No description available.

No description available.

Gas hydrates have attracted much interest among researchers recently because of their wide range of applications. The impact of natural gas hydrates in subsea sediments on the development of conventional hydrocarbon reservoirs in deep offshore and the potential role of CO2 hydrates as a secondary safety factor in subsurface storage of CO2 are the key areas in this thesis. Several experiments were conducted on synthetic samples containing methane hydrate with different hydrate saturations to measure their geophysical properties, mechanical properties and understand their mechanical behaviour at realistic conditions. A numerical model was also developed with ABAQUS (a finite element package) to investigate the casing stability of the wellbore drilled in gas hydrate bearing sediments in deep offshore environments using the measured properties of gas hydrate bearing sediments under different scenarios. The role of hydrates in subsurface storage of CO2 was studied using a unique experimental set-up by simulating geothermal temperature gradient. The objective was to investigate whether CO2 leaked from subsurface storage sites can be converted into hydrates, providing a secondary seal against further CO2 leakage to ocean/atmosphere.

Current gas hydrate flow assurance methods are becoming less economical and/or practical for deepwater operations, long tiebacks and ageing reservoirs. The industry thus needs novel flow assurance techniques to address these challenging conditions. An alternative approach called HYDRAFLOW, a chemical based wet Cold Flow method, has been presented in this thesis in which gas hydrate management, rather than prevention, is the aim. The idea is to convert most of the gas phase into hydrates and transfer it in the form of hydrate-slurry in the pipeline. This study investigates the concept, i.e. the transportability of hydrate slurries, for different systems (low and high GOR oil systems in the presence and absence of AAs) in different operating conditions, especially in conditions where the other flow assurance solutions either cannot be applied or are not economically viable, e.g. at high watercuts or under very high degree of subcoolings. The experiments involve investigating the rheological behaviour and flow properties of hydrate slurries using the HTI-set up (Helical Tube Impeller, an apparatus designed and build in-house for measuring viscosity of hydrate slurries at high pressures). Additionally, the rate of hydrate formation in low and high oil systems and also at subzero conditions has been measured. Furthermore, the effect of key variables, (e.g. heat transfer, mass transfer, degree of subcooling, salt, anti-agglomerants (AAs) and thermodynamic inhibitors) on the rate of hydrate formation and also on the rheology of hydrate suspensions have been studied in this work. The partitioning of a commercial AA between hydrate, oil and aqueous phases and its performances in each phase have also been determined which can help for decision making about recovering and/or recycling all or part of AAs. And finally, it has been shown that hydrate flow can potentially reducing wax deposition problems in pipeline by abrasion of the deposited wax.

In modern field management practices, there are two important steps that shed light on a multimillion dollar investment. The first step is history matching where the simulation model is calibrated to reproduce the historical observations from the field. In this inverse problem, different geological and petrophysical properties may provide equally good history matches. Such diverse models are likely to show different production behaviors in future. This ties the history matching with the second step, uncertainty quantification of predictions. Multiple history matched models are essential for a realistic uncertainty estimate of the future field behavior. These two steps facilitate decision making and have a direct impact on technical and financial performance of oil and gas companies. Population-based optimization algorithms have been recently enjoyed growing popularity for solving engineering problems. Population-based systems work with a group of individuals that cooperate and communicate to accomplish a task that is normally beyond the capabilities of each individual. These individuals are deployed with the aim to solve the problem with maximum efficiency. This thesis introduces the application of two novel population-based algorithms for history matching and uncertainty quantification of petroleum reservoir models. Ant colony optimization and differential evolution algorithms are used to search the space of parameters to find multiple history matched models and, using a Bayesian framework, the posterior probability of the models are evaluated for prediction of reservoir performance. It is demonstrated that by bringing latest developments in computer science such as ant colony, differential evolution and multiobjective optimization, we can improve the history matching and uncertainty quantification frameworks. This thesis provides insights into performance of these algorithms in history matching and prediction and develops an understanding of their tuning parameters. The research also brings a comparative study of these methods with a benchmark technique called Neighbourhood Algorithms. This comparison reveals the superiority of the proposed methodologies in various areas such as computational efficiency and match quality.

Modern reservoir management has an increasing focus on accurately predicting the likely range of field recoveries. A variety of assisted history matching techniques has been developed across the research community concerned with this topic. These techniques are based on obtaining multiple models that closely reproduce the historical flow behaviour of a reservoir. The set of resulted history matched models is then used to quantify uncertainty in predicting the future performance of the reservoir and providing economic evaluations for different field development strategies. The key step in this workflow is to employ algorithms that sample the parameter space in an efficient but appropriate manner. The algorithm choice has an impact on how fast a model is obtained and how well the model fits the production data. The sampling techniques that have been developed to date include, among others, gradient based methods, evolutionary algorithms, and ensemble Kalman filter (EnKF). This thesis has investigated and further developed the following sampling and inference techniques: Particle Swarm Optimisation (PSO), Hamiltonian Monte Carlo, and Population Markov Chain Monte Carlo. The inspected techniques have the capability of navigating the parameter space and producing history matched models that can be used to quantify the uncertainty in the forecasts in a faster and more reliable way. The analysis of these techniques, compared with Neighbourhood Algorithm (NA), has shown how the different techniques affect the predicted recovery from petroleum systems and the benefits of the developed methods over the NA. The history matching problem is multi-objective in nature, with the production data possibly consisting of multiple types, coming from different wells, and collected at different times. Multiple objectives can be constructed from these data and explicitly be optimised in the multi-objective scheme. The thesis has extended the PSO to handle multi-objective history matching problems in which a number of possible conflicting objectives must be satisfied simultaneously. The benefits and efficiency of innovative multi-objective particle swarm scheme (MOPSO) are demonstrated for synthetic reservoirs. It is demonstrated that the MOPSO procedure can provide a substantial improvement in finding a diverse set of good fitting models with a fewer number of very costly forward simulations runs than the standard single objective case, depending on how the objectives are constructed. The thesis has also shown how to tackle a large number of unknown parameters through the coupling of high performance global optimisation algorithms, such as PSO, with model reduction techniques such as kernel principal component analysis (PCA), for parameterising spatially correlated random fields. The results of the PSO-PCA coupling applied to a recent SPE benchmark history matching problem have demonstrated that the approach is indeed applicable for practical problems. A comparison of PSO with the EnKF data assimilation method has been carried out and has concluded that both methods have obtained comparable results on the example case. This point reinforces the need for using a range of assisted history matching algorithms for more confidence in predictions.

Concerns over the environmental impact of carbon dioxide (CO2) have led to a resurgence of interest in CO2 injection (CO2I) in oil reservoirs, which can enhance oil recovery from these reservoirs and store large quantities of CO2 for a long period of time. Oil displacement and recovery by CO2I has been studied and applied in the field extensively. However, CO2I lacks acceptable sweep efficiency, due to the large viscosity contrast between CO2 and resident reservoir fluids. Various CO2I strategies e.g. alternating (WAG) or simultaneous injection of CO2 and water have been suggested to alleviate this problem. An effective alternative strategy is carbonated (CO2-enriched) water injection. In carbonated water, CO2 exists as a dissolved as opposed to a free phase, hence eliminating the problems of gravity segregation and poor sweep efficiency. In this thesis, the results of an integrated experimental and theoretical investigation of the process of carbonated water injection (CWI) as an injection strategy for enhanced oil recovery (EOR) with the added value of CO2 storage are described. High-pressure micromodel technology was used to physically simulate the process of CWI and visually investigate its EOR potential, at typical reservoir conditions. Using the results of these flow visualisation experiments, the underlying physical processes and the pore-scale mechanisms of fluid-fluid and fluid-solid interactions during CWI were demonstrated to be oil swelling, coalescence of the isolated oil ganglia, wettability alteration, oil viscosity reduction and flow diversion due to flow restriction in some of the pores as a result of oil swelling and the resultant fluid redistribution. A mathematical model was developed that accounts for the pore-scale mechanisms observed during the micromodel experiments. In this study, some of the micromodel experimental observations were interpreted and the impact of some of the pertinent parameters on CWI and CO2I processes was studied. The results predicted by the model were linked to the results obtained using a new relationship developed based on the dimensional analysis technique. To examine and investigate the effect of CWI on wettability, micromodel experiments, designed only to observe possible variation of contact angles and spontaneous imbibition displacement mechanisms due to CW, were performed. Contact angle measurements were also conducted to quantify different tendencies of CW and water to wet solid surfaces, using three different solid plates with different salinity of the aqueous phase, under different pressure and temperature conditions. Two other important parameters affecting the performance of CWI, i.e. CO2 solubility in water and its CO2 diffusion coefficient, were also experimentally studied and estimated. A mathematical model was developed to estimate CO2 diffusion coefficient from the corresponding experimental results. The results of this research show that CWI is an effective and efficient injection strategy that offers great potential for enhanced oil recovery and at the same time a unique solution to the problem of reducing CO2 emission.

Scale deposits, such as more conventional sulphate and carbonate scales, impair oil and gas production and lead to problems such as production loss, equipment failure and additional expenditure. However, more recently the occurrence of sulphide scales (e.g. FeS, ZnS and PbS) is increasingly being reported. The mechanisms of formation and inhibition of sulphide scales in oilfield systems are not yet fully understood. This thesis presents a modelling, methodological and mechanistic study of sulphide scale (FeS, ZnS, PbS) formation and inhibition. A number of specific aspects relating to sulphide scaling are studied in this thesis, as follows: (i) Sulphide scale formation and the related mechanisms of inhibition by chemical scale inhibitors; (ii) the effects of commercial scale inhibitors (e.g. PPCA, DETPMP and other blends) on sulphide and mixed scale formation; (iii) the effect of THPS as a sulphide scale dissolver and the additional effect of brine composition (Ca2+ and Mg2+ ) on its performance; (iv) the effect of scale inhibitors on the morphology of both BaSO4 and CaCO3 when co-precipitated with sulphide scales; (v) the effect of scale inhibitors on mixed sulphide scaling (e.g. ZnS/PbS etc.); (vi) a sulphide prediction model was also developed which gives a description of the sulphide precipitation interactions and this was tested against experiment. These various experimental studies were carried out using an integrated combination of techniques such as a modified static bottle tests (performed in an anaerobic apparatus for some cases to avoid Fe2+ oxidation), dynamic static tests, particle size analysis, inductively coupled plasma (ICP), scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). These studies have enabled us to develop some new insights into the mechanisms of sulphide scale formation and inhibition in this work. For example, some of the specific contributions to the understanding of sulphide scale formation an d inhibition mechanisms, from this work are listed as follows: • A number of predictions were made using a detailed sulphide model of experimental quantities such as final solution pH, saturation ratios (SR), mass of FeS etc. These predictions were compared directly with the experimentally measured quantities and excellent agreement has been found. • A number of novel types of FeS inhibition behaviour have been observed and describes when treated with scale inhibitors e.g. some FeS solutions are found to become clear from black 24hrs after the scale inhibitor treatment. • There is significant barite crystal distortion when co-precipitated with FeS, but no distortion is observed when barium sulphate co-precipitates with PbS and ZnS. • Mg2+ has a profound effect on the ability of THPS to inhibit FeS and this work demonstrates that THPS is significantly enhanced by the presence of Mg2+ which has more effect than any other ions. • CaCO3 crystals deposit in bulk solution, rather than on the metal surface when coprecipitated with ZnS. The polymorphs of CaCO3 form on the metal surface when coprecipitated with PbS. • Mixed PbS and ZnS sulphide scale is found to be easier to inhibit than either scale individually.

One of the challenges that the petroleum industry faces is to ensure unimpeded flow of hydrocarbons. During production, transportation and processing, there can be free water in the produced fluid, and/or changes in temperature and pressure can lead to water condensation causing ice and/or hydrates formation. Gas hydrates pose serious flow assurance, economic and safety concerns. Chemical inhibitors are widely used to reduce the risks associated with hydrates. However, the upstream injection of hydrate inhibitors is generally based on thermodynamic model predictions and estimations of the worst conditions without much downstream measurements. This thesis presents a research work in which a number of techniques were investigated with the ultimate aim to mitigate hydrate risks during hydrocarbon recovery. Hydrate Monitoring Techniques are where the hydrate stability zone (HSZ) could be determined by testing downstream samples. Spectroscopy, dielectric permittivity, and freezing point depression methods were experimentally examined. A novel pseudo concentration approach was created as a result of this research work. This approach is more reliable and robust than the historically developed correlation, since it takes into account the pressure, hydrate structure and inhibitor type effects. Spectroscopy, dialectic permittivity set-ups and a freezing point prototype device based on Peltier heat pumps have been designed, built and tested. Hydrate Early Warning Techniques are where the hydrate formation could be detected based on water memory phenomenon. This phenomenon suggests that sampled fluid under specific conditions can carry remnant molecular structure related to hydrate formation if it had taken place. Spectroscopy, onset of ice formation and onset of hydrate formation were investigated. During this work, a multiple probe freezing apparatus and hydrate mini-rig prototypes have been designed, built, and tested. These techniques can provide technical measures for hydrate monitoring and early warning, helping to lessen the risk of pipeline blockages as well as to minimise the amount of chemicals required to inhibit any hydrate formation, hence improve the production economics and reduce the impact on the environment. Moreover, the investigated techniques show a potential to be deployed in Supervisory Control And Data Acquisition (SCADA) systems widely used in the petroleum industry for reservoir/production monitoring and management.

No description available.