Open Access Open Access  Restricted Access Subscription or Fee Access

Improvement of the Methodology for Determining Reliability Indicators of Oil and Gas Equipment

Vladimir Bukhtoyarov(1*), Vadim Tynchenko(2), Eduard Petrovskiy(3), Valeriya Tynchenko(4), Vadim Zhukov(5)

(1) Institute of Oil and Natural Gas Engineering, Siberian Federal University, Russian Federation
(2) Institute of Oil and Natural Gas Engineering, Siberian Federal University, Russian Federation
(3) Institute of Oil and Natural Gas Engineering, Siberian Federal University, Russian Federation
(4) Institute of Space and Information Technologies, Siberian Federal University, Russian Federation
(5) Institute of Oil and Natural Gas Engineering, Siberian Federal University, Russian Federation
(*) Corresponding author



This article is aimed at defining and studying the ways to create new methods for determining reliability indicators (RIs) of oil and gas equipment and improving the existing ones. The currently used method for determining RIs in oil and gas industries is analysed. The most appropriate technique for monitoring the reliability of process facilities, adapting to the type of equipment considered, is discussed in detail. Various methods and options for improving such a technique are developed. The application of the obtained methodology results in information on the technical condition of the monitored facility and assistance in determining the timing and degree of technical intervention, which allows enhancing the operational efficiency and, consequently, increasing the service life of oil and gas equipment. The proposed method was approved in practice using a centrifugal pumping unit, resulting in the most effective proposals for improvement, and testing the feasibility of its implementation at oil and gas enterprises.
Copyright © 2018 Praise Worthy Prize - All rights reserved.


Oil And Gas Sector; Process Equipment; Reliability; Reliability Calculation; Reliability Indicators

Full Text:



J.D. Campbell, A.K. Jardine, Maintenance Excellence: Optimizing Equipment Life-Cycle Decisions (CRC Press, 2001).

A.C. Márquez, The Maintenance Management Framework: Models and Methods for Complex Systems Maintenance (Springer Science & Business Media, 2007).

E.V. Oleinikova, Innovative Approach to the Development of Repair Activities of Enterprises (Saratov State Technical University Press, 2004).

J. Santos, R.A. Wysk, J.M. Torres, Improving Production with Lean Thinking (John Wiley & Sons, 2014).

T. Tinga, Principles of Loads and Failure Mechanisms. Applications in Maintenance, Reliability and Design (Springer, 2013).

RD 50-690-89. Guidance document on standardization. Methodical instructions. Reliability in technology. Methods for estimating reliability indicators from experimental data.

B.V. Gnedenko, Y.K. Belyayev, A.D. Solovyev, Mathematical Methods of Reliability Theory (Academic Press, 2014).

P.D. O’Connor, A. Kleyner, Practical Reliability Engineering (John Wiley & Sons, 2012).

A.M. Smith, Reliability-Centered Maintenance (McGraw-Hill, 1993).

F. Haghighi, S.J. Bae, Reliability Estimation from Linear Degradation and Failure Time Data with Competing Risks under a Step-Stress Accelerated Degradation Test, IEEE Transactions on Reliability, Vol. 64 (Issue 3): 960-971, 2015.

J.A. Nachlas, Reliability Engineering: Probabilistic Models and Maintenance Methods (CRC Press, 2017).

W.Q. Meeker, L.A. Escobar, Statistical Methods for Reliability Data (John Wiley & Sons, 2014).

Q. Yang, N. Zhang, Y. Hong, Reliability Analysis of Repairable Systems with Dependent Component Failures under Partially Perfect Repair, IEEE Transactions on Reliability, Vol. 62 (Issue 2): 490-498, 2013.

K.C. Kapur, M. Pecht, Reliability Engineering (John Wiley & Sons, 2014).

S.S. Rao, Reliability Engineering (Prentice Hall Press, 2014).

E. Calixto, Gas and Oil Reliability Engineering: Modeling and Analysis (Gulf Professional Publishing, 2016).

N. Paltrinieri, F. Khan, Dynamic Risk Analysis in the Chemical and Petroleum Industry: Evolution and Interaction with Parallel Disciplines in the Perspective of Industrial Application (Butterworth-Heinemann, 2016, pp. 181-192).

J.D. Campbell, A.K. Jardine, J. McGlynn, Asset Management Excellence: Optimizing Equipment Life-Cycle Decisions (CRC Press, 2016).

M.Yu. Zemenkova, System monitoring of reliability indicators of pipeline transport facilities, Ph.D. dissertation, Tyumen State Oil and Gas University, Tyumen, Russia, 2007.

F. Borrelli, A. Bemporad, M. Morari, Predictive Control for Linear and Hybrid Systems (Cambridge University Press, 2017).

E.F. Camacho, C.B. Alba, Model Predictive Control (Springer Science & Business Media, 2013).

V.V. Rybalko, Mathematical Models of Control of Reliability of Energy Objects (Saint Petersburg State Technological University of Plant Polymers, 2010).

G.E. Box, G.M. Jenkins, G.C. Reinsel, G.M. Ljung, Time Series Analysis: Forecasting and Control (John Wiley & Sons, 2015).

C. Chatfield, The Analysis of Time Series: an Introduction (CRC Press, 2016).

M. Paulescu, E. Paulescu, P. Gravila, V. Badescu, Weather Modeling and Forecasting of PV Systems Operation (Springer, 2013).

A. Asuncion, D. Newman, UCI Machine Learning Repository (University of California, 2007).


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2021 Praise Worthy Prize