Housing provision has become a global issue as the need for affordable housing kept increasing in various communities especially in Akure, Nigeria. This has emerged due to various economic, socio-cultural and environmental factors which has increased pressure on conventional building materials thereby leading to the invention of alternative building materials. This paper looks at the barriers to the adoption of expanded polystyrene (EPS) for building construction in Akure, Nigeria. The methodology adopted elicited information through structured questionnaire which assessed the socio-economic characteristics of the respondents, their level of awareness of EPS and its application in building construction, the rate at which they specify EPS for designs and construction and the hindrances to its adoption for building construction. A total of 60 questionnaires were administered on the architects in practice and in the academia environment but 45 were retrieved. This was the bases to which the conclusion of this research was made. The outcome of the research shows that lack of awareness is a key hindrance to the adoption of EPS for construction as most architects in Akure do not know much about expanded polystyrene, thereby, cannot fully decipher its qualities and/or suitability for construction. As such, most questions pertaining the durability, cost implication or client's preference could not be answered by the architects since their knowledge on the subject matter is minimal. However, those who knows about EPS confirms its flexibility, quick construction time and its environmental friendliness but stated that EPS is not readily available like other conventional materials. As such, their specification always goes towards the available materials.

Agbami field is a deep-water field located offshore Nigeria. The oil production system is a complex intelligent production network that consists of 22 subsea production wells (19 wells are dual zone completion while 3 wells are single zone completion), 8 subsea manifolds, 8 infield subsea flowlines and 8 subsea flowlines/risers. A production network model for Agbami production network was built in GAP production modeling tool. The model consists of 41 inflow elements, 177 pipe elements, 68 chokes and 200 nodes with real-time pressure/temperature (P/T) measurements. Due to the large number of elements and P/T nodes in the model, it was very daunting to calibrate the model by unstructured manual tuning of the model calibration parameters. In fact, it takes several days to manually calibrate the whole production network. A structured computer assisted calibration workflow was developed to aid in fast calibration of the Agbami production model. The structured approach to the Agbami production network model calibration used in this work is to first break down the model into 8 independent riser subsystems. Each riser subsystem is then further broken down into segments. The segments are zones, wells, infield flowlines, and flowlines/risers; with each segment having several elements and P/T nodes. Each segment of the model is independently calibrated using the latest production test data corresponding to that segment. A computer guided wizard was developed to sequentially match the P/T at different nodes of the segment using the Secant root-finding algorithm1. The calibrated segments are then coupled together into riser subsystems and each riser subsystem is then calibrated to the latest riser tests by manual adjustment of few parameters. The riser subsystems are further calibrated to the current conditions. The use of the structured computer assisted workflow has resulted in the faster model calibration time of within a day.

Agbami is a prolific deep-water field which commenced production in 2008 and achieved peak production a year later, in 2009. Plateau production has been maintained in the field since 2009 through various efforts which include drilling of additional wells, pressure maintenance by gas and water injection, acid stimulation and choke/well-lineup optimizations. This paper focuses on the production optimization in the Agbami field obtained from choke and well-lineup optimizations. Agbami production system is an intelligent network that comprises of completions, wells, subsea flowlines and risers. Currently there are 24 wells, 8 subsea flowlines and 8 production risers in the production system. Multiple wells flow commingled in each riser, but each well can be lined-up to either of two risers in a riser loop. Parameters such as pressure, temperature etc. are monitored in real time at different nodes in the network. Production optimizations are achieved by manipulating the production control chokes at the completions, wells or risers; and/or by changing the line-up of the wells. Robust surveillance and monitoring are key to achieving successful production optimization. Periodic production tests are done at the completion, well and commingled riser level; while periodic pressure build-ups are done on the completion level. These surveillance data (plus real-time data) are used to update the completion, well and riser constraints and to calibrate the production network model. By continuously monitoring the operating constraints and comparing the constraints with the current production data, optimization opportunities are routinely identified. The identified opportunities are evaluated using the calibrated model and if viable, are proposed for execution. The key challenge is having good calibrated production network model to use for optimization. Choke and well lineup optimizations have proven to be an effective approach to obtaining increased production at no cost. These efforts have led to an average production gain of 12,000 BOPD per year in the past 8 years in Agbami field.