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VMGSim for Integrated Modeling of Multiphase Slip-Flow Pipelines with Plant Process Equipment

Common industry practice is to design pipelines and gathering systems in isolated phases, using different and decoupled software programs. Recent advances in VMGSim now enable multiphase slip-flow simulations of pipelines and connected process units in one integrated VMGSim model (which can include rigorous dynamic pigging, slugging, surge analysis, blowdowns, etc).

Our first article on the subject of integrated pipeline and process modeling will address two key questions:

“What’s so different about multiphase flow?”

and

“Does VMGSim really contain tools which can ‘understand’ multiphase slip flow in pipelines, including coupled plant effects?”

Abstract                                                                                                                                               

This introductory article includes:

  • Key fundamental considerations in multiphase slip flow (pipelines & connected plants)
  • VMGSim methods for multiphase pipeline dP and holdup – comparison and recommendations
  • An illustration of how the VMGSim Pipe Segment ‘understands’ key multiphase fundamentals
  • A multiphase pipeline size selection ‘lifecycle’ example, illustrated by a VMGSim Case Study Plot

A future article will delve further into VMGSim Dynamics, including cause/effect analysis of multiphase slugging pipeline flows entering plants due to pigging, rampup, or flow regime, evaluation of mitigation options, plus networking of VMGSim Pipe Segments (i.e., to simulate a gathering system).

Multiphase Fundamentals affecting Pipelines and Connected Plants

Multiphase pressure drop mechanisms are more complex than single-phase mechanisms. Multiphase flow regimes (e.g., Bubble, Stratified, Slug, Annular, Transition, Mist) describe complex distributions of vapor and liquid phases under different geometric, process, and phase conditions. Many excellent advanced textbooks and handbooks describe these, such as [3].

In the Upstream and Midstream markets, multiphase pipelines and gathering systems typically accept saturated or wet raw inlet gases, then deliver these compositions into distant plants. Even if they enter the pipeline as saturated vapors, these transported fluids often cool to a multiphase state due to pipeline heat losses to ambient surroundings, where in many cases fluid T > ambient T.

Multiphase flows can separate in the pipeline, leaving liquids behind. Slipped liquids (aka holdup) can then cause backpressure problems in the pipeline. Transient multiphase outflow variations can surge or slug, tripping the connected plant. Heavier plus fractions in shale fluids can increase problems

Engineers already use VMGSim to model many plants which are fed by incoming multiphase pipelines. Therefore, this article will illustrate some benefits of adding VMGSim’s Pipe Segment to extend such VMGSim models ‘in front of the plant’.

Upstream field development schedules typically show at least 5:1 ranges of lifecycle flowrates, or even 10:1. Engineers must ideally design Multiphase Pipelines and Gathering Systems to remain (at least somewhat) operable across the increasing, then decreasing flow velocities, temperatures, and pressures expected throughout their lifecycles.

Therefore, selecting an ‘optimal’ design requires informed compromise. But, that selection process won’t be well-informed unless multiphase slip-flow effects are considered.

So, what do we mean by multiphase slip flow?

Consider the following two diagrams of “up-and-down” pipelines. Both flow up and back down over the same distances. So, their uphill and downhill elevation changes each net to a total elevation change of zero.

The first contains an all-liquid (single-phase, constant-density) fluid. The second contains a multiphase fluid, flowing (for the sake of this illustration) below its homogeneous (no-slip) velocity threshold – probably at some turndown flowrate. So, that second pipeline “feels” relatively stronger gravitational forces, by comparison to its reduced (turndown) vapor shear forces. Multiphase slip flow is the result of this shear-vs-gravity ‘battle of the forces’ in the second pipeline, as shown by the variations in its uphill vs downhill liquid phase fractions (aka, slip-flow holdups).

Dewaynesmall.png

See how the multiphase slip-flow pipeline always loses (uphill) elevation dP (or ρgΔh) at a higher liquid holdup fraction (multiphase ρ), but always gains back (downhill) elevation dP at a lower multiphase ρ?

Therefore, each equal up-and-down elevation run of a hilly pipeline ‘feels’ a net elevation pressure loss (because of higher uphill multiphase slip-flow mixture ρ, by comparison to lower downhill mixture ρ).

Low multiphase vapor velocity generally gives more liquid slip (and holdup, or volume fraction of liquid ‘left behind’ in low spots and uphill sections). Even very small uphill inclinations cause excess holdup (and potential slugging) at turndown rates. Expect operating challenges whenever a hilly multiphase (i.e., wet-gas) pipeline must operate far below its maximum design flowrate.

Why can we observe such high holdups in the uphill sections, but such low holdups in the downhill sections? Because gravity is pulling the dense liquids back down (against upward vapor shear) in uphill flow. In contrast during downhill flow, vapor shear pushes liquids forward (now working in the same direction with gravity, as vapor shear and gravity both respectively push and pull the liquids in the same general direction - downward and forward).

Engineers working with multiphase pipelines must be mindful that gravity always acts downward, but vapor shear on the associated dense liquids can act downward or upward (in local downhill vs uphill sections, respectively). Wherever shear and gravity oppose each other, the stronger force tends to ‘win’, dictating the multiphase flow regime, holdup, and dP. Total multiphase pipeline dP is the superposition of these major shear and gravity dP effects (plus acceleration dP, which is often a smaller dP effect).

So, unlike a single-phase pipeline, a multiphase pipeline can truly be ‘too large’ in diameter for a given flowrate and maximum dP spec. This is because vapor velocity will decrease quadrically with increasing pipe diameter, allowing a larger fraction of any entering or condensed liquids to slip behind (as excess holdup).

That excess liquid holdup will cause excess elevation dP (ref: the hilly pipeline above). Finally, that excess multiphase elevation dP (i.e., excess backpressure at pipeline inlet, assuming flow into the same plant receiver P) may prevent the upstream wells from delivering their full design production schedules into this pipeline – simply because it was oversized.

Failure to design for slip can limit or even prevent successful operations. Either an oversized or undersized multiphase pipeline can reduce its Return on Investment (ROI), and may even cause early field abandonment (after fewer years of profitable operations than the well and pipeline operators had forecast when justifying their respective capital investments).

Therefore, engineers designing or operating such pipelines need advanced slip-flow software tools.

VMGSim Pipe Segment – Multiphase Methods for Pipeline Design and Operability Analysis

Did you know? The VMGSim Pipe Segment now includes advanced methods (for dP, holdup, and heat transfer) which ‘understand’ about multiphase slip flow, including both steady-state and dynamics. Therefore, VMGSim is one of very few products which can seamlessly integrate rigorous multiphase pipeline simulation together with rigorous plant simulation and mixture modeling, in powerful ways.

VMGSim’s Pipe Segment can be used in Steady State (e.g., to choose new multiphase pipeline diameters which should be optimal over their lifecycle, or to select required insulation for a minimum multiphase outlet temperature).

This same Pipe Segment can also be used in Dynamics to help operate sub-optimal pipelines as efficiently and profitably as possible (e.g., choosing best-compromise pigging schedule, troubleshooting and mitigating slugging effects on the plant, fastest pipeline inlet ramp-up time which won’t trip the plant with its outlet surge).

If you want to exploit these VMGSim capabilities for yourself, read on to learn which current (Pipe Segment) pressure drop and holdup methods are recommended for multiphase applications.

Preferred Multiphase Methods

VMGSim allows the user to select ‘Pressure Drop Corr.’ via a list box on the Summary tab of its Pipe Segment properties.

Image_form_pipe.PNG

Which correlations should users select (i.e., for a hilly wet-gas pipeline)?

As described in the VMGSim User Manual (see Unit Operations / Pipe Segment), several of those available correlations are only suitable for single-phase use. All such correlations (including the default Colebrook) can therefore be ruled out for multiphase fluids.

Three multiphase methods stand out as general-purpose choices (listed below, in purely alpha order). A fourth is also listed for context and comparison.

1-Beggs and Brill – It’s been Famous for Decades. Therefore, all multiphase pipeline and process software products include this ‘standard’ method. Many engineers (including this author) have sometimes chosen this method because of its leading familiarity. However, a reference check reveals that it is an empirical correlation based upon limited data, developed more than forty years ago, with a few suggested improvements by others in separate subsequent papers. Therefore, as its authors noted in their paper, extrapolation into uncorrelated regions (where Beggs and Brill did not fit their empirical curves through any comparable research data points for all of similar fluids, diameter, roughness, inclination, and phase velocities) can give very uncertain predictions. And, any such empirical method is not optimal for use with Dynamics (whether in VMGSim, or any other software).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              As As shown in the following VMGSim Case Study plot, even this formidable Beggs & Brill method (perhaps the most widely respected empirical method) is not able to ‘understand’ the gravity-dominated load-up region for these hard-to-predict wet-gas systems at turndown. To understand why, let’s consider Dr. Brill’s own reflections about this topic almost forty years later (now also with awareness of modern compute power and newer mechanistic models):

Although some of the better empirical correlations (like Beggs and Brill) have survived the test of time, they all suffer from significant errors in some ranges of input variables and cannot be improved because of their simplistic nature. (In contrast,) the (newer) mechanistic models are more accurate, more sophisticated, and more difficult to understand. [1]

Also consider a classic paper by Shea and Rasmussen [2], which compares predictions of five multiphase methods against almost 150 industrial-scale research datapoints for wet-gas systems. They have this to say about the predictions from Beggs and Brill (plus another empirical method by Eaton) for their Proprietary Datapoints representing the hard-to-predict wet-gas systems:

Good prediction of the liquid holdup for wet-gas pipelines is critical in the design of pipeline slug catchers. For hilly terrain pipelines, the liquid holdup also has a significant influence on the pressure-drop predictions at low rates. Despite the importance of this parameter, many engineers in operating companies and contractors use methods which give extremely poor predictions (for such wet-gas fluids, flowing through hilly pipelines).

The (empirical) Beggs and Brill and Eaton predictions are poor (for the inclined wet-gas datapoints which were the focus of Shea and Rasmussen’s paper). These methods grossly overestimate the liquid holdup at high rates and grossly underestimate it at low rates. Eaton's method gives better predictions than Beggs and Brill, but the average error (even) for Eaton is greater than 100%. Neither method properly (mechanistically) accounts for angle of inclination dependencies or pressure effects. [2]

Therefore, Shea and Rasmussen warn that even this well-known Beggs and Brill method doesn’t give the most accurate prediction of dP and holdup in cases with wet gas and hilly pipelines. In VMGSim Dynamics, the good mechanistic models predict transients more realistically.

2-OLGAS – This proprietary mechanistic method is available in 3P and 2P versions (for use in systems with and without water, respectively). OLGAS is the steady-state mechanistic model related to the proprietary OLGA® multiphase transient slip-flow pipeline software. It was scored best for wet-gas systems by Shea and Rasmussen [2]. However, the very delicate shear/gravity force balance in these wet-gas fluid systems still caused significant error even in OLGAS predictions versus experimental data for their most challenging datapoints of wet gas with low vapor shear (where shear and gravity forces are almost exactly balanced against each other at the threshold of ‘load-up’). Note that the proprietary OLGAS method requires an additional license fee. And, this steady-state-only OLGAS is not usable with VMGSim Dynamics.

3-Oliemans – That same classic Shea and Rasmussen paper [2], which didn’t recommend Beggs and Brill (or any empirical method) for the difficult wet-gas systems but did recommend OLGAS, also found an earlier (wet-gas-only, but mechanistic) Oliemans method to be the next most predictive method:

(Original Oliemans) doesn't predict (as well as OLGAS) the point at which the holdup increases rapidly. It does, however, show the correct trends and clearly indicates the improved performance of mechanistic models.

Therefore, VMGSim includes a newer Enhanced Oliemans Method [3]. In this significant mechanistic enhancement, Oliemans also adds support for more flow regimes and inclinations (from horizontal all the way to vertical, somewhat like OLGAS), including new and specific holdup and dP methods for each.

This Enhanced Oliemans Method is therefore more comprehensive, and should help to improve VMGSim’s Oliemans predictions across the widest range of Flow Regimes, Inclinations, etc. Recall that the original Oliemans was already found to be ‘next best’ (versus OLGAS) in Shea and Rasmussen’s classic evaluation for wet-gas systems. VMGSim’s Enhanced Oliemans builds upon that.

4-Petalas - The VMGSim Pipe Segment has long included another mechanistic multiphase method developed for use with pipelines – Petalas. When evaluated across several small steady-state VMGSim Case Studies, the Enhanced Oliemans Method (simply named ‘Oliemans’ in VMGSim’s Pipe Segment list box) tracked better than Petalas with the ‘loadup’ predictions of Shea and Rasmussen’s best-scoring legacy OLGAS Method. For several wet-gas fluids investigated, Petalas generally seems to predict lower Holdup and dP than either OLGAS, or VMGSim’s Enhanced Oliemans. Analysis also traced some differences to a more comprehensive range of flow regimes (and regime-specific dP / holdup methods) in the Enhanced Oliemans method, versus fewer regimes in Petalas. These case studies were all investigating the predicted onset of ‘load-up’ with decreasing flowrates, for various wet gases flowing through different hilly pipelines. 

Also look for these Pipe Segment Pressure Drop Methods (and Multiphase Slip-Flow / Holdup Methods) to be added in upcoming VMGSim releases:

  • Kongsberg’s LedaFlow® 1D Point Model (another respected proprietary mechanistic model; developed in recent years; competitive with OLGAS; also available in 2-phase and 3-phase)
  • Oliemans 3-phase (a new VMG extension to the Enhanced Oliemans mechanistic method)

Look for more information in future articles, or ask your VMG Representative.

Methods Recommendations for Multiphase Slip Flow in VMGSim Pipe Segment

VMGSim’s Enhanced Oliemans Method is expected to perform better in the Pipe Segment than Petalas, across the broadest range of multiphase slip-flow use (i.e., all Flow Regimes). This same mechanistic (Enhanced) Oliemans method has the advantage of being usable (and recommended for consistency) in both VMGSim Steady State and Dynamics.

VMGSim’s (Enhanced) Oliemans does not require any additional proprietary methods license – unlike the steady-state-only OLGAS. However, in steady-state-only cases where the OLGAS license is available, OLGAS is also recommended.

When available, we will also evaluate Oliemans3P (the new three-phase extension to VMGSim’s Enhanced Oliemans) and (the licensed) LedaFlow 1D. Pending almost certain favorable evaluations, these should both be added to this article’s list of Recommended Methods for Multiphase Slip Flow in the VMGSim Pipe Segment.

Illustrating Multiphase Slip-Flow Methods Fundamentals with the VMGSim Pipe Segment

Consider the following VMGSim (Steady State) case study plot of liquid holdup volume versus Standard Gas Flowrate (MMSCFD). It was computed over a 10:1 range of min to max wet-gas flowrates (and vapor velocities) for a 20-mile hilly wet-gas pipeline with a 740 psia inlet P and a 16-inch diameter.

graph11.png

Note how each mechanistic method associates the same Total dP (psi) with two different vapor flowrates on that VMGSim case study plot. In that shear-vs-gravity holdup ‘battleground’ with low vapor velocities in wet-gas systems, some of the best mechanistic methods (e.g., OLGAS, Oliemans) separate themselves from the empirical methods (i.e., Beggs and Brill).

Inside those mechanistic methods, superposition of separate friction and holdup dP terms (plus acceleration) can give a minimum Total dP. Therefore, double-valued Total dP solutions (gravity-dominated, and friction-dominated) may occur at lower and higher flowrates, respectively.

The above plot uses VMGSim (and overlaid Case Study trendlines for different Pipe Segment methods) to show the benefits of using leading mechanistic dP and holdup methods.

The circled area confirms that the empirical multiphase methods (like Beggs and Brill), developed from curve fits of friction-dominated data, lack any proper means to ‘understand’ gravity-dominated liquid load-up. However, most wet-gas pipelines will need to operate within that gravity-dominated region under their design conditions for certain operating years, as discussed above.

This VMGSim Case Study graph comparing OLGAS, Beggs and Brill, and Oliemans reinforces key points from [1] and [2]. Empirical methods like Beggs and Brill are not predictive for multiphase holdup and dP evaluations of troublesome low-vapor-shear flows in wet-gas pipelines. They may do better when interpolating their correlated ranges, as illustrated in the plot above for its moderately friction-dominated region. But, Shea and Rasmussen also noted Beggs and Brill’s tendency to overpredict holdup (and therefore slip, and dP) in more highly friction-dominated regions.

Example - Multiphase Pipeline Size Selection with VMGSim Pipe Segment in Steady State

The VMGSim Plot below illustrates a key capability required for multiphase pipeline diameter selection. That is, a steady-state case study of total multiphase dP for a range of considered diameters, with each considered diameter also evaluated across the same range of expected lifecycle flowrates. FYI, this Case Study was run with VMGSim's (Enhanced) Oliemans Method, as recommended above for Steady State and Dynamic simulation of wet-gas systems

graph2.png

Note that the highest flowrate curves show continuously decreasing dP with increasing design pipe diameter. The monotonic slope of these curves (with no double-valued dP vs velocity behavior) indicates that these flowrate curves would be in shear-controlled (aka friction-dominated) flow for any of our considered design diameters.

This friction-dominated flow regime does avoid both inefficient (gravity-dominated) liquid loadup and that gravity regime’s potential safety hazard of inverse control response (requiring higher inlet pressure to drive smaller flowrates against the same outlet pressure – aka, ‘loadup’). But, this regime can waste energy in its own different way (requiring excess frictional pressure drop) when a pipe diameter is very much too small for a given (i.e., highest) design flowrate.

Notably, most flowrate curves on this same case study plot show a concave response of dP versus increasing design diameter. The double-valued dP vs velocity tendencies of these flowrate curves (NOTE: Same Q and Larger D implies lower V) indicates that ‘friction is winning’ in the smaller diameters on their left. In contrast ‘gravity is winning’ (that is elevation dP, with high holdup) in the larger diameters on the right of these flowrate curves.

Let’s assume a key design goal to avoid any excessively high pressure drop for any design flowrate (in any expected operating year). Then in that case, we might choose the ‘middle course’ of the 8-inch pipeline, because that avoids the highest gravity-controlled pressure drops (of the 10-inch) at the lowest design flowrates, while also avoiding the highest friction-controlled pressure drops (of the 6-inch) at the highest design flowrates.

So, these Case Study graphs have shown that VMGSim is capable of performing the most essential steady-state design task for a multiphase slip-flow pipeline – diameter selection. This same Case Study tool may also be used with the same Pipe Segment and multiphase method to study variations in the ‘Layer 2’ insulation thickness versus its resulting effects on outlet temperature.

Summary

  • The leading mechanistic multiphase methods in the VMGSim Pipe Segment (currently the proprietary / licensed OLGAS; VMGSim’s Enhanced Oliemans; LedaFlow 1D and Oliemans3D coming soon) are able to properly capture the shear-vs-gravity ‘battle’ and properly model trends in multiphase holdup and dP for wet-gas systems. In contrast, the empirical multiphase methods (i.e., Beggs and Brill) suffer extrapolation problems. 
  • The VMGSim Pipe Segment can also run with the (Enhanced) Oliemans method in Dynamics. In contrast, the proprietary OLGAS method is only available in VMGSim Steady State.
  • Therefore, both the mechanistic OLGAS and (Enhanced) Oliemans Methods are recommended for use with the VMGSim Pipe Segment when analyzing wet-gas pipelines in steady-state simulations. As of this writing, LedaFlow 1D will soon become another option.
  • The mechanistic (Enhanced) Oliemans Method (or Petalas, but note its limitations above) may also be combined with VMGSim Dynamics to model pipeline pigging surges and ramp-up surges, in a completely integrated way with their effects on plant equipment including separators (aka slug catchers), valves, controllers and actuators, downstream pumps and compressors, etc.
  • VMGSim (and Dynamics) offers a uniquely powerful combination of leading multiphase slip-flow pipeline capabilities together with leading plant simulation capabilities and leading non-ideal fluid mixture modeling capabilities.
  • Therefore, VMGSim allows uniquely integrated design and analysis of multiphase pipelines plus connected plants with one single software.

If you’ve found this article interesting, look for a future VMG newsletter article which will build upon this current basis of multiphase slip-flow fundamentals and VMGSim Steady State workflows. That coming article will first discuss dynamic multiphase problems such as terrain slugging, pipeline pigging surges, rampup surges, rupture or blowdown, etc. Then, it will illustrate powerful uses of VMGSim Dynamics and its Pipe Segment to analyze (and mitigate) such problems.

References

[1]Brill, J. P. (2010). Modeling Multiphase Flow in Pipes. SPE - The Way Ahead, Volume 6, Number 2, 16-17.

[2]Shea, R., Rasmussen, J., Malnes, D., & Hedne, P. (1997). Holdup predictions for wet-gas pipelines compared. The Oil and Gas Journal, Vol 95, Number 20, Page 73.

[3]Oliemans, R. (2005). Gas-Liquid Transport in ducts, in Multiphase Flow Handbook, C. Crowe Ed. Boca Raton, FL (USA): CRC Press.

 

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