Abstract

At present in China, the prevailing optimization method for an individual rod pumped well pursues the maximum system efficiency under the condition of given production, which is ineffective for some high water cut oil wells and contributes a little to the oil production of a block. As a result, the maximum overall profit cannot be achieved. With the continuance of low oil prices and the increase of artificial lift cost, the individual well optimization method can no longer meet the requirements for field energy conservation and cost reduction. The energy consumption and contribution to oil production of every well are analyzed. Based on an analysis of the inter-relations between individual well production, energy consumption and efficiency, the energy consumption of individual wells and their contributions to oil production by utilizing relevant analytical approach, an objective function with the minimum overall block energy consumption is established in this paper to realize the overall profit maximization of block by allocating individual well fluid production, optimizing production parameters and using non-decreasing oil production as constraint condition. In view of the established optimization model characterized by complicated influence factors, multiple optimization parameters, enormous calculations and several constraint conditions, a penalty function algorithm is applied to optimization to convert a constrained optimization problem into the solution of an unconstrained optimization problem. In this way, fast solution of the model is realized. 154 wells of one oil production plant in Daqing Oilfield were subjected to overall block optimization. Since site execution of an optimization program, there are 63 wells with an increased fluid production, there are 91 wells with a decreased fluid production, the total oil production has basically remained unchanged, the total fluid production has decreased by 10.2%, the total energy consumption has decreased by 16.3%, and the average system efficiency has been improved by 5.1%. It is shown by field application that this technology can further decrease the overall cost and increase the overall profit of a block by allocating per well liquid production and optimizing production parameters comparing with the previous individual well optimization. It may be beneficial to any teams who are looking to lift more oil with less energy consumption.

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