Intertek (Sweden)

SummaryStreptococcus equisubspeciesequi(S. equi) is the causative organism of the upper respiratory disease of equids, strangles, characterised by pyrexia, lymphadenopathy and mucopurulent nasal discharge. Strangles was first reported over 750 years ago and continues to be of significance in equine populations across the globe. This review discusses howS. equihas adapted, the clinical manifestation of strangles, and how clinicians and caregivers can tackle the disease in the future.S. equievolved from the commensal, and occasionally opportunistic pathogen,Streptococcus equisubspecieszooepidemicusrefining its capabilities as it became host restricted. The success ofS. equican be attributed to its ability to cause both acute and persistent infection, the latter occurring in about 10% of those infected. In this carrier state,S. equipersists in the guttural pouch without causing clinical signs, intermittently shedding into the environment, and encountering naïve animals. Insight into theS. equigenome and lifestyle has led to advances in diagnostic assays and the development of a safe and efficacious recombinant‐fusion vaccine, giving clinicians and caregivers the tools to better combat this infection. Alongside rigorous biosecurity protocols and pragmatic control measures such as screening new arrivals for exposure and carrier status, these new technologies demonstrate that strangles can be an increasingly preventable infection.

Abstract Microbiologically Influenced Corrosion (MIC) is a well-documented phenomenon that involves microorganisms and affects multiple industries with untold economic impact. The most well- known microorganisms within the oilfield, by far, are Sulphate-Reducing Bacteria (SRB). It is thought that through SRB respiration, corrosion of metals can occur. An exact figure for MIC responsibility in overall corrosion is currently unknown. However estimates of between 10-50% are not uncommon, when coupled with estimated costs of metal corrosion in developed countries to be between 2-3% of Gross Domestic Product (GDP), suddenly the cost implications of MIC gain significance. The technical and economic implications have gained recognition within the oil and gas industry within the last thirty to forty years and monitoring techniques to detect microorganisms and corrosion have progressed and developed through increased interest in microorganisms commonly found within the oilfield. As with human nature, the ability to predict the future, rather than deal with the consequence is a preferred approach, which is one of the main driver's to pro-active monitoring techniques for detection of microorganisms to help determine the risk of MIC to occur, rather than a reliance on rate of corrosion alone. This approach has led to increased research in to the subject of oilfield microbiology and development of modern molecular techniques, often borrowed from other industries such as medical microbiology, that have come to the fore recently. However a significant focus on cost saving practices within the oil and gas industry has a significant and direct impact on the type and frequency of monitoring applied (if any). The objective of this review is to discuss and evaluate the available techniques and review the most common problems associated with microorganisms within the oil and gas industry. To determine effective monitoring practices in a practicable and economically viable manner to ensure monitoring can be carried out effectively, understood and evaluated while implementing control and mitigation strategies with confidence.

Abstract This paper studies the effect of viscosity and fines particle loading on the pressure drop across a 4mm orifice in a specific geometry built to mimic a representative well completion. In previous studies, most of these orifices have been validated experimentally for viscosities up to 200cp only for such completions. The current study focused on a wider viscosity variation (1cp – 3000cp) with lower flow rates (0.1m3/day - 30m3/day). The pressure drop was measured across the orifice and through the entire pipe assembly. The measured data was non-dimensionalized using the Euler number and plotted against the Reynolds number for all the rates and viscosities. The orifice pressure drop data overall agreed well with the limited data that was available from the literature. It was also compared and validated against commercially available CFD software. The effect of sand particle loading was also studied and its effect on apparent viscosity increase was measured in the laboratory. The pressure drop-flow rate relationship disclosed in this paper can be used to design effective completions for intermediate/high viscosity oil applications and will be able to predict the completions pressure drop more accurately.

As the use of quantitative techniques has become more widespread in the investment industry, the issue of how to handle portfolio estimation and model risk has grown in importance. Robust optimization is a technique for incorporating estimation errors directly into the portfolio optimization process, and is typically applied in conjunction with robust statistical estimation methods. The robust optimization approach uses the distribution from the estimation process to find a portfolio allocation in one single optimization, while keeping the computational costs low. Robust portfolios tend to be less sensitive to estimation errors, offer some improved portfolio performance, and often have lower turnover ratios. Keywords: portfolio optimization; robust modeling; investment management; uncertainty sets; Bayesian methods; robust portfolio management

Trading costs can be classified as fixed versus variable transaction costs and explicit versus implicit transaction costs. Portfolio managers and traders need to be able of effectively model the impact of trading costs of their portfolios and trades. In doing so, they seek to minimize the total transaction costs. There are several approaches for the modeling of transaction costs in portfolio optimization models and optimal execution applications.