Admicellar Polymerization to Compatibilize Calcium Carbonate With Oil-Based Drilling Mud

Weighting agents like calcium carbonate (CC) are added to drilling mud to improve mud properties and performance during oil and gas drilling operations. Oil-based mud (OBM), a more preferred drilling mud, being hydrophobic is particularly non-compatible with hydrophilic CC. This work explored an economically viable admicellar polymerization technique to surface-modify the high energy hydrophilic CC surface to a low energy hydrophobic surface by polymerizing organic styrene monomer within an admicelle of nonionic surfactant Triton X-100 adsorbed on the CC surface. BET N2 particle size analysis, Soxhlet extraction of the coated polymer, Fourier transform infrared-attenuated total reflectance (FTIR-ATR) spectra analysis, and thermogravimetric analysis (TGA) of the treated CC and polymer extract confirmed the production of a successful thin film polystyrene-coated CC. The coarse CC size grade had the most polymer. Consequently, OBM formulated with the treated CC is expected to; be more homogeneous, achieve higher wellbore pressure, remove drill cuttings better, have a more stable thin film low-permeability filter cake, and exhibit an enhanced overall performance. Pilot mud testing of a surface-modified CC formulated OBM is under way

Damage detection in composites using e-glass fibre and small diameter optical fibre

The primary aim of this study was to demonstrate that E-glass and custom-made small diameter optical fibres, with an outer diameter of 12 micrometres, can be used to monitor the following: (i) In-situ monitoring of the partial dissolution of the cladding on the small-diameter optical fibres in hydrofluoric acid. This was necessary for the small-diameter optical fibres as the thickness of the original cladding was not appropriate to enable evanescent wave spectroscopy. (ii) In-situ monitoring of the impregnation process. Since the cladding was etched to access the evanescent field in the optical fibres, it was demonstrated that the impregnation of the fibres by the resin could be monitored. (iii) In-situ cure monitoring. After impregnation, the cross-linking reactions taking place at the surface of the glass fibres were monitored using near-infrared spectroscopy. The feasibility of using the glass fibres for monitoring temperature was also demonstrated. (iv) Finally, after the composite was cured, it was tensile tested to failure whilst monitoring the transmitted light intensity through the optical fibres. The un-impregnated bundles were also tensile tested to failure. The failure of the individual filament in the bundle (un-impregnated) and composites were monitored by tracking the intensity of the transmitted light through each filament. Conventional acoustic emission was used to cross-correlate the fracture of the individual filaments. Conventional E-glass fibres can be used as light guides if the conditions for total internal reflection is enabled. In this current study, the matrix served as the cladding. This study has developed a range of techniques that can potentially facilitate the full life cycle monitoring of glass fibre composites. In other words, the same test specimen can be used to monitoring the surface treatment, temperature during drying or heat treatment, cross-linking kinetics and damage during mechanical loading. The self-sensing technique developed in this study can also be used as a tool to study the degradation of properties when the fibres are recycled and reused

Evaluation of net radiation using the autoregressive models with higher orders over Nigeria

In this study, monthly surface net radiation data were collected from the Nigeria Meteorological Agency, Lagos covering a duration of 31 years (1983- 2013) spatially distributed across the four climatic regions: Semi-Arid (SAR), Sub-humid Dry (SHD), Sub-humid Humid (SHH) and Humid (HUM) regions. The net radiation was evaluated using different forms of Auto-Regressive models – AR {p} where p is the number of orders of the auto-regressive. The analysis showed that AR {4} performed best in all the regions and stations investigated. Regionally, AR {4} has maximum values of coefficient of determination of 0.8127 in HUM, 0.7876 in SHH, 0.5765 in SHD and 0.7973 in SAR regions. It can be concluded that the higher the order of auto-regressive models, the more accurate estimation of net radiation it will give irrespective of location in Nigeria

Growth and Migration of Benthic Habitats: A Spatial Microsimulation Approach

Spatiotemporal visualization of the impact of geomorphological changes in coastlines benthic habitats can generate insight needful in understanding the spatial ecology of seafloors and in anticipating the location, growth and migration of marine sanctuary and marine protected areas (MPAs). Such understanding has implication for effective development and conservation of these MPAs. To date, there are limited studies that have applied complex adaptive systems (CAS) to investigate the impact of geomorphological changes on the location, growth and migration of benthic habitats. Also, there is a gap in our knowledge of the marine geographical information system (marine GIS). To fill these gaps in the literature, we propose the use of the CAS theory as a lens to study the growth and migration of underwater (benthic) habitats in the Hawaii coastline using bathymetric SoNAR Multibeam data. We investigate the research question that concerns whether spatial approach helps in understanding the impact of projected geomorphological changes on patterns of growth and migration of benthic habitats of Hawaii coastlines. We develop a spatiotemporal IT antifact that engages a prediction machine to project individual data units (micro-data) to future states based on geomorphological changes using dynamic spatial microsimulation based method. The results of our study provide evidence of the contributions of spatial approach to understanding benthic habitat. The results also present research and practical implications for marine exploration and resource managers, and governments

Global governance of finance and African relations with the world

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Effect of surface treatment and recycling on the mechanical properties of e-glass

The primary focus of this study was to investigate the effect of removing the binder, by specified method, on the tensile strength of E-glass fibre bundle and composites. The methods investigated for removing the binder from E-glass fibres were: (i) fibre spreading; (ii) acetone-based treatment; and (iii) heat treatment in air and in a vacuum. In the first phase of the research, the effect of the above mentioned binder removal methods were investigated using the single-bundle tensile test. Binder removal via fibre spreading did not cause any reduction in the properties of E-glass fibre bundles. However, binder removal by acetone extraction led to a decrease of 37% in the tensile strength. The most detrimental effect on the tensile strength was found to be when E-glass was exposed to temperatures in excess of 450 °C. The percentage reduction in tensile strength for E-glass fibre bundle for 450 °C, 550 °C and 650 °C were 60%, 66% and 90% respectively. In the second phase of the research, E-glass bundles that were subjected to the above-mentioned treatments were used to fabricate single bundle composites. The procedure for manufacturing these composites was developed. It was established that the reduction in the strengths of the E-glass composites after specified treatment could be correlated to the reduction in properties experience by the fibre bundles. Attempts were made to analyse the treated fibres using a range of analytical techniques such as X-ray diffraction, thermographic analysis, differential scanning calorimetry and infrared spectroscopy analysis. Heat treating E-glass fibres in the absence of air was shown to bring about a reduction in the tensile strength by 58% as compared to 78% when the fibres were previously heated in air at 650 °C

Application of nonlinear autoregressive neural network to estimation of global solar radiation over Nigeria

In this paper, surface data meteorological were used as input variables to create, train and validate the network in which global solar radiation serves as a target. These surface data were obtained from the archives of the European centre for Medium-Range weather forecast for a span of 36 years (1980-2015) over Nigeria. The research aims to evaluate the predictive ability of the nonlinear autoregressive neural network with exogenous input (NARX) model compared with the multivariate linear regression (MLR) model using the statistical metrics. Model selection analysis using the index of agreement (dr) metric showed that the MLR and NARX models have values of 0.710 and 0.853 in the Sahel, 0.748 and 0.849 in the Guinea Savannah, 0.664 and 0.791 in the Derived Savannah, 0.634 and 0.824 in the Coastal regions, and 0.771 and 0.806 in entire Nigeria respectively. Meanwhile, error analyses of the models using root mean square errors (RMSE) showed the values of 1.720 W/m2 and 1.417 in the Sahel region, 2.329 W/m2 and 1.985 W/m2 in the Guinea Savannah region, 2.459 W/m2 and 2.272 W/m2 in the Derived Savannah region, 2.397 W/m2 and 2.261 W/m2 in the Coastal region and 1.691 W/m2 and 1.600 W/m2 in entire Nigeria for MLR and NARX models respectively. These showed that the NARX model has higher dr values and lower RMSE values over all the climatic regions and entire Nigeria than the MLR model. Finally, it can be inferred from these metrics that the NARX model gives a better prediction of global solar radiation than the traditional common MLR models in all the zones in Nigeria

Developing a Rural Tourism Destination Brand Framework from the Perspective of a Relationship-Based Approach

The aim of this paper is to develop a destination brand framework for rural tourism destination. Bario a rural community in Sarawak (Borneo) in Malaysia was chosen as a study context. The choice of Bario over other pre-selected rural destinations is because of its unique remote destination. The primary data collection method for this paper was the in-depth interview with 48 participants; this was supplemented by participant observation and documentary evidence. From the perspective of relationship-based approach adopted in this paper, the findings outline three components for a theoretical construction of rural tourism destination brand framework that comprise tourism destination appeals, branding strategies, and stakeholders’ roles. Findings also indicate that the development of rural tourism destination brand should be from the bottom-up, where community-driven strategies can be most effectively delegated to the local leadership system and community’s association. Implications for practice and host community well-being are discussed in detail

IMPACT OF CLIMATE CHANGE ON LAND-USE AND LAND-COVER OF YEWA SOUTH LOCAL GOVERNMENT AREA, NIGERIA

Agricultural products, which include farming and forestry, and raising livestock, are the main occupation of Yewa South Local Government of Ogun State in Nigeria which is the case in this study area. Climate change has been a significant threat to the study area. The burning of bush has given rise to an increase in greenhouse gas pollution in the atmosphere. The intensive use of land through dynamic human activities and climate changes has also affected the study area's agricultural product. It is necessary to understand the dynamic and climatic changes of the study area. It is on this basis, that this study was carried out to determining the effect of climate change on land use/land cover of the study area. The specific objective is to model the impact of the relationship between climate change and land use/land cover change (LULC) and predict for future planning of land use/land cover change of the study area. This study used multi-temporal data sets between 2000 and 2019 from LANDSAT-7 ETM+ and LANDSAT-8 OLI/TIRS, and climatic variables obtained from Ogun-Osun River Basin Development Authority. The general design and methods used in the study include image acquisition, image classification, and preparation of the thematic map. A supervised Parallelepiped classification scheme was used to classify the images into five different classes of LULC types. The classes are vegetation, wetland, waterbody, agricultural land and built-up. The study developed a multivariate regression model that established the relationship between climate data and (LULCC) that helped predict future planning of LULC of the study area. The LULC classification results revealed that the agricultural land use type was extensively used in the study area, with the percentage ranging from 33.82% (222.17km2) in 2000 to 66 56% (436.84km2) in 2011. The high value of yearly rainfall throughout the study period led to an increase in water resources' agricultural consumption. The growth rate of the built-up area between 2000 and 2019 snowballed, rising from 3.85% in 2000 to 10.33%, with actual areal expansion increasing from 25.28 km2. to 67.83 km2. The rapid increase in the population during the year of study also attributed to the expansion of farmland, where many farmers obtained land for large-scale agriculture, suggesting that farmland is the most predominant LULC category in the study area. The technique to predict LULC distribution for 2040 was successful, and the results were compared with the LULC from 2000 to 2019. The study also established that there are distinct changes in climate variability between the years 2000 and 2019, leading to changes in the land use/land cover of the study area. The statistical analysis result indicated that the climatic parameters have an accuracy of 84.12 % Prediction for land use/land cover classification. The projected LULC for 2040 revealed potential expansion in agriculture and growth in population. It is envisaged that the study will help improve the social-economic activities without further disintegrating the environment for planning, administration, and exploitation of lands in the Yewa South Local Government area of Ogun State, Nigeria