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OPERATIONAL EXPERIENCE WITH ULTRASONIC METERS FOR ALLOCATION MEASUREMENT OF LNG
Stuart Christie Herry Kurniawan
Michael Scott RasGas Company Ltd, Qatar
Gregor Brown Alastair McLachlan
Cameron, UK
ABSTRACT
In 2005 RasGas, QatarGas, ExxonMobil and ConocoPhillips embarked on a project to investigate the use of in-line metering for measurement of cryogenic LNG. The project was driven by the desire to use in-line metering for allocation of LNG into common storage, thus enabling huge capital cost savings at the RasLaffan complex. Candidate metering technologies were chosen and a test programme was conducted at the ConocoPhillips LNG plan in Alaska. The background, results and conclusions from these tests were presented at the LNG15 conference in Spain in 2007. Following the successful outcome of the tests, 22 ultrasonic meters have been installed on allocation measurement duties in the RasLaffan complex. The first of these were commissioned in June 2009 and have been in continuous service since that time. This paper will follow up on the presentation made at LNG15, sharing the experience that RasGas have gained with operation of these meters. The presentation will include an analysis of the reduction in measurement uncertainty and the corresponding improvement in allocation obtained by using ultrasonic meters that have a low sensitivity to upstream hydraulic effects. Practical aspects of the RasGas experience with these meters will also be shared.
1 INTRODUCTION
In 2005 RasGas, QatarGas, ExxonMobil and ConocoPhillips embarked on a project to investigate the use of in-line metering for measurement of cryogenic LNG. The project was driven by the desire to use in-line metering for allocation of LNG into common storage, thus enabling huge capital cost savings at the RasLaffan complex.
Candidate metering technologies were chosen and a test programme was conducted at the ConocoPhillips LNG plan in Alaska. The background, results and conclusions from these tests were presented at the LNG15 conference in Spain in 2007.
Following the successful outcome of the tests, 22 ultrasonic meters have been installed on allocation measurement duties in the RasLaffan complex. The first of these were commissioned in June 2009 and have been in continuous service since that time.
This paper is a follow up on the presentation made at LNG15, sharing the experience that RasGas have gained with operation of these meters. The presentation includes an analysis of the reduction in measurement uncertainty and the corresponding improvement in allocation obtained by using ultrasonic meters that have a low sensitivity to upstream hydraulic effects. Practical aspects of the RasGas experience with these meters are also shared.
2 LNG PRODUCTION IN QATAR
The state of Qatar is currently one of the largest LNG producers in the world. In 2008 it was estimated that Qatar’s proven reserves of natural gas represent around 12 % of the global total [1].
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Figure 1 - Global natural gas reserves by country
Qatar’s North Field is the largest non-associated natural gas reservoir in the world. It was discovered in 1971 and is located about 100 km offshore, north east of Doha, the capital city of Qatar, as illustrated in Figure 2 below. The estimated reserve is in excess of 900 trillion standard cubic feet.
Qatar has taken great strides in LNG production; the production rose to 77 million metric tons per annum in 2010. The production is shared between two major LNG industries in Qatar, RasGas and Qatargas, which each operate 7 LNG trains.
Figure 2 - The location of Qatar’s North Field
Influenced by the growth in LNG demand around the world, today Qatar supplies LNG customers in Asia, Europe and America. For RasGas, the customers include Kogas (South Korea), Petronet LNG Limited (India), Edison (Italy), CPC Corporation (Taiwan), Endesa Generacion (Spain), Exxon Mobil Corporation (United State), EDF Traiding (Belgium) and Distrigas (Belgium).
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3 THE NEED FOR LNG ALLOCATION METERING
LNG production in Qatar is concentrated in the Ras Laffan industrial complex. The concentration of production in one large site creates opportunities for significant cost savings. Already major capital cost savings have been achieved by employing common storage, thus reducing the number of storage tanks and LNG tanker berths required. As shown in Figure 3, multiple trains produce into two common storage lots, with trains 6 and 7 capable of being produced to either lot N or lot H. A bi-directional interconnection also exists to facilitate the transfer of LNG from one lot to the other. Cost savings achieved by adoption of the common facilities approach have been estimated to be in the region of 1 Billion dollars ($1,000,000,000) [2].
As there are various partners involved with different splits in ownership of the production from each train, it is necessary to allocate production back to each venture by metering the LNG rundown. As such, the availability of accurate in-line LNG metering was a key requirement in the development of the common facilities project.
The financial sums involved in the allocation and custody transfer measurement of LNG are significant. A Q-Max LNG tanker can hold 266,000 m3 of LNG, the equivalent of approximately 162 million cubic metres of natural gas at standard conditions. Based on recent global prices we can assume that the value of natural gas is approximately $4 per MMBtu (~ $4 per GJ). The energy value of natural gas is approximately 40 MJ per standard cubic meter which is the equivalent of roughly 24 GJ per cubic meter of LNG. From these numbers we can calculate that the value of a cubic meter of LNG is approximately $100, that the daily production from trains 6 and 7 is worth more than $10 million, and that a single tanker load is worth more than $25 million.
Figure 3 – A schematic of the common facilities operated by RasGas and Qatargas
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4 THE QUALIFICATION AND SELECTION PROCESS
As custody transfer measurement of cryogenic LNG is normally performed by onboard tank measurements, limited research had previously been conducted regarding the performance of in-line LNG metering systems. In addition to the general shortage of information about in-line LNG metering that was available at that time, there was the added complication that conventional proving systems used for liquid metering cannot be used on typical LNG applications. Therefore, in 2005 a jointly funded project was established to evaluate the performance of in-line metering technology for the Qatar Common LNG Project.
The philosophy that the parties agreed upon was to adopt the same technology for all of the metering stations in order that measurement uncertainties would also have a common basis. It was also planned that the metering system would allow two meters to be operated in series for checking purposes. Basic pre-qualification requirements used in the selection of appropriate technologies for evaluation were:
• No rotating parts • No wetted sensors • Advanced diagnostics • Proven reliability in other applications • Proven accuracy for liquid custody transfer • Proven performance in (other) extreme temperature applications
On the basis of the above criteria, both ultrasonic and Coriolis technologies were selected by the project team for evaluation.
After the project team had made their decision on generic technologies, specific meters were selected for evaluation on the basis that they should be able to operate reliably and accurately at cryogenic temperatures, be able to withstand large temperature swings, have self-diagnostic capabilities and have relatively little pressure drop.
Based on discussions with various manufacturers, two different makes of Coriolis meter and one ultrasonic meter were chosen for evaluation. The ultrasonic meter was a six-inch 8-path Caldon LEFM280C supplied by Caldon Inc (now part of Cameron).
Field qualification tests were performed at the ConocoPhillips LNG plant located in Kenai, Alaska. This location was selected as it was an operational facility with appropriate infrastructure for the meter evaluation. The test line was installed as a bypass loop on the rundown line with a double-block-and-bleed valve, allowing installation and maintenance of the test meters without interfering with the production.
This infrastructure allowed the meters to be tested by comparing the ultrasonic meter against one or the other of the Coriolis meters while using them to meter LNG into the plant’s storage tanks. At that time the Kenai plant was producing approximately 50,000 barrels/day of lean LNG. The storage tank measurements were also compared against certified tanker measurements. Figure 4 shows a schematic diagram and of the test set up.
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From LNG plant
Caldon ultrasonic
meter
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Figure 4 - The Kenai test set-up
The Caldon meter and the two Coriolis meters were tested at Kenai over a three month period at the end of 2005. The Caldon 280C was supplied with two sets of electronics as shown in Figure 5. Each set of electronics produces a flow output derived from one set of four paths. Each set of four paths are grouped in a single plane at either plus or minus 45 degrees to the pipe axis. Each of the two planes (A & B) is the equivalent of a Caldon 4-path meter. For the field trial the outputs from planes A and B were input separately to the Kenai data acquisition system such that the results could be evaluated both individually and in the desired 8-path combination.
Today the Caldon 280C flow meter can be provided either with two sets of electronics, each operating four paths and providing an output for each, or with one set of electronics that operates all 8 paths, with various output options.
Figure 5 - Caldon LNG meter installed at Kenai in Alaska
The main part of the test programme involved comparing the Caldon ultrasonic meter against both of the Coriolis meters in order to assess the reproducibility of the results. The philosophy behind this was that any lack of reproducibility in either technology would be apparent, given that the comparison was between two completely different technologies, including two variants of Coriolis design. The stated aim was that the day-to-day reproducibility should be better than +/- 0.25 %.
In terms of reproducibility the comparisons were similar in the case of both Coriolis meters. In terms of the absolute values there was good agreement between the ultrasonic meter and one of the Coriolis meters, with a more significant bias existing between these two and the second Coriolis meter. Figure 6 below shows the comparison of the Caldon ultrasonic meter and one of the Coriolis meters, using the percentage deviation in
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8-hour totals taken over a period of twelve days. The average agreement between the two meters was better than 0.1 %, with a statistical uncertainty of less than +/- 0.15 %. These results were taken as a positive confirmation of the performance of both technologies.
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Figure 6 - Comparison of Caldon USM and Coriolis meter totals on LNG [2]
The project team responsible for the trials at Kenai were satisfied with the flow measurement performance of the ultrasonic meter and the Coriolis meters. However, other factors proved to be more important in the final selection.Ensuring minimal pressure drop was the biggest factor in the final meter selection. The importance of this issue was increased further by the project requirement to be able to employ two meters in series. Observation of differential pressures measured at the Kenai site demonstrated that use of two Coriolis in series would have created too much pressure drop. In contrast the Caldon 280C is non-intrusive. It also has two 4-path planes in which each path is used to make an independently velocity measurement with each plane having its own set of electronics. Full redundancy is achieved, with the result that the meter can still operate even in the unlikely event of one or more component faults.
5 SWIRL IMMUNITY OF THE 8-PATH METER DESIGN
Another important feature of the 8-path meter design is its immunity to the effects of swirl. Swirl occurs when the flow changes direction in more than one plane, such as when it passes through two close-coupled out-of-plane bends. Swirl interferes with the performance of ultrasonic meters by introducing an unwanted non-axial component of velocity in each measurement path. This unwanted component of velocity can be additive or subtractive. If the non-axial flow velocity is going in the same direction as the ultrasound when it travels from the upstream transducer to the downstream transducer then the effect will be to increase the measured velocity. If the non-axial velocity is opposite in direction to the downstream travel of the ultrasound then the effect will be to decrease the measured velocity.
Most multipath meters provide some swirl compensation by having opposing paths on opposite sides of the pipe axis. That means that one path may compensate the other for the effect of the swirl, as illustrated in Figure 7 below. However, this is only effective if the swirl is a single-vortex swirl that is centred exactly on the pipe axis. If the swirl is slightly off-centre or has a more complex pattern containing multiple vortices, then this form of swirl cancellation is not effective.
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Figure 7 - An illustration of swirl cancellation in a 2-path meter
The Caldon LEFM 280C differs from the parallel and criss-crossed arrangements generally used in ultrasonic meters by having crossed paths in each of four chordal planes as shown in Figure 8 below. This is a much more successful strategy for creating immunity to the effects of swirl as the non-axial velocity component is cancelled in each pair of overlapping paths. With reference to Figure 8, if the swirl effect is positive on path 1, it will cancel with the negative effect on path 5; likewise the swirl effects on paths 2 and 6 will cancel one another and so on.
Figure 8 - An Illustration of an 8-path with crossed paths at each chord location
The effectiveness of the swirl immunity of the 8-path meter was unintentionally demonstrated during the Kenai LNG field trials. As two outputs were logged from the Caldon meter, it was possible for the project team to evaluate the outputs from both plane A (i.e. paths 1 – 4) and plane B (paths 5 – 8) separately. When this was done it was found that, relative to the Coriolis meter, one plane was biased by approximately +0.4 % and the other by approximately -0.4 %, as illustrated in the results shown in Figure 9 below.
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A symmetrical bias of this magnitude between the two planes of an 8-path meter is normally indicative of strong asymmetric swirl. The ultrasonic meter was installed at Kenai with approximately 37 diameters of straight pipe upstream and no flow conditioning. In most applications this would normally be considered an acceptable installation condition. However, immediately upstream of the straight pipe there were three out-of-plane bends. This sort of arrangement of bends is notorious for producing strong swirl. Add to this the fact that low viscosity of LNG results in such high Reynolds numbers that swirl perpetuates for longer than is usual in liquid applications [9] and it is perhaps not so surprising that there would be a significant level of swirl present at the location of the meter.
The presence of swirl was confirmed by analysis of a data log of the individual path velocity data from the meter. Figure 10 shows the normalised path velocities obtained during logging at a flow rate of approximately 400 m3/hr. This pattern, with two paths from Plane A high on one side of the pipe and two paths from Plane B high on the opposite side is typical of swirl.
The velocity profile data obtained from the meter can be used to estimate the strength or magnitude of the swirl. The pair of path velocities at each chord position can be used to yield a transverse (non-axial) velocity, which can in turn be converted to an equivalent tangential (rotational) velocity at the pipe wall. Performing this calculation for the data shown in Figure 10 results in an average tangential velocity equal to 6.5% of the axial velocity. Another way of interpreting this data is to say that the flow undergoes one complete rotation for every 48 pipe diameters travelled.
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Figure 10 - Path velocity information confirming the presence of swirl
The most important thing to note about the Kenai data with respect to swirl is that despite the biases that were present in the results from each plane, the combined result from the 8-path meter was within 0.1% of the Coriolis meter. This clearly demonstrates the immunity to swirl of the 8-path meter configuration. This swirl-immune performance cannot be achieved with simpler 4 or 5-path meter configurations that use single-plane or staggered criss-crossed path arrangements.
6 CALIBRATION AND MEASUREMENT UNCERTAINTY
For high value liquid transfers in the oil and gas industry, it is common practice to calibrate meters in-situ using a volumetric prover. However, at the present time such provers are not available for LNG duties at the temperatures and flow rates required in the application. In future large scale cryogenic provers could be developed, and then their use would be dependent on the capital, operational and maintenance costs relative to the reduction in uncertainty that can be achieved.
The current lack of in-situ proving equipment means that at present meters have to be calibrated in a laboratory environment. This presents a challenge as no test facilities exist that use LNG or other cryogenic liquids and can achieve the flow rates typically required for ultrasonic meters. For example, the NIST cryogenic calibration facility in the USA uses liquid nitrogen and has a maximum flow limitation of around 45 m3/hr (which is around 14 % of the nominal maximum of a 4-inch ultrasonic meter).
To overcome this limitation Cameron applies a methodology that allows calibration of Caldon ultrasonic meters using another working fluid such as water or refined hydrocarbon liquids. The basis of this methodology is a rigorous analysis of the factors affecting the acoustic signals and meter body geometry, and a process that accounts for variations in hydraulic conditions.
The influence of different fluid properties on the acoustic signals can be shown to be relatively small and is included in the uncertainty budget for the final application [3, 4]. Geometry changes are compensated as a function of temperature, which is measured by the meter, and again the uncertainty in these corrections are included in the overall uncertainty budget for the gross volumetric flow rate.
The hydraulic correction factor or meter factor is a term used for ultrasonic meters that is analogous to the discharge coefficient of a differential pressure flow meter. Ultrasonic meters are velocity measuring devices that sample the velocity on a discrete number of paths. Therefore this value of ‘discharge coefficient’ for the ultrasonic meter is dependent on the velocity profile of the fluid presented in the meter body.
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The shape of the velocity profile is affected by the flow rate, the pipe diameter, the fluid viscosity, wall roughness and also the form and proximity of upstream fittings such as bends and valves. The effects of flow rate, diameter and viscosity are characterised by Reynolds number (Re), which is a dimensionless quantity that represents the balance of inertial to viscous forces in the flow. Owing to the low viscosity of LNG, the Reynolds numbers experienced in LNG applications tend to be high (Re of 500,000 to 30,000,000 could be expected). Normally it is an aim of the calibration process to cover the Reynolds number range that is expected to be encounter in practice. However, it is not currently possible to achieve the high-end Reynolds numbers in existing liquid calibration facilities owing to the fact that typical calibration fluids have higher viscosity than LNG.
However, the important fact is that the calibration of the ultrasonic meter is dependent on the time averaged velocity profile and not some other property of the high Reynolds number flow.
At this stage in the discussion it is important to emphasise some particular characteristics of Caldon 8-path (and 4-path) meters with respect to axial velocity profile. Caldon meters employ in their design a chordal measurement layout based on Gaussian integration, named after the mathematician Carl Friedrich Gauss. It can be shown in theory (and backed up with laboratory data) that this method of integration results in a very low sensitivity to changes in velocity profile at high Reynolds numbers, including a high degree of insensitivity to asymmetric distortions of the flow caused by pipe bends etc [5, 6].
A second important point about the chordal path layout of the Caldon meter design is that the meter itself can characterise the shape of the velocity profile as a ‘flatness ratio’, which is the sum of the outside path velocities divided by the sum of the inside path velocities. This allows the meter factor to be determined as a function of flatness ratio, as the flatness ratio increases with Reynolds number. Figure 11 below shows the flatness ratio and meter factor derived from experimental velocity profile data for Reynolds numbers ranging from 234,000 to 35,724,000 [7, 8]. It can be observed that the meter factor varies only slightly and that the relationship is linear.
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Figure 11 - Meter factor vs. flatness ratio for the Gaussian configuration
Owing to the low sensitivity of the meter design to velocity profile and the linear relationship extrapolation from the calibration data is possible with very little impact on the overall uncertainty. During calibration the meter factor and flatness is determined. Then during operation the meter calculates the actual flatness and applies the required meter factor according to the slope of the line in Figure 11. This is illustrated for the
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RasGas calibration and operational conditions, where the calibration profile flatness range is shown as a blue band in Figure 11 and the profile flatness range at operational conditions is shown by the green band. By extending the line from the maximum flatness at calibration to the maximum flatness in application it can be observed that the extrapolation applied amounts to a correction of less than 0.05 %.
The calibration methodology described above is well supported by theory and an extensive database of laboratory test results obtained with different meter sizes and different pipe configurations. NMi, the Dutch weights and measures authority, first reviewed this information in 2006 in the process of performing an independent assessment of the calibration methodology for Caldon LNG flow meters [3]. Their assessment included a review of the uncertainty contributions resulting from the effects of operation at cryogenic temperatures on the dimensional and acoustic aspects of the measurements, as well as the meter factor determination. This evaluation was revised in 2012 and extended to include additional calibration liquids and a wider range of application conditions. In this most recent evaluation of the Caldon LNG measurement technology, NMi estimate the uncertainty in gross volumetric measurement to be +/- 0.18 % for calibration using water or refined liquid hydrocarbon [4].
7 LOT-H LNG METERING SYSTEM
As was shown in Figure 3, there are four points where the cryogenic LNG flows to or from the Lot H that must be metered. In accordance with the allocation philosophy, at each of these points there is a metering skid that uses Caldon LEFM 280C 8-path ultrasonic meters as the primary measurement elements. The application data for these four metering skids is shown in Table 1 below.
Table 1 - Lot H metering systems
Density Viscosity Pressure Temp Min Max(kg/m3) (cP) (Bar a) (°C) (t/h) (t/h)
71-Y071 3 x 10" 439.1 0.117 6.4 -161.1 240 1250 No71-Y072 3 x 10" 464.9 0.148 6.4 -161.1 120 1200 No71-Y073 3 x 8" 464.8 0.147 6.4 -161.1 120 950 No71-Y074 2 x 12" 436.1 0.117 6.4 -161.1 220 2250 Yes
Bi-directionalStreamsSystem
Medium Operating Conditions Flow
Each metering skid has a metering computer system and one associated gas chromatograph. A FloBoss S600 flow computer is provided for each metering steam. Data from each flow computer is gathered by fully redundant Flow Metering Supervisory (FMS) computers for display, reporting, alarming, trending and onward data transmission to other systems.
The FMS computers link the communications data to RasGas DCS. A separate OPC server computer provides read-only communications for the QatarGas DCS.
The Caldon LEFM 280C 8-path ultrasonic meters used have the same architecture as the Kenia test meter, consisting of two independent planes of 4-paths. The electronics associated with each plane generate the following outputs:
• Modbus serial communication data • Single-pulse frequency signal representing actual volume flow • Digital fault status • Digital flow direction status
The flow calculated by the computer is referred to standard conditions of 15°C and 1.01325 bar a. The gross volume flow is obtained directly from the output of the ultrasonic meter. Internal to the Caldon LEFM 280C flow meter, a correction is applied to the gross volume flow to compensate for temperature related changes
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in the meter body geometry. Mass flow, standard volume flow rate, and energy flow rate then calculated by S600 flow computer using calculated values of meter density, standard density and calorific value.
There is one on-line Gas Chromatograph (GC) installed on each skid. LNG is sampled from the stream and then sent to an electrical evaporator to change the sample to the gaseous phase prior to the GC analysis. The compositional analysis from the GC is then used as input for the calculation of density and calorific value. In this application, the line density is calculated based on the revised Klosek-McKinley calculation (ISO 6578). For standard density and calorific value the calculations are based on ISO 6976-1995.
8 OPERATIONAL DATA AND EXPERIENCE
At the time of writing this paper the Lot H Caldon LEFM 280C ultrasonic meters have been in service for approximately 38 months. Commissioning of all four systems was carried in a period between July and August 2009. The commissioning process involved checking that the meters had been properly installed and wired on site and then logging and examining diagnostics once the meters were in a flowing condition. No significant issues were encountered during the commissioning process.
From an operational point of view, it is a challenge to validate flow meters on site when operating with cryogenic LNG. Owing to operational and practical constraints, there is no proving facility or separate check meter installed in series with the meters.
The meters in each skid are installed in parallel. Each 8-path meter has separate electronics with fully redundant flow rate calculations and can be evaluated as a combination of a 4-path duty meter and a 4-path check meter. Therefore it was not considered necessary to provide a means of series operation of the meters in one skid. During operation it is of course possible to compare the flow rates from the meters that are operating in parallel. As would be expected, there are differences among the streams caused by the differences in natural flow resistance (pressure loss) that create an unequal distribution of the flow.
A method that has been used to establish confidence in the meters is the analysis of diagnostic data from the meters. This capability to produce detailed diagnostics is one of the benefits of ultrasonic meters in these applications.
From the meter diagnostic data it is possible to determine the health of the meter electronics and transducers, the performance and also the process conditions that the meter is measuring.
The health and performance are monitored by individual by individual path by path analysis of Path Performance, Automatic Gain Control and Signal to Noise Ratio.
Path Performance –qualified pulses received and used in the measurement as a percentage of pulses transmitted, displayed per path.
Automatic Gain Control (AGC) – the level of amplification applied to the signal received by the transducer to account for changes in operating conditions.
Signal to Noise Ratio (SNR) – the quality of the signals received by the transducers in terms of the ratio of signal strength to background noise.
Upstream pipe fittings will affect the incoming hydraulics in terms of the amount of non-axial flow (swirl) and the symmetry of the axial flow profile. By comparing the measured velocities on individual paths it is possible to calculate the degree of swirl and asymmetry.
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During commissioning, the diagnostic data was recorded from each meter and was saved as the meter’s signature or baseline. As part of the regular checks performed on the metering systems, every month a data log is recorded and compared with the baseline for individual path analysis for Plane A and Plane B of each meter.
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Plane A (SNR)P1 A (SNR)
P1 A (SNR)_Start Up
P2 A (SNR)
P2 A (SNR)_Start Up
P3 A (SNR)
P3 A (SNR)_Start Up
P4 A (SNR)
P4 A (SNR)_Start Up
Figure 12 - 71Y073 Stream A, Meter S/N 070703003 Plane A monthly analysis
5152535455565758
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P2 B (Performance)
P2 B (Performance)_Start Up
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P3 B (Performance)_Start Up
P4 B (Performance)
P4 B (Performance)_Start Up
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P3 B (SNR)_Start Up
P4 B (SNR)
P4 B (SNR)_Start Up
Figure 13 - 71Y073 Stream A, Meter S/N 070703003 Plane B monthly analysis
It can be seen in Figure 12 and 13 that by trending the monthly data against the base line data obtained from commissioning, long term stability from start-up of the meter becomes apparent.
14
The velocity of sound (VOS) ratio for each plane can then be derived from the individual path velocities to display the operating characteristics in the form of a curve and also to monitor drift over time. When compared to the VOS Ratio from commissioning, as per Figures 14 and 15, it can be demonstrated that the ratio has remained within +/- 0.01% of the base line, further enhancing confidence that the meter conditions have not changed. This is an important parameter as the VOS is derived from the same transit time measurements and geometric information that is used for the flow measurement. Therefore stable VOS values over time give a strong indication that every part of the meter is operating as expected.
0.9994
0.9996
0.9998
1
1.0002
1.0004
P1 A (VOS) P2 A (VOS) P3 A (VOS) P4 A (VOS)
Ratio
Plane A VOS Ratio Curve 23/01/2011
20/02/2011
23/03/2011
20/04/2011
18/08/2011
26/09/2011
31/10/2011
21/11/2011
26/12/2011
23/01/2012
27/02/2012
26/03/2012
4/25/2012
5/27/2012
6/27/2012
7/24/2012
18/01/2013
Start Up
( + 0.01%)
( - 0.01%)
0.99955
0.99965
0.99975
0.99985
0.99995
1.00005
1.00015
1.00025
1.00035
23/01/2011 20/02/2011 23/03/2011 20/04/2011 18/08/2011 26/09/2011 31/10/2011 21/11/2011 26/12/2011 23/01/2012 27/02/2012 26/03/2012 4/25/2012 5/27/2012 6/27/2012 7/24/2012 18/01/2013
Ratio
Plane A VOS Ratio Against Time
P1 A (VOS)
P1 A (VOS)_Start Up
P2 A (VOS)
P2 A (VOS)_Start Up
P3 A (VOS)
P3 A (VOS)_Start Up
P4 A (VOS)
P4 A (VOS)_Start Up
Figure 14 - 71Y073 Stream A - Meter S/N 070703003 Plan A VOS Ratio
15
0.9996
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0.9999
1
1.0001
1.0002
1.0003
1.0004
1.0005
P1 B (VOS) P2 B (VOS) P3 B (VOS) P4 B (VOS)
Ratio
Plane B VOS Ratio Curve 23/01/2011
20/02/2011
23/03/2011
20/04/2011
18/08/2011
26/09/2011
31/10/2011
21/11/2011
26/12/2011
23/01/2012
27/02/2012
26/03/2012
4/25/2012
5/27/2012
6/27/2012
7/24/2012
18/01/2013
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( + 0.01%)
( - 0.01%)
0.99955
0.99965
0.99975
0.99985
0.99995
1.00005
1.00015
1.00025
1.00035
23/01/2011 20/02/2011 23/03/2011 20/04/2011 18/08/2011 26/09/2011 31/10/2011 21/11/2011 26/12/2011 23/01/2012 27/02/2012 26/03/2012 4/25/2012 5/27/2012 6/27/2012 7/24/2012 18/01/2013
Ratio
Plane B VOS Ratio Against Time
P1 B (VOS)
P1 B (VOS)_Start Up
P2 B (VOS)
P2 B (VOS)_Start Up
P3 B (VOS)
P3 B (VOS)_Start Up
P4 B (VOS)
P4 B (VOS)_Start Up
Figure 15 - 71Y073 Stream A, Meter S/N 070703003 Plane B VOS Ratio
The second method of validation that has been used is the comparison the ultrasonic allocation metering systems against production meters. As the production metering systems are not designed or operated to allocation standards, it is not a highly accurate means of checking the meters but it does serve to increase confidence that there are no large scale errors. An analysis of this sort has been performed by comparing the ultrasonic meters with the production orifice meter over a period of 1 month. The result was an average difference of 0.625 % between the ultrasonic meters and the production meter. Given that the uncertainty in the discharge coefficient of an orifice plate is 0.5 % at best, and that the production metering system does not comply with all of the provisions of ISO5167, the uncertainty of the production metering is estimated to be greater than +/- 1 %. As such this difference of 0.625 % is clearly less than the measurement uncertainty of the production orifice metering.
The third method used for the validation of these meters is to utilise the LNG mass balance model within RasGas Hydrocarbon Accounting system. Sigmafine is the software used to provide the framework to collect, monitor and reconcile inventory and production data. There are two types of data source, which are automatic and manual.
Automatic data from the Real Time Information System (RTIS) include fluid quantity from meter, fluid quality from analyser and inventory from tank levels. Manual data is input for cargo loading and transfer of Lot H to/from Lot N.
An overview of the allocation meters to loading berth can be seen in Figure 16.
16
Figure 16 - Lot H LNG mass balance model
The methodology for this model is to subtract daily tank inventory, loading, Boil Off Gas (BOG) for fuel and to flare, transfer from Lot H to N from the total production measurement through the LNG meter systems 71-Y071,71-Y072, 71-Y073 and transfer from Lot N to H. This calculation is described below in Calculation 1.
Calculation 1 - Lot H LNG mass balance calculation
The inputs to the systems can be summarised as follows:
• Ultrasonic flow meter based metering systems for measuring the total Lean and Rich allocated product, including transfer with an individual design measurement uncertainty of 0.33% on Mass.
• Inventory level of the tank is continuously measurement with dual redundant ENRAF Honeywell Automatic Tank Guage (ATG) system with associated measurement uncertainty better than 1% per tank.
• Ship loading is also continuously measured, normally with Radar level system with a measurement uncertainty better than 1%.
• BOG fuel gas to supply 4 compressors is measured by the means of orifice and DP flow transmitter with an estimated measurement uncertainty of 3% per meter.
• BOG flare gas is derived by an accumulation for basic orifice meter configuration and calculation from valve position. This will equate to a large measurement uncertainty as flow calculated derived from valve position can have an uncertainty in the region of 30 - 50%.
17
The Lot H Mass Balance for 2011 and 2012 results for total in against total out can be seen below in Figure 17. To ensure the validation of the measurement from the LNG Allocation Measurement system is done accurately and un-biased, the raw measurement data for each contributor has been used. The raw data, or in the terminology of RTIS, Process Value (.PV), is the value prior to being reconciled in Sigmafine by the Hydrocarbon Accounting Department.
Tota
l (To
n)
LNG Mass Balance
Input (Ton)
Output (Ton)
System Restoration
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Diff
eren
ce (%
)
LNG Mass Balance
Balance (%)
Figure 17 – Lot H mass balance 2011 and 2012
As mentioned previously, each 8-path meter can viewed as two separate 4-path meters (plane A and plane B) that can be compared. Under all circumstances, the two planes should produce results that are reasonably close to one another, but as explained earlier in the paper, if swirl is present this will cause a difference between the two planes. Indeed, this is one of the reasons that the 8-path design was selected rather than a lower cost 4-path solution.
As part of the monthly planned maintenance, in accordance with the diagnostic analysis, the flow rate from Plane A is compared to that of Plane B over a 1 hour period. The results of this testing can be seen in Figure 18. It can be observed that the difference between planes is fairly constant, varying at most by about 0.6%, which is about an amount consistent with the swirl sensitivity of the 4-path meter, as demonstrated in the Kenia tests.
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Flowrate Difference
Flowrate Difference_Start Up
Figure 18 - 71Y073 Stream A, Meter S/N 070703003 Plane A vs. Plane B
18
Data from the RasGas metering stations has been analysed to estimate the amount swirl present and compare that with the calibration conditions (where by design there was little swirl). Owing to the favourable hydraulic design of the metering skids, which included 20 diameters of straight length upstream of each meter, in all cases there was relatively little swirl. If calculated in percentage terms in the same way as described earlier, the swirl was always less than 3%. Given the low levels of swirl it could therefore be asked if the 8-path meter actually provides a worthwhile improvement in uncertainty. This question is now examined in detail.
Two examples are used here, one where the meter diagnostics do not show any obvious swirl and another where there is a small amount of swirl. Figures A1 to A4 in the appendix show calibration and operational data from metering system 71Y073 Stream C, Meter S/N 070703002 and 71Y073 Stream A, Meter S/N 070703003. It can be observed that in the case of steam C both during calibration in the laboratory and in operation there is very little difference between the profiles displayed for Planes A and B, and consequently there is also little difference in the reported flow rates. However, if we look at the same data from stream A, we see that good agreement between the Plane A and B profiles existed in the calibration lab, but when installed in the skid, there the profiles are different, as reproduced in Figure 19 below.
An explanation for the swirl observed in the case of stream A can be found by studying the inlet piping to the streams. The arrangement of out-of-plane bends at the inlet on the right-hand side is known to generate swirl. The stream closest to the inlet, where the swirl will be strongest, is stream A, whereas stream C is at the far end of the inlet header, furthest from the out-of-plane bends.
0.8673
1.0293 1.0393
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Plane A Plane B
Figure 19 - Operational velocity profile data from 71Y073 Stream A
Table 2 summarises the data from these two meters. It can be observed that during calibration each of the 4-path planes of both meters agreed to within less than 0.01% of the 8-path result. In operation the meter used in Stream C showed a difference of +/- 0.072% between the 4-path planes and the 8-path result, which means that both of the 4-path planes and the 8-path meter are comfortably within the uncertainty requirements of the application. In the case of Stream A however, we see a different story. In that case, the results show a difference of +/- 0.371% between the 4-path planes and the 8-path results. This means if a 4-path meter had been used (with no flow conditioning), the swirl level present in this stream would have resulted in errors greater than the budgeted uncertainty of +/- 0.2 %, easy justifying the selection of the 8-path design on the basis of the financial cost/benefit analysis associated with this reduction in uncertainty.
19
Table 2 - Summary of 4-path versus 8-path data comparison
Flow rate (m3/hr)
Plane A Plane B Average (8-path result)
Difference between 4-path and 8-path
results (+/- %)
71Y073 Stream C - Calibration 652.7 652.7 652.7 0.007 71Y073 Stream C - Operation 636.1 635.2 635.6 0.072 71Y073 Stream A - Calibration 634.9 634.9 634.9 0.003 71Y073 Stream A - Operation 648.3 643.5 645.9 0.371
9 SUMMARY AND CONCLUSIONS
Key to the success of the common facilities at Ras Laffan is the implementation of in-line, dynamic measurement of LNG rundown from the production trains to enable allocation of production back to the ventures involved in the project.
Ultrasonic technology has been evaluated, implemented, and validated throughout the service for LNG allocation metering. In this application, ultrasonic technology is advantageous over other meter types owing to its non-intrusive low pressure drop design. The Caldon 8-path meter design does not require flow conditioning, which is a further advantage in this respect.
Calibration of flow meters for LNG applications still remains a challenge owing to the lack of test facilities that operate at appropriate conditions. This potential limitation can be overcome by using ultrasonic meters, but only if the particular meter design has the following two features:
1) A low sensitivity to changes in velocity profile at high Reynolds numbers, and
2) The ability to measure the velocity profile shape and apply a correction.
The methodology applied in the Caldon LNG meters has been independently assessed and it can be shown that the velocity profile based extrapolation from laboratory to field conditions contributes very little additional uncertainty.
The meters operated by RasGas were commissioned without difficulty and have now been in continuous service for 38 months without the occurrence of any problems.
By trending the data obtained from the meter diagnostics on a monthly basis and making comparison with the base line from commissioning proves that the condition and performance of the meter has not changed. This check allows for each meter to be individually verified as it is independent to the measurement system.
The approach of using diagnostics to monitor the meter health will be investigated and validated further in combination with RasGas plans for performing a flow laboratory calibration check on these meters.
The mass output from each LNG Allocation Measurement system has been checked against the corresponding Train LNG production meter. As already stated, this comparison is a less accurate and reliable due to the production meter not being in compliance to ISO5167. There is a maintenance program in place to verify differential pressure transmitter and input to DCS for flow computation. This has been verified to be within +/- 3% of calculated value.
When looking at the mass balance for Lot H, the total LNG measurement can be assessed. All inputs to this mass balance have planned maintenance schedules to comply with their associated measurement classification and to ensure measurement uncertainty is maintained. The main contribution to error in this method is the BOG Flare Gas due to valve position being used to calculate flow rate. However, as the flare
20
gas is an averaged 0.2% of the total production during 2011 and 2012, the overall effect will be insignificant. The mass balance analysis for the total LNG production is only meaningful when in-line dynamic measurement with a low uncertainty is used in the manner proposed at the outset of this project. The mass balance data presented in this paper vindicates the use of in-line dynamic measurement for this purpose.
In summary it can be concluded that the use of in-line metering has been successful for allocation purposes at the RasLaffan site, and that the selection of flow meters with low uncertainty both enables and is justified by the good levels of agreement in terms of the system mass balance.
REFERENCES
[1] PennWell Corporation, Oil & Gas Journal, Vol. 106.48 (December 22, 2008) [2] Mullally, M, Stobie, G J, and Salavudheen, K H (2007) “In-line measurement of LNG for fiscal
allocation”, 15th International Conference & Exhibition on Liquified Natural Gas, Poster #56 Handout, Barcelona, Spain, April 2007
[3] van Wijngaarden, H and van der Grinten, J G M (2006) Evaluation of the Caldon scaling methodology
to convert water calibrations of an ultrasonic meter, type LEFM, into an LNG meter curve, NMi Report No. C-SP/606627-HvW/Rap
[4] van Rooy, P A W (2010) Evaluation of the calibration methodology applied to Cameron LEFM
ultrasonic meters for high Reynolds numbers and extreme temperatures, NMi Report No. C-PC – 10200743 – PR – 01
[5] Moore, P I, Brown, G J and Stimpson, B P (2000) “Ultrasonic transit-time flowmeters modelled with
theoretical velocity profiles: methodology”, Measurement Science and Technology, Vol. 11, No. 12, pp 1802-1811.
[6] Brown, G J, Augenstein, D R and Cousins, T (2006) The relative merits of ultrasonic meters employing
between two and eight paths Proceedings of the 5th South East Asia Hydrocarbon Flow Measurement Workshop, Kuala Lumpur, Malaysia.
[7] Zagarola, M V and Smits, A J (1998) Mean flow scaling of turbulent pipe flow, J. Fluid Mech, 373, 33 -
79. [8] McKeon, B J, Li, J, Jiang, W, Morrison, J F and Smits, A J (2004) Further observations on the mean
velocity in fully-developed pipe flow, J. Fluid Mech. 501, 135 - 147. [9] Halsey, D M (1987) Flowmeters in swirling flows, J. Phys. E: Sci. Instrum., 20, pp1036 – 1040.
21
APPENDIX
0.8568
1.0324 1.0439
0.87860.8575
1.0372 1.0418
0.8685
0.70
0.75
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0.95
1.00
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Plane A Plane B
640
642
644
646
648
650
652
654
656
658
660
13:27:49 13:36:09 13:44:29 13:52:49
Flow
Plane A Plane B
Figure A1 - Velocity profile and flow rate data acquired during calibration
Ras Laffan 71Y073 Stream C, Meter S/N 070703002
22
0.8799
1.0371 1.0301
0.88710.8868
1.0366 1.0318
0.8759
0.70
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Plane A Plane B
610
615
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625
630
635
640
645
650
12:00:01 12:08:21 12:16:41 12:25:01 12:33:21 12:41:41 12:50:01 12:58:21
Flow
Plane A Plane B
Figure A2 - Velocity profile and flow rate data acquired during operation
Ras Laffan 71Y073 Stream C, Meter S/N 070703002
23
0.8532
1.0399 1.0389
0.87350.8674
1.0335 1.0428
0.8681
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
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Velocity vs. Path Position
Plane A Plane B
625
630
635
640
645
650
12:00:01 12:08:21 12:16:41 12:25:01
Flow
Plane A Plane B
Figure A3 - Velocity profile and flow rate data acquired during calibration
Ras Laffan 71Y073 Stream A - Meter S/N 070703003
24
Figure A4 - Velocity profile and flow rate data acquired during operation
Ras Laffan 71Y073 Stream A, Meter S/N 070703003
