Oil refineries are among the most complex of processing sites, requiring the combination of many, entirely different, physical and chemical processes. Since the product from one process will provide the feed for another, consecutive process, differences in crude oil composition from various locations impact the production capacity of the entire refinery.
It is thus critical to ensure the characteristics of the crude oil are monitored continually. Real-time adjustment and fine-tuning of process conditions is critical to achieving maximum production efficiency and product yield.
A key parameter is the viscosity of the oil, and so this is a frequently monitored characteristic1.
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The value of heavy oils
There is a wide range of different types of crude oil that are largely categorized according to their viscosity. Light oil has the lowest viscosity and higher viscosity crude oils are referred to as heavy oil or extra-heavy oil. This characteristic is also used as a determination of oil quality and value.
Conventional light oil can typically be produced at a high rate and a low cost and consequently it has been targeted in preference to other types of oil. Heavy and extra-heavy crude oils have also been important hydrocarbon resources, but now there are increasing efforts to develop new technologies to optimize the production of heavy oils as many areas of conventional oil have been exhausted2.
An increasingly popular strategy for enhancing oil recovery methods is the addition of polymers and nanoparticles3. It is thus important that the effects of such additives can be effectively monitored.
Physical characterization of heavy crude oil is routine for monitoring fluid properties. However, although it is relatively easy to obtain bulk measurements of viscosity, monitoring of the fluid response on a microscale (microrheology) is becoming increasing desirable. Microrheology provides a more direct reflection of fluid microstructure, and this might be more readily relatable to interactions with colloids and nanoparticles.
Time-domain or low-field nuclear magnetic resonance (TD-NMR) spectroscopy has proved to be an effective and efficient mean of assessing microrheological properties of crude oil.
Time-domain nuclear magnetic resonance spectroscopy
Nuclear magnetic resonance (NMR) is a powerful non-destructive analytical tool based on the excitation of nuclei through exposure to a magnetic field. By measuring the return of the nuclei to their base energy level, it provides detailed information about the structure, dynamics, reaction state, and chemical environment of molecules. There are many variations of the technique, each suited to specific applications.
TD-NMR is a relaxometry analysis suited to the determination of fluidity. It measures the time required for the nuclei to return to equilibrium after excitation. It provides data rapidly and with high reproducibility without the need for sample preparation.
NMR relaxation characteristics alter with changes in viscosity; heavy crude oils relax faster than light or medium gravity oils. Partial least squares regression (PLSR) models have also been developed to predict oil viscosity from transverse relaxation time (T2) distributions and diffusion coefficients estimated from NMR4.
Assessing the effects of nanoparticles on heavy oil
Recently, it was shown that the addition of nanoparticles to heavy- and extra-heavy crude oils reduced their viscosity. Furthermore, this effect was found to result from the nanoparticles altering the internal structure of the heavy crude oil5.
Since the addition of nanoparticles considerably alters the internal behaviour of crude oil, this should be reflected in altered NMR measurements. It was thus inferred that NMR should be able to monitor the microrheological properties of crude oil. Analysis of the molecular interactions between crude oil and nanoparticles should correlate with bulk viscosity or other rheometric measurements.
This hypothesis was tested recently by evaluating the effect of silica nanoparticles on the microrheological properties of heavy- and extra-heavy crude oils using TD-NMR techniques6. This is the first time that these characterization tools have been used in heavy crude oils in the presence of nanoparticles.
Three heavy crude oils with different asphaltene contents were studied using NMR. T2 relaxation and diffusion coefficient measurements were used as probes of microrheological effects on the crude oil. T2 relaxation time was measured using a Bruker Minispec LF110 spectrometer. NMR measurements of the diffusion coefficient for hydrocarbon molecules in the presence or absence of nanoparticles were conducted using an NMR Minispec Bruker mq20 with a gradient coil delivering a maximum gradient strength of 4 T/m.
The refractive index of the heavy oil decreased on addition of the nanoparticles, confirming adsorption of polar material to the nanoparticles. The T2 and the diffusion coefficient were found to increase around the optimal concentration of nanoparticles and decrease at higher concentrations. The improved NMR responses, which reflect the enhanced translational and rotational motion of restricted hydrogen-bearing oil molecules, proves that microrheological changes occur as oil polar molecule aggregates break down due to the adsorption of asphaltenes.
There was an inverse correlation between either the log-mean T2 or the diffusion coefficient and the rheometric oil viscosity in the presence of nanoparticles6. Viscosity was reduced by 35–45% in each of the three heavy crude oils.
The authors estimated that the optimal concentration of nanoparticles for reducing the viscosity of heavy crude oil was around 1000 mg/L.
References
- Ghannam MT, et al. J Pet Sci Eng 2012;81:122–128.
- Williams B. Oil Gas J 2003;101(29):20–20.
- Kamal MS, et al. Journal of Nanomaterials 2017; volume 2017, Article ID 2473175
- Wen Y, et al. Estimation of diffusion coefficients in bitumen solvent mixtures as derived from low field NMR spectra. Canadian International Petroleum Conference Petroleum Society of Canada 2003
- Taborda EA, et al. Fuel 2017;189:322–333.
- Wang H, et al. Fuel 2019;241(1):962-972. https://www.sciencedirect.com/science/article/pii/S0016236118321677
This information has been sourced, reviewed and adapted from materials provided by Bruker BioSpin - NMR, EPR and Imaging.
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