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Slugging in wells result in operation issues such as increased average pressure drop, potentially increased sand production, increased loads on topside piping and increased separator control issues which can even lead to separator trips. These large amplitude slugging phenomena are well known from long horizontal flowlines (terrain induced slugging), and from flowline-riser systems (severe slugging). But also in wells these mechanisms can lead to large dynamic disturbances. On top of that, in wells often slugging is induced by area transitions such as at the end-of-tubing and due to system instabilities such as void waves. For both flowlines/risers and wells, slugging monitoring and classification is an important step for production forecasting and in mitigating the production setbacks induced by slugging. This holds for predicting slugging operational envelopes depending on boundary conditions such as choke or gas lift setting and in predicting the liquid rates at the separator. Prediction of the liquid rates would allow for preemptive level-control actions using for instance MPC (Model Predictive Control) strategies (1). In relation with slugging prediction, several research questions can be formulated.
A comprehensive three-phase flow campaign, funded by Equinor as part of the Tanzania gas field development project   , was carried out in the SINTEF Large Scale Loop at Tiller in 2017-2018. The experiments were conducted in a 94 meter long 8" pipe, with 2.5° inclination at 60 bar nominal system pressure, using nitrogen, Exxsol D60 and water with and without glycerol. The motivation for performing this study was to support model development targeted towards reducing prediction uncertainty for high-rate low liquid loading conditions. Specifically, the experiments were conducted at conditions that to a certain extent matched those expected during plateau production for the subsea gas development in Block 2 offshore Tanzania. One of the key concerns was that the presence of oil, water and MEG increases the frictional pressure drop more than current multiphase models predict.
The focus of the work was on gas dominated three-phase flows, with low liquid rates (USL=0.0001-0.1 m/s), and mainly high gas rates (USG=4-14 m/s). The effect of the water viscosity was investigated by mixing glycerol (70-74%) with the water, and conducting experiments at different temperatures, yielding water viscosities in the range 14-42 cP. The aim of the experimental campaign was to produce experimental data relevant for modelling two- and three-phase low liquid loading flows at high gas rates. Earlier experiments  had revealed that the pressure drop was significantly higher in three-phase flows compared to two-phase flows, and the current experiments were conducted to investigate this phenomenon more thoroughly.
In this paper we provide an overview of the experimental campaign, and we show some of the key results. Some of the main findings from the experiments were:
Three phase flow system instabilities have recently been investigated in a 3" flowline-riser medium scale model system at the Equinor Porsgrunn test facilities in Norway. The test setup is well instrumented and comprises an 87 [m] long horizontal flowline followed by a 13 [m] high C-shaped riser. At riser top the riser is connected to both 1st and 2nd stage separators, thus reflecting a setup similar to that typically found in a real offshore flowline-riser process plant system. The model fluids used in the current work are air, Exxsol D60 and a viscous water/MEG phase. The system pressure is 4 [bara]. In this paper selected experimental results and observations will be presented, supporting increased understanding of the underlying physical phenomena and the coupled system instability resulting from interaction between the different process elements. Selected OLGA simulations are also presented.
Three phase surge wave instabilities have been observed in the Mikkel/Midgard (1, 2013) and Snøhvit (2, 2009) gas condensate fields at turn down rates and during late life production. This phenomenon can have large operational effects on a receiving facility. For the Mikkel/Midgard fields, which are tied back to the Åsgard B platform, the instabilities enforce minimum flow rates in the flowlines due to liquid handling of the surges topside. Åsgard B has also experienced hydrate problems related to no liquid MEG inhibitor arriving topside between each liquid surge. In a recent study (3, 2017) it was demonstrated that a 1D transient flow model can reproduce the observed surge waves at Åsgard B. The model, which was tuned against field data from Åsgard B, predicts that the surges originate in the lazy-S riser at Åsgard B due to water/MEG accumulation with no water/MEG arriving topside between each surge. The field data and model show that condensate arrives topside also in the accumulation period. The model predicts that along with the release of the accumulated water/MEG from the riser a condensate surge is initiated in the flowline close to the riser.
Farokhpoor, Raheleh (Institute for Energy Technology) | Liu, Lan (Institute for Energy Technology) | Langsholt, Morten (Institute for Energy Technology) | Hald, Karin (Institute for Energy Technology) | Amundsen, Joar (Institute for Energy Technology) | Lawrence, Chris (Schlumberger Software Technology)
Improving the fidelity of multiphase flow models is critical for the ability of the energy industry to reduce the costs of development and operation. The principal challenge for multiphase flow models, in terms of uncertainty, is the difference in scale and some of the fluid properties between field and laboratory conditions. Therefore, the models may become unreliable when they are applied to conditions that are very different from those in the laboratory. For multiphase flow, studies on dimensional analysis and scaling are quite scarce due to the complexity of the systems.
IFE has recently developed and demonstrated scale-up rules for the most basic multiphase pipe flows. Earlier, the scaling rules were tested by designing experiments in IFE’s medium-scale multiphase flow loop to compare with data from SINTEF’s largescale facility. The focus of this paper is on the selection of appropriate data from our existing data base and on the design of new, scaled laboratory experiments, which will be well suited to demonstrate (or test) the scaling rules. The data include fluid properties, pipe configurations and flow rates. Besides the observed flow pattern, the liquid holdup and pressure gradient are the two main parameters for comparison.
IFE’s CO2 flow loop, with an inner diameter (ID) of 44 mm, operates for two-phase flows over a large range of pressures and temperatures to cover the equilibrium line. A set of experiments was run to simulate similar conditions, according to the scaling rules, to verify the scale-up principles. The flows are fully developed, steady state, two-phase vapour-liquid, in a horizontal or near-horizontal pipe. The flow regimes include stratified, annular, and slug flows. The experimental results showed that flow regimes, liquid holdups, and pressure gradients in the CO2 flow loop are in excellent agreement with the experimental data from the large-scale facilities. The results also confirm that the gas-to-liquid density ratio plays an important role, as showed in . The experiments have provided valuable data sets for the verification of the scaling laws.
The present work investigate the effect of droplets entrainment on critical gas velocity, using the liquid film reversal model from Barnea (1986), Luo et al. (2014) and Shekhar et al. (2017). Especial attention was given to the onset of liquid loading in gas well. Experimental and field data were considered for model evaluation. Field data were taken from published data (Turner et al., 1969, Belfroid et al., 2008 and Veeken et al., 2010). Experiments were performed at the multiphase laboratory (EPT-NTNU) in an upward inclinable pipe. The test section was 6 m long and 60 mm ID. Inclination angles varied from 30 ͦ to 70 ͦ from horizontal. The fluids used were air and water. Measurements included fluid velocities and reversal point. High-speed video cameras were used to record the flow regime transition (slug to annular) present in the system. Prediction using the film reversal models revealed that the model over-estimate the critical gas velocity compared to results where entrainment is neglected.
Most gas wells produce liquid as co-produced fluid during well production. Liquid flows along with the gas core as droplets or liquid film on the tubing wall. At the beginning of the production, the gas rate is sufficient to carry all the produced fluid to the surface. However, the declining on the reservoir pressure, the gas production rate decreases until the current gas velocity is insufficient to lift the liquid to the surface. Once this condition is establish, fraction of the liquid starts to flow counter-current to the gas core and accumulates at the bottom of the well, creating a static column of liquid. This accumulation causes backpressure against the formation, which affect the production capacity of the well, making the well produce at unstable flow condition. If the well keep producing at unstable condition, it may lead to a premature abandonment of the well or in some case to wrong well test calculations due to slugging or churning of the liquid.
Pasqualette, M. A. (ISDB FlowTech) | Carneiro, J. N. E. (ISDB FlowTech) | Ribeiro, G. G. (ESSS) | Soprana, A. B. (ESSS) | Girardi, V. (ESSS) | Bassani, G. S. (Repsol Sinopec Brasil) | Merino-Garcia, D. (Repsol)
Since the path between the reservoir to the surface facilities is long and with a broad range of pressures and temperatures, it is almost certain that the fluids (gas, crude oil and water) will be within a hydrate formation region during the field lifetime (23). It can be in a normal producing condition, which is avoided most of the time using insulation or injection of inhibitors, or during a well shutdown/restart, which would require other techniques, such as fluid replacement and heating (25). In any case, hydrate prevention and management methods can add significant CAPEX or OPEX costs to the project and minimizing them can be of utmost importance to a safe and profitable operation. In that light, alternative production methods, like cold-flow (10), intend to produce hydrocarbons within the hydrate stability region expecting that they will be formed, but its crystals would only be transported without significant agglomeration and deposition and thus, will not block the pipeline. However, to guarantee such operation, not only a very reliable simulation model has to be used in the design phase, but it is also important to have a monitoring system that can foresee and advise the possibility of a pipeline blockage due to unexpected conditions.
Bassani, Carlos L. (Federal University of Technology - Paraná) | Barbuto, Fausto A. A. (Federal University of Technology - Paraná) | Morales, Rigoberto E.M. (Federal University of Technology - Paraná) | Cameirão, Ana (Mines Saint-Etienne, Univ Lyon, CNRS) | Herri, Jean-Michel (Mines Saint-Etienne, Univ Lyon, CNRS) | Sum, Amadeu K. (Colorado School of Mines)
Abstract. A new predictive model for hydrate formation kinetics that captures the porous structure evolution in time is coupled with a multiphase flow mechanistic model. It is assumed that the hydrate particles behave as sponges, related to hydrate formation under flow shear. The multiphase flow is considered as a gas-liquid slug flow, where the liquid is a water-in-oil emulsion. Closure parameters for the model are thoroughly discussed and the model trend is validated against experimental results obtained in a flow loop. Mass and heat transfer limitation processes are discussed in terms of the theoretical predictions from the model.
Gas hydrates are crystals formed by the imprisonment of gas molecules in cages formed by hydrogen-bonded water molecules (1). The high pressure and low temperature conditions often found in offshore oil and gas production operations favor gas hydrate formation. The uncontrolled growth and agglomeration of these crystals can cause pipeline plugging, with production stop and related revenue losses, and thus such phenomenon is nowadays regarded as the main challenge in flow assurance (2).
ABSTRACT An X-ray 2D and 3-phase computed tomography (CT) device has been used within NEL's multiphase facility to identify multiphase flow structures and flow regimes for mixtures of gas, oil and water flows at low pressure. This paper demonstrates the application of this technology for the digital reconstruction of flow regimes and assessment of slugging frequencies. Experiments were conducted in a 4-inch section of horizontal pipework for mixtures of gas, oil and water at various superficial velocities. The X-ray 2D and 3-phase device is shown to be a valuable tool which is suitable for high pressure applications to quantify flow structures. 1 INTRODUCTION During the extraction of oil from a well, a multiphase flow exists which comprises timedependent ratios of oil, water and gas. The ratio of the 3 phases will lead to various flow patterns dependent on the ratios of gas and liquid, operating pressure, temperature, velocity, pipe deviation and fluid properties. The principal method of determining flow patterns has been by visual observation through a transparent viewing section and more recently with tomography equipment which typically has limited resolution and is restricted mainly to 2-phase gas-liquid regimes (1, 2).
Computational Fluid Dynamics (CFD) are used to simulate flow-induced vibrations (FIV) in high-pressure multiphase pipe flow. Furthermore, empirical correlations from the literature is compared and validated against computational and experimental results. Based on the CFD results and in conjunction with the reference 6” (internal diameter (ID)) data new scaling rules are proposed.
Flow-Induced Vibration (FIV) in subsea production systems (SPS) may lead to fatigue fracture in piping, support structure and at welds. There are multiple physical mechanisms through which internal flow in subsea production systems may induce a vibrating response of the structure and fatigue issues. One of these mechanisms involve multiphase flow induced excitations, where variations in density lead to time-varying reaction forces that induce time-varying motion of the piping. Currently used empirical relations are mainly based on low pressure experiments. These relations provide a description of the frequency spectrum of the dynamic loads induced by multiphase flows and are partly validated with field case observations and measurements. Despite this, former investigations have shown that the remaining uncertainty is still large, for instance regarding the width of the frequency spectra at high pressures. In this paper, Computational Fluid Dynamics (CFD) simulations are used to understand impact of certain parameters and to bridge the gaps between the low-pressure experiments vs. field specific conditions. The CFD methodology is validated against literature data. With the same schemes, field cases are simulated. Based on the CFD results, adapted scaling rules for the force spectrum are derived and compared against the available laboratory data. The mechanical response due to multiphase flow can be calculated either in the time domain or in the frequency domain. In the time domain, the wave/slug frequency and heights are required including the wave/slug velocity. This is often the most accurate description and can for instance be obtained from CFD. On the other hand, the mechanical simulations are often easier in the frequency domain. From previous experiments, it turns out that the power spectral density (PSD) of the force looks like a “triangle” in the log-log scale (Figure 1). This means that to describe this PSD for general conditions, four relations are required: The peak frequency, the slope parameters m1 and m2 and the total rms value (equals the square root of the integral of the PSD). Therefore, correlations for these four parameters are sought-after for a fast prediction of the expected forces.
Hydraulic simulators represent the multiphase flow workhorse of upstream production. Because these tools are not a panacea for every flow assurance challenge, application programming interfaces (APIs) provide users the ability to add fit for purpose analyses while leveraging the hydraulic simulator backbone. ExxonMobil Upstream Research Company (EMURC) has developed a number of custom tools that fully integrate with in-house and commercial flow simulators through these APIs. Demonstrated here, EMURC’s proprietary Sand Transport Model has been used to manage decisions for pipelines, completions, and facilities. In addition to highlighting successes, we also share our learnings how multiphase flow model uncertainty ranges propagate to these models and the importance of versatile API capabilities as the industry continues toward its digital transformation.
In oil and gas production, multiphase flow (MPF) represents the fundamental basis of transport from the reservoir to the point of sale. Along the way, thermodynamic and physical processes can lead to deposits of hydrates, wax, asphaltenes, sand, and inorganic scales. While most rely on commercial tools for multiphase flow, many rely on internal proprietary tools for other flow assurance analyses. This workflow typically involves an inefficient back and forth between platforms and may not capture the representative physics in either the fluid mechanics or the thermodynamics.