American Petroleum Institute Gravity Research Articles

VARIABLE SELECTION METHODS APPLIED IN HTGC DATA TO DETERMINE PHYSICOCHEMICAL PROPERTIES OF CRUDE OILS

High-temperature gas chromatography (HTGC) is an analytical technique employed in the petroleum industry for component separation. By incorporating chemometrics, HTGC data can be effectively utilized to predict various properties of crude oil. However, HTGC chromatograms generate a substantial number of variables, some of which may lack pertinent chemical information. Consequently, employing variable selection methods becomes crucial to reduce the number of variables and enhance the predictive capability of calibration models. In this study, the interval partial least squares (iPLS), synergy interval partial least squares (siPLS), and ordered predictors selection (OPS) methods were applied for variable selection to construct linear regression models. The main objective was to investigate the potential of these methods in predicting eight properties of crude oil: American Petroleum Institute (API) gravity, standardized kinematic viscosity at 50 °C (VISp), flash point (FP), Reid vapor pressure (RVP), micro carbon residue (MCR), saturates (SAT), aromatics (ARO), and polar (POL) content. While all variable selection methods yielded satisfactory results, the OPS-PLS regression models consistently exhibited the best performance in estimating these properties, achieving root mean squared error of prediction (RMSEP) values of 1.244 for API, 0.029 for VISp, 15.356 °C for FP, 0.324 kPa for RVP, 0.629 wt% for MCR, 3.691 wt% for SAT, 2.939 wt% for ARO, and 3.374 wt% for POL. Variable selection demonstrated remarkable effectiveness, significantly improving the accuracy of the models, and allowing for the creation of concise models with a focused set of variables.

Co-movements of crude oil prices

ABSTRACT This paper investigates whether the world crude oil market is globalised in a ‘one great pool’ or is regionalised by examining the prices of 21 different types of crude oil from various regions worldwide. We employ monthly data from October 2011 to November 2020 to construct spatial panel data models. Using three weight matrices, we account for the physical properties affecting crude oil quality and geographical factors. The resulting empirical evidence reveals that although we cannot refute the globalisation hypothesis, there are distinct price mechanisms specific to each type of crude oil. The pricing of crude oil appears to be influenced by a combination of similar and dissimilar qualities, including American Petroleum Institute gravity (API) gravity, sulfur content and geographical location.

Association parameters for Cubic-Plus-Association equation of state determined by molecular dynamics and Petroleomics: Prediction of asphaltene precipitation

In this study, petroleomics characterization, molecular dynamics (MD) simulations, and a cubic-plus-association (CPA) equation of state (EoS) were conducted to understand how the structural characteristics affect the phase behavior of a fluid. To do this, the asphaltene onset pressure (AOP) was estimated by CPA EoS using association parameters determined from MD simulations. Petroleomics characterization and gas chromatography were conducted to identify appropriate representative molecular structures for describing a live crude oil. The American Petroleum Institute (API) gravity, dead and live crude oil densities, and viscosities at reservoir conditions were calculated from the MD simulation results and were found to differ from the experimental measurements by less than 5%, indicating accurate characterizations for both real dead and live crude oil. A formation damage diagnosis from a compositional perspective was conducted because oxygenated aromatic compounds, which are highly active in aggregation terms, were identified in the aromatic fraction by Fourier-transform ion cyclotron resonance mass spectrometry (FT–ICR MS). The association parameters for the self-associating organics (So: asphaltenes and oxygenated aromatics) and the cross-interaction between these Sos and the maltenes were calculated from the MD simulation results. To the best of our knowledge, this is the first time that association parameters have been obtained from an MD model and successfully implemented in a CPA EoS, allowing the prediction of AOP with an accuracy close to 1% compared to the experimentally determined value for live crude oil. This study provides a promising framework to develop an EoS for crude oils based on their molecular characteristics, reducing the need to perform parametric tuning with experimental data. In addition, this structural characterization proposed could be important to other key topics such as enhanced oil recovery (EOR) and carbon capture use and storage (CCUS), relating the structural composition to phase behavior.

Oil content removal from oil water emulsion by super magnetic nanoparticles

Oily wastewater treatment processes are facing challenges due to strict regulations in the quality of effluent standards and waste production. The reuse of oily wastewater treatment effluents is rapidly gaining attention for achieving sustainable water supply. Fe3O4 magnetic nanoparticles (MNPs) are widely applied as super adsorbents in industry. In the present study, the MNP was sprayed and mixed with oil-water emulsion, after the application of a magnetic field, a clear effluent was seen within minutes. The effects of the varying process parameters including, adsorbent dose, particle size, mixing time, American Petroleum Institute gravity (API gravity), pH, temperature, and oil concentration, on the percentage of oil removal and the removal capacity (mg/g) were studied. In this paper, six types of Fe3O4 magnetic nanoparticles (A:50 nm, B:15–20 nm, C:3 nm) and functionalized NH2/-COOH (A1:20–30 nm, B1:15–20 nm and C1:3 nm) were used as oil adsorbent. The highest percentage of oil removal was reached at 20 min, using 150 mg/L oil concentration, 100 mg adsorbent dose, room temperature, 28 API, and at 4 pH, and the results were 60 % (A), 72 % (B), 81 % (C), 85 % (A1), 88 % (B1) and 94 % (C1). Functionalized Fe3O4 nanoparticles exhibited higher reusability than uncoated MNPs (A-C). The results showed that Fe3O4 were highly effective, reusable, and suitable for oil removal from the oil-water emulsion. Kinetic models fit effectively with pseudo-second-order mode, and Freundlich model. This work also matches the research conducted by various researchers for oil removal from oily water using magnetic nanoparticles.

A modified isooctane‐based DNA extraction method from crude oil

AbstractMicrobes from oil reservoirs shape petroleum composition through processes such as biodegradation or souring. Such processes are considered economically detrimental and might pose health and safety hazards. It is therefore crucial to understand the composition of a reservoir's microbial community and its metabolic capabilities. However, such analyses are hindered by difficulties in extracting DNA from such complex fluids as crude oil. Here, we present a novel DNA extraction method from oils with a wide American Petroleum Institute (API) gravity (density) range. We investigated the ability to extract cells from oils with different solvents and surfactants, the latter both nonionic and ionic. Furthermore, we evaluated three DNA extraction methods. Overall, the best DNA yields and the highest number of 16S rRNA reads were achieved with isooctane as a solvent, followed by an ionic surfactant treatment using sodium dodecyl sulfate and DNA extraction using the PowerSoil Pro Kit (Qiagen). The final method was then applied to various oils from oil reservoirs collected in aseptic conditions. Despite the expected low cell density of 101–103 cells/ml, the new method yielded reliable results, with average 16S rRNA sequencing reads in the order of 41431 (±8860) per sample. Thermophilic, halophilic, and anaerobic taxa, which are most likely to be indigenous to the oil reservoir, were found in all samples. API gravity and DNA yield, despite the sufficient DNA obtained, did not show a correlation.

Relative compatibility index for evaluation of the compatibility of crude oil blends

A new relative compatibility index is proposed to evaluate the compatibility of blends of crude oils. The approach considers the calculation of solvent power of individual crude oil and their blends, the critical solvent power for blends of crude oils with required amount of n-heptane when precipitation of asphaltenes begins, and a graphical comparison of both parameters (solvent power and critical solvent power) to determine the maximum proportion of crude oils in the blend to avoid incompatibility problems. The proposed method requires experimental data that are commonly available, such as specific gravity, TBP (True Boiling Point) distillation, and S-value (fuels stability determination according ASTM D 7157). Eight crude oils with a wide range of API (American Petroleum Institute) gravity (10–52°) were used to validate the method. It was demonstrated that the proposed approach accurately predicts the compatibility of blends of crude oils, and that relative compatibility index is an effective parameter to define appropriate amounts of crude oils to avoid asphaltenes precipitation during blending.

Preparation of Fe‐based magnetic‐core‐supported Co and Ni catalyst: application in viscosity reduction of heavy oil hydrocracking

AbstractBACKGROUNDHeavy oil has the characteristics of high viscosity and low American Petroleum Institute gravity, which makes it difficult to transport and produce. The key to efficiently utilizing heavy oil is reducing viscosity and improving quality. Hydroconversion has the advantages of viscosity reduction and decreased coke production, but it is difficult to separate nonmagnetic catalysts from the reaction system, which affects the industrial application.RESULTSA spherical Fe3O4 (74.71 emu g−1) and a chain FeFe2O3 (110 emu g−1) were prepared as magnetic cores, and coated with SiO2 and Al2O3 layers, respectively. The metal‐supported catalyst modified with Co and Ni show irregular and honeycomb‐shaped surfaces, and the magnetic saturation strength decreases to 24.91 and 14.63 emu g−1, but still possessing superparamagnetic properties, enabling the catalysts to be separated from the reaction mixture. Fe‐Fe2O3@SiO2@Al2O3@CoNi catalyst has the best viscosity reduction effect for Canadian oil sands asphalt residue at about 410 °C and 10 MPa hydrogen pressure. The viscosity of the liquid product decreased significantly from 56 600 to 135 mPa s at 50 °C, with a viscosity reduction of 99.8%.CONCLUSIONMagnetic catalyst prepared from chain‐like Fe‐Fe2O3 has an excellent honeycomb structure, which can provide increased active surfaces and exhibit improved viscosity reduction performance. This work provides a strategy for the recovery of heavy oil hydrogenation catalysts and is expected to play a key role in the practical application of heavy oil hydrogenation catalytic viscosity reduction. © 2023 Society of Chemical Industry.

Thermal cracking of Al-Dora asphalt for the simultaneous production of light fuel and activated carbon for desulfurization process

Thermal cracking of an Iraqi asphalt, namely Al-Dora asphalt, at multiple temperatures for various durations was first achieved. The main target of this investigation was to produce an upgraded liquid fuel and microporous activated carbon. The thermal pyrolysis of asphalt was carried out in the temperature range of 400–600 °C for different durations (30–150 min) at a 20 °C/min heating rate. The maximum liquid fuel yield (51.55%) was produced at 450 °C for 1 h. This treatment process raised the American Petroleum Institute (API) gravity of the original asphalt from 3.26 to 34.54, while its viscosity was reduced from 422.0 mm2.s−1 to 3.76 mm2.s−1. Analysis of the produced liquid fuel by 1H NMR spectroscopy,13C NMR spectroscopy, and GC-MS disclosed that it was a mixture of n-paraffins (57.05%), isoparaffins (12.68%), and alkenes (30.27%) with a C6 and C19 carbon distribution. The physical and chemical features of the liquid were also determined following ASTM procedures, and the outcomes revealed that the produced liquid fuel had preferable properties to that of the authentic asphalt, suggesting its suitability as an alternative to diesel fuel. The coke produced after thermal pyrolysis of Al-Dora asphalt was successfully converted into active carbon (AC) via the optimized KOH-activation route, and the selected AC was prepared using a 2:1 KOH: coke impregnation ratio at 750 °C for 1 h. The AC was characterized by various techniques, including BET surface area and pore volume, X-ray diffractometry (XRD), field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray analysis (EDX), and infrared spectroscopy (FTIR). The total acid and basic surface groups besides the pHPZC of the AC were also determined. The adsorption efficiency of the as-obtained AC was tested in the adsorptive desulfurization process. For this target, dibenzothiophene (DBT) in n-hexane was selected as a model fuel. The AC showed an excellent efficiency of 99.33% for eliminating DBT from a model fuel containing 500 mg/L DBT using 0.35 g of AC at 40 °C for 30 min. Moreover, the removal of S- compounds from commercial gasoline using the AC under typical experimental conditions reached 65.12%. The adsorption of DBT by the produced AC offered an excellent fitting for Freundlich isotherm and the pseudo-2nd-order kinetics model. Finally, the regenerated AC demonstrated its ability to eliminate DBT up to the 6th reuse cycle efficiently.

Application of robust principal component analysis–multivariate adaptive regression splines for the determination of °API gravity in crude oil samples using ATR-FTIR spectroscopy

The robust principal component analysis-multivariate adaptive regression splines (r-PCA-MARS) has been applied and verified for analysis of the quantitative determination of American Petroleum Institute (°API) gravity values in crude oils. Seven principal component (PC) scores using 95.00% variance by principal component analysis (PCA) were applied as inputs in the MARS model. The calibration and prediction sets were obtained using duplex algorithm for the construction of the model and the then for the validation of the model. The calibration set (67*7) was used for the r-PCA-MARS model. The partial least squares regression (PLS-R), and support vector machine regression (SVM-R) models were utilized for comparison the quantitative value of the °API gravity in crude oils. In this paper, we also conducted a comparison study of Kennard-stone (KS) and duplex splitting methods on PLS-R and SVM-R models. The efficiency of the r-PCA-MARS model was evaluated using coefficient of determination (R2), R2 estimated by generalized cross-validation (R2GCV), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and mean absolute error (MAE). The optimal r-PCA-MARS model uses 32 basis functions to characterize the °API gravity values in crude oils. The correlation coefficients value for calibration and prediction sets were 0.997 and 0.926, respectively. The RMSEC, RMSEP, MAE, and R2GCV in the piecewise-cubic r-PCA-MARS model was 6.726*10-13, 0.538, 0.290 and 0.988, respectively. According to the results, the r-PCA-MARS model provided high efficiency than commonly used regression models for prediction of °API gravity values in crude oils. The result of this study confirmed that the r-PCA-MARS model is the best model with more successful than the PLS-R and SVM-R models. It can be concluded that the r-PCA-MARS model is an appropriate model for describing the physicochemical properties of crude oil samples in the oil industry.

Co-liquefaction of faecal sludge and water hyacinth: Exploring the fuel characteristics of biocrude including thermal maturation and petroleum fractionation

Today's world is facing a great economic crisis due to the increasing rate of fuel prices as well as irreversible depletion of it has gained major concern regarding future energy security. To mitigate such a problem this study investigated co-liquefaction (co-HTL) of faecal sludge (FS) and water hyacinth (WH) at varying FS to WH ratios (3:1, 1:1, 1:3) for biocrude production. The maximum biocrude yield was 33.47% with a higher heating value (HHV) of 29 MJ kg−1 and an energy recovery (ER) rate of 70.11% for a 1:1 ratio. The comprehensive characteristics of co-HTL biocrude showed 61.84%, 10.16%, 25.23%, 2.37%, 0.39% of C, H, O, N, S, and the highest HHV of 30.88 MJ kg−1 for 1:3 ratio. Co-liquefaction significantly improved the H/C ratio and ER of biocrude. The thermal maturation properties showed biocrudes were mainly immature quality with highly oil-prone which implies predominant hydrocarbon potential. The American Petroleum Institute (API) gravity analysis based on FTIR revealed that biocrudes were heavy type oil due to higher specific gravity (≥1). GC-MS results demonstrated that biocrude contained fatty acids, ester, alcohols, hydrocarbons, phenol, and ketone. The petroleum fractionation of co-HTL (1:1) biocrude showed a tendency to produce kerosene-like fuel. An economic valuation was predicted that through the co-HTL maximum of 6.39 bbls Mt−1 of biocrude could be produced according to the 1:3 mixing ratio of biomass which could revenue $ 683.73. The energy balance analysis suggested that the co-HTL of FS and WH is an energetically viable and economic system.

Biosurfactant Production from the Biodegradation of n-Paraffins, Isoprenoids and Aromatic Hydrocarbons from Crude Petroleum by Yarrowia lipolytica IMUFRJ 50682

Yarrowia lipolytica is a unique, strictly aerobic yeast with the ability to degrade efficiently hydrophobic substrates. In the present work, we evaluated the degrading potential of Yarrowia lipolytica IMUFRJ 50682, isolated from tropical estuarine water in Rio de Janeiro (Brazil), and the possible biomolecules produced during this process. To investigate which crude oil compounds are degraded by Y. lipolytica IMUFRJ 50682, this microorganism was grown in a medium containing Marlim petroleum (19 °API, American Petroleum Institute gravity) at 28 °C and 160 rpm for 5 days. The residual petroleum was submitted to gas chromatograph-mass spectrometric analysis (GC-MS). The chromatographic fingerprints of the residual petroleum were compared with the abiotic control test incubated in the same conditions. Y. lipolytica assimilates high molecular weight hydrocarbons, such as n-alkanes (C11-C19), isoprenoids (pristane and phytane), aromatics with two or three aromatics rings (naphthalene, methylnaphthalenes, dimethylnaphthalenes, trimethylnaphthalenes, phenanthrene, methylphenanthrenes, dimethylphenanthrenes, anthracene). This strain was also capable of consuming more complex hydrocarbons, such as tricyclic terpanes. During this biodegradation, the emulsification index of the culture medium increased significantly, showing that biosurfactant molecules can be produced from this process. Therefore, Y. lipolytica IMUFRJ 50682 showed to be a potential crude oil degrading yeast, which can be used for bioremediation processes and simultaneously produce bioproducts of commercial interest.

Characterization of the Different Oils Obtained through the Catalytic In Situ Pyrolysis of Polyethylene Film from Municipal Solid Waste

Nowadays, the thermal and catalytic decomposition of plastic wastes by pyrolysis is one of the best alternatives to convert these wastes into quality fuel oils, thus replenishing some petroleum resources. This work studied the catalytic pyrolysis of polyethylene film waste from the remaining organic fraction on different catalysts under dynamic operating conditions in a batch reactor. These catalysts have been characterized through isotherms of adsorption-desorption with N2 and X-ray powder diffraction for structural characterization to see the differences in their use. The results obtained have been compared with the pyrolysis of the same material without a catalyst. Special attention has been paid to the similarities and differences with thermal pyrolysis. The characterization of the liquid fraction, including physical and chemical properties, has been carried out. The liquid yield varies from 37 to 43%; it has good calorific values of 46–48 MJ/kg, an average density of 0.82 g/cm3, and a fairly low viscosity compared to the product without the catalyst. Other properties like the American Petroleum Institute (API) gravity or pH were also determined and found to be similar to conventional fuels. Oils are mainly composed of paraffins, naphthenes, and aromatic hydrocarbons. The general distribution of carbons is C7 to C31. Finally, a detailed analysis of the composition of liquid products shows they present heavy naphtha, kerosene, and diesel fractions in different proportions in the function of the catalyst used.

Optimization of Distribution Control System in Oil Refinery by Applying Hybrid Machine Learning Techniques

In this research, prediction of crude oil cuts from the first stage of refining process field is laid out using rough set theory (RST) based adaptive neuro-fuzzy inference system (ANFIS) soft sensor model to enhance the performance of oil refinery process. The RST was used to reduce the fuzzy rule sets of ANFIS model, and its features in the decision table. Also, discretisation methods were used to optimise the continuous data’s discretisation. This helps to predict the two critical variables of light naphtha product: Reid Vapor Pressure (RVP) and American Petroleum Institute gravity (API gravity), which detect the cut’s quality. Hence, a real-time process of Al Doura oil refinery is examined and the process data of refining crude oil from these two sources improve the knowledge provided by the data. The response variables represent the feedback measured value of cascade controller in the top of the splitter in crude distillation unit (CDU) in the rectifying section, which controls the reflux liquid’s flow towards the splitter’s head. The proposed adaptive soft sensor model succeeded to fit the results from laboratory tests, and a steady-state control system was achieved through an embedded virtual sensor. The predictive control system has been employed using cascade ANFIS controller in parallel with the soft sensor model to keep the purity of the distillate product in the stated range of the quality control of oil refinery. The results obtained from the proposed ANFIS based cascade control have no over/undershoots, and the rise time and settling time are improved by 26.65% and 84.63%, respectively than the conventional proportional-integral-derivative (PID) based cascade control. Furthermore, the results of prediction and control model are compared with those of other machine learning techniques.

Microseepage through evaporite sequences — A Gulf of Suez example

Salt is one of the most effective agents for trapping oil and gas. As a ductile material, it can move and deform surrounding sediments and create traps. However, effective sealing of reservoirs for movement of hydrocarbons along breaching faults or fracture swarms (i.e., macroseepage) is a different mechanism than the movement of hydrocarbons on a molecular scale along grain boundaries and microfractures as happens with microseepage. To address salt seal integrity, Forum Exploration has chosen to evaluate the applicability of passive surface geochemical surveys for mapping hydrocarbons in their onshore West Gebel El Zeit lease in part due to difficulties in seismic imaging through salt and anhydrite sequences. Two economic producing wells have been drilled in the lease, but due to compartmentalization and complexity in the area, three dry wells also have been drilled. Target formations include the Kareem Formation at approximately 2700 m and the Rudeis Formation at approximately 3000 m. The geochemical survey encompasses 100 passive geochemical modules. Passive samplers also have been deployed around two producing wells and one dry well for geochemical calibration. Calibration data indicate positive thermogenic signatures around the two producing wells in contrast to the background or baseline signature from around the dry well. The Kareem Formation calibration signature ranges from approximately C6 to C12 with the Rudeis Formation calibration signature ranging from C5 to C9. This suggests that the Rudeis calibration signature is lighter than the Kareem, in agreement with independent measurement of American Petroleum Institute (API) gravity on produced oil samples (API gravity 41° oil for the Rudeis and 35° oil for the Kareem). A postsurvey well, Fh85-8, has been drilled based on combined geochemical and seismic data results. The well is a Kareem oil discovery, with an initial production of approximately 800 barrels of oil per day. We have developed evidence in this Gulf of Suez example to show that microseepage occurs through substantial salt sequences. Consequently, ultrasensitive passive surface geochemical surveys provide a powerful tool for derisking salt plays.

Production of light oil-prone biocrude through co-hydrothermal liquefaction of wastewater-grown microalgae and peat

Bioenergy production from biomass through thermochemical conversion is an emerging technological advancement that can offset the use of fossil fuels and reduce greenhouse gas (GHGs) emissions. This study investigated novel co-hydrothermal liquefaction (co-HTL) using peat (P) and wastewater-grown microalgae (MA) for enhancing biocrude production as waste to energy approach. The operating conditions were: temperature- 300 ºC, biomass loading- 10 mL, and reaction time- 60 min. The improvement of biocrude yield was investigated using three co-HTL ratios of P and MA (75:25, 50:50, 25:75) and compared with two individual biomass HTL. Between individual HTL of P and MA sample, MA sample yielded higher biocrude (31 wt%) than P sample (26 wt%). In addition, the highest higher heating value (HHV) of 35.8 MJ/kg and energy recovery of 59.8% were observed for individual HTL of the MA sample. However, the highest biocrude yield (36.6 wt%) was observed for co-HTL of 50:50 ratios with a biomass conversion rate of 54.7 wt% and HHV of 32 MJ/kg. Fourier-transform infrared (FTIR) spectroscopy detected alcohol, phenolic, and ester compounds in the biocrude samples. All of the biocrude samples were mainly premature quality with kerogen type I (highly oil-prone). The co-HTL biocrude samples exhibited heavy to medium type oil based on American Petroleum Institute (ºAPI) gravity analysis. The elemental analysis showed that the H/C ratio of biocrude samples was within 1.5–2.0, similar to Petro-crude quality. Gas chromatography flame ionization detection (GC-FID) analysis confirmed that the co-HTL biocrude had higher lighter fraction oil than HTL. Energy balance analysis revealed that the system was energetically feasible, and net energy gain significantly improved during co-HTL. The overall assessment summarized that a positive synergistic effect was achieved during co-HTL of P and MA on the improvement of the biocrude yield and quality.

Application of Different Vegetable Fibers as Natural Sorbents and Their Use in Water Decontamination from Crude Oil

AbstractThe petroleum sorption capacities of plant fibers from Eucalyptus sp., Bambusa tuldoides, and sugarcane bagasse fibers were investigated as innovative and low‐cost alternatives from renewable sources. Characterization of the fibers was performed according to their morphological aspects and physicochemical characteristics. The oil used was classified according to its American Petroleum Institute (API) gravity, viscosity, and density. Sorption tests performed with crude oil mixed with deionized water in a static or agitated system revealed maximum sorption capacities of the fibers in the range of 5.08–5.87 g g−1. The biosorbent based on eucalyptus fibers is a promising material for the cleaning of oil spills in water bodies as it is the most hydrophobic material. Sugarcane bagasse and bamboo gave good results for oil sorption applications in the absence of water, validating their use as well.

Basin-wide rock-physics analysis in Campeche Basin, Gulf of Mexico — Phase II: Reservoir rock and fluid properties

We present a basin-wide rock-physics analysis of reservoir rocks and fluid properties in Campeche Basin. Reservoir data from discovery wells are analyzed in terms of their relationship between P-wave velocity, density, porosity, clay content, Poisson's ratio (PR), and P-impedance (IP). The fluid properties are computed by using in-situ pressure, temperature, American Petroleum Institute gravity, gas-oil ratio, and volume of gas, oil, and water. Oil- and gas-saturated reservoir sands show strong PR anomalies compared to modeled water sand at equivalent depth. This suggests that PR anomalies can be used as a direct hydrocarbon indicator in the Tertiary sands in Campeche Basin. However, false PR anomalies due to residual gas or oil exist and compose about 30% of the total anomalies. The impact of fluid properties on IP and PR is calibrated using more than 30 discovery wells. These calibrated relationships between fluid properties and PR can be used to guide or constrain amplitude variation with offset inversion for better pore fluid discrimination.

Size exclusion chromatography of petroleum samples using amino-bonded silica phase

Amino-bonded silica phase, frequently used in adsorption chromatographic mode for petroleum analysis, was evaluated for the separation of petroleum components based on polymer liquid chromatographic modes (viz. size exclusion, critical condition, and interaction). After verification of the stationary phase for polymer chromatography using polystyrene standards at different compositions of cyclohexane and dichloromethane, a similar approach was attempted for a distilled fraction of a crude oil. The approach was successful in size exclusion chromatographic mode whereas other modes were partially achievable because of the complex nature of petroleum samples. Subsequently, size exclusion mode was applied in crude oils with different American Petroleum Institute (API) gravity values. An inverse linear relationship between the API gravity value and the average molecular weights of the aromatic compounds of crude oils was established. It was found that the weight average molecular weight (Mw) was more sensitive to changes in API gravity values of the crude oils in comparison to number average molecular weight (Mn). Additionally, crude oil with lower API gravity value reflected broader distribution of species. Further studies on crude oils with lower API gravity value (<20°) and of different geographical origins will confirm the universality of the method. This method will provide reliable average molecular weights of the aromatic content for aromatic rich refinery streams to optimize process conditions. Furthermore, the developed method can potentially be extended to a two-dimensional LC method using the same stationary phase with different mobile phase compositions for comprehensive characterization of petroleum samples.

Study on waxy crudes characterisation and chemical inhibitor assessment

Wax deposition brings severe challenges to the production, transportation, and storage of crude oils. Accumulation of wax can block the pipeline, lead to equipment failure, and lose production. The use of chemical inhibitors has been reported as one of the most effective measures to mitigate wax deposition in the pipeline. The inhibition efficiency depends on the effects of the inhibitor molecules on the formation, growth, agglomeration and morphology of wax crystals. The chemicals and their compositions in the inhibitor together with the crude composition determine wax inhibition performance. Many different types of chemical inhibitors have been developed. Oil industry benefits significantly from high-efficiency inhibitors. This paper reported a simple method to optimise the inhibition performance by blending different inhibitors. Firstly, a comprehensive characterisation of two naturally waxy crude oils (KSG#49 and Ex Mwambe) and a synthetic crude oil was presented. The synthetic crude oil was prepared by mixing a dead oil of 3% wt wax content with a solid wax sample obtained from the North Sea field. The variation in properties of the three oils was evaluated through cloud point measurements, pour point, wax content, SARA fractions, colloidal instability index, American Petroleum Institute gravity (APIg), and the n-Paraffin distribution. Then, the influence of four Polymer-based pour point depressants (PPDs) on wax crystallization were critically assessed. The PPDs induced morphological changes to wax crystals transformed the needle-shaped crystals into an agglomerate. The small particles dispersed in the oil matrix reduced the apparent viscosity and wax gelling properties, and the efficiency of PPDs could be affected by the SARA fraction. A higher fraction of flocculated asphaltenes provides active sites for wax crystallization. Hence it increases cloud point and interferes with the crystal inhibition mechanism. Finally, a blended PPD produces a synergistic effect on inhibition performance that effectively reduces apparent viscosity, wax appearance temperature (WAT) and pour point (PP). The improvement can be attributed to the interactions between the molecules of wax inhibitors with wax crystals. This works sheds light on new inhibitor development by blending different inhibitors to promote performance synergies. • The properties of three waxy crude oil were thoroughly characterised by defined methods. • The effectiveness of polymer based chemical inhibitors on wax crystallization was investigated through viscometric analysis and morphological characterisation. • The synergistic effect as a result of blending different inhibitors leads to the improved efficiency of a new inhibitor.

Species Identification and Effects of Aromatic Hydrocarbons on the Fluorescence Spectra of Different Oil Samples in Seawater

The identification of oil species and their characteristics in oil spills is particularly important for their efficient disposal. Since aromatic hydrocarbons (AHs) with various characteristics are the major fluorescent components of oils in seawater, they can be used to detect different oil species in seawater. Here, we developed a composition method using the fluorescence spectra of eight AH categories analyzed by gas chromatography-mass spectrometry (GC-MS) to evaluate the contribution of AHs to the total fluorescence of six different oil species. Qualitative and quantitative difference analysis of the experimental and composite fluorescence spectra was performed based on the redshift of the main peak position, the fluorescence intensity distance, and the generalized included angle cosine, while correlation analysis was used to establish the relationship between the different fluorescence spectral parameters and the American Petroleum Institute gravity and viscosity of the oil species. The fluorescence spectra recorded for heavy oil samples indicated a reduction in the fluorescence signal of fluorene series and an increase in the contribution of acenaphthene and pyrene series, indicating that the currently developed composition method by fluorescence spectroscopy combined with GC-MS can be used to distinguish and identify oil species in seawater samples.