反映了经济下限产量在分析期内不是一个固定值，而是随影响因子的变化而不同的。
第三，首次尝试性地将软计算方法引入到经济指标与其影响因子的关联性分析中，得到了比传统的硬计算方法(如回归分析法)更为精确的分析结果；而基于软计算的经济指标与多因子的综合关联性分析更是前人未曾涉足的。
第四，在进行油田宏观产量预测时，提出了基于软计算与硬计算融合的最近邻径向基-马尔可夫预测模型，该模型在宏观产量预测中的运用是一种全新的尝试，并且能够得到比传统的产量预测方法(灰色系统预测模型)更为精确的结果。
论文的主要研究内容和章节安排如下：
第一章绪论部分，主要内容包括论文的选题背景、研究的必要性和意义，以及全文的主要研究内容和研究方法、主要的创新点等。
第二章是关于中外石油储量经济评价方法的综述。论文首先介绍了中外石油储量分级标准，并对中外石油储量分级标准进行了比较，提出应进一步改进我国石油储量分级标准，并使之与国际接轨；然后介绍了国内外项目经济评价的发展状况；最后是国内外石油储量经济评价方法概述，指出我国石油储量经济评价方法在资金时间价值的动态体现、变动因子与经济指标的动态关联性、经济评价方法的适用性等方面存在不足。而这些不足之处正是本论文研究的重点。
第三章是石油储量动态经济评价的理论基础研究。文中分别从资源的劳动价值、资源的地租、资源的效用价值、资源的稀缺性价值和资源的耗竭性补偿价值以及环境的破坏补偿价值等价值理论论证矿产资源的价值体现。为后面的石油储量经济评价研究打下理论基础。
第四章是石油探明未开发储量的动态经济评价研究。论文以贴现现金流净值(DCF-NPV)为方法基础，考虑到石油工业企业生产经营中石油价格的随机波动性、石油产量的递减性、石油开发成本的递增性等具体特点，建立了基于若干假设前提的DCF-NPV拓展模型。其假设条件包括：第一，将整个项目寿命期分为勘探开发期、上产期、稳产期、减产期。产量分为稳产期产量(上产期一般时间较短，为便于计算，将上产期与稳产期合并，以稳产期产量代入模型)、递减期产量，假设稳产期的产量保持不变，递减期产量成指数递减；第二，假设石油价格以固定比率递增；第三，假设石油开发成本在稳产期保持不变，减产期以固定比率递增；第四，假设计息周期为年，即每年复利一次；第五，假设相关税费率在计算期内是不变的。由此建立的DCF-NPV拓展模型既体现了石油行业的特点，又体现了石油储量经济评价的动态特点，相对于传统的基于确定参数下的DCF-NPV模型来讲，更具有现实可操作价值。根据建立的拓展模型，不仅可以通过计算对石油储量开发的可行性进行经济评价，而且可以通过该模型进行决策控制，根据现有的储量规模，获取企业对利率、价格、成本等因素变动的最大承受力和投资极限，以利于风险防范和投资决策。最后以某油区的实际案例来展示拓展模型的可操作性。
第五章是石油探明已开发储量的动态经济评价研究。探明已开发储量的研究实际上就是剩余可采储量的研究，其开发的经济性评价也就是剩余可采储量的经济性评价。对探明已开发储量进行经济分析时，关键是分析追加投资(成本)的必要性与可行性，常用于企业内部管理和决策，而企业对剩余可采储量的评价常用单位时间的井产量来表示。基于此，本文关于探明已开发储量的动态经济评价研究重点在产量。作者在论文中提出了经济下限产量的概念，并对经济下限产量的内涵作了界定，即在现有的技术经济条件下，能保证企业获得经济效益的最低可开采产量。论文以盈亏平衡分析和净现值为方法基础，建立了体现资金时间价值、价格和成本以固定比率变动的动态经济下限产量分析模型和最低储量规模模型。与传统的静态分析模型相比较，建立的动态模型更能反映项目的经营安全率，更能直观地反映价格、成本、折现率等因子的变动对经济下限产量的影响以及企业的经营风险承受力，从而为企业是否继续对开发井进行追加成本提供决策依据。文中还特别对相关参数的确定提出了自己的看法。最后以某油田的某区块为实际案例，分别运用传统的静态分析方法和本文的动态分析模型进行计算，通过对结果的比较，得出动态模型的优越性和实用性。同时提出，经济下限产量在项目寿命期内不是固定不变的，而是不断变化着的，其大小与影响因子关系密切。因此，在计算项目经济下限产量时必须充分考虑各种因子的变化，以更加客观地进行油田项目的经济可采性评价。
第六章是基于人工神经网络(ANN)的经济下限产量(储量)与影响因子的关联性分析，该部分内容是第五章内容的延续。论文首次尝试性地以软计算(ANN)为分析方法基础，结合具体的油田，根据石油开发的实际情况和资料的可得性，选取原油价格、油藏埋深、油藏面积、采收率等作为论文中影响经济下限产量(储量)的因子，并将其划分为外部因子(价格)和内部因子(油藏埋深、油藏面积、采收率等)。文中，首先用软计算方法分别进行了价格、深度等因子与经济下限产量的单因子关联性分析，得到各因子与经济下限产量的关系模型。同时，为了论证软计算方法的精确性，文中还将软计算分析结果与传统的回归分析结果进行了比较，得出软计算方法比传统的硬计算方法具有更高的精确度。在单因子关联性分析的基础上，为进一步反映因子与经济指标之间的关系的复杂性、关联性和因子之间关系的不可分割性，以使建立的关联性模型具有更强的可解释性，文中又运用软计算进一步进行了经济下限产量(储量)与外部因子、经济下限产量与内部因子、经济下限产量与内外部因子的综合关联性分析，以提高企业的综合预测能力和控制能力。
第七章是对江汉油田的宏观储量-产量预测研究。对石油工业企业而言，石油产量的宏观预测对油田企业的勘探开发规划、生产经营计划均具有重要的意义，可为石油企业合理制订生产任务、避免盲目投资和开发提供决策支持，保证每年的开采量遵从既定的开发模式，以达到长期可持续发展的战略目标。本文首次尝试将软计算(最近邻径向基法)与硬计算(马尔可夫法)方法相结合，以江汉油田为研究对象，对江汉油田未来几年的产量进行宏观预测。同时，将文中所用的分析方法与传统灰色系统GM(1，1)模型进行比较，得到最近邻径向基-马尔可夫模型在宏观产量预测中比传统的硬计算方法精确性更高。从而证明了作者首次所尝试采用的最近邻径向基-马尔可夫模型在宏观产量预测方面的可解释性和实际可推广价值。
第八章是作者对全文的总结以及为保证科学合理的储量经济评价的建议。主要建议包括：第一，加强历史数据的收集、整理和保存工作，并完善和规范各项分析指标，以便于经济评价工作的顺利开展；第二，提高现有的折现率水平，以使石油企业合理地规避风险；第三，改革现有的二档油价制度，实施不同的储量评价目的采用不同的油价标准；第四，改变现有的平均折旧法为快速折旧法，以确保企业资金的尽快回笼和二次开发资金；第五，改变现有的一刀切的税收制度，采取分级税制。此外，应关注软计算集成方法在石油勘探开发和经营管理中的应用。
As we all know, oil is the important strategic resource, and the oil industry is the pillarindustry of the national economy and social development. Recently the strategic pattern of "fullyutilizing the both domestic and international markets and resources" has been formed, and threeleading oil companies such as Petrochina have listed overseas successfully. Therefore, it is anurgent and essential problem about how to evaluate oil reserves economically and how to make theresults conform to the globally accepted rules. The scientific dynamic economic evaluation of oilreserves is the premise of enhancing the connection of the intemational standards, is the safeguardof the implementation of scientific resolution of oil companies, and the strengthen of the riskprevention, paving the way for the deep reforms of oil companies, and thoroughly change theconcept of emphasizing on technical reserves instead of economic reserves. Consequently, thispaper has better global theoretical research value and practical value.
The international authorities focus on the economical evaluation of the proved reserves,including proved developed reserves and proved undeveloped reserves. Therefore, the dynamiceconomic evaluation of oil reserves in this paper concentrates on proved developed reserves andproved undeveloped reserves.
This paper carries on the research by adopting the following methods: First, the methods ofthe quantitative analysis and qualitative analysis in order to embody the scientificalness ofdecisions and the complexity of oil resources. Second, the methods of the standardized analysisand empirical analysis. This paper sets up the theoretical model on the basis of QuantitativeEconomics, Technical Economics, Mathematics, and Complex Analysis. It combines the modeland cases, thus making the model theoretical and practical. Third, comparative analysis methods.This paper emphasizes both the theoretical methods and comparatives of empirical results. Forexample, the comparison of NPV value between the model of expanding DCF-NP and thetraditional method on the same oil area, the comparison of the soft computing and the hardcomputing and so on. Fourth, the methods of the macro-scope and micro-scope. The body of thispaper on the dynamic analysis of oil reserves is to make micro-economic evaluation and the macroproduction forecast, the micro-economic evaluation lays emphasis on the research of one orseveral specific blocks, and the macro production forecast focus on the research of the whole oilfield; Fifth, system analysis. The dynamic economic evaluation of oil reserves in this paper basedon the concept of large system, lays emphasis both on the micro-economic evaluation of somespecific oil fields and micro-development planning of the oilfield enterprises, thus the mainstructure of this paper is macro forecast and micro evaluation. At the same time, in some specificresearch, especially during the process of the model constructing, it's not only to analysis andfigure out question solely, but to make the object in a system background, construct indicators andchoose index from the system aspects, in this method, it embodies the oil field characteristic andthe influence of non-artificial factors to Economic indicators, what more, it reflects the influence of social factors besides it 'self objectively, which the two factors is objective existence andinfluent the Economic indicators together.
The innovation of this paper reflects in the following mainly:
First, it has constructed the dynamic economical evaluation of proved undeveloped reservesDCF-NPV expanding model ,which model can dived the economic life period into exploration anddevelopment phase ,output rising period, phase stability and output reducing period, it reflects thechanging of the oil price under fixed ratio ,the output of the oil in a phase stability ,the reducingphase with exponential decline, the development cost remains unchanged in the period of thePhase Stability, the characteristics of the increasing under fixed ratio during output reducingperiod, to objective evaluate the influence generated by the changing of the time value of capitaland altering factors during the economic life period.
Second, it has set up the analytical model of the dynamic economical evaluation of provedundeveloped reserves lower limited output (reserve), which reflects that the economic lowerlimited output varies with the impact factors instead of stabilizing during the analytical period.
Third, the soft computing method is initially adopted in the study of correlation betweeneconomic indicators and impact factors which gives us more accurate analytical results than thosefrom traditional hard computing method (e.g. regression analysis). Moreover, the study of thecorrelation of economic indicators and multiple factors based on soft computing method is thestudy which has never been anglicized by predecessors.
Fourth, Radial Basis Function of Nearest Neighbor-Markov (RBFNN-Markov)forecasting model based on soft computing and hard computing method is put forward in theprocess of oilfield production macro predication. The model is a brand new attempt in the field ofproduction macro predication, and gets more accurate results than those of the traditionalproduction predication method (Gray Model).
Major chapters are organized as the following:
Chapter 1 is the preface including subject-selecting background, the necessity andsignificance for studying, the main research contents and the research approaches, as well as themain innovative points.
Chapter 2 is the summary of the economic evaluation of domestic and international oilreserves. First of all, the paper introduces grade scales of domestic and international oil reserves,compares grade scale of domestic oil reserves and that of international oil reserves, advocates theimprovement of domestic oil reserves grade scale and makes domestic grade scale conform to theinternational standard. Then, the paper demonstrates development situation of economicevaluation of projects at home and abroad. Last, the paper outlines economic evaluation methodsof domestic and international oil reserves, as well as the in adequacies the dynamic embodiment ofeconomic evaluation methods of domestic and international oil reserves in the value of capital andtime, the dynamic correlation between variance factors and economic indicators, the applicabilityof economic evaluation methods. The inadequacies mentioned above are the focus of this paper.
Chapter 3 is the research on the theoretical base of oil reserves dynamic economic evaluation.The paper proves the value embodiment of mineral resources in the aspects of value theories such as labor value, rent, utility value, and scarcity value of resources, as well as compensation value ofexhaustible and breakage resources. It lays the solid theoretical foundation for the followingresearch on economical evaluation of oil reserves.
Chapter 4 is about the dynamic economic evaluation of proved undeveloped oil reserves. TheDCF-NPV expanding model on the basis of several assumptions and DCF-NPV is set up, with thefollowing factors considered, such as the stochastic fouctuation of oil price, decreasing of oilproduction and increasing of oil development cost .The assumptions include: first, the economiclife period is divided into exploration and development period, the middle period, the stableproduction period, the production declining period. The output include the output of the oil instable production period, the output in the production declining period, suppose the output in thestable phase remains unchanging, the output in the production declining period declinesexponentially; second, suppose the oil price increases under a fixed ratio; third, suppose thedevelopment cost remains unchanging in the stable production period, the cost decreases under afixed ratio in the production declining period; fourth, suppose a year is the interest bearing period,that is compound interest is calculated every year; fifth, suppose the relative tax rate remainsunchanging in the calculating period. The expanding DCF-NPV model embodies both the featuresof oil industry and the dynamic features of oil reserves economic evaluation. The model is morepractical and operable than the traditional DCF-NPV model based on the determined parameters.According to the founded expanding model, economical evaluation of the applicability of oilreserves development can be calculated and control decisions can be made to get the maximumand investment limit of the following factors such as interest ratio, price and cost as well as todefend the risk and decide the investment based on the current reserve scale. At last a case in aspecific oilfield will be presented to prove the applicability of the expanding model.
Chapter 5 deals with the research on dynamic economic evaluation of proved developed oilreserves. Proved developed oil reserves refer to the remaining recoverable reserves. Economicalevaluation of the development refers to economical evaluation of the remaining recoverablereserves. Economical evaluation of proved developed oil reserves focuses on the analysis of thenecessity and applicability of additional investment (cost), the management policy and decisionsapplied in the enterprises, while the evaluation of the remaining recoverable reserves is usuallydemonstrated by the well production in the unit time. Therefore, the paper focuses on the output.The author demonstrates the concept of the economic lower output and defines the connotation ofthe economic lower output, which refers to the minimum output to ensure that the enterprise gainthe profit under the current technical and economic situation. The paper sets up the minimumreserve scale model and the analytical model of dynamic economic lower output under thesituation when capital, time, price, value and cost change under fixed ratios. Compared with thetraditional static analytical model, the dynamic model can reflect operational security rate, theinfluence on the economic lower output by the alteration of price, cost, and discount rate and theoperational risk tolerance to provide basis for decision making for the further additionalinvestment in the well development. At last a case of a specific oilfield will be presented to provethe superiority and practicality of the dynamic model through the comparison between the results of the traditional static model and the dynamic model discussed in the paper. At themeantime, it demonstrates the economic lower output varies in the life period with the closecorrelation with the impact factors. Therefore, various factors should be considered whencalculating the economic lower output in order to evaluate the recoverability of oilfield projectsmore objectively.
Chapter 6 is about the study of the correlation between the lower output and the impactfactors based on the automated neural network (ANN). It is the continuation of the chapter 5. Thepaper selects the crude oil price, oil layers depth reservoir area and recovery rate as the impactfactors which influence the lower output by the means of the soft computing method (ANN), thereal situation and the accessibility of materials. The factors can be divided into external factors andinternal factors. The paper adopts the soft computing method to study the correlation betweenprice, depth and lower output, thus getting the model about those factors. At the same time, itcompares the results of the soft computing analysis with traditional regression analysis to provethat the former method is more accurate. On the basis of the correlation study of single factor, thepaper adopts soft computing method further to study the correlation between the lower output andexternal factors, internal factors to reflect the complexity, correlation and indivisibility and toenhance the predictable and controllable ability.
Chapter 7 is about the research of Jianghan Oil Field macro-preserve--prediction studies. Asfor the oil industry, the macro prediction of the output of the oil has great significance inExploration and Development planning and production planning. It offers the decision -support forthe reasonable task planning, development and avoidance of blind investment. It ensures that theannual recovery abide by the established development model to reach the strategic goal ofsustainable development in the long run. The paper initially combines the soft computing method(RBFNN) with the hard computing method (Markov) and takes Jianghan oilfield for example toconduct macro predication of the output in the following years. Meanwhile, it proves that model ismore accurate in output macro predication by comparing the method in this paper with thetraditional GM (1,1). The result proves that the model is explainable, practical and operable inmacro prediction.
Chapter 8 is the conclusion and the recommendation on scientific and reasonable reserveseconomic evaluation. It includes: first, collection, arrangement and perseverance of historicalstatistics should be strengthened; various analytical index should be regulated to pave the way forsuccessful evaluation. Second, current discount rate should be raised to evade risk. Third, currentsecond gear oil price system should be reformed and different price standards should be adopted indifferent evaluation projects. Fourth, straight-line depreciation method and accelerateddepreciation method should be altered to speed up return of capital and ensure the developmentfund. Fifth, current tax system of guillotine principle in cutting stock should be changed andclassification tax system should be adopted. In addition, the application of soft computing methodin the exploration and management should be emphasized.
根据国际权威机构对石油储量评价主要集中于探明储量的经济评价，而探明储量包括了探明已开发储量和探明未开发储量。因此，本文对石油储量动态经济评价研究的重点也放在探明未开发储量和探明已开发储量上。
论文采用的主要研究方法有：第一，定性分析与定量分析相结合的研究方法，以体现决策的科学性和石油资源的复杂性等特点；第二，规范分析与实证分析相结合的研究方法。论文以数量经济学、技术经济学、数学、复杂系统分析等学科知识为基础建立理论模型，将模型与实际案例结合作实证分析，使得建立的模型既具有理论性又具有实用性；第三，比较分析法。文中既注重理论方法的比较，又注重实证结果的比较。如对拓展的DCF-NPV模型和传统方法在同一油区的NPV值大小的比较、软计算方法和硬计算方法的比较等；第四，宏观与微观相结合的研究方法。论文主体关于石油储量动态分析部分总体思路是进行微观经济评价和宏观产量预测，微观经济评价侧重于油田的某一具体区块或某几个具体区块的研究，而宏观产量预测侧重于整个油田的研究；第五，系统分析法。本文的石油储量动态经济评价研究，既注重某具体油区的微观经济分析，又兼顾油田企业宏观发展规划，因而文章的主体构架就是宏观预测和微观评价。同时在具体的研究中，特别是模型的构建过程中，不是孤立地分析问题解决问题，而是将研究对象放在一个系统中，从系统的角度进行指标的构建、参数的选取，既体现了油田自身的特点以及非人为因子对经济指标的影响，又客观反映油田自身因子之外的社会因素的影响，这二类因子客观存在且共同影响经济指标。
论文的创新点主要体现在以下几方面：
第一，构建了探明未开发储量动态经济评价的DCF-NPV拓展模型，该拓展模型将项目经济寿命期分为勘探开发期、产量上升期、稳产期、减产期几个阶段，体现了石油价格以固定比率变化，石油产量稳产期保持不变，递减期成指数递减，开发成本在稳产期维持不变，在减产期以固定比率递增等特点，以客观地评价项目寿命期内资金的时间价值以及因素的变化对储量价值的影响情况。
第二，构建了探明已开发储量的动态经济下限产量(储量)分析模型，该模型反映了经济下限产量在分析期内不是一个固定值，而是随影响因子的变化而不同的。
第三，首次尝试性地将软计算方法引入到经济指标与其影响因子的关联性分析中，得到了比传统的硬计算方法(如回归分析法)更为精确的分析结果；而基于软计算的经济指标与多因子的综合关联性分析更是前人未曾涉足的。
第四，在进行油田宏观产量预测时，提出了基于软计算与硬计算融合的最近邻径向基-马尔可夫预测模型，该模型在宏观产量预测中的运用是一种全新的尝试，并且能够得到比传统的产量预测方法(灰色系统预测模型)更为精确的结果。
论文的主要研究内容和章节安排如下：
第一章绪论部分，主要内容包括论文的选题背景、研究的必要性和意义，以及全文的主要研究内容和研究方法、主要的创新点等。
第二章是关于中外石油储量经济评价方法的综述。论文首先介绍了中外石油储量分级标准，并对中外石油储量分级标准进行了比较，提出应进一步改进我国石油储量分级标准，并使之与国际接轨；然后介绍了国内外项目经济评价的发展状况；最后是国内外石油储量经济评价方法概述，指出我国石油储量经济评价方法在资金时间价值的动态体现、变动因子与经济指标的动态关联性、经济评价方法的适用性等方面存在不足。而这些不足之处正是本论文研究的重点。
第三章是石油储量动态经济评价的理论基础研究。文中分别从资源的劳动价值、资源的地租、资源的效用价值、资源的稀缺性价值和资源的耗竭性补偿价值以及环境的破坏补偿价值等价值理论论证矿产资源的价值体现。为后面的石油储量经济评价研究打下理论基础。
第四章是石油探明未开发储量的动态经济评价研究。论文以贴现现金流净值(DCF-NPV)为方法基础，考虑到石油工业企业生产经营中石油价格的随机波动性、石油产量的递减性、石油开发成本的递增性等具体特点，建立了基于若干假设前提的DCF-NPV拓展模型。其假设条件包括：第一，将整个项目寿命期分为勘探开发期、上产期、稳产期、减产期。产量分为稳产期产量(上产期一般时间较短，为便于计算，将上产期与稳产期合并，以稳产期产量代入模型)、递减期产量，假设稳产期的产量保持不变，递减期产量成指数递减；第二，假设石油价格以固定比率递增；第三，假设石油开发成本在稳产期保持不变，减产期以固定比率递增；第四，假设计息周期为年，即每年复利一次；第五，假设相关税费率在计算期内是不变的。由此建立的DCF-NPV拓展模型既体现了石油行业的特点，又体现了石油储量经济评价的动态特点，相对于传统的基于确定参数下的DCF-NPV模型来讲，更具有现实可操作价值。根据建立的拓展模型，不仅可以通过计算对石油储量开发的可行性进行经济评价，而且可以通过该模型进行决策控制，根据现有的储量规模，获取企业对利率、价格、成本等因素变动的最大承受力和投资极限，以利于风险防范和投资决策。最后以某油区的实际案例来展示拓展模型的可操作性。
第五章是石油探明已开发储量的动态经济评价研究。探明已开发储量的研究实际上就是剩余可采储量的研究，其开发的经济性评价也就是剩余可采储量的经济性评价。对探明已开发储量进行经济分析时，关键是分析追加投资(成本)的必要性与可行性，常用于企业内部管理和决策，而企业对剩余可采储量的评价常用单位时间的井产量来表示。基于此，本文关于探明已开发储量的动态经济评价研究重点在产量。作者在论文中提出了经济下限产量的概念，并对经济下限产量的内涵作了界定，即在现有的技术经济条件下，能保证企业获得经济效益的最低可开采产量。论文以盈亏平衡分析和净现值为方法基础，建立了体现资金时间价值、价格和成本以固定比率变动的动态经济下限产量分析模型和最低储量规模模型。与传统的静态分析模型相比较，建立的动态模型更能反映项目的经营安全率，更能直观地反映价格、成本、折现率等因子的变动对经济下限产量的影响以及企业的经营风险承受力，从而为企业是否继续对开发井进行追加成本提供决策依据。文中还特别对相关参数的确定提出了自己的看法。最后以某油田的某区块为实际案例，分别运用传统的静态分析方法和本文的动态分析模型进行计算，通过对结果的比较，得出动态模型的优越性和实用性。同时提出，经济下限产量在项目寿命期内不是固定不变的，而是不断变化着的，其大小与影响因子关系密切。因此，在计算项目经济下限产量时必须充分考虑各种因子的变化，以更加客观地进行油田项目的经济可采性评价。
第六章是基于人工神经网络(ANN)的经济下限产量(储量)与影响因子的关联性分析，该部分内容是第五章内容的延续。论文首次尝试性地以软计算(ANN)为分析方法基础，结合具体的油田，根据石油开发的实际情况和资料的可得性，选取原油价格、油藏埋深、油藏面积、采收率等作为论文中影响经济下限产量(储量)的因子，并将其划分为外部因子(价格)和内部因子(油藏埋深、油藏面积、采收率等)。文中，首先用软计算方法分别进行了价格、深度等因子与经济下限产量的单因子关联性分析，得到各因子与经济下限产量的关系模型。同时，为了论证软计算方法的精确性，文中还将软计算分析结果与传统的回归分析结果进行了比较，得出软计算方法比传统的硬计算方法具有更高的精确度。在单因子关联性分析的基础上，为进一步反映因子与经济指标之间的关系的复杂性、关联性和因子之间关系的不可分割性，以使建立的关联性模型具有更强的可解释性，文中又运用软计算进一步进行了经济下限产量(储量)与外部因子、经济下限产量与内部因子、经济下限产量与内外部因子的综合关联性分析，以提高企业的综合预测能力和控制能力。
第七章是对江汉油田的宏观储量-产量预测研究。对石油工业企业而言，石油产量的宏观预测对油田企业的勘探开发规划、生产经营计划均具有重要的意义，可为石油企业合理制订生产任务、避免盲目投资和开发提供决策支持，保证每年的开采量遵从既定的开发模式，以达到长期可持续发展的战略目标。本文首次尝试将软计算(最近邻径向基法)与硬计算(马尔可夫法)方法相结合，以江汉油田为研究对象，对江汉油田未来几年的产量进行宏观预测。同时，将文中所用的分析方法与传统灰色系统GM(1，1)模型进行比较，得到最近邻径向基-马尔可夫模型在宏观产量预测中比传统的硬计算方法精确性更高。从而证明了作者首次所尝试采用的最近邻径向基-马尔可夫模型在宏观产量预测方面的可解释性和实际可推广价值。
第八章是作者对全文的总结以及为保证科学合理的储量经济评价的建议。主要建议包括：第一，加强历史数据的收集、整理和保存工作，并完善和规范各项分析指标，以便于经济评价工作的顺利开展；第二，提高现有的折现率水平，以使石油企业合理地规避风险；第三，改革现有的二档油价制度，实施不同的储量评价目的采用不同的油价标准；第四，改变现有的平均折旧法为快速折旧法，以确保企业资金的尽快回笼和二次开发资金；第五，改变现有的一刀切的税收制度，采取分级税制。此外，应关注软计算集成方法在石油勘探开发和经营管理中的应用。
As we all know, oil is the important strategic resource, and the oil industry is the pillarindustry of the national economy and social development. Recently the strategic pattern of "fullyutilizing the both domestic and international markets and resources" has been formed, and threeleading oil companies such as Petrochina have listed overseas successfully. Therefore, it is anurgent and essential problem about how to evaluate oil reserves economically and how to make theresults conform to the globally accepted rules. The scientific dynamic economic evaluation of oilreserves is the premise of enhancing the connection of the intemational standards, is the safeguardof the implementation of scientific resolution of oil companies, and the strengthen of the riskprevention, paving the way for the deep reforms of oil companies, and thoroughly change theconcept of emphasizing on technical reserves instead of economic reserves. Consequently, thispaper has better global theoretical research value and practical value.
The international authorities focus on the economical evaluation of the proved reserves,including proved developed reserves and proved undeveloped reserves. Therefore, the dynamiceconomic evaluation of oil reserves in this paper concentrates on proved developed reserves andproved undeveloped reserves.
This paper carries on the research by adopting the following methods: First, the methods ofthe quantitative analysis and qualitative analysis in order to embody the scientificalness ofdecisions and the complexity of oil resources. Second, the methods of the standardized analysisand empirical analysis. This paper sets up the theoretical model on the basis of QuantitativeEconomics, Technical Economics, Mathematics, and Complex Analysis. It combines the modeland cases, thus making the model theoretical and practical. Third, comparative analysis methods.This paper emphasizes both the theoretical methods and comparatives of empirical results. Forexample, the comparison of NPV value between the model of expanding DCF-NP and thetraditional method on the same oil area, the comparison of the soft computing and the hardcomputing and so on. Fourth, the methods of the macro-scope and micro-scope. The body of thispaper on the dynamic analysis of oil reserves is to make micro-economic evaluation and the macroproduction forecast, the micro-economic evaluation lays emphasis on the research of one orseveral specific blocks, and the macro production forecast focus on the research of the whole oilfield; Fifth, system analysis. The dynamic economic evaluation of oil reserves in this paper basedon the concept of large system, lays emphasis both on the micro-economic evaluation of somespecific oil fields and micro-development planning of the oilfield enterprises, thus the mainstructure of this paper is macro forecast and micro evaluation. At the same time, in some specificresearch, especially during the process of the model constructing, it's not only to analysis andfigure out question solely, but to make the object in a system background, construct indicators andchoose index from the system aspects, in this method, it embodies the oil field characteristic andthe influence of non-artificial factors to Economic indicators, what more, it reflects the influence of social factors besides it 'self objectively, which the two factors is objective existence andinfluent the Economic indicators together.
The innovation of this paper reflects in the following mainly:
First, it has constructed the dynamic economical evaluation of proved undeveloped reservesDCF-NPV expanding model ,which model can dived the economic life period into exploration anddevelopment phase ,output rising period, phase stability and output reducing period, it reflects thechanging of the oil price under fixed ratio ,the output of the oil in a phase stability ,the reducingphase with exponential decline, the development cost remains unchanged in the period of thePhase Stability, the characteristics of the increasing under fixed ratio during output reducingperiod, to objective evaluate the influence generated by the changing of the time value of capitaland altering factors during the economic life period.
Second, it has set up the analytical model of the dynamic economical evaluation of provedundeveloped reserves lower limited output (reserve), which reflects that the economic lowerlimited output varies with the impact factors instead of stabilizing during the analytical period.
Third, the soft computing method is initially adopted in the study of correlation betweeneconomic indicators and impact factors which gives us more accurate analytical results than thosefrom traditional hard computing method (e.g. regression analysis). Moreover, the study of thecorrelation of economic indicators and multiple factors based on soft computing method is thestudy which has never been anglicized by predecessors.
Fourth, Radial Basis Function of Nearest Neighbor-Markov (RBFNN-Markov)forecasting model based on soft computing and hard computing method is put forward in theprocess of oilfield production macro predication. The model is a brand new attempt in the field ofproduction macro predication, and gets more accurate results than those of the traditionalproduction predication method (Gray Model).
Major chapters are organized as the following:
Chapter 1 is the preface including subject-selecting background, the necessity andsignificance for studying, the main research contents and the research approaches, as well as themain innovative points.
Chapter 2 is the summary of the economic evaluation of domestic and international oilreserves. First of all, the paper introduces grade scales of domestic and international oil reserves,compares grade scale of domestic oil reserves and that of international oil reserves, advocates theimprovement of domestic oil reserves grade scale and makes domestic grade scale conform to theinternational standard. Then, the paper demonstrates development situation of economicevaluation of projects at home and abroad. Last, the paper outlines economic evaluation methodsof domestic and international oil reserves, as well as the in adequacies the dynamic embodiment ofeconomic evaluation methods of domestic and international oil reserves in the value of capital andtime, the dynamic correlation between variance factors and economic indicators, the applicabilityof economic evaluation methods. The inadequacies mentioned above are the focus of this paper.
Chapter 3 is the research on the theoretical base of oil reserves dynamic economic evaluation.The paper proves the value embodiment of mineral resources in the aspects of value theories such as labor value, rent, utility value, and scarcity value of resources, as well as compensation value ofexhaustible and breakage resources. It lays the solid theoretical foundation for the followingresearch on economical evaluation of oil reserves.
Chapter 4 is about the dynamic economic evaluation of proved undeveloped oil reserves. TheDCF-NPV expanding model on the basis of several assumptions and DCF-NPV is set up, with thefollowing factors considered, such as the stochastic fouctuation of oil price, decreasing of oilproduction and increasing of oil development cost .The assumptions include: first, the economiclife period is divided into exploration and development period, the middle period, the stableproduction period, the production declining period. The output include the output of the oil instable production period, the output in the production declining period, suppose the output in thestable phase remains unchanging, the output in the production declining period declinesexponentially; second, suppose the oil price increases under a fixed ratio; third, suppose thedevelopment cost remains unchanging in the stable production period, the cost decreases under afixed ratio in the production declining period; fourth, suppose a year is the interest bearing period,that is compound interest is calculated every year; fifth, suppose the relative tax rate remainsunchanging in the calculating period. The expanding DCF-NPV model embodies both the featuresof oil industry and the dynamic features of oil reserves economic evaluation. The model is morepractical and operable than the traditional DCF-NPV model based on the determined parameters.According to the founded expanding model, economical evaluation of the applicability of oilreserves development can be calculated and control decisions can be made to get the maximumand investment limit of the following factors such as interest ratio, price and cost as well as todefend the risk and decide the investment based on the current reserve scale. At last a case in aspecific oilfield will be presented to prove the applicability of the expanding model.
Chapter 5 deals with the research on dynamic economic evaluation of proved developed oilreserves. Proved developed oil reserves refer to the remaining recoverable reserves. Economicalevaluation of the development refers to economical evaluation of the remaining recoverablereserves. Economical evaluation of proved developed oil reserves focuses on the analysis of thenecessity and applicability of additional investment (cost), the management policy and decisionsapplied in the enterprises, while the evaluation of the remaining recoverable reserves is usuallydemonstrated by the well production in the unit time. Therefore, the paper focuses on the output.The author demonstrates the concept of the economic lower output and defines the connotation ofthe economic lower output, which refers to the minimum output to ensure that the enterprise gainthe profit under the current technical and economic situation. The paper sets up the minimumreserve scale model and the analytical model of dynamic economic lower output under thesituation when capital, time, price, value and cost change under fixed ratios. Compared with thetraditional static analytical model, the dynamic model can reflect operational security rate, theinfluence on the economic lower output by the alteration of price, cost, and discount rate and theoperational risk tolerance to provide basis for decision making for the further additionalinvestment in the well development. At last a case of a specific oilfield will be presented to provethe superiority and practicality of the dynamic model through the comparison between the results of the traditional static model and the dynamic model discussed in the paper. At themeantime, it demonstrates the economic lower output varies in the life period with the closecorrelation with the impact factors. Therefore, various factors should be considered whencalculating the economic lower output in order to evaluate the recoverability of oilfield projectsmore objectively.
Chapter 6 is about the study of the correlation between the lower output and the impactfactors based on the automated neural network (ANN). It is the continuation of the chapter 5. Thepaper selects the crude oil price, oil layers depth reservoir area and recovery rate as the impactfactors which influence the lower output by the means of the soft computing method (ANN), thereal situation and the accessibility of materials. The factors can be divided into external factors andinternal factors. The paper adopts the soft computing method to study the correlation betweenprice, depth and lower output, thus getting the model about those factors. At the same time, itcompares the results of the soft computing analysis with traditional regression analysis to provethat the former method is more accurate. On the basis of the correlation study of single factor, thepaper adopts soft computing method further to study the correlation between the lower output andexternal factors, internal factors to reflect the complexity, correlation and indivisibility and toenhance the predictable and controllable ability.
Chapter 7 is about the research of Jianghan Oil Field macro-preserve--prediction studies. Asfor the oil industry, the macro prediction of the output of the oil has great significance inExploration and Development planning and production planning. It offers the decision -support forthe reasonable task planning, development and avoidance of blind investment. It ensures that theannual recovery abide by the established development model to reach the strategic goal ofsustainable development in the long run. The paper initially combines the soft computing method(RBFNN) with the hard computing method (Markov) and takes Jianghan oilfield for example toconduct macro predication of the output in the following years. Meanwhile, it proves that model ismore accurate in output macro predication by comparing the method in this paper with thetraditional GM (1,1). The result proves that the model is explainable, practical and operable inmacro prediction.
Chapter 8 is the conclusion and the recommendation on scientific and reasonable reserveseconomic evaluation. It includes: first, collection, arrangement and perseverance of historicalstatistics should be strengthened; various analytical index should be regulated to pave the way forsuccessful evaluation. Second, current discount rate should be raised to evade risk. Third, currentsecond gear oil price system should be reformed and different price standards should be adopted indifferent evaluation projects. Fourth, straight-line depreciation method and accelerateddepreciation method should be altered to speed up return of capital and ensure the developmentfund. Fifth, current tax system of guillotine principle in cutting stock should be changed andclassification tax system should be adopted. In addition, the application of soft computing methodin the exploration and management should be emphasized.
引文
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