Optimization and operational maximization of oil wells/fields production

有杆泵抽油是最广泛使用的人工举升采油方式，在加拿大/美国的所有生产威尔斯井中约有85%至90%是有杆泵抽油。分析有杆泵抽油系统产能的方法是利用现有的抽油杆位置和所施加载荷的测量结果，并推断油井的工作条件（每次冲程的抽油量和/或气量，机械元件的条件，所施加的力等）。通常，油井状况的直接测量是不可能实现的，因为它需要在井内安装额外的设备，使得识别油井状况和生产参数的任务在模型识别、参数估计、控制和优化的工程方法内。换句话说，我们将开发一个数学模型，该模型考虑井动态特性，为参数估计和井况识别提供自适应和自学习机制，为决策结构构建逻辑以考虑环境、安全和总体操作参数，为抽油杆系统提供最佳调节并考虑操作经济约束，并提供包括供需市场和资源动态的长期和短期经济运行条件的优化。

The sucker-rod pumping is the most widely used means of artificial lift of oil and about 85% to 90% of all producing wells in Canada/US are sucker-rod pumps. The way to analyze productivity of the sucker-rod pumping system is to use available measurements of the sucker-rod position and load applied and deduce the oil well operating conditions (the amount of oil and/or gas pumped out per stroke, the conditions of mechanical elements, forces applied, etc.). In general, direct measurement of the oil well conditions is not realizable since it requires additional equipment installation within the well, so that the task of identification of oil well conditions and production parameters is within the engineering methodologies of model identification, parameter estimation, control and optimization. In other words, we will develop a mathematical model which account for well dynamical characteristics, provide an adaptive and self learning mechanism for parameter estimation and well conditions identification, construct logic for the decision making structure to account for environmental, safety and overall operational parameters, provide an optimal regulation of the sucker-rod system with the account for the operational economic constraints, and provide an optimization of both long and short terms economic operational conditions which include supply-demand market and the resources dynamics.