Nowadays, the importance of energy management and optimization by means of smart devices has arisen as an important issue. On the other hand, the intelligent application of smart devices stands as a key element in establishing smart cities, which have been suggested as the solution to complicated future urbanization difficulties in coming years. Considering the scarcity of traditional fossil fuels in the near future, besides their ecological problems the new smart grids have demonstrated the potential to merge the non-renewable and renewable energy resources into each other leading to the reduction of environmental problems and optimizing operating costs. The current paper clarifies the importance of smart grids in launching smart cities by reviewing the advancement of micro/nano grids, applications of renewable energies, energy-storage technologies, smart water grids in smart cities. Additionally a review of the major European smart city projects has been carried out. These will offer a wider vision for researchers in the operation, monitoring, control and audit of smart-grid systems.

Summary Underbalanced operations (UBO) are carried out to bypass drilling challenges that could be difficult to resolve by use of conventional drilling techniques. Steady-state multiphase-flow models are used to construct underbalanced-drilling operational windows. These advanced software models are deterministically formulated. It is known that some of the model input parameters, such as the multiphase-flow parameters, friction factors, and reservoir productivity, are subject to uncertainties. Failures to capture these variabilities may introduce some error in the model prediction, resulting in poor well planning and implementation. The purpose of this work is to implement probabilistic modeling of underbalanced drilling by use of a simple steady-state two-phase model. Both predefined uncertain and fixed factors serve as inputs to a pre-existing deterministic model. By applying Monte Carlo simulations, the model predicts outputs that follow a statistical distribution. A sensitivity analysis is conducted to determine the input factor that is most responsible for the uncertainty in the predicted bottomhole pressure (BHP). The results demonstrate that uncertainty modeling can improve underbalanced-drilling design and operations. A more realistic operational window is obtained, ensuring that underbalanced condition is maintained throughout the target section. With a better understanding of uncertainties and the corresponding impacts, well planners can make better decisions regarding well design criteria and safe operational conditions, and avoid huge economic consequences.

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Summary The current practice on the Norwegian Continental Shelf (NCS) when designing solutions for permanent plug and abandonment (P&A) complies with NORSOK Standard D-010 (2013). This is a prescriptive approach to P&A, as opposed to a “fit-for-purpose” risk-based approach. A risk-based approach means that any given P&A solution is expressed in terms of the leakage risk, which can be formulated in terms of the following quantities: the probability that the (permanent) barrier system will fail in a given time period, and the corresponding consequence in terms of leakage to the environment. As part of building a leakage-risk model for permanently plugged-and-abandoned wells, a simple leakage-rate calculator has been developed for quick evaluation of the leakage potential from a given (permanent) well-barrier solution. This tool is developed to serve the second aspect of the risk-based approach: the consequence in terms of leakage rate to the environment. The leakage potential from the well can then be quantitatively assessed, taking into account different leakage pathways including leakage through bulk cement, through cement cracks, and through microannuli along cement interfaces. In the paper, we will provide models to estimate leakage rate for each leakage pathway and show how to integrate them in the leakage calculator to obtain a description of leakage flow from the reservoir through failed barriers to the environment. The information and input parameters needed to achieve this will be discussed, and uncertain parameters will be treated probabilistically, thus allowing for expressing uncertainty in the leakage-rate estimate. Results from the leakage calculator will be demonstrated on a synthetic case, showing variants of a permanently plugged-and-abandoned well.

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