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.

PCA-FNN based performance prediction for water injection in oilfields.

In order to solve the problem of uncertain cycle of water injection in the oilfield, this paper proposed a numerical method based on PCA-FNN, so that it can forecast the effective cycle of water injection. PCA is used to reduce the dimension of original data, while FNN is applied to train and test the new data. The correctness of PCA-FNN model is verified by the real injection statistics data from 116 wells of an oilfield, the result shows that the average absolute error and relative error of the test are 1.97 months and 10.75% respectively. The testing accuracy has been greatly improved by PCA-FNN model compare with the FNN which has not been processed by PCA and multiple liner regression method. Therefore, PCA-FNN method is reliable to forecast the effectiveness cycle of water injection and it can be used as an decision-making reference method for the engineers.

English: its role as the language of comity in an employment programme for Canadian immigrants.

This study explores the experiences of a culturally and linguistically diverse group of immigrant adult students as they attended a 12-week employment preparation course for newcomers to Canada. The main aim of the course was to equip the immigrants with knowledge and skills, including English for employment purposes, which are necessary to be competitive in the labour market. Using ethnographic methods, mainly participant observation with audio recording, to collect data, this paper analyses the communicative strategies that this group of multilingual speakers and their Canadian teachers deployed to discursively construct a ‘heterotopia’ defined here as ‘intensely affective spaces that redefine the experiential feeling of being and becoming’. Analysis of transcribed audio recordings reveals that despite differences in communication conventions and sociocultural backgrounds, the research participants from Congo, Haiti, India, Bangladesh, Jordan and the Philippines managed to establish a socially cohesive team that emphasises shared relational identity and in-group membership. The findings show how they creatively mobilised previously acquired pragmatic strategies and resources from their L1 to suit the demands of the ongoing interaction in English. It is suggested that language teaching in the context of preparing immigrants for labour market integration entails a pedagogical approach that foregrounds the affordances of English not only as the language of employment but perhaps more importantly as the ‘language of comity’. It is therefore suggested that the teaching of the host country’s language should focus less on grammatical correctness and focus more on providing the adult learners with opportunities to activate existing pragmatic resources and strategies which have to do with establishing rapport and friendly relations.