Rhegmatogenous retinal detachment (RD) is a sight threatening condition. In this type of RD a break in the retina allows retrohyaloid fluid to enter the subretinal space. The prognosis concerning the patients’ visual acuity is better if the RD has not progressed to the macula. The patient is given a posturing advice of bed rest and semi-supine positioning (with the RD as low as possible) to allow the utilisation of gravity and immobilisation in preventing progression of the RD. It is, however, unknown what external loads on the eye contribute the most to the progression of a RD. The goal of this exploratory study is to elucidate the role of eye movements caused by head movements and saccades on the progression of an RD. A finite element model is produced and evaluated in this study. The model is based on geometric and material properties reported in the literature. The model shows that a mild head movement and a severe eye movement produce similar traction loads on the retina. This implies that head movements—and not eye movements—are able to cause loads that can trigger and progress an RD. These preliminary results suggest that head movements have a larger effect on the progression of an RD than saccadic eye movements. This study is the first to use numerical analysis to investigate the development and progression of RD and shows promise for future work.

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Water-Alternating-Gas (WAG) injection could be an efficient way to improve recovery factors in fractured carbonate reservoirs. However, there are many geological uncertainties and engineering designs that influence the efficiency of the WAG process. In this study, we explore the challenges of combining polynomial chaos expansion (PCE)-based proxy modelling with multi-objective optimization using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to optimize the design of a WAG injection method under pseudo-miscible conditions for a fractured carbonate reservoir that is an analogue for the Arab D formation. A range of realistic geological uncertainties and engineering parameters are considered. Our results show that the order of the PCE-based proxy model needs to be carefully established for each geological scenario in a fractured reservoir. Likewise, the iterative enrichment of the proxy-model is non-monotonic, and each geological scenario requires its own evaluation of the proxy model during iterative enrichment. The convergence of the proxy is independent of the degree at which the reservoir is fractured but depends on the dimensions of the parameter space. The more engineering controls are considered, the more iterations are needed. Without a continuous and careful evaluation of the proxy model, the resulting simulation estimates may deviate significantly from full-physics simulations.@en

Water-Alternating-Gas injection could be an efficient way to improve recovery factors in fractured carbonate reservoirs. However, the complex geology of fractured carbonate reservoirs and the complexity of the WAG process itself create uncertainties when predicting the efficiency of WAG. It is hence challenging to identify engineering controls that allow us to optimize recovery during WAG while accounting for geological uncertainties. To overcome this challenge, we use Latin Hypercube and Box-Behnken experimental designs to set up multiple screened simulations of WAG injection in a fractured carbonate reservoir model that contains multiple geological uncertainties. From these simulations we construct surrogate response surfaces using polynomial chaos expansion. The response surface allow us to predict recovery factor, gas cumulative production, water cumulative production and NPV for different geological scenarios and engineering controls. Finally, we run the Non-dominated Sorting Genetic Algorithm-II on the response surface to obtain an optimal engineering design that not only accounts for geological uncertainties but also competing objectives. Our results show that only such a comprehensive simulation approach, which nevertheless can still be carried out on modern desktop PCs, is capably of analysing the complex interactions between geological and physical uncertainties and engineering controls to identify the most suitable WAG implementation.@en