Caracterização e estudo comparativo de exsudações de hidrocarbonetos e plays petrolíferos em bacias terrestres das regiões central do Irã e sudeste do Brasil usando sensoriamento remoto espectral

Orientador: Carlos Roberto de Souza FilhoTese (doutorado) - Universidade Estadual de Campinas, Instituto de GeociênciasResumo: O objetivo desta pesquisa foi explorar as assinaturas de exsudações de hidrocarbonetos na superfície usando a tecnologia de detecção remota espectral. Isso foi alcançado primeiro, realizando uma revisão abrangente das capacidades e potenciais técnicas de detecção direta e indireta. Em seguida, a técnica foi aplicada para investigar dois locais de teste localizados no Irã e no Brasil, conhecidos por hospedar sistemas ativos de micro-exsudações e afloramentos betuminosos, respectivamente. A primeira área de estudo está localizada perto da cidade de Qom (Irã), e está inserida no campo petrolífero Alborz, enterrado sob sedimentos datados do Oligoceno da Formação Upper Red. O segundo local está localizado perto da cidade de Anhembi (SP), na margem oriental da bacia do Paraná, no Brasil, e inclui acumulações de betume em arenitos triássicos da Formação Pirambóia. O trabalho na área de Qom integrou evidências de (i) estudos petrográficos e geoquímicos em laboratório, (ii) investigações de afloramentos em campo, e (iii) mapeamento de anomalia em larga escala através de conjuntos de dados multi-espectrais ASTER e Sentinel-2. O resultado deste estudo se trata de novos indicadores mineralógicos e geoquímicos para a exploração de micro-exsudações e um modelo de micro-exsudações atualizado. Durante este trabalho, conseguimos desenvolver novas metodologias para análise de dados espectroscópicos. Através da utilização de dados simulados, indicamos que o instrumento de satélite WorldView-3 tem potencial para detecção direta de hidrocarbonetos. Na sequência do estudo, dados reais sobre afloramentos de arenitos e óleo na área de Anhembi foram investigados. A área foi fotografada novamente no chão e usando o sistema de imagem hiperespectral AisaFENIX. Seguiu-se estudos e amostragem no campo,incluindo espectroscopia de alcance fechado das amostras no laboratório usando instrumentos de imagem (ou seja, sisuCHEMA) e não-imagem (ou seja, FieldSpec-4). O estudo demonstrou que uma abordagem espectroscópica multi-escala poderia fornecer uma imagem completa das variações no conteúdo e composição do betume e minerais de alteração que acompanham. A assinatura de hidrocarbonetos, especialmente a centrada em 2300 nm, mostrou-se consistente e comparável entre as escalas e capaz de estimar o teor de betume de areias de petróleo em todas as escalas de imagemAbstract: The objective of this research was to explore for the signatures of seeping hydrocarbons on the surface using spectral remote sensing technology. It was achieved firstly by conducting a comprehensive review of the capacities and potentials of the technique for direct and indirect seepage detection. Next, the technique was applied to investigate two distinctive test sites located in Iran and Brazil known to retain active microseepage systems and bituminous outcrops, respectively. The first study area is located near the city of Qom in Iran, and consists of Alborz oilfield buried under Oligocene sediments of the Upper-Red Formation. The second site is located near the town of Anhembi on the eastern edge of the Paraná Basin in Brazil and includes bitumen accumulations in the Triassic sandstones of the Pirambóia Formation. Our work in Qom area integrated evidence from (i) petrographic, spectroscopic, and geochemical studies in the laboratory, (ii) outcrop investigations in the field, and (iii) broad-scale anomaly mapping via orbital remote sensing data. The outcomes of this study was novel mineralogical and geochemical indicators for microseepage characterization and a classification scheme for the microseepage-induced alterations. Our study indicated that active microseepage systems occur in large parts of the lithofacies in Qom area, implying that the extent of the petroleum reservoir is much larger than previously thought. During this work, we also developed new methodologies for spectroscopic data analysis and processing. On the other side, by using simulated data, we indicated that WorldView-3 satellite instrument has the potential for direct hydrocarbon detection. Following this demonstration, real datasets were acquired over oil-sand outcrops of the Anhembi area. The area was further imaged on the ground and from the air by using an AisaFENIX hyperspectral imaging system. This was followed by outcrop studies and sampling in the field and close-range spectroscopy in the laboratory using both imaging (i.e. sisuCHEMA) and nonimaging instruments. The study demonstrated that a multi-scale spectroscopic approach could provide a complete picture of the variations in the content and composition of bitumen and associated alteration mineralogy. The oil signature, especially the one centered at 2300 nm, was shown to be consistent and comparable among scales, and capable of estimating the bitumen content of oil-sands at all imaging scalesDoutoradoGeologia e Recursos NaturaisDoutor em Geociências2015/06663-7FAPES

Electromagnetic characterization of barefaced terrain for oil sand exploration

The scant difference in the electromagnetic (EM) reflectivity of barefaced terrain often imposes challenges in differentiating between such terrain types and deployment of synthetic aperture radar to oil sand exploration. Microwave remote sensing has a proven ability to provide valuable information about targets. However to derive geoscientific information, a profound understanding of the EM interaction with terrain is vital. The challenge is to identify scattering characteristics relevant to oil sand fields. While various terrain identification methods and signature databases have been developed in the optical domain, only few examples of barefaced terrain discrimination in the microwave domain have been reported. In this thesis a three step multi-sensor approach has been used to identify EM signature of barefaced terrain encompassing homogeneous and heterogeneous materials, in the optical and microwave range. The combined method also led to the development of a large database of hyperspectral reflectivity, dielectric and backscattering data relevant to geointelligence analysis. The geochemical signature identification and prediction (GSIP) process required spectral data acquisition, chemometric model implementation and postprocessing to determine the spectral fingerprints and components of two strains of Nigerian oil sands. The results were compared with available hydrocarbon databases and four new features of Nigerian oil sands were observed. The dielectric discrimination statistical model (DDSM) involved three studies of the dielectric properties of oil sands and other barefaced terrain with different weight percentage of moisture and statistical processing of data to identify the 1 – 2 GHz and 5 – 7 GHz as most suitable frequency bands for microwave imaging. The GSIP and DDSM provided new empirical data on the geochemical and electrical behaviour of oil sand particularly the contrasting effects of bitumen, sand and moisture. Finally computer EM (CEM) models of barefaced terrain and sensors were used to identify the backscattering behaviour of the terrain for analysis in 2D/3D format. The results provided good agreement with classical surface roughness models particularly the Surface Perturbation and Kirchoffs Scattering model. They also enabled the investigation of the effect of wide variations in the sensor and terrain parameters on backscattering in order to evolve a radar signature necessary for identification of oil sand terrain for petroleum exploration. A laboratory scatterometer system (LSS) was developed and deployed in three imaging scenarios to verify aspects of the derived microwave EM signature of the terrain. The LSS measurements and the results from the CEMs were complimentary

Characterization of heavy oil fractions using spectrometric techniques

The work presented in this thesis was focused on developing spectroscopic techniques that can be easily incorporated in an instrument for the rapid characterization of heavy oil fractions. Transmission infrared, attenuated total reflectance infrared, visible, and nuclear magnetic resonance spectroscopy were the techniques studied in the course of this project. The key properties of the heavy petroleum fraction that were characterized are as follows: Viscosity parameter: Viscosity at 210 and 100 °F, Viscosity Index Compositional: Relative percentage content of paraffin, naphthene, and aromatic Optical: Color of the heavy oil fraction The techniques developed in this project would reduce the labor and maintenance involved in the quality control labs in the industry. The time scale of characterization by these techniques is of the order of 4 minutes and hence, the results can be used more effectively for process feedback. This is in stark contrast to the time taking characterization techniques prevalent in the industry. The following are the outcome of the project: The transmission Infrared (IR) is inappropriate for predicting the heavy oil properties Attenuated Total Reflectance (ATR) Infrared (IR) measurement is better for the present purposes Predictions o key viscosity parameters of the heavy oil fraction (Viscosity at 100 and 210°F, and Viscosity Index) based on ATR IR measurements are good ATR IR spectra also correlated well with the compositional properties (percentage paraffin, naphthene,and aromatic) of the heavy oil fractions derived from the Nuclear Magnetic Resonance (NMR) spectra of the oil fractions For color characterization, IR spectrum was found inadequate. Visible spectra of the samples was found to be more useful for color characterization The findings from the project suggest that a combination of ATR IR and visible spectroscopic measurement techniques can successfully characterize the properties of heavy oil fractions. In future, these methods of analysis can be formalized into procedures transferable to a prototype analyzer

Characterization and mathematical modeling of the structure of Canadian crude asphalt binders by x-ray diffraction

Eight samples of asphalt binder were retrieved from the provinces of Ontario and Alberta, Canada. Then they were pre-processed in thin film (1mm) on glass slides. X-ray diffraction (XRD) is used to perform profile fits, aromaticity and crystallite parameters in asphalt binder samples, and patterns were gotten by employing monochromatic Cu-K-a radiation (40kV and 40mA) using a Rigaku DMax 2200V-PC. Additionally, profile fitting was carried out by applying Pearson VII and Pseudo-Voigt functions from 5° to 35° as well as 60° to 110°= 2θ. The broadening of the diffraction line was simulated and analyzed using X-ray thin film. Outcome indicated a notable relationship between Pearson VII, Pseudo-Voigt, and Generalized Fermi Function (GFF). X-ray line broadening experiments using either the integral or full width at half maximum (FWHM) from diffraction lines are employed in order to simulate X-ray line profiles that emerged from the samples. For researchers as well as workers in the field, issues such as rutting of asphalt pavements in hot environments and cracking in cold ones are issues that not only persist but remain unresolved. Therefore, with the aim of enhancing asphalt pavement performance, it is worth examining compositional and structural characteristics in binders on a microscopic level

The molecular composition and geochemical applications of asphaltenes

PhD ThesisAsphaltenes are the heaviest components of petroleum and bitumen consisting of a complex mixture of heteroaromatic substances that have been associated with various deposition problems in both upstream and downstream sectors of the petroleum industry. This thesis describes characterisation of asphaltenes from a variety of sources and geographical areas using FTIR, NMR, as well as selective chemical degradation methods in combination with GC/MS & GC/IRMS with the aim of understanding how their compositions vary with source and geochemical history. Asphaltenes were observed to co-precipitate with substances such as waxes that are components of the maltene fraction. Quantitative removal of the co-precipitated substances requires Soxhlet extraction of the asphaltenes for several hours. The extraction time was found to vary with different asphaltenes. The so-called occlusion or physical entrapment of biomarkers in the cage-like structure of the asphaltenes is more than likely a consequence of the co-precipitation of the waxes. Analysis of mid-infrared spectra of the asphaltenes revealed that petroleum asphaltenes consist predominantly of aliphatic moieties bonded to condensed aromatic structures with relative proportions of aromatic carbon in range of 30 to 40% for non-biodegraded petroleum asphaltenes as revealed by 13C NMR. Biodegraded asphaltenes are less aromatic with relative aromatic carbon being 27% or less although the aromatic moieties tend to have relatively greater degree of condensation than asphaltenes from ono-degraded oils . Although n-alkyl and iso-alkyl groups are the dominant aliphatic moieties, naphthenic groups, mainly in form of homohopanoids and steroids, are significantly present. Oxygen functionalities are mainly in form of hydroxyl, ether, ester, and carboxyl as well as conjugated ketone groups. Ester groups were detected only in coal and black shale asphaltenes. Carboxyl groups were detected in all the asphaltenes irrespective of source and geographical region, although they were particularly prominent in black shale and coal asphaltenes even at a relatively high rank of Ro = 1.5%. Nitrogen functionalities were present as pyridinic and pyrrolic heteroaromatic systems in addition to tertiary aromatic amines. With increasing thermal stress, asphaltenes were observed to evolve towards an equilibrium structure or composition in which aromatic moieties become dominant over aliphatic moieties as a result of increasing condensation and dealkylation. Distribution of alkyl moieties shifts towards increasing proportions of the lower molecular weight homologues with increasing thermal maturity. The thermal stress also results in loss of oxygen functionalities mainly from ester and carboxyl groups. At the molecular level, isomerisation of bound hopanoids and steroids to form an equilibrium composition was observed with increasing maturity. However, while isomerisation of bound hopanoids in asphaltenes appear to be in phase with the corresponding isomerisation of hopanes in the maltene fraction, the isomerisation of bound steroids lags significantly behind the corresponding isomerisation of the steranes in the maltenes. There is good potential in using multivariate pattern recognition tools in oil/oil correlations based on asphaltene bulk composition as measured using FTIR. Notwithstanding some misclassification, the techniques tend to correlate asphaltenes with common source. Similarly, the aliphatic moieties of asphaltenes also reflect the organic matter sources of the asphaltenes. The n-alkyl moieties from asphaltenes with common source not only show similar distributions, but also similar δ13C trends even in asphaltenes from biodegraded oils. Likewise, bound hopanoids also reflect the organic matter source such that asphaltenes with common source show similar hopanoid distributions. The aliphatic moieties therefore have good potential that may be comparable to the conventional hydrocarbon-based biomarkers in oil/oil correlations. In general, the composition of asphaltenes is controlled by the source organic matter and its thermal evolution. The effect of biodegradation is not yet completely understood but, with the exception of steroids, it does not appear to affect the aliphatic composition of the asphaltenes. There is therefore a significant potential in using asphaltenes in discrimination/correlation of oils particularly where the hydrocarbons in the maltene fraction are lost to biodegradation.Petroleum Technology Development Fund (PTDF), Nigeri

Effect of pore diameter variation of FeW/SBA-15 supported catalysts on hydrotreating of heavy gas oil from Athabasca bitumen

The pore diameter of a catalyst support controls the diffusion of reactant molecules to the catalytic active sites; thus, affecting the rates and conversions of the hydrotreating reactions. Desirable textural properties of SBA-15 makes it a potential alternative to the conventionally used γ-Al2O3 support due to the fact that its pore size can be manipulated via controlling the synthesis parameters, while maintaining relatively high surface area. Larger pore diameter SBA-15 supports may facilitate the diffusion of bulky molecules as that of the asphaltenes present in the heavy petroleum fractions, making it a potential catalyst support for hydrotreating operations. Considering the very sour nature of Canada’s bitumen with high sulfur contents in the range of 2-6 wt %, the appreciably high sulfur contents particularly present in Athabasca derived heavy gas oils (about 4 wt % sulfur), the rising demand for cleaner fuels, and also the increasing stringency on environmental standards, the need for novel and improved hydrotreating catalysts cannot be overemphasized. By varying the molar ratio of hexane to ammonium fluoride, the pore channels of SBA-15 could be varied. Controlling the pore diameter of these supports via micelle swelling facilitated the production of larger pore diameter SBA-15-supported catalysts. In this project, four mesoporous silica SBA-15 catalyst supports with pore diameters in the range of 5-20 nm were synthesized in the preliminary phase using hexane as the micelle swelling agent and subsequently utilized for the loading of 2 wt.% Fe and 15 wt.% W catalyst metals, respectively. The hexagonal mesoscopic structure of these materials were characterized using powder small-angle X-ray scattering (SAXS), N2 adsorption-desorption isotherms, TEM and SEM images. Powder XRD analysis evidenced inhomogeneous metal dispersion on the largest pore diameter catalyst. An optimum pore diameter of 10 nm was found for Cat-B and subsequently used to obtain the optimum Fe and W loadings required to achieve the best hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) activities. The optimum catalyst was found to be Cat-H with metal loadings of 3 wt.% Fe and 30 wt.% W. At these loadings and temperatures of 375°C, 388°C, and 400°C, HDS activities of 53.4%, 64.1%, and 73.3% with corresponding HDN activities of 21.9%, 26.2%, and 38.3%, respectively, were recorded. Catalytic performance evaluations conducted on equal mass loading using a reference commercial γ-Al2O3-supported FeW catalyst offered HDS activities of 69.3%, 80.4%, and 89.1%, with corresponding HDN activities of 16.4%, 32.4%, and 49.3% at the same temperatures studied. However, no significant changes in HDS and HDN activities were observed for similar evaluations on volume percent metals loading basis. Kinetic studies performed with the optimum FeW/SBA-15 catalyst suggested activation energies of 147.2 and 150.6 kJ/mol for HDS and HDN, respectively, by the Langmuir-Hinshelwood’s model. Similar results were predicted by the Power Law and Multi-parameter models for HDS (129.6 and 126.7 kJ/mol, respectively), which does not conclusively make the latter model clearly stand out as the best. Data fitting by the Power Law suggested reaction orders of 2 and 1.5 for HDS and HDN, which seem to be consistent for the hydrotreatment of heavy gas oil. Finally, a long-term deactivation study spanning a period of 60 days time-on-stream showed the optimum catalyst to be stable under hydrotreating experiments conducted in a downward flow micro-trickle bed reactor at temperature, pressure, liquid hourly space velocity (LHSV), and gas/oil ratio of 375–400˚C, 8.8 MPa, 1h-1, and 600 mL/mL (at STP), respectively

Marine Oil Spills

Major oil spills attract the attention of the public and the media. This was especially the case after the Deepwater Horizon spill. In recent years, this attention has created a global awareness of the risks of oil spills and the damage they do to the environment. Oil is a necessity in our industrial society, however, and a major component of our lifestyle. This means that the risk of major spills continues as does the interest in spills. The Deepwater Horizon spill began a new series of scientific studies that have greatly increased our understanding of oil spills. This book contains 10 such studies. These studies vary from toxicity studies to social studies of human reaction to spills and risk. Importantly, the book is a sampling of important new topics that have become important after the Deepwater Horizon spill. These new topics include new chemical and tracing techniques, new risk perception techniques, perspectives on human health and spills, and discussion on new fuels. This book makes a significant contribution to the understanding of facets of spills and explores 10 very different facets of oil spills

Mineral identification using data-mining in hyperspectral infrared imagery

Les applications de l’imagerie infrarouge dans le domaine de la géologie sont principalement des applications hyperspectrales. Elles permettent entre autre l’identification minérale, la cartographie, ainsi que l’estimation de la portée. Le plus souvent, ces acquisitions sont réalisées in-situ soit à l’aide de capteurs aéroportés, soit à l’aide de dispositifs portatifs. La découverte de minéraux indicateurs a permis d’améliorer grandement l’exploration minérale. Ceci est en partie dû à l’utilisation d’instruments portatifs. Dans ce contexte le développement de systèmes automatisés permettrait d’augmenter à la fois la qualité de l’exploration et la précision de la détection des indicateurs. C’est dans ce cadre que s’inscrit le travail mené dans ce doctorat. Le sujet consistait en l’utilisation de méthodes d’apprentissage automatique appliquées à l’analyse (au traitement) d’images hyperspectrales prises dans les longueurs d’onde infrarouge. L’objectif recherché étant l’identification de grains minéraux de petites tailles utilisés comme indicateurs minéral -ogiques. Une application potentielle de cette recherche serait le développement d’un outil logiciel d’assistance pour l’analyse des échantillons lors de l’exploration minérale. Les expériences ont été menées en laboratoire dans la gamme relative à l’infrarouge thermique (Long Wave InfraRed, LWIR) de 7.7m à 11.8 m. Ces essais ont permis de proposer une méthode pour calculer l’annulation du continuum. La méthode utilisée lors de ces essais utilise la factorisation matricielle non négative (NMF). En utlisant une factorisation du premier ordre on peut déduire le rayonnement de pénétration, lequel peut ensuite être comparé et analysé par rapport à d’autres méthodes plus communes. L’analyse des résultats spectraux en comparaison avec plusieurs bibliothèques existantes de données a permis de mettre en évidence la suppression du continuum. Les expérience ayant menés à ce résultat ont été conduites en utilisant une plaque Infragold ainsi qu’un objectif macro LWIR. L’identification automatique de grains de différents matériaux tels que la pyrope, l’olivine et le quartz a commencé. Lors d’une phase de comparaison entre des approches supervisées et non supervisées, cette dernière s’est montrée plus approprié en raison du comportement indépendant par rapport à l’étape d’entraînement. Afin de confirmer la qualité de ces résultats quatre expériences ont été menées. Lors d’une première expérience deux algorithmes ont été évalués pour application de regroupements en utilisant l’approche FCC (False Colour Composite). Cet essai a permis d’observer une vitesse de convergence, jusqu’a vingt fois plus rapide, ainsi qu’une efficacité significativement accrue concernant l’identification en comparaison des résultats de la littérature. Cependant des essais effectués sur des données LWIR ont montré un manque de prédiction de la surface du grain lorsque les grains étaient irréguliers avec présence d’agrégats minéraux. La seconde expérience a consisté, en une analyse quantitaive comparative entre deux bases de données de Ground Truth (GT), nommée rigid-GT et observed-GT (rigide-GT: étiquet manuel de la région, observée-GT:étiquetage manuel les pixels). La précision des résultats était 1.5 fois meilleur lorsque l’on a utlisé la base de données observed-GT que rigid-GT. Pour les deux dernières epxérience, des données venant d’un MEB (Microscope Électronique à Balayage) ainsi que d’un microscopie à fluorescence (XRF) ont été ajoutées. Ces données ont permis d’introduire des informations relatives tant aux agrégats minéraux qu’à la surface des grains. Les résultats ont été comparés par des techniques d’identification automatique des minéraux, utilisant ArcGIS. Cette dernière a montré une performance prometteuse quand à l’identification automatique et à aussi été utilisée pour la GT de validation. Dans l’ensemble, les quatre méthodes de cette thèse représentent des méthodologies bénéfiques pour l’identification des minéraux. Ces méthodes présentent l’avantage d’être non-destructives, relativement précises et d’avoir un faible coût en temps calcul ce qui pourrait les qualifier pour être utilisée dans des conditions de laboratoire ou sur le terrain.The geological applications of hyperspectral infrared imagery mainly consist in mineral identification, mapping, airborne or portable instruments, and core logging. Finding the mineral indicators offer considerable benefits in terms of mineralogy and mineral exploration which usually involves application of portable instrument and core logging. Moreover, faster and more mechanized systems development increases the precision of identifying mineral indicators and avoid any possible mis-classification. Therefore, the objective of this thesis was to create a tool to using hyperspectral infrared imagery and process the data through image analysis and machine learning methods to identify small size mineral grains used as mineral indicators. This system would be applied for different circumstances to provide an assistant for geological analysis and mineralogy exploration. The experiments were conducted in laboratory conditions in the long-wave infrared (7.7μm to 11.8μm - LWIR), with a LWIR-macro lens (to improve spatial resolution), an Infragold plate, and a heating source. The process began with a method to calculate the continuum removal. The approach is the application of Non-negative Matrix Factorization (NMF) to extract Rank-1 NMF and estimate the down-welling radiance and then compare it with other conventional methods. The results indicate successful suppression of the continuum from the spectra and enable the spectra to be compared with spectral libraries. Afterwards, to have an automated system, supervised and unsupervised approaches have been tested for identification of pyrope, olivine and quartz grains. The results indicated that the unsupervised approach was more suitable due to independent behavior against training stage. Once these results obtained, two algorithms were tested to create False Color Composites (FCC) applying a clustering approach. The results of this comparison indicate significant computational efficiency (more than 20 times faster) and promising performance for mineral identification. Finally, the reliability of the automated LWIR hyperspectral infrared mineral identification has been tested and the difficulty for identification of the irregular grain’s surface along with the mineral aggregates has been verified. The results were compared to two different Ground Truth(GT) (i.e. rigid-GT and observed-GT) for quantitative calculation. Observed-GT increased the accuracy up to 1.5 times than rigid-GT. The samples were also examined by Micro X-ray Fluorescence (XRF) and Scanning Electron Microscope (SEM) in order to retrieve information for the mineral aggregates and the grain’s surface (biotite, epidote, goethite, diopside, smithsonite, tourmaline, kyanite, scheelite, pyrope, olivine, and quartz). The results of XRF imagery compared with automatic mineral identification techniques, using ArcGIS, and represented a promising performance for automatic identification and have been used for GT validation. In overall, the four methods (i.e. 1.Continuum removal methods; 2. Classification or clustering methods for mineral identification; 3. Two algorithms for clustering of mineral spectra; 4. Reliability verification) in this thesis represent beneficial methodologies to identify minerals. These methods have the advantages to be a non-destructive, relatively accurate and have low computational complexity that might be used to identify and assess mineral grains in the laboratory conditions or in the field

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Characterisation of Deposited Foulants and Asphaltenes using Advanced Vibrational Spectroscopy

The magnitude and significance of crude oil fouling have led to a number of studies; however, the fundamentals of the complex fouling process are not fully understood. This thesis describes the use of the high chemical specificity, imaging capabilities and fast acquisition times offered by advanced vibrational spectroscopic techniques to characterise and understand the physicochemical behaviour of these complex materials. Rapid and reliable methodologies are developed to provide an important chemical characterisation tool which will advance research into crude oil fouling. An emerging and powerful imaging technique based on Fourier transform infrared (FTIR) spectroscopy is applied for the first time to the characterisation of deposited foulants and asphaltenes. Attenuated total reflection (ATR)-FTIR spectroscopic imaging has the advantage of being a non-destructive analytical technique and most importantly, is able to provide both chemical and spatial information about a sample. The novel application, of combining macro and micro ATR modes in FTIR imaging, yields important information about the spatial distribution of different components in deposited foulants and laboratory-extracted asphaltenes. Clusters of chemically different compounds in crude oil deposits from the refinery, such as asphaltenes, carbonates, sulphates, sulfoxides, oxalates and even “coke-like” materials, were identified and analysed. A lab-made aperture is utilised in the macro ATR diamond accessory to correct spectral distortions that occur for high refractive index materials. This approach has been extended to monitor the heating of crude oil in situ and the onset of asphaltene deposition was determined. Micro ATRFTIR imaging of the particulates formed in the crude oil after heating has identified seven chemically different species, namely, silicates, amides, sulphates, carbonates, sulfoxides, vitrinite compounds and “coke-like” materials which are products of different reactions in fouling. The complementary use of Raman and FTIR spectroscopy has been demonstrated to characterise the carbon structures in asphaltenes. The ID/IG and IV/IG parameters derived from the Raman spectra on real deposits showed that it has more ordered structures compared to petroleum asphaltenes which may be linked to the ageing effects of the deposit in heat exchangers. The ATR-FTIR spectra of petroleum asphaltenes suggest that the shape of an average asphaltene is more similar to a wide continental model than the archipelago model