Characterization of wood biochar and evaluation of its adsorption potential for removal of sulphate from produced water in offshore oil and gas industry

This thesis analyses the potential of wood biochar as an adsorbent in removal of sulphate from produced water. In worldwide offshore oil and gas industry, a large volume of waste water is generated as produced water. Sulphur compounds present in these produced water streams can cause environmental problems, regulatory problems and operational issues. Among the various sulphur removal technologies, the adsorption technique is considered as a suitable method since the design is simple, compact, economical and robust. Biochar has been studied as an adsorbent for removal of contaminants from water in a number of studies due to its low cost, potential availability, and adsorptive characteristics. In this study, biochar produced through fast pyrolysis of bark, hardwood sawdust, and softwood sawdust were characterized through a series of tests and were analysed for adsorbent properties. Treating produced water using biochar sourced from wood waste is a two-fold solution to environmental problems as it reduces the volume of these wastes. Batch adsorption tests were carried out to obtain adsorption capacities of each biochar sample using sodium sulphate solutions. The highest sulphur adsorption capacities obtained for hardwood char, softwood char and bark char were 11.81 mg/g, 9.44 mg/g, and 7.94 mg/g respectively at 10 °C and pH=4. The adsorption process followed the second order kinetic model and the Freundlich isotherm model. Adsorption reaction was thermodynamically favourable and exothermic. The overall analysis concludes that the wood biochar is a feasible, economical, and environmental adsorbent for removal of sulphate from produced water.

Design and implementation of a relative localization system for ground and aerial robotic teams

The main focus of this thesis is to address the relative localization problem of a heterogenous team which comprises of both ground and micro aerial vehicle robots. This team configuration allows to combine the advantages of increased accessibility and better perspective provided by aerial robots with the higher computational and sensory resources provided by the ground agents, to realize a cooperative multi robotic system suitable for hostile autonomous missions. However, in such a scenario, the strict constraints in flight time, sensor pay load, and computational capability of micro aerial vehicles limits the practical applicability of popular map-based localization schemes for GPS denied navigation. Therefore, the resource limited aerial platforms of this team demand simpler localization means for autonomous navigation. Relative localization is the process of estimating the formation of a robot team using the acquired inter-robot relative measurements. This allows the team members to know their relative formation even without a global localization reference, such as GPS or a map. Thus a typical robot team would benefit from a relative localization service since it would allow the team to implement formation control, collision avoidance, and supervisory control tasks, independent of a global localization service. More importantly, a heterogenous team such as ground robots and computationally constrained aerial vehicles would benefit from a relative localization service since it provides the crucial localization information required for autonomous operation of the weaker agents. This enables less capable robots to assume supportive roles and contribute to the more powerful robots executing the mission. Hence this study proposes a relative localization-based approach for ground and micro aerial vehicle cooperation, and develops inter-robot measurement, filtering, and distributed computing modules, necessary to realize the system. The research study results in three significant contributions. First, the work designs and validates a novel inter-robot relative measurement hardware solution which has accuracy, range, and scalability characteristics, necessary for relative localization. Second, the research work performs an analysis and design of a novel nonlinear filtering method, which allows the implementation of relative localization modules and attitude reference filters on low cost devices with optimal tuning parameters. Third, this work designs and validates a novel distributed relative localization approach, which harnesses the distributed computing capability of the team to minimize communication requirements, achieve consistent estimation, and enable efficient data correspondence within the network. The work validates the complete relative localization-based system through multiple indoor experiments and numerical simulations. The relative localization based navigation concept with its sensing, filtering, and distributed computing methods introduced in this thesis complements system limitations of a ground and micro aerial vehicle team, and also targets hostile environmental conditions. Thus the work constitutes an essential step towards realizing autonomous navigation of heterogenous teams in real world applications.