Expert diagnostic system of water pipes gusts in reservoir pressure maintenance processes

Katasev, Alexey Sergeevich; Kataseva, Dina Vladimirovna

doi:10.1109/icieam.2016.7911651

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…To solve the problem of selecting GTM in the oil fields, it is advisable to use intelligent decision-making support systems (DSS) [11][12][13] based on the fuzzy logic methods and fuzzy inference algorithms [14]. Such systems, due to the knowledge of experts accumulated in them, make it possible to recommend a decision-maker (DM), rational in the current conditions of GTM [15].…”

Section: Introductionmentioning

confidence: 99%

Neurofuzzy Model of Formation of Knowledge Bases for Selection of Geological and Technical Measures in Oil Fields

Panischev¹,

Ahmedshina²,

Kataseva³

et al. 2020

International Journal of Engineering Research and Technology

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This paper poses and solves the problem of developing the upto-date neuro-fuzzy model of formation of a knowledge base for an intelligent decision-making support system for selection of geological and technical measures in oil fields. The analysis of the traditional approach to the formation of fuzzy knowledge bases made it possible to reveal its shortcomings associated with the need to attract experts, structure and formalize the system of decision-making rules by them. This process is laborious and does not always provide an acceptable result. To eliminate the disadvantages of the traditional approach, we proposed an approach to the automatic formation of a knowledge base based on the construction of a neuro-fuzzy model of a collective of fuzzy neural networks. We formulated the requirements in view of the formed fuzzy rules. We developed a scheme for using the rules of the knowledge base to solve the problem of selecting geological and technical measures in oil fields. We tested the generated knowledge base on the example of solving the problem of selecting geological and technical measures for various wells of the Feofanovskoye Field. Application of the knowledge base made it possible to select a list of optimal measures for given wells. The experiment results are satisfactory and are confirmed by the positive expert assessments, selecting geological and technical measures at this field.

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Section: Introductionmentioning

confidence: 99%

Neurofuzzy Model of Formation of Knowledge Bases for Selection of Geological and Technical Measures in Oil Fields

Panischev¹,

Ahmedshina²,

Kataseva³

et al. 2020

International Journal of Engineering Research and Technology

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“…These difficulties make it difficult to solve efficiently the task of planning geological and technical measures by the experts of OGPD, which leads to the need to develop a knowledge representation model for them [12] and a decision support system [13][14][15][16], which helps to select geological and technical measures in the conditions of the above difficulties. These issues were studied in the works by R.Kh.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Multi-Criterial Choice of Geological and Technical Measures

Panischev¹,

Davydov²,

Anikin³

et al. 2020

International Journal of Engineering Research and Technology

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“…In addition, the use of such methods is complicated by a number of circumstances, one of which is the possible inaccuracy and vagueness of the raw information about the object being assessed. To analyze the objects and phenomena in the indicated conditions, nowadays, the methods of expert estimation [12] and the theory of fuzzy sets [13][14][15][16] are being actively used, which makes their application relevant for solving the problem of data security risk assessment [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Security Risk Assessment Method Using Fuzzy Logic

Ismagilov¹

2018

helix

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The article solves the problem of assessing security risks in information systems using the methods of the theory of fuzzy sets. The urgency of solving this problem is determined by the complexity of applying a number of existing methods, the possible inaccuracy of quantitative assessments of risk factors, and the possible inadequacy, uncertainty and quality of the initial information. The paper carries out formalization of the subject area "Information Security Risk" in the form of a conceptual model within the framework of the types of ER diagram, and determines the semantics of its concepts within the framework of the theory of categories and factors. The developed methods for assessing information security risks and evaluating the effectiveness of countermeasures are capable of solving problems in the indicated conditions. We have conducted the experiments on the application of the technique on a specific object of protection. The set of countermeasures recommended for implementation shows high efficiency in terms of absolute risk reduction. Recommendations on the choice of forms of membership functions of fuzzy scales used in risk assessment, as well as recommendations on the choice of fuzzy operations when performing calculations are given. The practical application of the developed methodology has a high practical value for building effective information protection systems in terms of expected damage.

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Expert diagnostic system of water pipes gusts in reservoir pressure maintenance processes

Cited by 6 publications

References 15 publications

Neurofuzzy Model of Formation of Knowledge Bases for Selection of Geological and Technical Measures in Oil Fields

Neurofuzzy Model of Formation of Knowledge Bases for Selection of Geological and Technical Measures in Oil Fields

Fuzzy Multi-Criterial Choice of Geological and Technical Measures

Security Risk Assessment Method Using Fuzzy Logic

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