From Components to Phase-Dependent Dynamics of Diffusivity in Wax Solutions Subjected to Fluid–Solid Phase Transition: Insights from Pulsed Field Gradient NMR

Abstract

The evolution of solvent and solute diffusivity during fluid−solid phase transition was studied in model wax in ndodecane solutions in a wide concentration range. Studied systems were characterized using viscosity measurements to provide supplementary information related to wax precipitation onset, while diffusion coefficients of n-dodecane and paraffin molecules were quantified using Pulsed Field Gradient (PFG) NMR. It was revealed that above the wax appearance temperature (WAT), the Hayduk−Minhas equation adequately predicts the solute and solvent diffusivity. At lower temperatures (below the WAT), three distinct diffusive components appear, which no longer originate from individual molecular components but correspond to a liquid phase differing in terms of association to the wax crystal network. These diffusion components were concluded to contain dodecane and the residual dissolved wax; the major components among them correspond to fluid, which relatively freely diffuses between the wax microcrystals and experiences the hindrance due to the wax gel network, and the minor components correspond to the fluid closely associated with the wax crystals. Unlike at high temperatures, the Hayduk−Minhas equation was found to be unable to predict adequately the diffusivity below the WAT. Using Singh's approach, the aspect ratio of wax crystals was calculated for different temperatures and concentrations and its complex nonlinear behavior was observed. It turned out that none of the models available differentiate the fluids with respect to the wax crystal network that leaves out of modeling the diffusion components with reduced mobility. The results indicate that the intuitive paradigm of component-dependent dynamics of solvent and solute diffusivity should be changed to phase-dependent dynamics once the system turns into wax gel since the diffusion of separate components becomes the diffusion of separate phases. This understanding shows a new route to improving the wax deposition modeling, which will facilitate an increase of effectiveness of the remedial strategies in the petroleum industry.

Understanding the Effect of Asphaltenes and Wax Inhibitors on Wax Crystallization by Improved NMR Techniques

“…This was confirmed by the strongly reduced mobility of solvent molecules (toluene) in Figure and . Previously, a population of wax with intermediate mobility, i.e., mobility between that of liquid and solid wax, was identified below the WAT . Several possibilities for the origin of this population have been put forward: trapping of wax molecules between the interlocking wax crystals , (illustrated in Scheme , 1a), formation of pores within the precipitated wax crystal containing less mobile wax , (illustrated in Scheme , 2a), and an amorphous, softer layer of less mobile wax surrounding the wax crystals (illustrated in Scheme , 3a).…”

“…Previously, a population of wax with intermediate mobility, i.e., mobility between that of liquid and solid wax, was identified below the WAT . Several possibilities for the origin of this population have been put forward: trapping of wax molecules between the interlocking wax crystals , (illustrated in Scheme , 1a), formation of pores within the precipitated wax crystal containing less mobile wax , (illustrated in Scheme , 2a), and an amorphous, softer layer of less mobile wax surrounding the wax crystals (illustrated in Scheme , 3a). All these mechanisms need further verification but are nevertheless considered in the following discussion of how the presence of asphaltenes and PPD can alter the wax crystal network.…”

Modeling multicomponent wax deposition and aging on cold surfaces with application to pipeline fouling

“…The wax precipitation curves for the six-component wax mixture, WAT from the Coutinho model is 37 C, as shown in Figure 2, which is higher than the experimental cloud point of the mixture and higher even than the jacket temperature of the cold-finger apparatus. To keep the waxy oil temperature above the cloud point in the simulations and to provide a thermal driving force for the transport of wax from the oil to the deposit that is similar to that in the experiment, in equation 20 is reported in the literature to, in some cases, underpredict 26,27 and in others to overpredict 28 the bulk diffusivity of the wax, which affects both mass transfer coefficients and diffusivities in the deposit. Reasons given for this are that the Hayduk-Minhas empirical correlation 20 is developed based on binary solutions, and hence not necessarily suitable for multicomponent mixtures, and that the dependency of diffusivity on solvent viscosity is lower than the correlation predicts, especially for a more viscous solvent.…”

Dynamics of Asphaltene Aggregates under High-Pressure CO2 Revealed by Pulsed-Field Gradient NMR

“…Unfortunately, the air flow mode widely used in NMR probes for sample heating/cooling is highly prone to creating an inhomogeneous and unstable temperature distribution within the 5 mm NMR tube. To address this issue, a previously developed approach was used: 71 the temperature inside the probe was reached and then maintained by using the water circuit of the BCU 20 cooling unit, which provided superior temperature stability within the thick-walled quartz capillary (D in = 2 mm) and minimized the possible temperature gradients. Yet the comparatively narrow channel inside the sealed capillary hindered any potential convection processes.…”