The paper describes the application of modern digital technologies combined within the framework of complex approach during the bringing the oil wells equipped by electrical submersible and sucker rod pumps on to stable production. On the base on the expert rules, digital twins and methods of machine learning the uniform decision support system is developed, which allows to support the process of bringing the well on to stable production beginning from preparation the oil well to startup and finishing when it goes to the normal production. The set of intellectual algorithms is designed, which enable to provide remote diagnostics of complications in the pump operation, lift leaks, operability of measuring systems and to recommend the optimal operating regime, speed of acceleration, configuration of control station, tap transformer, and other activities. On the example of description of scheme of bringing the well, which is equipped by electrical submersible or sucker rod pump, on to stable production the sequence of execution of intellectual algorithms is presented within the framework of complex approach. The results of testing are given, in particular it is shown that the prediction of the well operating regime by digital twin allows to achieve the target parameters and avoid to making the additional bringing on to stable production after the main process is over or, otherwise, to diminish the time of bringing the well to the stable production. With examples of real wells a new method of detecting the direction of rotation of submersible motor shaft is illustrated. The estimation of technical and economic effects of implementation of the complex approach during bringing the well on to stable production is done. The total annual effect for the Bashneft-Dobycha wells achieves 35 million rubles due to diminishing of the number of pump stops and failures during the bringing on to stable production.
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