In the second part of this series, we introduce the mathematical model for the growth kinetics of gas hydrates in oil continuous flow. Mathematical description of the capillary filling-up process is given (porosity evolution), coupled with growth phenomena already described in the literature (gas absorption by the oil bulk, mass transfer particle/bulk, outer growth due to permeation). The range of closure parameters reported in the literature for CH 4 hydrates is used to understand the limiting steps of crystallization, the evolution of porosity being the controlling factor in the asymptotic trend of the gas consumed over time. Furthermore, gas absorption by the bulk and mass transfer particle/bulk is shown to be negligible for oil-continuous flow when considering a gas that is much more soluble in oil than in water. The model is simplified for engineering purposes, giving rise to an explicit semi-empirical equation for the gas consumption rate because of hydrate formation based on two independent parameters that are experimentally regressed. A criterion for the existence of wet or dry particles (the water layer covering the particles in oilcontinuous flow) is proposed in means of the competition of crystal integration in the outer surface versus water permeation through the porous hydrate.

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A new topological model on how gas hydrates form, grow, and agglomerate for oil and water continuous flow, with and without surfactant additives, is presented. A multiscale approach is used to explain how the porous structure of gas hydrates and the affinity between the phases affect the particle morphology and their agglomeration. We propose that gas consumption due to hydrate growth happens mostly in the water trapped inside the capillaries of the hydrate structure near the outer surface of the particles. This approach is herein referred to as the “sponge approach” and is treated as a surface problem, instead of the volume problem often treated in literature (the “shell approach”). Affinity between phases (which in a macro point of view is interpreted as a wetted angle that gives rise to capillarity forces and that can be changed by the use of surfactant additives) describes the preferential entrapment of oil or water inside the hydrate sponge structure. Yet by splitting agglomeration into smaller processes and depending on the morphology of the particles and on the evolution of the porous structure of the hydrates, (i) capillarity bridges may form, causing particles to be sticky, and (ii) water may be available at the outer surface of the particles and may promote consolidation of particle–particle (agglomeration) or particle-wall (deposition). The settling of slurries is treated as a separated solid–liquid flow instability problem once mixture deceleration (due to phase consumption during crystallization) and particle size (due to growth and agglomeration) are known. We also propose a new explanation on how surfactants act as anti-agglomerants in oil continuous flow, differently from the common DLVO theory used in literature, which can only explain anti-agglomeration of particles much smaller than the ones formed over droplets of a very fine dispersion flow.

Three-phase gas–liquid–liquid flows are very common in petroleum extraction, production, and transport. In this work a dual-modality measuring technique is introduced which may be well applied for three-phase flow visualization. The measuring principle is based on simultaneous excitation with two distinct frequencies to interrogate each crossing point of a mesh sensor, which in turn are linked to conductive and capacitive parts of fluid impedance. The developed system can operate eight transmitter and eight receiver electrodes at a frame repetition frequency up to 781 Hz. The system has been evaluated by measuring reference components. The overall measurement uncertainty was 8.4%, which considering the fast repetition frequency of measurements is suitable for flow investigation. Furthermore, a model-based method to fuse the data from the dual-modality wire-mesh sensor and to obtain individual phase fraction of gas–oil–water flow is introduced. Here a parametrized model is fitted to the measured conductivity and permittivity distributions enabling one to obtain phase fraction from measured data. The method has been applied and tested to the acquired data from a mesh sensor in static and dynamic three-phase mixtures of gas, oil, and water. Fused images and quantitative values show good agreement with reference values. The newly developed dual-modality wire-mesh sensor has the potential to investigate three-phase flows to a good degree of detail, being a valuable tool to investigate such flows.

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Flow assurance is a critical component in the design and operation of robust oil/gas production systems. Undesired precipitation of solids (gas hydrates, wax, asphaltenes, scale) reduces the production rate and often leads to costly and hazardous disruptions. Many experimental and modeling efforts have been made to build knowledge of managing such risks. However, a major difficulty is to transfer the laboratory data to the field conditions. We introduce a new experimental system, the rock-flow cell, which is compact and requires fewer resources to build and operate. This system can readily achieve different flow regimes by controlling the liquid loading, water cut, and rocking angle/speed. A sight glass visualizes when, where, how, and how much solid forms and precipitates out. Gas hydrate formation tests with anti-agglomerants are presented to demonstrate the capabilities. The rock-flow cell is an innovative testing tool for flow assurance studies by properly capturing thermohydraulic conditions in actual flowlines.

In the third part of this series, we introduce the mathematical model for the agglomeration of gas hydrate in oil continuous flow. The aim is to develop an expression for the agglomeration efficiency that considers the existence of a wet or a dry particle. If the particle is wet, then water is available at its outer surface, thus allowing the formation of a liquid bridge that holds the aggregate together.The criterion for a wet or dry particle was developed in part II of this series and comes from the competitions between water permeation through the porous hydrate particle, and water consumption caused by crystallization in the particle's outer surface. The new expression for the agglomeration efficiency is coupled with a population balance solved through the Method of Moments and considering simple expressions for the collision rate and the shear rate induced by the flow coming from Smoluchowski's and Kolmogorov's theory, respectively. When compared to experimental data, the model stays within the ±40% deviation range and shows capable of predicting smaller agglomerate size for higher subcooling and lower interfacial properties (use of surfactant additives).The influence of subcooling into changing the porous medium parameters (especially the porous medium interconnectivity) shows to be important into the determination of the time taken for the particle to dry out. The model is simplified for engineering purposes considering gases much more soluble in oil than in water (hydrocarbon gases) in oil-continuous flow, and a simple criterion is proposed to predict if the system behaves as dispersed (slurry) or if it agglomerates after the onset of hydrate formation.