Author:
Veliyev E.F., ,Aliyev A.A.,Mammadbayli T.E., ,
Abstract
The increase in number of the mature fields is accompanied by an increase in the water cut of the produced fluids. One of the most common causes of this phenomenon is the process of water coning, that is, the breakthrough of the bottom water to the wellbore, in which water flows form a figure similar to a cone. The paper proposes a ranking mechanism based on machine learning methods that allow to significantly reduce the resource intensity of existing prediction models. In order to preserve the simplicity of presentation, the proposed mechanism is considered on the example of one technology - DWL. Obtained results show about 10% smaller deviation values when using the least squares support vector machine in comparison with the ANN. Both developed models demonstrated acceptable results for practical application.
Publisher
Oil Gas Scientific Research Project Institute
Subject
Geology,Geophysics,Applied Mathematics,Chemistry (miscellaneous),Geotechnical Engineering and Engineering Geology,Fuel Technology,Chemical Engineering (miscellaneous),Energy Engineering and Power Technology
Cited by
35 articles.
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