Regulations governing offshore discharge are increasingly stringent and diverse, varying between country, legislative framework and type of discharge. One major waste stream is the slop generated during the drilling operation, which is collected in the rig drain systems or in surface pits. The slops come from multiple sources, vary widely in composition and are therefore challenging to treat to meet the discharge regulations of a global market. Slops are formed when drilling or displacement fluids, wash water from routine cleaning operations or rain water runoff become contaminated with drilling fluid components. The slops are captured, either in surface pits or through the rig drain system and collected in storage tanks. Chemical and physical treatments can be used to treat this stream to minimize the volume and cost of disposal, but due to the complex and varied nature of the slop stream, treatment methods must be tailored. Optimal solutions should treat the stream to recover and recycle any drilling fluid. Water should be separated and treated to meet the discharge criteria. In this way the total volume of waste requiring disposal can be significantly reduced. This paper will present a review of the discharge criteria relating to drilling slop waste, highlighting the variations seen between countries. The paper will discuss how this variability, together with the slop chemical characteristics, impacts optimum treatment methods. Examples will be provided of successful treatments of a variety of slop wastes, where both chemical and physical treatment was successfully applied to meet a range of discharge criteria from oil content to complex organic analysis. Understanding slop treatment and the multitude of discharge regulations that can be applied will permit the optimal solution for slop treatment to be selected to minimize waste and maximize reuse whilst ensuring compliance to the required environmental regulations.
In this paper, stochastic optimisation and risk estimation techniques are applied to the problem of hydroelectric generator design. Optimisation results from deterministic simulations can involve considerable risks due to unavoidable variations in system properties as well as environmental conditions. Therefore, stochastic simulation is used to include the effects of parameter scatter and noise effects in the computer models. This allows the evaluation of the scatter in performance and thus an assessment of reliability and quality of the simulated system.
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