Reliability Engineering Applied to Offshore Petroleum Production System

Summary This paper details the technical problems that the engineer will have to face and the qualifications that will be required of an entry-level service-company engineer in the year 2000. The environment in the year 2000 in which the E&P service-company engineer will have to function is addressed as background to these forecasts. Projections are provided for the likely economic, political, and business climates. By the year 2000, there will be far fewer international service companies, but they will be larger and more capable. The service-company engineers will have to understand better the needs and problems of the international oil companies because they will have to work in partnership with the international companies personnel in mostly hostile environments. The engineers will have to have broader skills and be more systems-oriented. They will have to be proficient in computer and software technology and effective team players with good communication and interpersonal skills. Introduction As a representative of the petroleum E&P service industry, I was asked to look at the role of engineering in the year 2000 by addressing five questions. What aspects of the petroleum (E&P) industry will your segment be primarily concerned with in the year 2000? What will be the significant technical problems addressed by the petroleum industry during the remainder of the century? What support will computers provide the engineer in the year 2000, and how should the engineer be prepared to use this technology effectively? How will the functions of engineers change during the remainder of this century? What qualifications will be required for an entry-level engineering position in the petroleum industry in the year 2000? Before I attempt to address these questions, I believe it is important to look at the likely economic, political, and business climates that will exist in the year 2000. (The Appendix provides a detailed look at these climates.)Worldwide demand for oil and gas will grow at a rate of 1 to 1½%/yr during the next 15 years.The current excess capacity in worldwide crude oil production will disappear by the mid-1990's.The increase in worldwide demand cannot be met by sufficient production increases outside the Middle East.U.S. crude oil needs will be increasingly met by imports. Imports will rise from approximately 25% of U.S. needs today to 43 to 52% by the year 2000.The U.S. must maintain a considerable E&P program to minimize its dependence on imports.In the year 2000, an investment of $22 will be required for 1 bbl [0.16 m3] of reserves added in North America, as opposed to $4.40 for the Middle East.The annual E&P investment in the U.S. during the 1990's will exceed the peak yearly investments of $42 billion to $43 billion in the early 1980's.In a rational market, the price of oil in the year 2000 will be in the range of $40 to $50/bbl [$252 to $314/m3] (1985 dollars).It is likely that Saudi Arabia will limit production, prolong the lives of its reservoirs, and promote a gradual increase in oil prices.The international oil companies should have the money and technology needed to find and to develop the needed reserves. Role of the International E&P Service Companies Exploration and development costs are currently very low as a result of the large overcapacity in the petroleum service industry. Drilling and development costs are very attractive today. Because of the great pressure on the going rate for their products and services, a crunching consolidation is taking place among the E&P service companies. At the end of this consolidation period, far fewer companies will exist. Those remaining will be financially stronger and should be able to meet the requirements of the domestic and international oil companies. At risk, however, is the experience level in the service industry. It is clear that the current downsizing and consolidation are removing many experienced people. It will be impossible to maintain the experience base developed in the service industry during the past 5 to 10 years. It is likely that companies will be forced to relearn a number of things. This learning process will not come cheaply to service companies or their customers.

In view of the current study on the reliability analysis for complex new equipment systems, the fault tree analysis method is used in reliability engineering (Fault Tree Analysis, FTA). However, qualitative and quantitative analysis for complex equipment systems reliability are difficult problems. In this paper, firstly, fault tree analysis method is introduced, secondly, through an instance of a certain type of equipment, mathematical description and analysis methods for qualitative and quantitative analysis of system reliability are carried out. Finally, the results from fault tree analysis is presented and discussed, which shows that FTA is a method can quickly and accurately analyze equipment systems reliability, and is a designer tool for evaluation and improvement of system reliability.

Accounting for the reliability analysis of a generalized phased-mission system (GPMS) with two-level modular imperfect coverage (MIPC), the dynamic behavior & the statistical dependencies across phases are the most important factors for reliability modeling & analysis. There exist several approaches, such as a family of decision diagrams called ternary decision diagrams (TDD) and a multi-state binary decision diagram (MBDD)-based approach, proposed for the GPMS reliability evaluation. Based on simple & efficient algorithm (SEA) and binary decision diagram for phased-mission systems (PMS-BDD), we present a separable solution called GPMS-BDD approach, adding some new rules of phase algebra and a new BDD operation to ordinary rules of phase algebra and BDD operations of PMS-BDD. The computational complexity decreases due to taking advantage of the nature of the SEA & PMS-BDD, the separation of mission/phase imperfect coverage from the solution combinatorics & uses of phase algebra dealing with the dependencies across the phases. In this paper, the GPMS-BDD is presented, and compared with existing methods for analyzing the reliability of GPMS with MIPC & combinatorial phase requirements (CPR). An example generalized phased-mission system is analyzed to illustrate the advantage of our approach. GPMS analysis approach is an important part of reliability engineering. The upward two-level modular imperfect coverage model (UIMIPCM) helps lower complexity of reliability analysis. The GPMS-BDD approach is efficient and integrated, helping a reliability engineer use existing software packages for fault-tolerant GPMS

In Reliability analysis, there are four main steps to perform. These steps are selection of the mathematical model that represents system states, selection of the mathematical representation that represents the operation of the system, quantitative and qualitative reliability analysis and to conclude the obtained results. In Faculty of Management Science and Informatics, there is a course called Reliability engineering in which reliability analysis is taught. During the course, the students are taught about the basic of the reliability engineering and reliability analysis. During this process, there are various topics that can be more challenging for a student, such as computation of the Importance measures. Thanks to this, we developed a software tool for such computation and this tool is also usable for the research activities in our faculty. By implementing this software tool in the teaching process in subject of the reliability engineering the students can better understand, how these measures can be computed and how can they be used for localizing weak spots in the system. Results from this tool can be then used in term projects and assignments by students of in research activities that uses these measures in reliability analysis.

One of the established trends of research areas and practices in software engineering that dealt with the measurement and enhancement of reliability is software reliability engineering. Stochastic software reliability models find typical usage for analysis. These are the models that perform modeling on failure process of the software and exploit other software metrics or failure data as cornerstone for parameter estimation. The ability of the models for estimating and predicting the current reliability and future failure behavior, respectively, is high. Due to any failures and faults in the system, a product becomes unreliable. The lack of understanding of nature of the software makes the measurement of software reliability as a challenging task. It is not possible to determine a best way to measure the reliability and other aspects of software. This paper proposes an efficient software reliability growth model (SRGM) in which logistic exponential TEF is exploited. This model offers increased failure rate recognition and suitable ways to resolve faults and so on. Our work estimates the SRGM parameters using optimization algorithm. Such estimation can aid in developing precise software reliability model. In order to accomplish the optimization, we use artificial bee colony (ABC) algorithm. As the parameters optimization considerably improves the quality of parameters to be used for reliability growth model, reliability growth can also be improved considerably.

At the LKAB Kiruna Iron Ore Mine in Sweden, reliability and maintainability analysis techniques have been gradually accepted as standard tools for planning and operation of automatic and complex mining systems since the mid-1980s. The reliability analysis and modeling of the production system at the Kiruna mine are discussed. Since a large number of random variables (phenomena) are involved in the analysis, a simulation program SIMURES was developed to model the reliability characteristics of the production process and analyze the criticality of the various units and operations. This program has helped in evaluating the gain in production volume with improvement in reliability of the various units, and thus forms a basis for future investment for increasing the production system efficiency and capability. >

This article deals with an artificial intelligence (AI) framework to support Internet-of-everything (IoE) applications over sixth-generation wireless (6G) networks. An integrated IoE-Edge Intelligence ecosystem is designed to effectively face the problems of Virtual Machines (VMs) placement based on their popularity, computation offloading optimization, and system reliability improvement predicting compute nodes faults. The main objective of the article is to increase performance in terms of minimization of worst end-to-end (e2e) delay, percentage of requests in outage, and the enhancement of reliability. The article focuses on the following main issues: (i) proposal of a channel-aware federated learning (FL) approach to forecast the popularity of the VMs required by IoE devices; (ii) use of an AI-based channel conditions forecasting module at the benefits of the FL process; (iii) development of a suitable VMs placement on the basis of their popularity and of an efficient tasks allocation technique based on a modified version of the auction theory (AT) and a proper matching game; (iv) enhancement of the system reliability by an echo-state-network (ESN), located on each computation node and running in the background to predict failures and anticipate tasks migration. Numerical results validate the effectiveness of the proposed strategy for IoE applications over 6G networks.

In recent years, the proliferation of large numbers of microcomputers has greatly changed the requirements for user support. Companies which have historically had strong centralized mainframe computer staffs are now required to support users in ways which were not necessary in the past. In mainframe systems, user support is usually limited to help in running programs and occasional hardware repairs. As microcomputers have spread throughout the workplace, support must now be expanded to include software and hardware distribution and installation, as well as training for a greatly expanded user community. The petroleum industry is a unique case in the user support problem, particularly for exploration and production companies. The normal support problems are complicated by the need to put computing assets in remote locations, often with hostile environments. The user community will often span a wide range of educational experience and computer experience. This paper discusses several concepts involved in developing a microcomputer user support strategy in the petroleum industry.

Most reliability models in the classical reliability theory use probability theory to quantify information under uncertainty and these models have a high demand of available data. While in practical applications, data related to system sand components are usually sparse or incomplete, moreover, some quantification of uncertainty should be based on subjective information and moreover subjective information may often be expressed in natural language. In these cases, classical reliability theory can not provide an effective way for the reliability analysis of systems. As a generalization of probability theory, imprecise probability theory may provide a tool which is called the natural extension to solve such problems. Research on the application of imprecise probability in reliability engineering has made a great progress. Unfortunately, this is all about theory and there are few applications and cases in practice. Therefore, this paper tried to overcome the flaws and shortcomings of classical reliability theory, and apply some theories of imprecise probability in practical engineering, and conduct reliability analysis on automotive semi-axle with establishing imprecise probability-based reliability model of automotive semi-axle. Natural extension is undoubtedly a powerful tool to compute reliability measures, however, when number of variables is large; the computation of natural extension is very difficult. Effective methods to simplify and build reliability models deserve more debate in the future.

The study of the First Passage Time (FPT) problem (also known as first passage problem, FPP) started more than a century ago, but its diverse applications in science and engineering mostly emerged in the last two to three decades. Assuming that X(t) is a one-dimensional stochastic process, the First Passage Time is defined as the time (T) when X(t) first crosses a threshold. Engineering reliability is obviously a suitable application domain, and indeed applications such as optimal dam design in hydrology and analysis of structural failure in civil and mechanical engineering are typical examples. Although we envision that the FPT problem has great potential in network and software reliability, it should be more useful for network security and survivability because the approaches developed for the FPT problem are mostly analytical. The assumption for this inference is that in reliability analysis, experimental or historical data are often more readily available, which makes statistical approaches such as survival analysis more convenient and likely more realistic. In contrast, data is generally more difficult to obtain in security and survivability analyses, and analytical approaches can be leveraged to play more important roles. Furthermore, security and survivability often have to deal with malicious actions that may be driven by sophisticated cognition and behavioral processes, which are highly variable over time and very difficult to detect with short term data. If the behavior of an intruder can be characterized with some stochastic process such as Brownian motion, then the FPT approach may be applied to find the closed-form solution of the probability density function (PDF) of the first passage time, which can be the time when the system breaks down or when the hacker is successful in compromising a network. In addition, the solutions to FPT depend on boundary and initial conditions of the corresponding partial differential equations, and they also describe the evolution of PDF over time. This may suggest that it is possible to model the behavior changes of an intruder over time and circumstances. Another advantage of FPT analysis is that it may help solve some non-Markov stochastic process problems in reliability analysis and survival analysis. In this article, we first briefly introduce the FPT problem with Brownian motion as an example, and then suggest its potential applications in software reliability and network security.

Comments on ‘Reliability and performance analysis for fault-tolerant programs consisting of versions with different characteristics’ by Gregory Levitin [Reliability Engineering and System Safety 86 (2004) 75–81

Objectives: Distribution automation is a pre requisite for an intelligent power network. In this paper we investigate the effect of control devices in distribution automation system. Methods/Analysis: According to the importance of improving reliability of electric distribution system, reliability improving approaches by developing control devices in the network is investigated. Also, the effect of developing control devices located in electric distribution network on reliability of system in the form of numerical studies on a sample network in two equipped and non-equipped steps by load cut keys is presented. Findings: Comparing the results obtained from two investigated steps. Shows that equipping the investigated network with control devices has no effect on SAIFI index, but developing load cut keys leads to the improvement of SAIDI and CAIDI indices. Developing control devices such as load cut keys allows the isolation of error place and detection of tripped loads. Thus detectable subscribers of damaged feeder experience shorter turn out time, which finally leads to the improvement of reliability in distribution system. Thus, according to the reliability measurements, control devices development leads to the improvement of reliability in electric distribution system. Conclusion/Application: According to the obtained results in measurements of reliability, it is observed that developing control devices leads to improving reliability and decreasing outages in electric distribution system. Keywords: Control Devices, Decreasing Outages Time, Electric Distribution Automation, Intelligent, Reliability

Security and Privacy challenges are the most obstacles for the advancement of cloud computing and the erosion of trust boundaries already happening in organizations is amplified and accelerated by this emerging technology. Policy Management Frameworks are the most proper solutions to create dedicated security levels based on the sensitivity of resources and according to the mapping process between requirements cloud customers and capabilities of service providers. The most concerning issue in these frameworks is the rate of perfect matches between capabilities and requirements. In this paper, a reliable ring analysis engine has been introduced to efficiently map the security requirements of cloud customers to the capabilities of service provider and to enhance the rate of perfect matches between them for establishment of different security levels in clouds. In the suggested model a structural index has been introduced to receive the requirement and efficiently map them to the most proper security mechanism of the service provider. Our results show that this index-based engine enhances the rate of perfect matches considerably and decreases the detected conflicts in syntactic and semantic analysis.

Human reliability in railway engineering: Literature review and bibliometric analysis of the last two decades

This paper describes the main challenges faced by asset intensive industries on achieving the operational goals related to reliability and maintainability, as well as how to overcome them using a simple yet powerful systematic approach within the framework of the right asset management strategy. In addition, this paper describes several examples of typical outcomes expected when Reliability Programs are properly defined and implemented as part of a customized Asset Management strategy.