This paper presents a statistical analysis of reported accidents related to the Skikda's Oil and Gas Refinery that led to a major explosion and loss of life. A historical review of fire, explosion and toxic release incidents that occurred during the period between 2002 and 2013 is presented. A brief description of each accident/incident is provided with the fatalities and personal injuries that resulted being described. These case studies have been analyzed with a view to understand the common causes including errors, which have led to catastrophic events. Accident frequency analysis has been applied to various types of primary accidental events such as fire, explosion and toxic gas releases to assess the potential damage of such events and the likelihood of such damage occurring. The basic principles of such analysis is to utilize the available information and use the most detailed elements to illustrate what the industry should learn from these accidents so that it can learn from them and hopefully prevent future major accidents.

In this paper, we will combine a statistical analysis of accident cases concerning the Algerian Oil and Gas Industry occurred during the period of 2003 to 2013 to a dynamic analysis based on the use of a numerical dispersion model. This combination lies in the use of the information obtained from the statistical analysis as input data in the Numerical Dispersion Model (NDM). This study may be useful to illustrate what the industry should learn from these accidents and in such a way be more alert to prevent future major accidents

Port approach for merchant ships (regarding docking) is a special event related to the safety of ships and port facilities. This maneuvre is for emergency situations, and the consequences can be very damaging because there is a high risk of occurrence and severity can be high. In Algeria, 90% of foreign trade depends on shipping, and commercial vessels must dock in the port safely. This study aims to contribute to the management of risks associated with port operations by designing a matrix for specific assessment of this type of risk based on analysis of several incidents and accidents regarding maneuvring ships in Algerian ports. The design of the evaluation matrix of risks associated with port operations in Algeria is done in the context of the application of the Formal Safety Assessment methodology for improved performance of this method regarding precision and accuracy of results.

Safety Instrumented Systems (SIS) constitute an indispensable element in the process of risk reduction for almost all of nowadays' industrial facilities. The main purpose of this paper is to develop a set of generalized and simplified analytical expressions for two commonly employed metrics to assess the performance of SIS in terms of safety integrity, namely: the Average Probability of Failure on Demand (PFD_avg) and the Probability of Dangerous Failure per Hour (PFH). In addition to the capability to treat any K-out-of-N architecture, the proposed formulas can smoothly take into account the contributions of Partial Stroke Testing (PST) and Common Cause Failures (CCF). The validity of the suggested analytical expressions is ensured through various comparisons that are carried out at different stages of their construction.

This article aims to propose a model for analyzing work situations. In this context, we focus our interest on the simplification of procedures for working where the proposed model is used to analyze human behavior in response to non-compliance of work procedures. From this analysis, ways to improve work processes will be identified.

Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.