SPE-170853-MS

Enhancements in Fraction Measurements and Flow Modeling forMultiphase Flowmeters

D. Chazal, M. Fiore, G. Jolivet, A. Lupeau (OneSubsea), C. Toussaint, B. Fournier, and F. Hollaender,Schlumberger

Copyright 2014, Society of Petroleum Engineers

This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in Amsterdam, The Netherlands, 2729 October 2014.

This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contentsof the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflectany position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the writtenconsent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations maynot be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

Multiphase flowmeters (MPFMs) have been used since the early 1990s in the oil and gas industry andhave gained acceptance in many environments. They have been considered the primary metering optionfor a wide range of applications - from heavy oil to wet gas. The combination of operational benefits,measurement robustness, demonstrable accuracy, and auditability has improved their status from new,unproven technology to that of the premium mainstream metering option.

With more than a decade of experience acquired using a combination venturi and gamma-raymultiphase flowmeters, further gains in measurement quality and operational robustness have beenachieved. We will illustrate how enhancements in fraction measurements using multi-energy gamma rayattenuation and a more comprehensive analysis of the gamma-ray spectrum have been developed andimplemented to provide better measurement accuracy and stability, leading to enhanced performances inmultiphase flow measurements.

Another area of improvement that has been pursued is in the field of modeling of multiphase flowsthrough a venturi. Historically, single-phase flow equations have been used, being adapted to multiphaseflows by semi-empirical means to account for their complexity. While such models have proven robustfor most standard applications, they can reach some limitations in particular conditions. We will presenthow a more dynamic model that considers the nature of the flow has led to improved accuracy ofmultiphase flow measurements.

We present the scientific basis for the new enhancements as well as illustrate the accuracy gainsachieved based on hundreds of flow loop test points, ultimately leading to the quantification of theaccuracy gains obtained through those technological improvements.

IntroductionSince their development and introduction in the late 1980s and early 1990s, multiphase flow meters(MPFM) have generated significant interest in the oil and gas industry. The primary drivers were initiallyto obtain production estimates from individual wells in conditions where the use of test separators wasimpossible or prohibitively expensive (e.g. subsea installations and small offshore platforms with limitedavailable space), but have since gained acceptance across the industry. It is estimated that more than 6,500

multiphase flow meters have been permanently installed with strong growth forecasted in years to come(Falcone et al., 2011; Yoder, 2013). This covers a wide range of applications from subsea wellhead or riserbase installations, to surface wellheads, test headers, trunk line monitoring or custody transfer measure-ments (Al-Hassaini et al., 2012, Syre et al., 2013). In addition, MPFMs have been deployed as mobiletesting units used in lieu of mobile test separators in applications from exploration and appraisal toproduction. The technologies are now being used in cases where deployment environments, facilitiesdesign, operational constraints and measurement quality are critical, making MPFMs the better option. Forinstance, a large number of subsea developments are now based on the use of commingled riser productionwhere individual well testing is impossible using surface facilities and, therefore, subsea MPFM areproving extremely valuable (Jackson et al., 2012). The same logic of ease of use applies at surface inremote locations (Navarette et al. 2010) but also in operations where MPFM have proven to be reliableand are even considered as references against tests separators (Al-Hammadi et al., 2012).

This rise in interest by the industry has led to numerous developments in the search for the besttechnology, or technologies capable of providing multiphase flow measurements in a wide range ofconditions with high levels of accuracy and moderate sensitivity to input parameters and their associateduncertainty. After early development efforts driven by academic institutions in the 1980s and 1990s,continuous work has been conducted both by large companies already present in the oil and gas industry(in services, instrumentation or facilities) as well as by smaller companies focusing solely on flowmetering. The principles of multiphase flow meters relies on the combination of fraction and velocitymeasurements, and a wide selection of technologies have been used by manufacturers over the years, somebeing already at their third generation of MPFM. More details can be found in previous publications(Falcone et al., 2011; and Pinguet, 2010) but for the sake of illustration, velocity measurements useddifferential pressure measurements (venturi, V-cones), positive-displacement meters, cross-correlationtechniques, ultrasonic Doppler measurements, Coriolis meters, passive and active ultrasonic measure-ments, or tracers. For fraction measurements, the range of technologies deployed is also wide from singleto multi-energy gamma ray, electrical capacitance and inductance/conductance, nuclear magnetic reso-nance, microwave transmission techniques, and near infra-red transmission.

Some specific principles were shown to have limitations when put to the rigor of field conditions, andseveral manufacturers have revised their MPFM architecture principles over the past few years. Thisincluded either replacing one or several core measurement blocks, or providing optional added measure-ments to improve accuracy, or completely changing the principles, either as a replacement of existingmeters or to target specific markets (Agar, 2010; Emerson Process management, 2013). It is not surprisingthat such a large technological turnover has been observed in a still relatively young domain. Indeed, mostof the MPFM are barely more than 10 years old, and still partly on the learning curve. What becomesinteresting to analyze in such environments is explaining why some principles have failed as well asrecognizing which principles have been kept.

Two core technologies have proven reliable in the field of multiphase metering: venturi meters for flowvelocities and gamma ray measurements to determine fractions of oil/water and gas. The MPFM providersthat can be considered as market leaders use both of these principles. It may be argued that, in someinstances, the use of radioactive-based measurements is considered optional; but in all cases this remainsthe best way of achieving optimal measurement accuracy (Pietro Fiorentini S.P.A., 2014; EmersonProcess Management, 2012; Weatherford, 2010). A key benefit of fraction measurements based ongamma ray attenuation is that it offers a straight path of measurement across the fluids independently oftheir distribution, whether oil, water, or gas continuous and therefore offers the ability to identifydispersed fluids entrapped in other phases, which is particularly important when considering emulsions orfoaming flows. Such measurements can also be performed with very good accuracy. Venturi metersbenefit from a simplicity of structure and ability to operate without the need for intrusive or movingelements potentially prone to damage, as well as from not relying on strong assumptions about the

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distribution and stability of various phases in flow such as would be the case of ultrasonic, Doppler orcross-correlation-based measurements (Huang et al., 2013).

While those two technological blocks have been at the core of most of the multiphase meters, theimplementations have been various. First, in a majority of cases, a single-energy gamma ray measurementis used (i.e., based on the determination of attenuation at a single photon energy level). In those cases, onlya single piece of information is obtained from that measurement, typically related to the split between gasand liquid phases linked to mixture density, and additional information is required to determine thefraction of three phases. This usually comes in the form of a measurement focusing on water content basedon the contrast in electromagnetic properties between water and hydrocarbons, or can also consist of adedicated water-cut measurement to split liquids between water and oil. This generally requires perform-ing measurements at multiple locations since the mechanical design required to collocate pressure tapping,gamma ray measurements, and electromagnetic probes or electrodes becomes very difficult to realizewhen considering the various metallic penetrations required. In such situations, the multiplicity ofmeasurements raises issues regarding the representativeness of correlating observations performed atmultiple locations at the same time in inherently chaotic and unstable flows.

Those observations, combined with significant in-house development work on alternative technologiesand subsequent analysis, led to focusing on a simple design that allowed for all measurements to beperformed at a high frequency at a single measurement cross-section. This removes the need for stringentflow conditioning or complex correlative interpretation of measured flow velocity and fractions. Themultienergy gamma ray measurement principle was employed at the throat of the venturi tube, providingboth total flow rate and all three fractions at a single cross-section. This technology was commerciallyintroduced in 2000 (Theuveny et al., 2001) and has since been used extensively in wide-rangingapplications after an early focus on standard black oil wells. The technology principles have been provenrobust enough to cover applications from heavy oil (Pinguet 2012) to gas condensates (Lomukhin 2011)while providing excellent metrological performance.

However, while the fundamental principles are sound and validated by the multiphase flow meteringindustry and by returns of experiences, there are still gains achievable through improvements of theacquisition and interpretation of the acquired signals. The summary of several years of work in that fieldthat have led to the launch of an evolution (JPT 2014). The initial interest in MPFM focused on high-valuewells producing at high rates and with low to moderate water cuts, with expectations of the meters toprovide reasonable accuracy for monitoring purposes. Today, more and more applications call fordeployment in either low net oil producers or, at the other end of the spectrum, for better accuracy toaddress fiscal or custody transfer applications, which have been tackled as part of this work.

In the following, and after providing some background on the main principles used, the workperformed on three main axes will be presented: enhancements in fraction measurements via a morecomprehensive interpretation of the measured gamma ray response; refinement of the flow modelingunder multiphase conditions, and improvements in the configurability and ease of maintenance of themeters.

Principles of multienergy gamma ray/venturi MPFMThe fundamental interpretation workflow of multienergy gamma ray/venturi MPFMs can be decomposedin three main blocks:

Determination of flowing phase fractions from the gamma ray measurements using at least twodistinctive energy levels

Determination of total mass rate flowing through the meter, leading to the determination of theflow rates of each phase at metering conditions after the application of slippage effect

SPE-170853-MS 3

Conversion of flow rates from metering pressure and temperature to the appropriate pressure-temperature standard conditions.

Fraction determination using gamma ray measurements

Determining flowing fractions based on multienergy gamma ray measurements relies on the response offluids to two different phenomena occurring within the range of photon energy in use: Compton(incoherent) scattering and photoelectric absorption. Both phenomena are related to the interactionbetween gamma ray photons and electrons present in the atoms of the flowing mixture. For furtherinformation, the reader can refer to Knoll (2000). The primary quantity of interest is the linear attenuationof each phase, which is the product of the density of the fluids by its mass attenuation (attenuating powerfor a unit of density). The attenuation of a fluid to gamma rays is obtained from the Beer-Lambert law(Lambert 1760):

(1)

where Io is the intensity of the incident photon beam; I the intensity of the transmitted beam; and A theabsorbance of the matter. The absorbance can, in turn be expressed as the product of the linear attenuationcharacterizing the fluids and thickness of the fluid penetrated. The linear attenuation coefficient can befurther expressed as the product of fluid density by its mass attenuation coefficient, leading to anexpression of measured counts over a given interval of time:

(2)

where No is the number of photons entering the matter; N the number of photons transmitted; d thethickness of material penetrated; the density of the matter; and its mass attenuation coefficient of thematter.

When considering gamma rays passing through a mixture of fluids, the resulting attenuation can beexpressed as the sum of the contribution of each atom/molecule or phase present in flow as:

(3)

where i is the index of the component and i the volumetric fraction of that component. It is interestingto note that this equation can be re-written in terms of mass fraction i by factoring in the mixture densitymix:

(4)

The mass attenuation coefficient of a given fluid is a strong function of the energy of incident photonsand by extension of the dominating physical phenomena taking place. Photoelectric absorption is an effectwhere an incident photon is absorbed by an electron (bound or orbital), leading to the electron beingejected from the atom. The probability of having photoelectric absorption is higher when the energy ofthe photon is close from the binding energy of the electron. This phenomenon is more likely with atomsof high atomic number because the binding energies of bound electrons are within the range of energiesof gamma ray considered at the lower energy level. The mass attenuation due to photoelectric absorptionobserved at a given energy level can be considered as proportional to the cube of the atomic number, thusshowing significant contrast between various atoms depending on their atomic number. In particular, thisprovides a good contrast between hydrocarbons (dominated by carbon, atomic number 6) and water(dominated by oxygen, atomic number 8).

Compton scattering, or incoherent scattering, is a different effect in which the photon is not absorbedbut collides with a free or weakly-bound electron and transfers part of his energy to it, thus coming outat a different angle and with lower energy/frequency. The probability for this to occur is higher when the

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incident photon energy is significantly larger thanthe binding energy of the electron. The attenuationof photons due to Compton scattering is essentiallyrelated to the electron density of the fluids and thusto a large extent to the density of the fluids them-selves. This is not a perfect correspondence though,as the electron density varies between atoms (Figure1). In particular, hydrogen (which does not have anyneutrons) has a higher electron density compared toother atoms. This means that, as shown in Figure 1,there exists a contrast between light hydrocarbons(with a high ratio of hydrogen to carbon atoms),long hydrocarbon chains (with nearly two hydrogenatoms per carbon atom), and other molecules suchas CO2 not bearing any hydrogen.

Other effects can take place such as pair produc-tion or Rayleigh (coherent) scattering but those areeither not active in the range of energies consideredhere or have a negligible contribution and will notbe discussed further.

To illustrate how different components respondat different photon energy levels, Figure 2 shows themass attenuation coefficient of various fluids (CH2representing long-chain hydrocarbons that would befound in oil, CH4 as an analog to gas, H2O forwater, and CO2 as a reference of hydrogen-freemolecule) at different energy levels, splitting thecontribution of each effect. This clearly shows how the combination of high-energy gamma raysmeasurements (above 70 keV) with low energy measurements can provide solid indications about oil,water and gas content in flow. The high-energy measurements show similar mass attenuations for thevarious fluid types and the measured linear attenuation will essentially depend on the mixture density(even though it cannot provide a direct measurement of density) and will therefore strongly relate to thegas fraction. The low-energy measurement will additionally show a strong contrast between hydrocarbonsand water and can therefore be used to determine the water fraction.

Using those two independent measurements as well as knowing that the sum of oil, water, and gasfractions is equal to one, the flowing fractions are then determined by solving the following system ofequations:

(5)

This can then be used to determine mixture density and perform flow-rate calculations based on themeasurement of differential pressure across the venturi.

Flow rate calculations at metering conditionsDetermining flow rate using a venturi tube is customarily used in the oil and gas industry as well as manyothers. It relies on Bernoullis principle, which states that a change of velocity in a fluid flowing througha pipe will induce a change in pressure. When combined with the mass conservation equation, this leadto the typical venturi equation:

Figure 1Ratio of electron over molar weight for different atoms andmolecules.

Figure 2Mass attenuation of various fluids (dashed photoelectric;dotted Compton; solid linetotal attenuation).

SPE-170853-MS 5

(6)

where Q is the mass flow rate; Ath the throat cross-sectional area; Dth and Din the throat and inletdiameters of the venturi tube respectively; P the measured differential pressure; g the acceleration ofgravity; is the mixture density, and h the height difference between the inlet and throat pressure tappingpoints used to measure differential pressure. The frictional losses in the venturi and the effect ofcompressibility are taken into account by means of two corrective factors respectively called dischargecoefficient and expansion factor. Discharge coefficient and expansion factor are normalized in ISOstandard 5167 (ISO 2003). The performance of venturi flow meters relies on the uncertainty of:

machined venturi geometry performance of the transmitters used knowledge of the fluid properties inputs (density and viscosity) discharge coefficient and expansion factors estimation

For multiphase flows, it is necessary to adapt the standard venturi equation to account for additionallosses due to the turbulent nature of multiphase flow in addition to discharge and expansion terms(Atkinson et al., 2000). This leads to determining the total flow rate through the meter that is then splitinto the flow rate of gas, oil and water according to measured phase holdups and the application of aslippage relationship. It is assumed that there is no slippage between oil and water thanks to flowconditioning via a blind-T spool located at the inlet of the meter that provides efficient mixing.

It is important to note that the determination of a slip law is not straightforward. The strength of thecurrent model relies on a very large database of tests point (over 12,000 test points) considering the largestpossible range of flow conditions. Trying to map velocities based on multiple cross-pipe measurementshas not yet been achieved at the required resolution level to allow for such claims. Instead, the solutionconsisting of performing all measurements at a single pipe location and at a high frequency allows for thelocal application of slippage without relying on a specific flow distribution assumption.

Conversion of flow rates to standard conditionsPerforming flow-rate conversions from measurement conditions to an agreed set of standard conditions isa requirement for any metering device to provide normalized data for production and reservoir engineer-ing use, or for production reporting purposes. This is well-known when using test separators where theflow rate of oil measured at separator pressure and temperature is converted to standard conditions eitherexplicitly through the application of a shrinkage factor or implicitly by calibration of the sensor readingsagainst a tank measurement, yielding a combined meter factor (CMF) accounting for both sensorcalibration against test fluids and oil shrinkage. Fluid properties are also required on reported gasmeasurements to account for gas deviation but also to consider the amount of gas released from the oilwhen flashing live oil to standard conditions (the dissolved gas-in-oil ratio being known as Rst or GOR2in well testing parlance).

This conversion process relies on a mass-conserving fluid properties model, ensuring that a consistentset of fluid properties is used for the various properties. A comprehensive conversion process is illustratedin Figure 3, and can be summarized in two main behaviors:

volumetric change of fluids between metering conditions and standard conditions: oil and watershrinkage (bo and bw respectively) and gas expansion (bg) factors

phase changes characterizing the amount of gas in solution in the liquids (Rst and Rwst for gasdissolved in oil and water respectively) as well as liquid condensing from the gas phase (rgmp forliquid condensate, rgwmp for water steam condensing out from the gas).

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Leveraging information from the full gamma ray spectrumThe metering principles described above have been those used since the first commercial deployment ofour multiphase metering technology and though the range of application has been extended over the years,the fundamental principles have not changed (Atkinson 1999). One characteristic of a multiphase meteris the use of a 133Ba isotope as a source of gamma rays. This source has several advantages:

a half-life of over ten years, allowing it to be used for at least twenty to thirty years withoutreplacement, while not creating major disposal issues (a source can be used for several half-livesas long as enough counts are measured without significant effect on the signal to noise ratio)

the possibility to use a low-activity source (10mCi) thanks to a design using pressure-retainingceramic windows that allow for the passage of gamma rays, removing the need for a high-activitysource required when having to penetrate metal pipes

a highest gamma ray energy level around 380 keV, reducing the need for heavy shielding no associated emission of alpha particles such as emitted by 241Am that are extremely harmful oreven significant emission of beta particles (133Ba is generally considered as a gamma ray onlysource)

a spectrum that bears several energy lines within the range of interest, at around 32 keV (in factseveral lines at very similar energy levels) and 81 keV respectively, in addition to several lines athigher energy levels above 270 keV, with the dominant one being at 356keV.

With this combination of HSE and information content benefits, 133Ba proved to be a very suitableisotope to the purpose of fraction determination through dual-energy gamma ray measurements, providingmore measurements than required for cross-validation purposes or to potentially obtain additionalinformation about the flow content (Pinguet et al., 2010). However, there are specific challengesassociated with the complexity of the spectrum of this barium isotope. The primary one is related to theimperfections of gamma ray detectors.

A scintillation detector operates as follows (Knoll 2000):

Each gamma ray entering the detector if first transformed into light with an intensity proportionalto the energy level of the incoming photon.

That light then enters a photomultiplier tube (PMT) that converts that light into electrons andamplifies the signal, thus generating an electrical pulse

That pulse is then converted into a shaped pulse that is analyzed through an electronics board tointerpret the signal and provides counting statistics as a function of incoming gamma ray energylevel

Figure 3Conversion process from multiphase conditions to standard conditions.

SPE-170853-MS 7

This process is illustrated on Figure 4.As is the case with any measurement, there are

imperfections related to such a nuclear system. Twoof which are of particular interest here and arerelated to the crystal and to the photomultiplier tube.Gamma rays emitted by radioactive isotopes aregenerated at very specific energy levels driven bythe isotope decay mechanism and associated quan-tum effects. When considering a narrow beam,those enter and exit the flowing fluids without mod-ification of their energies; however their measure-ment itself does affect the captured spectrum.

Considering the crystal first, a large majority of incident gamma rays may be properly captured andrecorded but the process of Compton scattering may take place in the crystal itself, leading to thegeneration and deposition of gamma rays of lower energy levels inside the crystal. In that situation, thedetector would record the energy of the main incident photon but also that of the scattered photon. Thosesecondary recordings can only occur at energy levels equal to or lower than a specific limit, called theCompton edge and corresponding to the energy of the photon generated from a head-on collision with anelectron. In addition to that effect, multiple collisions may also occur, creating measurements spanning thefull range of energies up to the total incident energy. This means that when measuring the gamma-rayspectrum of a single-energy photon source, a continuous spectrum of light will be emitted by thescintillator crystal and will be fed to the photomultiplier tube (Figure 5).

Then, in the process of converting the incident light into an electrical pulse, spectral smearing occursdue to the limited resolution of the measurement system. The output of the PMT is, in essence, a numberof electrical charges proportional to the number of gamma rays deposited in the crystal. However, due tothe statistical nature of the electron multiplication process, the output charge can vary from one event tothe other. This fluctuation follows a Poisson process which results into a broadening of the wholespectrum. The recorded spectrum then loses in sharpness and covers a wide range of energies besides theprimary incident one of interest (Figure 6).

The phenomena described above influence any radiation measurement, where the non-idealities of thesystem have to be taken into account when interpreting the data. It is not possible to focus themeasurement on a narrow range of energies since this would mean ignoring a potentially large number ofphotons whose signal has been smeared out of the range of recording, while considering a wide-enoughwindow requires applying a correction for signal stemming out of single or multiple Compton scattering.

When considering measurements targeting multiple levels of energy, this implies also that measure-ments performed at lower energy levels have to be corrected for contamination by Compton scatter fromhigher energy gamma rays. Since those effects are related to the detector system, they can be studied andproperly accounted for through calibration to determine correction coefficients. Such corrections dorequire proper detector control to account for aging of the scintillation crystal and associated electronics,

Figure 5Energy spectrum deposited on a crystal from a single-energyincident photopeak.

Figure 4Gamma-ray measurement chain when using a scintillation detector.

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affecting the efficiency of the system as well as the conversion from charged pulse energy to theappropriate gamma ray energy level.

When considering the incident spectrum of a 133Ba isotope, a significant number of different gammarays are generated by the decay process of that radioactive source as shown on Figure 7. It is particularlyclear that the higher-energy gamma rays will create a measured spectrum overlapping with the lowerlevels of energy used for interpretation purposes (the group in the range from 30 to 34 keV and the twopeaks at 81 keV). Historically, this effect has been accounted for through the determination of appropriatecorrection factors obtained from extensive laboratory measurements on the detector system used, and bymeans of detector control in terms of temperature regulation and signal gain control. The interpretationis then based on the measurement of gamma ray counts over specific windows of energy around the peaksof interest, with the higher energy emissions (above 240keV) being taken as one.

While this approach has proven over the 14 years of deployment in the field, it was clear that thisremained an imperfect way of properly accounting for incident gamma rays and that many incident countsof moderate intensity were ignored in the process. To close that gap, it was decided to update theacquisition and interpretation principles to perform a more comprehensive analysis of the measured signal.

Fundamentally, the effect of detector imperfections in measurements can be understood since thisdepends on well-known Compton scattering effects in the energy deposition process in the crystal, and canbe modelled. Similarly, spectral smearing is an intrinsic property of the detector system that can also beaccounted for. The implication of this ability to properly model the measured spectrum obtained from amono-energetic beam is that when considering a source emitting gamma rays a multiple energies, themeasured spectrum can be modeled by superposition of signals.

Considering that the counts deposited on the crystal at a level of energy e due to an incident gammaray at a level of energy e can be expressed by the crystal response function h(e,e) the deposited signald(e) can be expressed as: the sum of the contributions from all gamma rays :

Figure 6Impact of measurement chain on recorded gamma ray spectrum.

Figure 7Incident spectrum of 133Ba.

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(7)

where i(e) denotes the intensity of incident gamma rays at an energy e. At a second stage, themeasured response s(e) can then be considered as the convolution product of the deposited signal with thespectral smearing kernel (PMT response) g(e,e) as:

(8)

As the incident signal is not continuous but consists of a discrete set of energies, and considering thatthe measurement will bin data into sets corresponding to specific energy ranges, we can express the aboveequations in discretized matrix form:

(9)

where S is the vector of measured gamma ray counts at various energy levels of dimension nm; G isthe PMT response kernel; H is the deposition kernel; and I is the incident gamma ray intensity vector ofdimension nin.

To accurately determine the true incident gamma rays present in the vector I, two modifications wererequired in the acquisition and interpretation chain. The first is to acquire not just gamma ray counts overspecific ranges of energies but to perform a full spectrum measurement across the range from very lowenergies to significantly above the highest peak (at 384keV for 133Ba). In the new system, the measuredspectrum is captured over 512 bins of energy ranges using a dedicated multichannel analyzer (MCA), thusproviding a detailed signal for analysis. Having the measurement available, it was also required to buildan adequate interpretation scheme to obtain the incident energy vector I from the measured smeared signalS and the characteristic response matrices of the detector system G andH through a deconvolution processminimizing the appropriate error function to match noisy measurements to the modeled response. We cannote that since nm is significantly larger than nin, we have a strongly over-determined system to solve. Thisprocess is illustrated on Figure 8, showing a measured spectrum (gray bars) decomposed into thecontribution of the various incident energy levels presented in Figure 7. The modeled spectrum is the sumof the gamma rays emitted by each contributing energy line, whose intensity is determined as part of thesolving process.

Figure 8Decomposition of the full measured spectrum into the contribution of individual incident gamma ray energies.

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The acquisition system and interpretation model were extensively tested in static laboratory conditions,using materials of known attenuation for reference to ensure the correctness of the response againstexpected attenuation, as well as performing extended stability tests of the measurement system underelevated temperatures to simulate accelerated aging of the components.

This comprehensive formulation enable significantly improving the quality of measurements. First,moving away from windowed counts around the energies of interest to the comprehensive interpretationof the full spectrum means that every measured photon is now used in the analysis. This leads not onlyto better measurement statistics- only functions of the intrinsic behavior of naturally-decaying isotopesand not anymore of the counting system - but also provides a better analysis of the signal between itsindividual components, splitting the various energy lines at very high levels of energy as well as addinglow-intensity intermediate lines at 53keV and 161 keV that were previously not taken into account.Second, as the detailed spectrum is measured, the health status of the detector can easily be assessed andits controls automated to ensure that measurement efficiency is maintained via feedback control loops.Besides ensuring the long-term stability of the measurement, this also significantly reduces the need forthermal regulation of the detector system. This makes it possible to use a simpler system, operated atambient conditions while providing excellent measurement stability and consistency. Third, as the signalquality is enhanced, the technology can be used in an extended range of application where a low mixtureattenuation is measured, typically small pipe diameter allowing targeting low producers, as well asproviding better measurement quality with low-attenuation fluids, typically in high gas content applica-tions. When either d or the linear attenuation product . in equation (2) is small, the difference betweenemitted and measured counts N-No is small. Since this is the signal of interest, a measurement error of onlya few counts can have significant impact on the accuracy of the measurement, which has historically beena limiting factor to the development of small-size meters. With an enhanced measurement based on thefull-spectrum deconvolution, it was possible to expand the range of operations down to at least 2-innominal pipe size (19 mm diameter at the throat of the venturi) while keeping high metrologicalperformances.

Enhanced flow modeling under multiphase conditionsMultiphase flow modeling derived from Bernoulli equation can have some limitations when the wholeflow passing through the venturi becomes less homogeneous. In most cases the nature of the multiphaseflow produces heterogeneous distribution of velocities. This can affect the robustness of the flow modelif based on a genuine homogenous distribution assumption. This loss of homogeneity is extremelycomplex to predict and model. There have been multiple attempts to map flow regimes as a function ofsuperficial gas and liquid velocities, but such approaches remain qualitative and are only applicable forthe conditions where they have been established. Furthermore, the flow patterns depend on a large numberof parameters such as fluid density contrast and viscosities, relative velocities of each phase, interactionbetween the phases, and flow conditioning prior to the metering section. Some example behavior areillustrated on Figure 9 and Figure 10 and often several different flow patterns can be observed during asingle flow sequence as large-scale production instabilities occur. Besides flow pattern maps, the use ofdimensionless parameters such as the Lockhart-Martinelli parameter, the Froude number or Ohnesorgenumber are often referred to as ways of assessing the interaction forces between fluids and consequentiallyto evaluate the nature of the flow.

Current flow modeling derived from Bernoullis equation was based on the use of semi-empiricalmodels not assuming any particular fluid distribution and tuned to flow-loop measurements. To properlybuild and validate those models it is crucial to test in a wide range of flow conditions that can be observedin various flow loops. The operating pressure, fluid types, or piping layout of various test loops allowassessing meter performances under a wide range of conditions, starting from standard fluids at moderatepressures available in multiple flow labs but with different installation effects such as long slug lines,

SPE-170853-MS 11

viscous flows (Atkinson et al., 2000), or wet gas andhigh pressure conditions (Brister 2013). In addition,validation under real conditions can also be per-formed from field testing (Theuveny et al., 2001),but in those situations, the reference measurementswould have uncertainty levels significantly higherthan in flow loop conditions, and results have to betaken with proper care and cannot be used for thepurpose of model improvements (Hollaender 2013).Such extensive testing in multiple facilities is re-quired to avoid building models that are biased tothe behavior of one or two facilities.

To properly account for the inherently unsteadynature of multiphase flows, the approach consistingin using collocated fractions and velocity measure-ments and performing the interpretation at a highdata acquisition frequency to properly account forrapid changes has proven very robust to a largenumber of flow conditions. The collocation of mea-surements is critical to ensure consistency betweenthe observations with the throat of the venturi beingthe ideal measurement point. This is where the flowis best conditioned thanks to the acceleration expe-rienced by the fluids and where measurements arelittle affected by upstream flow patterns. As seen in Figure 10 - c, the fluid distribution changessignificantly between the inlet, throat, and outlet section of the venturi tube. At the inlet, a vertical lineof liquid can be clearly seen. This line is in fact static water and does not move along with the other fluidsat the core of the flow. At the venturi throat, the liquid film wetting the wall of the pipe thins down anda higher dispersed fraction is observed due to the acceleration of the fluids. On the divergent section, anear-cylindrical core of gas-dominated fluids flows at a high speed at the center of the pipe while liquiddroplets are shed to the near-wall region and fall back toward the venturi throat against the main flowdirection. This example illustrates how the location of fraction measurement can strongly influence theprocess of flow dynamics estimation when correlating different measurements exposed to differentbehavior.

Using more specific flow models in conditions where the nature of flow can be well estimated hassignificant value, for instance in the presence of wet gas flow (Cadalen, 2009), where fluids can beassumed to be distributed between an annular liquid layer with a few entrained gas bubbles and agas-dominated core with entrained mist. Having that knowledge enables the application of flow modelswith a well-refined velocity profile across the pipe and a proper conversion of measured holdups toflowing fractions under dynamic conditions. An opportunity of improving the computation was identifiedin the recognition of the acting flow-regime and proper consideration regarding the intermittency of flow.This can be evaluated directly from the high frequency nuclear measurement. Recognizing the occurrenceof permanent flow as shown in Figure 11-a is quite straightforward, and such information can be used torefine the flow model. Similarly, in the presence of intermittent flows, the frequency of variations can beused to refine the flow calculations and properly account for the nature of flow.

Such observations linking the behavior of flow through a high-frequency interpretation of flowingfractions proved instrumental in ensuring that both the fractions used as input to the flow model and theflow calculation process provides optimal results.

Figure 9Types of flow-regimes that exist in vertical flow conditions.

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Simplification of the MPFM systemBeside improving the acquisition and interpretation methods to offer more robust and accurate measure-ments, the review of the metering system also considered improvements to the metering hardware aroundthree main axes:

simplification of the meter arrangements ease of operation and maintenance modularity to adapt to operators specific requirements

The physical assembly is presented in Figure 12, with the main components highlighted:

Figure 10Example of flow patterns from high-speed capture - (a) bubbly flow, (b) slug flow and (c) annular dispersed.

Figure 11Nuclear response with stable flow (a) and very unstable flow (b) over a 10-mn period.

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the venturi body of the meter with the associated measurements of pressure, differential pressureand temperature acquired via a multivariable transmitter (within the blue border). Two pressuretapings at the inlet and throat of the venturi are used to measure flowing pressure and differentialpressure. An optimum place for the thermowell temperature sensor was made at the outlet of theventuri, near the throat.

the gamma detector with multichannel analyzer (with red border) is located at the level of thethroat of the venturi, opposite to the gamma-source holder under the cover on the right

the flow computer, along with power and data connectors is located in the small box with the greenborders

To simplify the system, a single multi-variable transmitter is used to provide the standard measure-ments (pressure, differential pressure, and temperature), making the system more compact and reducingthe number of spares if replacement is required. The nuclear detector itself is also fairly standard and doesnot use thermal regulation to maintain its response since the full-spectrum analysis allows for the propertracking and scaling of its response. This has two benefits: limiting the temperature exposure of associatedelectronics and minimizing power supply requirements. The flow computer has been upgraded to followindustry advances, minimizing its size while increasing its data storage capacity to provide full redun-dancy in data capture. It is attached to the meter through a mounting base that makes it hot-swappable,meaning that it can be replaced on site without requiring bleed-off and depressurization of the meter,without creating any risk of sparks in a Zone 1 area.

A significant change in the design of the meter was made to provide significant configurabilityfollowing each operators own standards and requirements. Historically, there has been some level ofcustomization required on each group of manufactured meters to apply specific standards for individualprojects. This has an impact on meter delivery time and cost due to re-engineering requirements, whichshould not be the case for widely deployed technologies. This was achieved by a modular design, makingit possible to build meters combining a large number of options:

meter size piping connection type material of construction certification standards

Figure 12Physical architecture of the meter.

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isolation system of sensors from flowing fluids various options on data connectivity, local display, and power supply

Those changes were implemented with considerations that, with a multiphase metering marketrequiring several hundreds of meters to be manufactured each year, efficiency gains were required in thedesign, manufacturing, and maintenance process. Therefore, a rationalization of the MPFM system wascalled for.

Test resultsAfter significant work on the fundamentals of the data acquisition and interpretation was performed, a firstset of experimental prototypes was built and the meters were used for a first round of flow-loop testing(over 300 test points in three different flow loops) as well as for stability testing. From the lessons learnedwith those units, some revisions were applied to both the meter design and to the data acquisition andinterpretation methodologies and final versions of the meter in various sizes were built and used for testing

Laboratory results in flow loops

The first method of validating performances of multiphase meters consists of using them in flow loopswith high accuracy references to determine metrological specifications. This was initially done in fourdifferent flow loop facilities, with more planned to cover the largest possible range of fluids and flowingconditions. To date, over 600 test points have been captured in different loops with different sizes ofmeters, increasing on a monthly basis.

The output parameters evaluated in multiphase flow loops can be several but, for the purpose ofillustration of the improvements achieved only two that are straightforward to evaluate will be shown, firstthe water/liquid ratio (WLR) to evaluate the gains achieved from the enhanced fraction measurement,second the liquid volumetric rate to illustrate the quality of the flow model over a wide range ofconditions. It is important to note that all the points shown below correspond to relatively short acquisitionperiods, in the range of 7 to 20 minutes. In those situations measurement noise plays a non-negligible part,in particular under elevated GVF conditions. Another point to note is that the lack of data at low gasfractions is essentially due to limitations of the test facilities. In order to perform a representativemeasurement, each individual single-phase meter has to be within its range of calibration and operation.When considering in particular a small meter size, this means that the loop may reach its lower limits interms of range of achievable gas rates and thus cannot be operated on the low end of the GVF range.

Figure 13 shows the WLR (water/liquid ratio) comparison between meter readings and flow-loop data.The data here comes from four different flow-loops, at low (8-10 bara) and moderate (18-20 bara)operating pressures, with light as well as viscous fluids and with various installation setups leading to bothstable and unstable flows. This shows that the deviations are small and for GVF values below 95% providean uncertainty of measurement of less than 2%. This is a reduction of the uncertainty of one thirdcompared with previous specifications and clearly shows the gains achieved.

Figure 14 shows results obtained on total mass flow rates with the 2-in (19 mm throat diameter) meterin three different flow loops. The data there shows no particular bias and excellent performancesvalidating the quality of the flow model in that situation. An improvement in measurement performancescompared with a previous meter version is observed, even though the small size creates a morechallenging environement for the measurement.

Field deploymentIn addition to testing in a controlled environment, multiple units have been deployed in several locationsacross the world to be exposed harsh field conditions. Those units were skidded and are used as mobiletest units to evaluate the response of the hardware system as well as to assess the representativeness and

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Figure 13Comparison of water liquid ratio (WLR) differences between MPFM and flow-loop measurements for a 4-in meter.

Figure 14Comparison of total mass rate differences between MPFM and flow-loop measurements for a 2-in meter

Figure 15Picture of a unit carrying two meters (a 19 mm and a 40 mm venturi) used for mobile field deployment.

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reliability of measurements under challenging environments in terms of ambient temperatures, humidity,shock, and vibrations.

Figure 15 shows a picture of a skid bearing two different meter sizes, providing a large operationalturndown of 50:1 with a compact setup that has been used for field introduction and validation. To date,no equipment failure has been observed from these units, which are used daily. Since this is not in itselfa new technology but an enhancement on a proven one, the units have been used only to demonstrate theoperability of the meter.

Conclusions and way forwardMultiphase metering using a combination of multienergy gamma ray measurements and a measurementof differential pressure across a venturi tube, collocated at the throat section, has proven to be a robust wayof obtaining high-quality multiphase flow rate measurements. Even with fifteen years of experience andcontinuous improvement, some enhancements in the data acquisition and interpretation processes yieldeda significant improvement in the metrological performances. The simple architecture of the meter as wellas the clear benefits of using collocated measurements allowed for a rationalization of the hardwaresystems are of particular interest for a mature market.

While the gains achieved are significant, work is still on-going to optimize measurement quality andits use. The enhancements in the fraction measurement process in particular offer significant opportunitiesto improve performances, but also offering additional deliverables as well as usability enhancements.

AcknowledgmentsSpecial thanks to Michel Brard, Sebastien Cadalen, Bruno Pinguet, Marcus Rossi, and the initialSchlumberger engineering team in Bergen (Norway) involved in the project development process formechanical design, instrumentation, and testing.

Nomenclature

A area / absorbanceD diameterd(e) deposition spectrume measured photon energy levele source photon energy levelg(e,e) spectral smearing impulse responseG spectral smearing kernel matrixh(e,e) crystal deposition impulse responseH crystal deposition kernel matrixI intensity of photon beamI incoming gamma ray vectorIo intensity of source photon beamnin number of incident energy linesnm number of measured energy binsN number of photons (counts per second, cps)No number of photons emitted by the radiation sourceQ mass flow rateq volumetric flow rates(e) smeared spectrumS measurement vector volumetric fraction, or holdup (-)

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mass fraction (-)P differential pressure density (kg/m3)Pmix mixture density (kg/m

3) mass attenuation coefficient (cm2/g or m2/kg)Subscriptsi index numberin inletg gaso oilth throatw water

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Enhancements in Fraction Measurements and Flow Modeling for Multiphase FlowmetersIntroductionPrinciples of multienergy gamma ray/venturi MPFMFraction determination using gamma ray measurementsFlow rate calculations at metering conditionsConversion of flow rates to standard conditions

Leveraging information from the full gamma ray spectrumEnhanced flow modeling under multiphase conditionsSimplification of the MPFM systemTest resultsLaboratory results in flow loopsField deployment

Conclusions and way forward

AcknowledgmentsReferences