Intellectual analysis of geological and technological data during the management of an oil field's well-stock

The drilling and putting into operation of new wells on the operated well-stocks are labor-intensive and expensive business processes. Therefore the actual direction at the operation of such well-stocks is the development of new methods and the implementing them tools of effective well-stock management of already existing wells that allow lowering costs at the production of hydrocarbon material (HM). In this regard, today the optimum management decision-making is impossible any more without the use of perspective methods and algorithms of the intellectual analysis of geological and technological data. Results of the analysis of a current state in the field of intellectual methods and algorithms in relation to problems of well-stocks management at the production of HM on oil fields are given in the article. Results of the efficiency research of cluster analysis methods and the deep artificial neural networks (deep ANN or DANN) at the solution of one of the main tasks of well-stock management are received and analyzed; the task is a candidates-wells selection for carrying out geological and technical arrangements on the well-stock.