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Transportation of unprocessed multiphase reservoir fluids from deep/ultra deep offshore through a long subsea tieback/pipeline is inevitable. This form of transportation is complex and requires accurate knowledge of critical transport velocity, flow pattern changes, phase velocity, pressure drop, particle drag & lift forces, sand/liquid/gas holdup, flow rate requirement and tieback sizing etc at the early design phase and during operation for process optimisation. This research investigated sand transport characteristics in multiphase, water‐oil‐gas‐sand flows in horizontal, inclined and vertical pipes. Two critical factors that influence the solid particle transport in the case of multiphase flow in pipes were identified; these are the transient phenomena of flow patterns and the characteristic drag & lift coefficients ( D C , L C ). Therefore, the equations for velocity profile were developed for key flow patterns such as dispersed bubble flow, stratified flow, slug flow and annular flow using a combination of analytical equations and numerical simulation tool (CFD). The existing correlations for D C & L C were modified with data acquired from multiphase experiment in order to account for different flow patterns. Minimum Transport Velocity (MTV) models for suspension and rolling were developed by combining the numerically developed particle velocity profile models with semi‐empirical models for solid particle transport. The models took into account the critical parameters that influence particle transport in pipe flow such as flow patterns and particle drag & lift coefficients, thus eliminate inaccuracies currently experienced with similar models in public domain. The predictions of the proposed MTV models for suspension and rolling in dispersed bubble, slug flow and annular flow show maximum average error margin of 12% when compared with experimental data. The improved models were validated using previously reported experimental data and were shown to have better predictions when compared with existing models in public domain. These models have the potential to solve the problems of pipe and equipment sizing, the risk of sand deposition and bed formation, elimination of costs of sand unloading, downtime and generally improve sand management strategies.

With burgeoning world demand and a limited rate of discovery of new reserves, there is increasing impetus upon the industry to optimize recovery from already existing fields. 4D, or time-lapse, seismic imaging is an emerging technology that holds great promise to better monitor and optimise reservoir production. The basic idea behind 4D seismic is that when multiple 3D surveys are acquired at separate calendar times over a producing field, the reservoir geology will not change from survey to survey but the state of the reservoir fluids will change. Thus, taking the difference between two 3D surveys should remove the static geologic contribution to the data and isolate the timevarying fluid flow component. However, a major challenge in 4D seismic is that acquisition and processing differences between 3D surveys often overshadow the changes caused by fluid flow. This problem is compounded when 4D effects are sought to be derived from vintage 3D data sets that were not originally acquired with 4D in mind. The goal of this study is to remove the acquisition and imaging artefacts from a 4D seismic difference cube using Curvelet processing techniques.

The study of phase behavior is important for the oil and gas industry. Many approaches have been proposed and developed for phase behavior calculation. In this thesis, an alternative method is introduced to study the phase behavior by means of minimization of Helmholtz free energy. For a system at fixed volume, constant temperature and constant number of moles, the Helmholtz free energy reaches minimum at the equilibrium state. Based on this theory, a stochastic method called Particle Swarm Optimization (PSO) algorithm, is implemented to compute the phase diagrams for several pure component and mixture systems. After comparing with experimental and the classical PT-ash calculation, we found the phase diagrams obtained by minimization of the Helmholtz Free Energy approach match the experimental and theoretical diagrams very well. Capillary effect is also considered in this thesis because it has a significant influence on the phase behavior of reservoir fluids. In this part, we focus on computing the phase envelopes, which consists of bubble and dew point lines. Both fixed and calculated capillary pressure from the Young-Laplace equation cases are introduced to study their effects on phase envelopes. We found that the existence of capillary pressure will change the phase envelopes. Positive capillary pressure reduces the dew point and bubble point temperatures under the same pressure condition, while the negative capillary pressure increases the dew point and bubble point temperatures. In addition, the change of contact angle and pore radius will affect the phase envelope. The effect of the pore radius on the phase envelope is insignificant when the radius is very large. These results may become reference for future research and study. Keywords: Phase Behavior; Particle Swarm Optimization; Capillary Pressure; Reservoir Fluids; Phase Equilibrium; Phase Envelope.