PCA-ANFIS based prediction for water Injection effectiveness cycle in oil fields.

By proposing a numerical based method on PCA-ANFIS(Adaptive Neuro-Fuzzy Inference System), this paper is focusing on solving the problem of uncertain cycle of water injection in the oilfield. As the dimension of original data is reduced by PCA, ANFIS can be applied for training and testing the new data proposed by this paper. The correctness of PCA-ANFIS models are verified by the injection statistics data collected from 116 wells inside an oilfield, the average absolute error of testing is 1.80 months. With comparison by non-PCA based models which average error is 4.33 months largely ahead of PCA-ANFIS based models, it shows that the testing accuracy has been greatly enhanced by our approach. With the conclusion of the above testing, the PCA-ANFIS method is robust in predicting the effectiveness cycle of water injection which helps oilfield developers to design the water injection scheme.

The contemporary NHS in Scotland.

This session provided an overview of the health services in Scotland. The challenges faced by healthcare services was discussed and the efforts made to ensure healthcare provision is of good quality while remaining efficient and affordable for all.

Construction Innovation Futures - Industry and Environmental Opportunities.

During the next two decades global construction investment will top $100 trillion (US). New directions in construction innovation will be driven by industry to address challenges in skills, environmental regulations and maximise the benefits of low carbon building systems. Growth productivity catalysts such as offsite construction, higher BIM levels and multi-skill operatives will be instrumental contributors in achieving some of these aims. The increasing use of timber architecture across domestic, public and commercial buildings also opens new pathways. This event will discuss some of the key changes taking place in the UK and parallels with Hong Kong’s ambitions towards delivering a sustainable legacy in this sector.