Optimization and operational maximization of oil wells/fields production

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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.