Niger Delta Crude Oil Research Articles

Evaluation of the Effects of Alcohol on De-Emulsification of Niger Delta Crude Oil Using Commercial De-Emulsifiers

This research work evaluates the effects of alcohol on de-emulsification of Niger Delta crude oil using RP6000 and Chimec 2439 as de-emulsifiers. The laboratory measurements were carried out as per API standard. Stable emulsion was prepared using brine. The samples were de-emulsified. Methanol and ethanol were added respectively, with water and without water as modifiers. The measurements of the effect of adding alcohols on water separation efficiency were carried out using methanol to water ratio, M = 4:1 and ethanol water ratio, E = 4:1. The results show that solubility with alcohol is greater in emulsion than the solubility of alcohol without water. Some comparisons were also made based on the plots on percent water separation versus time for the two modifiers and de-emulsifiers. The maximum separation efficiency of 61% was obtained at concentration of 25% methanol, 75% RP6000, 20 ppm and Chimec 2439 gave maximum separation efficiency of 56.6% at concentration of 75%, 20 ppm at 120 minutes. Based on the results, methanol therefore gave larger effect on water separation efficiency than ethanol.

Assessment of aromatics to saturate ratios in three Niger Delta crudes

This study was designed to determine the aromatics to saturate ratios in three Nigerian Niger Delta crude oils to ascertain the crude oil source with the highest asphaltene risk. Three crude oil samples were collected from different locations: Kokori, Afiesere and Nembe in the Niger Delta region, Nigeria. The physical properties of the crudes (viscosity, density, API gravity) were determined. Saturates, aromatics, resins, asphaltenes (SARA) fractionation method was employed to separate different components in the crude oil. The composition and concentration of the saturates and aromatics hydrocarbon fractions were determined using a gas chromatograph. Results showed that API gravities ranged from 34° to 39° indicating that the three crudes are light. n-Heptane precipitation showed that Kokori crude had the highest weight percent concentration of asphaltenes (2.33%) and Afiesere crude, the least (1.91%). The gas chromatographic analysis of the saturates and aromatics showed that the total concentrations (mg/L) of all the saturates in Kokori, Afiesere, and Nembe were 871.26, 885.56, and 780.21 respectively while the total concentration of all the aromatics in the crudes were 80.15, 89.73 and 75.11 respectively. The aromatics to saturate ratios were computed and the results showed that this ratio decreased in the order Kokori crude<Nembe crude<Afiesere crude. This implies that Kokori crude with the lowest ratio will cause most asphaltene deposition problems than the other crudes.

Chemometric representation of molecular marker data of some Niger Delta crude oils

Chemometric representation of data is the most preferred and adopted method of research reporting in contemporary times. Data are easily discerned and interpreted. Molecular maker parameters of some crude oils from the Nigerian’s Delta region are chemometrically expressed after data treatment using multivariate statistical analyses, other graphical representations were the star diagram and triangular (ternary) plot. The results indicated discrimination of samples into two genetic families corresponding to their primary oil fields. These groupings were more obvious for results obtained via principal component analysis. Genetic groupings are principally due to compositional differences which are commonly attributed to unique source rock depositional environments and/or sourcing organic matter. The two families of oils identified have both terrestrial inputs, but differ comparatively by relative marine inputs.

Development of PVT Correlations According to Geography

An enormous number of pressure–volume–temperature (PVT) correlations have been developed over the years for different types of hydrocarbon systems. However, the accuracy of these correlations is often limited due to crude oil compositional difference, impurities, etc., from different geographical locations. The literature has revealed that the predictive capabilities of the previously developed PVT correlations for Nigerian crude oil system are still associated with large errors and as the accurate determination of the PVT properties is uncompromising, it is of great importance to develop new models for the Niger Delta region. In this study, we present new empirical PVT correlations for calculating bubble point pressure (Pb ) and bubble point oil formation volume factor (Bob ) using Niger Delta crude oil data based on multiple regression methods. Performance prediction based on statistical and graphical methods was carried out. The performance prediction results of the developed Pb and Bob correlations, when used to predict PVT data of crude oil system from different geographical locations, showed very high relative errors. This implies that in order to predict PVT data for a crude oil systems with high accuracy, local PVT correlations need to be developed.

Fuzzy Sequential Forward Search for Oil Formation Volume Factor Predictive Tool Factor for Niger Delta Crude Oil

Accurateprediction of fl uid properties is essentials for all reservoir engineering calculations such as estimation of reserves, well testing analysis and in numerical reservoir simulation. Oil formation volume factor is one of the properties that can either be gotten from empiric al or experimental method. This work focuses on the use of fuzzy sequential forward techniques to develop a oil formation volume factor model using 1,316 data obtained from 45 different oil fields in the Niger Delta, Nigeria. The data set was randomly divi ded into two parts with 750 used for training and 566 for testing. The model developed has the lowest Root Mean Square Error (RMSE) of 0.0784 when compared with published correlation used for prediction. The accuracy of the developed model was tested with cross plotand statistical analysis. The model developed outperformed the existing correlations when subjected to further statistical analysis . Research Article

Comparison of the Performance of Empirical Models Used for the Prediction of the PVT Properties of Crude Oils of the Niger Delta

A review of the literature has revealed the lack of a formal analysis of the performance of empirical methods for the prediction of pressure volume temperature (PVT) properties of Niger delta crude oils. This study presents an assessment of the predictive accuracy of five bubble-point pressure (P b ) correlations and five bubble-point oil formation volume factor (B ob ) correlations against a large measured PVT data bank from Niger Delta crude oils. Statistical analysis techniques were used to evaluate the performance and the accuracy of the commonly used empirical models for estimating PVT properties of Niger crude oil in order to guide designers and operators in selecting the best correlations for their particular applications. Agreement between calculated and measured P b and B ob values for the various models was very poor. The model predictions of P b and B ob can be different from the measured values by 56% and 242%, respectively. Development of improved models for predicting the PVT properties of Niger delta crude oils is urgently required.

Determination of rare earth elements in Niger Delta crude oils by inductively coupled plasma-mass spectrometry

A profile for rare earth elements (REE) of crude oils from the offshore – shallow water and onshore fields in the Niger Delta, analyzed by inductively coupled plasma-mass spectrometry (ICP-MS) is reported. The oil samples were prepared for ICP-MS measurement by acid digestion into colourless aqueous solution. The analysis method was validated using standard reference materials SLRS-4 and NIST-1640. Results showed percentage recovery values that ranged from 81.8% to 115.4% for Co, Cu, Fe, Mn, Ni, Sb and U and from 98.8% to 104.7% for Co, Cu, Fe, Mn, Ni and Sb. The magnitude of deviation recorded in SLRS-4 for Co and Fe suggests that it may not be a suitable standard for these elements using the ICP-MS method outlined in this study. The concentrations of the detected REE; La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Er and Yb ranged from 0.01 to 1.58 ppb with an average of 0.98 ppb (%RSD < 5) for the oil samples analyzed. Light REEs (LREE) were identified in all the oil samples while heavy rare earth elements (HREE) were identified in offshore oil samples only. LREE patterns constructed from chondrite-normalized values for the oils show some similarities among the oils, which suggest common origin of the oils and that the REE got into the oils from similar source. While those with different chondrite-normalized REE patterns suggest different source input of the REE. This indicates that REE will be a useful tool in oil–oil correlation. Statistical evaluation of these oils by cluster analysis using the REE as variables clearly discriminated according to their geographic sources. Biodegradation has pronounced effect on the concentration of REE in oils. Therefore, REE contents of oils will be useful in oil classification. ICP-MS proved to be a versatile method for the determination of rare earth elements in Niger Delta oils.

Characterization of Niger Delta Crude Oil by Infrared Spectroscopy

Characterization of Niger Delta Crude Oil by Infrared Spectroscopy

MODELING THE VISCOSITY-TEMPERATURE RELATIONSHIP OF NIGERIAN NIGER-DELTA CRUDE PETROLEUM

The viscosity-temperature relationship of Nigerian Niger-Delta crude oils has been modelled using a generalized viscosity correlation developed by Puttagunta et al. (1992) for conventional crude oils. The correlation requires only one viscosity measurement for prediction, and the data fitting makes use of a simple algorithms. Predictions with the correlation yielded results that matched the experimental viscosities accurately. The correlation was modified by deriving new values of shape-factor and asymptotic limit. The difference in the results obtained with the original and modified correlation is well within the acceptable limits of experimental error, as both matched the experimental data very well with overall average absolute deviations of 2.4% and 2.3%, respectively.