Project reliability management of petroleum reservoirs
DOI:
https://doi.org/10.32347/2410-2547.2019.103.165-176Keywords:
petroleum reservoir, technical diagnostics, mathematical model, reliability managementAbstract
Raising of the problem. According to the regulatory documents in Ukraine [7,9], petroleum reservoirs (RVS) are designed on the basis of the limit state method. Using this method ensures the reliability of tanks in the conditions and modes of operation stipulated by regulatory documents [6,7]. However, issues related to ensuring the reliability of RVS designed for a service life exceeding the normative, as well as questions of the economic efficiency of the design decisions made, require further scientific study. This article provides a general methodology for assessing the reliability of the RVS over a given operating time. A model of optimal design of RVS is proposed according to the criterion of the minimum project cost while ensuring a given level of reliability over the required service life. This model is formulated in terms of a non-linear mathematical programming problem, and a special algorithm has been developed for its numerical implementation, based on the principles of constructing "greedy" algorithms. The economically rational design values of the thickness of the structural elements of the reservoir with a volume of 5000 m3 depending on the required level of reliability are given as a result of numerical experiments. Purpose of the article is to develop a method for rationally ensuring a given level of design reliability of the RVS over the required service life within the framework of the existing design standards and taking into account the available data of the technical diagnostics of the RVS. Conclusions. The proposed optimization model allows you to manage the design reliability of the RVS by the criterion of the minimum initial cost for a given period of operation. The parameters of this model are determined (and can be adjusted for a single tank or a fleet of tanks) based on the results of statistical processing of data from field surveys of similar objects, which improves the accuracy of the forecast in each individual case. As a result, the considered models and algorithms can serve as a rather effective mathematical tool in the study of the problems of reliability and durability of the RVS.
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