Using Big Data to manage safety-related risk in the upstream oil & gas industry: a research agenda

Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying ‘‘Big Data’’ analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance

JC and BK virus sequences are not detectable in leukaemic samples from children with common acute lymphoblastic leukaemia

Epidemiological evidence suggests that childhood leukaemia, and possibly common acute lymphoblastic leukaemia in particular, may have an infectious aetiology. Smith (1997 J Immunother20: 89–100) recently suggested that the critical infectious event occurs during pregnancy, and identified the polyoma virus JC as a candidate agent. In the present study we investigated whether genomes from the JC virus, and closely related BK virus, could be detected in leukaemic cells. No positive results were obtained suggesting that JC virus is unlikely to play a direct role in leukaemogenesis. © 1999 Cancer Research Campaig

Streamlining Digital Modeling and Building Information Modelling (BIM) Uses for the Oil and Gas Projects

The oil and gas industry is a technology-driven industry. Over the last two decades, it has heavily made use of digital modeling and associated technologies (DMAT) to enhance its commercial capability. Meanwhile, the Building Information Modelling (BIM) has grown at an exponential rate in the built environment sector. It is not only a digital representation of physical and functional characteristics of a facility, but it has also made an impact on the management processes of building project lifecycle. It is apparent that there are many similarities between BIM and DMAT usability in the aspect of physical modeling and functionality. The aim of this study is to streamline the usage of both DMAT and BIM whilst discovering valuable practices for performance improvement in the oil and gas projects. To achieve this, 28 BIM guidelines, 83 DMAT academic publications and 101 DMAT vendor case studies were selected for review. The findings uncover (a) 38 BIM uses; (b) 32 DMAT uses and; (c) 36 both DMAT and BIM uses. The synergy between DMAT and BIM uses would render insightful references into managing efficient oil and gas’s projects. It also helps project stakeholders to recognise future investment or potential development areas of BIM and DMAT uses in their projects

Signals in the Soil: An Introduction to Wireless Underground Communications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well