Refining solutions of development problems of the Volga-Ural oil and gas province fields using geological and statistical model ranking methods

R. Gilyazetdinov, L. Kuleshova, V. Mukhametshin, R. Yakupov, V. A. Grishchenko
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Abstract

The purpose of the present research is to provide a comprehensive analysis of data on the geological and physical properties of formations and the fluids saturating them in the Volga-Ural oil and gas province using the methods of geological and statistical model ranking. The discriminant analysis conducted on the basis of qualitative criteria (reservoir type and stratigraphic confinement) identified in all cases the zones of uncertainty, which affect the effectiveness of managerial decision-making in the conditions of analog objects. On this score, the results for six models were refined and updated according to the principle of rank uniqueness value calculation by three methods, both for each model individually and for model systems while using them within the obtained distributions of objects in the axes of canonical discriminant functions. Theoretical and practical recommendations were given regarding the use of geological and statistical models in the development of Volga-Ural oil and gas province fields. The results obtained can be used to solve a wide range of practical problems of proactive resource management, which enable effective determination of the best strategy for the successful extraction of residual and hard-to-recover oil reserves. The proposed parameter ranking table allows both to determine the most unstable parameters with a high degree of probability and to level the factor of heterogeneity and disequilibrium of field data. The conducted study established that identification of object association with a particular group in the axes of canonical discriminant functions leads to the formation of the zone of uncertainty. The latter increases the risks of making ineffective managerial decisions when developing different categories of subsoil users’ assets. Using the methods of ranking geological and statistical models, an algorithm for constructing a hierarchical system is proposed, which allows to expand the application field of the results of geological and statistical modeling in the oil and gas industry as well as to reduce the risk of nonrepresentative results.
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利用地质和统计模型排序方法完善伏尔加-乌拉尔油气田开发问题的解决方案
本研究的目的是利用地质和统计模型排序方法,对伏尔加-乌拉尔石油天然气省地层的地质和物理特性及其饱和流体的数据进行综合分析。在定性标准(储层类型和地层封闭性)基础上进行的判别分析确定了所有情况下的不确定性区域,这些不确定性区域会影响模拟对象条件下管理决策的有效性。在此基础上,根据等级唯一性值计算原则,通过三种方法对六个模型的结果进行了完善和更新,既针对每个模型,也针对模型系统,同时将它们用于在典型判别函数轴上获得的对象分布中。就伏尔加-乌拉尔油气田开发中地质和统计模型的使用提出了理论和实践建议。所获得的结果可用于解决主动资源管理的各种实际问题,从而有效确定成功开采残余和难采石油储量的最佳战略。所提出的参数排序表既能以高概率确定最不稳定的参数,又能消除油田数据的异质性和不平衡性因素。研究结果表明,在典型判别函数轴上确定与特定组相关的对象会导致不确定区域的形成。后者增加了在开发不同类别的底土使用者资产时做出无效管理决策的风险。利用地质和统计模型的排序方法,提出了一种构建分层系统的算法,从而扩大了地质和统计模型结果在石油和天然气行业的应用范围,并降低了结果不具代表性的风险。
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