Source: http://www.google.com/patents/US20050081643?dq=5,884,272
Timestamp: 2014-07-14 03:36:44
Document Index: 602801201

Matched Legal Cases: ['art 300', 'art 300', 'art 400', 'art 400', 'art 700', 'art 900', 'art 1000']

Patent US20050081643 - Multiphase coriolis flowmeter - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign in<nobr>Advanced Patent Search</nobr>PatentsA flowmeter is disclosed. The flowmeter includes a vibratable flowtube, and a driver connected to the flowtube that is operable to impart motion to the flowtube. A sensor is connected to the flowtube and is operable to sense the motion of the flowtube and generate a sensor signal. A controller is connected...http://www.google.com/patents/US20050081643?utm_source=gb-gplus-sharePatent US20050081643 - Multiphase coriolis flowmeterAdvanced Patent SearchPublication numberUS20050081643 A1Publication typeApplicationApplication numberUS 10/773,459Publication dateApr 21, 2005Filing dateFeb 9, 2004Priority dateFeb 10, 2003Also published asCN102589628A, DE112004000269T5, US7059199, US7207229, US7726203, US8109152, US20060161366, US20080046203, US20110016984, WO2004072588A2, WO2004072588A3Publication number10773459, 773459, US 2005/0081643 A1, US 2005/081643 A1, US 20050081643 A1, US 20050081643A1, US 2005081643 A1, US 2005081643A1, US-A1-20050081643, US-A1-2005081643, US2005/0081643A1, US2005/081643A1, US20050081643 A1, US20050081643A1, US2005081643 A1, US2005081643A1InventorsWade Mattar, Manus Henry, Mihaela Duta, Michael TombsOriginal AssigneeMattar Wade M., Henry Manus P., Duta Mihaela D., Tombs Michael S.Export CitationBiBTeX, EndNote, RefManReferenced by (16), Classifications (22), Legal Events (3) External Links: USPTO, USPTO Assignment, EspacenetMultiphase coriolis flowmeterUS 20050081643 A1Abstract A flowmeter is disclosed. The flowmeter includes a vibratable flowtube, and a driver connected to the flowtube that is operable to impart motion to the flowtube. A sensor is connected to the flowtube and is operable to sense the motion of the flowtube and generate a sensor signal. A controller is connected to receive the sensor signal. The controller is operable to determine a first flow rate of a first phase within a two-phase flow through the flowtube and determine a second flow rate of a second phase within the two-phase flow. Images(21) Claims(19)
DETAILED DESCRIPTION Types of flowmeters include digital flowmeters. For example, U.S. Pat. No. 6,311,136, which is hereby incorporated by reference, discloses the use of a digital flowmeter and related technology including signal processing and measurement techniques. Such digital flowmeters may be very precise in their measurements, with little or negligible noise, and may be capable of enabling a wide range of positive and negative gains at the driver circuitry for driving the conduit. Such digital flowmeters are thus advantageous in a variety of settings. For example, commonly-assigned U.S. Pat. No. 6,505,519, which is incorporated by reference, discloses the use of a wide gain range, and/or the use of negative gain, to prevent stalling and to more accurately exercise control of the flowtube, even during difficult conditions such as two-phase flow (e.g., a flow containing a mixture of liquid and gas). Although digital flowmeters are specifically discussed below with respect to, for example, FIGS. 1 and 2, it should be understood that analog flowmeters also exist. Although such analog flowmeters may be prone to typical shortcomings of analog circuitry, e.g., low precision and high noise measurements relative to digital flowmeters, they also may be compatible with the various techniques and implementations discussed herein. Thus, in the following discussion, the term �flowmeter� or �meter� is used to refer to any type of device and/or system in which a Coriolis flowmeter system uses various control systems and related elements to measure a mass flow, density, and/or other parameters of a material(s) moving through a flowtube or other conduit. FIG. 1A is an illustration of a digital flowmeter using a bent flowtube 102. Specifically, the bent flowtube 102 may be used to measure one or more physical characteristics of, for example, a (traveling) fluid, as referred to above. In FIG. 1A, a digital transmitter 104 exchanges sensor and drive signals with the bent flowtube 102, so as to both sense an oscillation of the bent flowtube 102, and to drive the oscillation of the bent flowtube 102 accordingly. By quickly and accurately determining the sensor and drive signals, the digital transmitter 104, as referred to above, provides for fast and accurate operation of the bent flowtube 102. Examples of the digital transmitter 104 being used with a bent flowtube are provided in, for example, commonly-assigned U.S. Pat. No. 6,311,136. FIG. 1B is an illustration of a digital flowmeter using a straight flowtube 106. More specifically, in FIG. 1B, the straight flowtube 106 interacts with the digital transmitter 104. Such a straight flowtube operates similarly to the bent flowtube 102 on a conceptual level, and has various advantages/disadvantages relative to the bent flowtube 102. For example, the straight flowtube 106 may be easier to (completely) fill and empty than the bent flowtube 102, simply due to the geometry of its construction. In operation, the bent flowtube 102 may operate at a frequency of, for example, 50-110 Hz, while the straight flowtube 106 may operate at a frequency of, for example, 300-1,000 Hz. The bent flowtube 102 represents flowtubes having a variety of diameters, and may be operated in multiple orientations, such as, for example, in a vertical or horizontal orientation. Referring to FIG. 2, a digital mass flowmeter 200 includes the digital transmitter 104, one or more motion sensors 205, one or more drivers 210, a flowtube 215 (which also may be referred to as a conduit, and which may represent either the bent flowtube 102, the straight flowtube 106, or some other type of flowtube), and a temperature sensor 220. The digital transmitter 104 may be implemented using one or more of, for example, a processor, a Digital Signal Processor (DSP), a field-programmable gate array (FPGA), an ASIC, other programmable logic or gate arrays, or programmable logic with a processor core. It should be understood that, as described in U.S. Pat. No. 6,311,136, associated digital-to-analog converters may be included for operation of the drivers 210, while analog-to-digital converters may be used to convert sensor signals from the sensors 205 for use by the digital transmitter 104. The digital transmitter 104 generates a measurement of, for example, density and/or mass flow of a material flowing through the flowtube 215, based at least on signals received from the motion sensors 205. The digital transmitter 104 also controls the drivers 210 to induce motion in the flowtube 215. This motion is sensed by the motion sensors 205. Density measurements of the material flowing through the flowtube are related to, for example, the frequency of the motion of the flowtube 215 that is induced in the flowtube 215 by a driving force supplied by the drivers 210, and/or to the temperature of the flowtube 215. Similarly, mass flow through the flowtube 215 is related to the phase and frequency of the motion of the flowtube 215, as well as to the temperature of the flowtube 215. The temperature in the flowtube 215, which is measured using the temperature sensor 220, affects certain properties of the flowtube, such as its stiffniess and dimensions. The digital transmitter 104 may compensate for these temperature effects. Also in FIG. 2, a pressure sensor 225 is in communication with the transmitter 104, and is connected to the flowtube 215 so as to be operable to sense a pressure of a material flowing through the flowtube 215. It should be understood that both the pressure of the fluid entering the flowtube 215 and the pressure drop across relevant points on the flowtube may be indicators of certain flow conditions. Also, while external temperature sensors may be used to measure the fluid temperature, such sensors may be used in addition to an internal flowmeter sensor designed to measure a representative temperature for flowtube calibrations. Also, some flowtubes use multiple temperature sensors for the purpose of correcting measurements for an effect of differential temperature between the process fluid and the environment (e.g., a case temperature of a housing of the flowtube). As discussed in more detail below, one potential use for the inlet fluid temperature and pressure measurements is to calculate the actual densities of a liquid and gas in a two-phase flow, based on predefined formulae. A liquid fraction probe 230 refers to a device for measuring a volume fraction of liquid, e.g., water, when a liquid in the flowtube 215 includes water and another fluid, such as oil. Of course, such a probe, or similar probes, may be used to measure the volume fraction of a fluid other than water, if such a measurement is preferred or if the liquid does not include water. In the below description, a measured liquid is generally assumed to be water for the purposes of example, so that the liquid fraction probe 230 is generally referred to as a water fraction probe 230, or a water-cut probe 230. A void fraction sensor 235 measures a percentage of a material in the flowtube 215 that is in gaseous form. For example, water flowing through the flowtube 215 may contain air, perhaps in the form of bubbles. Such a condition, in which the material flowing through the flowtube 215 contains more than one material is generally referred to as �two-phase flow.� In particular, the term �two-phase flow� may refer to a liquid and a gas; however, �two-phase flow� also may refer to other combinations of materials, such as two liquids (e.g., oil and water). Various techniques, represented generally in FIG. 2 by the void fraction sensor 235, exist for measuring the gas void fraction in a two-phase flow of liquid and gas. For example, various sensors or probes exist that may be inserted into the flow to determine a gas void fraction. As another example, a venturi tube (i.e., a tube with a constricted throat that determines fluid pressures and velocities by measurement of differential pressures generated at the throat as a fluid traverses the tube), relying on the fact that gas generally moves with a higher velocity than liquid(s) through a restriction, may be used to determine a pressure gradient and thereby allow a determination of the gas void fraction. Measurements of gas void fractions also may be obtained using equipment that is wholly external to the flowtube. For example, sonar measurements may be taken to determine gas void fraction. As a specific example of such a sonar-based system, the SONARtracTM gas void fraction monitoring system produced by CiDRA Corporation of Wallingford, Conn. may be used. In this description, an amount of gas in a flowing fluid, measured by the void fraction sensor or otherwise determined, is referred to as void fraction or α, and is defined as a α=volume of gas/total volume=volume of gas/(volume of liquid+volume of gas). Accordingly, a quantity referred to herein as the liquid fraction is defined as 1−α. In many applications where mass flow measurements are required, the void fraction of the flow can be as high as 20, 30, 40% or more. However, even at very small void fractions of 0.5%, the fumdamental theory behind the coriolis flowmeter becomes less applicable. Moreover, a presence of gas in the fluid flow also may affect a measurement of a density of the fluid flow, generally causing the density measurement to read lower. That is, it should be understood that a density ρliquid of a liquid flowing by itself through a flowtube will be higher than an actual density ρtrue of a two-phase flow containing the liquid and a gas, since a density of the gas (e.g., air) will generally be lower than a density of the liquid (e.g., water) in the two-phase flow. In other words, there is a density reduction when gas is added to a liquid flow that previously contained only the liquid. Beyond this physical phenomenon, a coriolis meter measuring a two-phase fluid flow containing gas may output a density reading ρapparent that is an ostensible measurement of the bulk density of the two-phase flow (e.g., of the water and air combined). This raw measurement ρapparent will generally be different (lower) than the actual bulk density ρtrue of the two-phase flow. For example, the resonant frequency used by the flowmeter may be artificially high, due to relative motion of the gas in the fluid flow, which would cause the density measurement to read low. It should be understood that many conventional prior art flowmeters were unconcerned with this problem, since most such coriolis meters fail to continue operating (e.g. stall or output inaccurate measurements) at even the slightest amounts of void fraction. U.S. Pat. No. 6,505,519, which is incorporated by reference above, discloses that such a variation of ρapparent (i.e., an indicated raw or bulk density reading of a two-phase flow that is output by a coriolis flowmeter) from ρtrue (i.e., an actual raw or bulk density of the two-phase flow) may be characterized by a variety of techniques. As a result, a measured ρapparent may be corrected to obtain an actual bulk density ρcorrected, which is, at least approximately, equal to ρtrue. Somewhat similarly, an indicated raw or bulk mass flow rate MFapparent (i.e., a mass flow rate of the entire two-phase flow) measured by a coriolis flowmeter may be different by a predictable or characterizable amount from an actual bulk mass flow rate MFtrue. It should be understood that correction techniques for corrected bulk mass flow rate MFtrue may be different than the techniques for correcting for density. For example, various techniques for correcting a measured MFapparent to obtain an actual MFtrue (or, at least, MFcorrected) are discussed in U.S. Pat. No. 6,505,519. Examples of detailed techniques for correcting ρapparent and MFapparent are discussed in more detail below. Generally speaking, though, with respect to FIG. 2, the digital transmitter is shown as including a density correction system 240, which has access to a density correction database 245, and a mass flow rate correction system 250, which has access to a mass flow correction database 255. As discussed in more detail below, the databases 245 and 255 may contain, for example, correction algorithms that have been derived theoretically or obtained empirically, and/or correction tables that provide corrected density or mass flow values for a given set of input parameters. The databases 245 and 255 also may store a variety of other types of information that may be useful in performing the density or mass flow corrections. For example, the density correction database may store a number of densities ρliquid corresponding to particular liquids (e.g., water or oil). Further in FIG. 2, a void fraction determination/correction system 260 is operable to determine a void fraction of a two-phase flow including a liquid and a gas. In one implementation, for example, the void fraction determination/correction system 260 may determine an actual void fraction αtrue from the corrected density ρtrue. In another implementation, the void fraction determination/correction system 260 may input an apparent or indicated void fraction measurement obtained by the void fraction sensor 235, and may correct this measurement based on an error characterization similar to the density and mass flow techniques referred to above. In another implementation, the void fraction sensor 235 may be operable to directly measure an actual void fraction αtrue, in which case the void fraction determination/correction system 260 simply inputs this measurement. Once the factors of ρtrue, MFtrue, and αtrue have been determined, and perhaps in conjunction with other known or discoverable quantities, a flow component mass flow rate determination system 265 operates to simultaneously determine a mass flow rate for the liquid phase component and a mass flow rate for the gas phase component. That is, the transmitter 104 is operable to determine individual flowrates MFliquid and MFgas of the flow components, as opposed to merely determining the bulk flowrate of the combined or total two-phase flow MFtrue. Although, as just referred to, such measurements may be determined and/or output simultaneously, they also may be determined separately or independently of one another. Once the component flow rates MFliquid and MFgas have been determined in the manner generally outlined above, these initial determinations may be improved upon by a process that relies on superficial velocities of the flow components, slip velocities between the components, and/or an identified flow regime of the flow. In this way, improved values for flow rates MFliquid and MFgas may be obtained, or may be obtained over time as those flow rates change. Superficial velocities are referred to herein as those velocities that would exist if the same mass flow rate of a given phase was traveling as a single phase through the flowtube 215. A superficial velocity determination/correction system 270 is included in the transmitter 104 for, for example, determining an apparent or corrected superficial velocity of a gas or liquid in the two-phase flow. Slip velocities refer to a condition in which gas and liquid phases in a two-phase flow have different average velocities. That is, an average velocity of a gas AVgas is different from an average velocity of a liquid AVliquid. As such, a phase slip S may be defined as S=AVgas/AV liquid. A flow regime is a term that refers to a characterization of the manner in which the two phases flow through the flowtube 215 with respect to one another and/or the flowtube 215, and may be expressed, at least partially, in terms of the superficial velocities just determined. For example, one flow regime is known as the �bubble regime,� in which gas is entrained as bubbles within a liquid. As another example, the �slug regime� refers to a series of liquid �plugs� or �slugs� separated by relatively large gas pockets. For example, in vertical flow, the gas in a slug flow regime may occupy almost an entire cross-sectional area of the flowtube 215, so that the resulting flow alternates between high-liquid and high-gas composition. Other flow regimes are known to exist and to have certain defined characteristics, including, for example, the annular flow regime, the dispersed flow regime, and froth flow regime, and others. The existence of a particular flow regime is known to be influenced by a variety of factors, including, for example, a gas void fraction in the fluid flow, an orientation of the flowtube 215 (e.g., vertical or horizontal), a diameter of the flowtube 215, the materials included within the two-phase flow, and the velocities (and relative velocities) of the materials within the two phase flow. Depending on these and other factors, a particular fluid flow may transition between several flow regimes over a given period of time. Information about phase slip may be determined at least in part from flow regime knowledge. For example, in the bubble flow regime, assuming the bubbles are uniformly distributed, there may be little relative motion between the phases. Where the bubbles congregate and combine to form a less uniform distribution of the gas phase, some slippage may occur between the phases, with the gas tending to cut through the liquid phase. In FIG. 2, a flow regime determination system 275 is included that has access to a database 280 of flow regime maps. In this way, information about an existing flow regime, including phase slip information, may be obtained, stored, and accessed for use in simultaneously determining liquid and gas mass flow rates within a two-phase flow. In FIG. 2, it should be understood that the various components of the digital transmitter 104 are in communication with one another, although communication links are not explicitly illustrated, for the sake of clarity. Further, it should be understood that conventional components of the digital transmitter 104 are not illustrated in FIG. 2, but are assumed to exist within, or be accessible to, the digital transmitter 104. For example, the digital transmitter 104 will typically include (bulk) density and mass flow rate measurement systems, as well as drive circuitry for driving the driver 210. FIG. 3 is a flowchart 300 illustrating an operation of the coriolis flowmeter 200 of FIG. 2. Specifically, FIG. 3 illustrates techniques by which the flowmeter 200 of FIG. 2 is operable to simultaneously determine liquid and gas flow rates MFliquid and MFgas for a two-phase flow. In FIG. 3, it is determined that a gas/liquid two-phase flow exists in the flowtube 215 (302). This can be done, for example, by an operator during configuration of the mass flowmeter/densitometer for gas/liquid flow. As another example, this determination may be made automatically by using a feature of the coriolis meter to detect that a condition of two-phase gas-liquid flow exists. In the latter case, such techniques are described in greater detail in, for example, U.S. Pat. No. 6,311,136 and U.S. Pat. No. 6,505,519, incorporated by reference above. Once the existence of two-phase flow is established, a corrected bulk density ρtrue is established (304) by the density correction system 240, using the density correction database 245 of the transmitter 104. That is, an indicated density ρapparent is corrected to obtain ρtrue. Techniques for performing this correction are discussed in more detail below. Once ρtrue is determined, a corrected gas void fraction αtrue may be determined (306) by the void fraction determination/correction system 260. Also, a corrected bulk mass flow rate MFtrue is determined (308) by the mass flow rate correction system 250. As with density, techniques for obtaining the corrected void fraction αtrue and mass flow rate MFtrue are discussed in more detail below. In FIG. 3, it should be understood from the flowchart 300 that the determinations of ρtrue, αtrue, and MFtrue may occur in a number of sequences. For example, in one implementation, the corrected void fraction αtrue is determined based on previously-calculated corrected density ρtrue, whereupon the corrected mass flow rate MFtrue is determined based on αtrue. In another implementation, αtrue and ρtrue may be calculated independently of one another, and/or ρtrue and MFtrue may be calculated independently of one another. Once corrected density ρtrue, corrected void fraction αtrue, and corrected mass flow rate MRtrue are known, then the mass flow rates of the gas and liquid components are determined (310) by the flow component mass flow rate determination system 265. Techniques for determining the liquid/gas component flow rates are discussed in more detail below with respect to FIG. 4. Once determined, the liquid/gas component flow rates may be output or displayed (312) for use by an operator of the flowmeter. In this way, the operator is provided, perhaps simultaneously, with information about both the liquid mass flow rate MFliquid and the gas mass flow rate MFgas of a two-phase flow. In some instances, this determination may be sufficient (314), in which case the outputting of the liquid/gas component flow rates completes the process flow. However, in other implementations, the determination of the individual component mass flow rates may be improved upon by factoring in information about, for example, the superficial velocities of the gas/liquid components, the flow regime(s) of the flow, and phase slip, if any, between the components. In particular, superficial velocities of the gas and liquid, SVgas and SVliquid are determined as follows. Gas superficial velocity SVgas is defined as: SV gas =MF gas/(ρgas *A T) Eq. 1 where the quantity AT represents a cross-section area of the flowtube 215, which may be taken at a point where a void fraction of the flow is measured. Similarly, a liquid superficial velocity SVliquid is defined as: SV liquid =MF liquid/(ρliquid *A T) Eq. 2 As shown in Eqs. 1 and 2, determination of superficial velocities in this context relies on the earlier determination of MFgas and MFliquid. It should be understood from the above description and from FIG. 3 that MFgas and MFliquid represent corrected or true mass flow rates, MFgas true and MFliquid true since these factors are calculated based on ρtrue, αtrue, and MFtrue. As a result, the superficial velocities SVgas and SVliquid represent corrected values SVgas true and SVliquid true. Further, the density values ρgas and ρliquid refer, as above, to known densities of the liquid and gas in question, which may be stored in the density correction database 245. As discussed in more detail below with respect to techniques for calculating corrected density ρtrue, the density values ρgas and ρliquid may be known as a function of existing temperature or pressure, as detected by temperature sensor 220 and pressure sensor 225. Using the superficial velocities and other known or calculated factors, some of which may be stored in the flow regime maps database 280, a relevant flow regime and/or phase slip may be determined (318) by the flow regime determination/correction system 275. Once superficial velocities, flow regime, and phase slip are known, further corrections may be made to the corrected bulk density ρtrue, corrected bulk mass flow rate MFtrue, and/or corrected void fraction αtrue. In this way, as illustrated in FIG. 3, component flow rates MFgas and MFliquid may be determined. Flow regime(s) in two phase liquid/gas flow may be described by contours on a graph plotting the liquid superficial velocity versus the gas superficial velocity. As just described, an improvement to determinations of ρtrue, αtrue, and/or MFtrue may be obtained by first establishing an approximate value of the liquid and gas flow rates, and then applying a more detailed model for the flow regime identified. For example, at relatively low GVF and relatively high flow there exists a flow regime in which the aerated fluid behaves as a homogenous fluid with little or no errors in both density and mass flow. This can be detected as homogenous flow requiring no correction, simply using observation of the drive gain, which shows little or no increase in such a setting, despite a significant drop in observed density. FIG. 4 is a flowchart 400 illustrating techniques for determining liquid and gas flow rates MFliquid and MFgas for a two-phase flow. That is, the flowchart 400 generally represents one example of techniques for determining liquid and gas flow rates (310), as described above with respect to FIG. 3. In FIG. 4, the determination of liquid and gas flow rates (310) begins with inputting the corrected density, void fraction, and mass flow rate factors ρtrue, αtrue, and MFtrue (402). In a first instance, (404), the liquid and gas flow rates are determined (406) using Eqs. 3 and 4: MF gas=αtrue(ρgas/ρtrue)(MF true) Eq. 3 MF liquid=(1−αtrue)(ρliquid/ρtrue)(MF true) Eq. 4 Eqs. 3 and 4 assume that there is no slip velocity (i.e., phase slip) between the liquid and gas phases (i.e., average velocity of the gas phase, AVgas, and average velocity of the liquid phase, AVliquid, are equal). This assumption is consistent with the fact that, in the first instance, superficial velocities and flow regimes (and therefore, phase slip) have not been determined. In the second instance and thereafter (404), a determination is made, perhaps by the flow regime determination/correction system 275, as to whether phase slip exists (408). If not, then Eqs. 3 and 4 are used again (406) or the process ends. If phase slip does exist (408), defined above as S=AVgas/AVliquid, the terms MFgas and MFliquid are calculated using the cross-sectional area of the flowtube 215, AT, as also used in the calculation of superficial velocities in Eqs. 1 and 2 (410). Using the definition of slip S just given, MF gas=ρgas(αtrue A T)(AV gas)=ρgas(αtrue A T)(S)(AV liquid) Eq. 5 MF liquid=ρliquid((1−αtrue)A T)(AV liquid) Eq. 6 Since MFtrue=MFgas+MFliquid, Eqs. 5 and 6 may be solved for AVliquid to obtain Eq. 7: AV liquid =MF true/(A T(ρgasαtrue S+ρ liquid(1−αtrue))) Eq. 7 As a result, the liquid and gas flow rates are determined (406) using Eqs. 8 and 9: MF liquid=[ρliquid(1−αtrue)/(ρgasαtrue S+ρ liquid(1−αtrue))][MF true] Eq. 8 MF gas =MF true −MF liquid Eq. 9 As described above, gas entrained in liquid forms a two-phase flow. Measurements of such a two-phase flow with a Coriolis flowmeter result in indicated parameters ρapparent, αapparent, and MFapparent for density, void fraction, and mass flow rate, respectively, of the two-phase flow. Due to the nature of the two-phase flow in relation to an operation of the Coriolis flowmeter, these indicated values are incorrect by a predictable factor. As a result, the indicated parameters may be corrected to obtain actual parameters ρtrue, αtrue, and MFtrue. In turn, the actual, corrected values may be used to simultaneously determine individual flow rates of the two (gas and liquid) components. FIGS. 5A and 5B are graphs illustrating a percent error in a measurement of void fraction and liquid fraction, respectively. In FIG. 5A, the percent error is a density percent error that is dependent on various design and operational parameters, and generally refers to the deviation of the apparent (indicated) density from the true combined density that would be expected given the percentage (%) of gas in liquid. In FIG. 5B, true liquid fraction versus indicated liquid fraction is illustrated. FIG. 5B shows the results, for the relevant flowmeter design, of several line sizes and flow rates. In more general terms, the functional relationship may be more complex and depend on both line size and flowrate. In FIG. 5B, a simple polynomial fit is shown that can be used to correct the apparent liquid fraction. Other graphing techniques may be used; for example, true void fraction may be plotted against indicated void fraction. For example, FIG. 6 is a graph illustrating a mass flow error as a function of a drop in density for a flowtube having a particular orientation and over a selected flow range. FIG. 7 is a flowchart 700 illustrating techniques for correcting density measurements (304 in FIG. 3). In FIG. 7, the process begins with an inputting of the type of flowtube 215 being used (702), which may include, for example, whether the flowtube 215 is bent or straight, as well as other relevant facts such as a size or orientation of the flowtube 215. Next, a gas-free density of the liquid, ρliquid is determined (704). This quantity may be useful in the following calculation(s), as well as in ensuring that that other factors that may influence the density measurement ρapparent, such as temperature, are not misinterpreted as void fraction effects. In one implementation, the user may enter the liquid density ρliquid directly, along with a temperature dependence of the density. In another implementation, known fluids (and their temperature dependencies) may be stored in the density correction database 245, in which case the user may enter a fluid by name. In yet another implementation, the flowmeter 200 may determine the liquid density during a time of single-phase, liquid flow, and store this value for future use. An indicated mass flow rate MFapparent is read from the Coriolis meter (706), and then an indicated density ρapparent is read from the Coriolis meter (708). Next, the density correction system 240 applies either a theoretical, algorithmic (710) or empirical, tabular correction (712) to determine the true density ρtrue of the gas/liquid mixture. The quantity ρtrue may then be output as the corrected density (714). An algorithmic density correction (710) may be determined based on the knowledge that, if there were no effect of the two-phase flow from the normal operation of a Coriolis meter when used to measure density, the indicated density would drop by an amount derived from the equation describing void fraction, which is set forth above in terms of volume flow and repeated here in terms of density as Eq. 10: α(%)=[(ρapparent−ρliquid)/(ρgas−ρliquid)]=100 Eq. 10 This can be used to define a quantity �density drop,� or Δρ, as shown in Eq. 11: Δρ=(ρapparent−ρliquid)=α(%)�(ρgas−ρliquid)/100 Eq. 11 Note that Eq. 11 shows the quantity Δρ as being positive; however, this quantity could be shown as a negative drop simply by multiplying the right-hand side of the equation by −1, resulting in Eq. 12: Δρ=(ρliquid−ρapparent)=α(%)�(ρliquid−ρgas)/100 Eq. 12 The quantity ρgas may be small compared to ρliquid, in which case Eq. 12 may be simplified to Eq. 13: αρ=(ρliquid-ρapparent)=α(%)�ρliquid/100 Eq. 13 As discussed extensively above, density measurements by a Coriolis meter, or any vibrating densitometer, generally are under-reported by the meter, and require correction. Accordingly, under two-phase flow Eqs. 12 or 13 may thus be used to define the following two quantities: a corrected or true density drop, Δρtrue, and an indicated or apparent density drop, Δρapp. Using Eq. 13 as one example, this results in Eqs. 14 and 15: Δρtrue=(ρliquid−ρtrue)=α(%)�ρliquid/100 Eq. 14 Δρapp=(ρliquid−ρapparent)=α(%)�ρliquid/100 Eq. 15 There can be derived or empirically determined a relationship between Δρtrue and Δρapparent and apparent mass flow rate, MFapparent, as well as other parameters, such as, for example, drive gain, sensor balance, temperature, phase regime, etc.). This relationship can be expressed as shown as Δρtrue=f (MFapparent, drive gain, sensor balance, temperature, phase regime, and/or other factors). As a result, the relationship may generally be derived, or at least proven, for each flowtube in each setting. For one model flowtube, known and referred to herein as the Foxboro/Invensys CFS10 model flowtube, it has been empirically determined that for some conditions the above functional relationship can be simplified to be only a function Δρapparent and of the form shown in Eq. 16: Δρ true = ∑ i = 0 M ⁢ a i ⁡ ( Δρ apparent ) i Eq . ⁢ 16 To force the condition for both sides of Eq. 16 to be zero when there is no apparent density drop relationship results in Eq. 17: Δρ true = ∑ i = 1 M ⁢ a i ⁡ ( Δρ apparent ) i Eq . ⁢ 17 M generally depends on the complexity of the empirical relationship, but in many cases can be as small as 2 (quadratic) or 3 (cubic). Once the true density drop is determined, then working back through the above equations it is straightforward to derive the true mixture density ρtrue, as well as the true liquid and gas (void) fractions (the latter being discussed in more detail with respect to FIG. 9). A tabular correction for density (712) may be used when, for example, a functional relationship is too complex or inconvenient to implement. In such cases, knowledge of the quantities Δρapparent and ΔMFapparent may be used to determine Δρtrue by employing a table having the form of a table 800 of FIG. 8. The table 800 may be, for example, a tabular look-up table that can be, for example, stored in the database 245, or in another memory, for use across multiple applications of the table. Additionally, the table may be populated during an initialization procedure, for storage in the database 245 for an individual application of the table. It should be understood that either or both of the algorithmic and tabular forms may be extended to include multiple dimensions, such as, for example, gain, temperature, balance, or flow regime. The algorithmic or tabular correction also may be extended to include other surface fitting techniques, such as, for example, neural net, radical basis functions, wavelet analyses, or principle component analysis. As a result, it should be understood that such extensions may be implemented in the context of FIG. 3 during the approach described therein. For example, during a first instance, density may be determined as described above. Then, during a second instance, when a flow regime has been identified, the density may be further corrected using the flow regime information. FIG. 9 is a flowchart 900 illustrating techniques for determining void fraction measurements (306 in FIG. 3). In FIG. 9, the process begins with an inputting by the void fraction determination system 240 of the previously-determined liquid and bulk (corrected) densities, ρliquid and ρtrue (902). A density of the gas, ρgas is then determined (904). As with the liquid density ρliquid, there are several techniques for determining ρgas. For example, ρgas may simply be assumed to be a density of air, generally at a known pressure, or may be an actual known density of the particular gas in question. As another example, this known density ρgas may be one of the above factors (i.e., known density of air or the specific gas) at an actual or calculated pressure, as detected by the pressure sensor 225, and/or at an actual or calculated temperature, as detected by the temperature sensor 220. The temperature and pressure may be monitored using external equipment, as shown in FIG. 2, including the temperature sensor 220 and/or the pressure sensor 225. Further, the gas may be known to have specific characteristics with respect to factors including pressure, temperature, or compressibility. These characteristics may be entered along with an identification of the gas, and used in determining the current gas density ρgas. As with the liquid(s), multiple gasses may be stored in memory, perhaps along with the characteristics just described, so that a user may access density characteristics of a particular gas simply by selecting the gas be name from a list. Once the factors ρliquid, ρgas, and ρtrue are known, then it should be clear from Eq. 10 that void fraction αtrue may be easily determined (906). Then, if needed, liquid fraction may be determined (908) simply by calculating 1−αtrue. Although the above discussion presents techniques for determining void fraction αtrue based on density, it should be understood that void fraction may be determined by other techniques. For example, an indicated void fraction αapparent may be directly determined by the Coriolis flowmeter, perhaps in conjunction with other void fraction determination systems (represented by the void fraction sensor 235 of FIG. 2), and then corrected based on empirical or derived equations to obtain αtrue In other implementations, such external void fraction determining systems may be used to provide a direct measurement of αtrue. FIG. 10 is a flowchart 1000 illustrating techniques for determining corrected mass flow rate measurements (308 in FIG. 3). In FIG. 10, the mass flow rate correction system 250 first inputs the previously-calculated corrected density drop Δρtrue (1002), and then inputs a measured, apparent mass flow rate MFapparent (1004). The mass flow rate correction system 250 applies either a tabular (1006) or algorithmic correction (1008) to determine the true mass flow rate MFtrue of the gas/liquid mixture. The quantity MFtrue may then be output as the corrected mass flow rate (1010). In applying the tabular correction for mass flow rate (1006), knowledge of the quantities Δρtrue and ΔMFapparent may be used to determine MFtrue by employing a table having the form of a table 1100 of FIG. 11. The table 1100, as with the table 800 may be, for example, a tabular look-up table that can be, for example, stored in the database 245, or in another memory, for use across multiple applications of the table. Additionally, the table may be populated during an initialization procedure, for storage in the database 255 for an individual application of the table. Normalized values MFnorm � app and MFnorm � true may be used in place of the actual ones shown above, in order to cover more than one size coriolis flowtube. Also, the entries can be in terms of the correction, where the correction is defined by Eq. 18: ΔMF=MF true −MF apparent Eq. 18 The values in Eq. 18 should be understood to represent either actual or normalized values. In an algorithmic approach, as with density, the correction for mass flow may be implemented by way of a theoretical or an empirical functional relationship that is generally understood to be of the form ΔMF=f (MFapparent, void fraction, drive gain, sensor balance, temperature, phase regime, and/or other factors). For some cases the function can simplify to a polynomial, such as, for example, the polynomial shown in Eq. 19: Δ ⁢ ⁢ M ⁢ ⁢ F = ∑ i - 0 M ⁢ ∑ j = 0 N ⁢ a i ⁢ b j ⁡ ( Δρ true i ) ⁢ ( M ⁢ ⁢ F norm_app j ) Eq . ⁢ 19 For some set of conditions, the functional relationship can be a combination of a polynomial and exponential, as shown in Eq. 20: ΔMF=a 1 de (a 2 d 2 +a 3 d+a 4 m 2 +a 5 m) +a 6 d 2 +a 7 d+a 8 m 2 +a 9 m Eq. 20 In Eq. 20, d=Δρtrue, and m=f (MFapparent). In one implementation, m in Eq. 20 may be replaced by apparent superficial liquid velocity SVliquid which is given as described above by Eq. 2 as SVliquid=MFliquid/(ρliquid* AT). In this case, ρliquid and flowtube cross-section AT are known or entered parameters, and may be real-time corrected for temperature using, for example, the on-board temperature measurement device 220 of the digital controller/transmitter 104. It should be understood that, as with the density corrections discussed above, either or both of the algorithmic and tabular forms may be extended to include multiple dimensions, such as, for example, gain, temperature, balance, or flow regime. The algorithmic or tabular correction also may be extended to include other surface fitting techniques, such as, for example, neural net, radical basis functions, wavelet analyses, or principle component analysis. As a result, it should be understood that such extensions may be implemented in the context of FIG. 3 during the approach described therein. For example, during a first instance, mass flow rate may be determined as described above. Then, during a second instance, when a flow regime has been identified, the mass flow rate may be further corrected using the flow regime information. All of the above functional relationships for mass flow rate may be restated using gas fraction (α) or liquid fraction (100−α) instead of density drop, as reflected in the table 1100 of FIG. 11. Also, although the above described methods are dependent on knowledge of the corrected density drop Δρtrue, it should be understood that other techniques may be used to correct an indicated mass flow rate. For example, various techniques for correcting mass flow rate measurements of a two-phase flow are discussed in U.S. Pat. No. 6,505,519, incorporated by reference above. Having described density, void fraction, and mass flow rate corrections above in general terms, for the purpose of, for example, simultaneously calculating individual flow component (phases) flow rates in a two-phase flow, the below discussion and corresponding figures provide specific examples of implementations of these techniques. FIGS. 12-14 are graphs illustrating examples of density corrections for a number of flowtubes. In particular, the examples are based on data obtained from three vertical water flowtubes, the flowtubes being: �″, �″, and 1″ in diameter. More specifically, the �″ data was taken with a 0.15 kg/s flow rate and a 0.30 kg/s flow rate; the �″ data was taken with a 0.50 kg/s flow rate and a 1.00 kg/s flow rate; and the 1″ data was taken with a 0.50 kg/s flow rate, a 0.90 kg/s flow rate, and a 1.20 kg/s flow rate. FIG. 12 illustrates an error, ed, of the apparent density of the fluid-gas mixture (two-phase flow) versus the true drop in density of the fluid-gas mixture, Δρtrue: Δρ true = 100 � ρ liquid - ρ true ρ liquid Eq . ⁢ 21 e d = 100 � ρ apparent - ρ true ρ true Eq . ⁢ 22 where, as above, ρliquid is the density of the gas-free liquid, ρtrue is the true density of the liquid-gas mixture, and ρapparent is the apparent or indicated density of the liquid-gas mixture. In FIG. 12, the correction is performed in terms of the apparent drop in mixture density, Δρapparent, as shown in Eq. 23: Δρ apparent = 100 � ρ liquid - ρ apparent ρ apparent Eq . ⁢ 23 In FIG. 12, when fitting the data, both the apparent and true drop in density of the mixture were normalized to values between 0 and 1 by dividing them through by 100, where this normalization is designed to ensure numerical stability of the optimization algorithm. In other words, the normalized apparent and true drop in mixture density are the apparent and true drop in mixture density defined as a ratio, rather than as a percentage, of the liquid density ρliquid, as shown in Eq. 24: Δρ apparent normalized = Δρ apparent 100 Eq . ⁢ 24 The model formula, based on Eq. 17, provides Eq. 25: Δρ true normalized = ⁢ a 1 ⁡ ( Δρ apparent normalized ) 3 + a 2 ⁡ ( Δρ apparent normalized ) 2 + ⁢ a 3 ⁡ ( Δρ apparent normalized ) Eq . ⁢ 25 In this case, the coefficients are a1=−0.51097664273685, a2=1.26939674868129, and a3=0.24072693119420. FIGS. 13A and 13B illustrate the model with the experimental data and the residual errors, as shown. FIGS. 14A and 14B give the same information, but with each flow rate plotted separately. To summarize, the drop in density correction is performed in the transmitter 104 by calculating the apparent density drop Δρapparent, using the apparent density value ρapparent and the liquid density ρliquid. The value of the apparent drop in density is normalized to obtain Δρ apparent normalized = Δρ apparent 100 , so that, as explained above, the drop in density is calculated as a ratio rather than a percentage. The density correction model(s) may then be applied to obtain the normalized corrected drop in mixture density Δρ true normalized . Finally, this value is un-normalized to obtain the corrected drop in density Δρ true = 100 � Δρ true normalized . Of course, the final calculation is not necessary if the corrected drop in mixture density Δρtrue is defined as a ratio rather than percentage of the true value. FIGS. 15-20 are graphs illustrating examples of mass flow rate corrections for a number of flowtubes. In particular, the examples are based on data obtained from three vertical water flowtubes, the flowtubes being: �″, �″, and 1″ in diameter. More specifically, the �″ data was taken with a 0.15 kg/s flow rate and a 0.30 kg/s flow rate; the �′ data was taken with a 0.50 kg/s flow rate and a 1.00 kg/s flow rate; and the 1″ data was taken with 18 flow rates between 0.30 kg/s and 3.0 kg/s flow rate, with a maximum drop in density of approximately 30%. FIGS. 15A and 15B illustrate apparent mass flow errors for the data used to fit the model versus corrected drop in mixture density Δρtrue and normalized true superficial fluid velocity; i.e., the apparent mass flow error curves per flowline, together with a scatter plot of the apparent mass flow error versus corrected drop in density Δρtrue and normalized true superficial fluid velocity νm, as shown in Eq. 26: v tn = v t v max , v t = m t ρ liquid � A T Eq . ⁢ 26 where m, is the true fluid mass flow, i.e. the value of the mass flow independently measured, ρliquid is the liquid density, AT is the flowtube cross-section area, and νmax is the maximum value for the superficial fluid velocity (here considered 12), so that νn gives the ratio of the true superficial fluid velocity from the whole range of the flowtube 215. In these examples, both drop in mixture density and superficial fluid velocity are normalized between 0 and 1 prior to fitting the model, for the purpose of ensuring numerical stability for the model optimization algorithm. FIG. 16 illustrates apparent mass flow errors versus corrected drop in mixture density and normalized apparent superficial fluid velocity, with safety bounds for the correction mode. That is, FIG. 16 gives the scatter plot of the apparent mass flow errors versus corrected drop in density and, this time, normalized apparent superficial fluid velocity v n = v v max = m v max � ρ � A , where m is the apparent fluid mass flow (i.e. as measured by the transmitter 104). Superimposed on the plot are the boundaries defining the safe region for the model, i.e., the region for which the model is expected to give an accuracy similar with the one for the fit data. Using this nomenclature, the apparent mass flow error e is given by e = 100 � m - m t m t . The model formula for this situation is shown as Eq. 27: e n =a 1 dd cn �e a 2 dd cn 2 +a 3 dd cn +a 4 ν n 2 +a 5 ν n +a 6 dd cn 2 +a 7 dd cn +a 8νn 2 +a 9νn Eq. 27 where e n = e 100 = m - m t m t Eq . ⁢ 28 where, in Eqs. 27 and 28, ddcn is the normalized corrected drop in mixture density, and νn is the normalized apparent superficial velocity of the liquid. In this case, the coefficient are: a1=−4.78998578570465, a2=4.20395000016874, a3=−5.93683498873342, a4=12.03484566235777, a5 =−7.70049487145105, a 6=0.69537907794202, a7=−0.52153213037389, a8=0.36423791515369, and a9=−0.16674339233364 FIG. 17 illustrates a scatter plot for the model residuals, together with the model formula and coefficients; i.e., shows model residuals versus the corrected drop in mixture density and normalized true fluid velocity. FIGS. 18A-18D and FIGS. 19A-19D give the model residual errors for the whole data set used to fit the model and the actual data alone, respectively. Finally, FIGS. 20A and 20B illustrate the model surface both interpolating and extrapolating outside the safe fit area. From FIGS. 16, 20A, and 20B, the apparent mass flow (superficial liquid velocity) and drop in density bounds for the model should be understood. To summarize, mass flow correction in the transmitter 104 is undertaken in this example by calculating an apparent drop in density, correcting it using the method(s) described above, and normalizing the resulting value by dividing it by 100 (or use the obtained normalized corrected drop in density from the density model). Then, a normalized superficial fluid velocity νn is calculated, and the model is applied to obtain an estimation of the normalized mass flow error en where this value gives the error of the apparent mass flow as a ratio of the true mass flow. The obtained value may be un-normalized by multiplying it by 100, to thereby obtain the mass flow error as a percentage of the true mass flow. Finally, the apparent mass flow may be corrected with the un-normalized mass flow error m c = m e n + 1 . As will be appreciated, the above description has a wide range of applications to improve the measurement and correction accuracy of a coriolis meter during two phase flow conditions. In particular, the techniques described above are particularly useful in measurement applications where the mass flow of the liquid phase and the mass flow of the gas phase must be measured and/or corrected to a high level of accuracy. One exemplary application is the measurement of the mass flow of the liquid phase and the measurement of the gas phase in oil and gas production environments. The above discussion is provided in the context of the digital flowmeter of FIG. 2. However, it should be understood that any vibrating or oscillating densitometer or flowmeter, analog or digital, that is capable of measuring multi-phase flow that includes a gas phase of a certain percentage may be used. That is, some flowmeters are only capable of measuring process fluids that include a gas phase when that gas phase is limited to a small percentage of the overall process fluid, such as, for example, less than 5%. Other flowmeters, such as the digital flowmeter(s) referenced above, are capable of operation even when the gas void fraction reaches 40% or more. Many of the above-given equations and calculations are described in terms of density, mass flow rate, and/or void fraction. However, it should be understood that the same or similar results may be reached using variations of these parameters. For example, instead of mass flow, a volumetric flow may be used. Additionally, instead of void fraction, liquid fraction may be used. A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made. Accordingly, other implementations are within the scope of the following claims. Referenced byCiting PatentFiling datePublication dateApplicantTitleUS7040181Mar 21, 2005May 9, 2006Endress + Hauser Flowtec AgCoriolis mass measuring deviceUS7284449Mar 21, 2005Oct 23, 2007Endress + Hauser Flowtec AgIn-line measuring deviceUS7296484Oct 31, 2006Nov 20, 2007Endress + Hauser Flowtec AgIn-line measuring deviceUS7334450Nov 14, 2005Feb 26, 2008Phase Dynamics, Inc.Water cut measurement with improved correction for densityUS7357039Mar 21, 2006Apr 15, 2008Endress + Hauser Flowtec AgCoriolis mass measuring deviceUS7457714Jul 20, 2006Nov 25, 2008Phase Dynamics, Inc.Autocalibrated multiphase fluid characterization using extrema of time seriesUS7523647Jul 11, 2006Apr 28, 2009Phase Dynamics, Inc.Multiphase fluid characterizationUS7599803Aug 4, 2006Oct 6, 2009Phase Dynamics, Inc.Hydrocarbon well test method and systemUS7660689 *May 7, 2007Feb 9, 2010Invensys Systems, Inc.Single and multiphase fluid measurementsUS7716994May 7, 2007May 18, 2010Invensys Systems, Inc.Single and multiphase fluid measurements using a Coriolis meter and a differential pressure flowmeterUS7775085Sep 18, 2006Aug 17, 2010Phase Dynamics, Inc.High water cut well measurements with hydro-separationUS8126661 *Nov 6, 2009Feb 28, 2012Henry Manus PWet gas measurementUS8141432May 17, 2010Mar 27, 2012Invensys Systems, Inc.Single and multiphase fluid measurements using a coriolis meter and a differential pressure flowmeterUS8447535Jan 24, 2012May 21, 2013Invensys Systems, Inc.Wet gas measurementEP1720013A2 *Jul 11, 2006Nov 8, 2006Phase Dynamics, Inc.Multiphase fluid characterizationWO2007134009A2 *May 7, 2007Nov 22, 2007Invensys Sys IncSingle and multiphase fluid measurements* Cited by examinerClassifications U.S. Classification73/861.355International ClassificationG01N21/65, G01J3/44, G01F, G01F25/00, G01N33/28, G01F1/84, G01F1/00, G01F1/74Cooperative ClassificationG01F1/8436, G01F1/74, G01F1/8486, G01F1/849, G01F25/0007, G01N33/2823, G01N2009/006European ClassificationG01F1/84D10, G01F1/84F8S, G01F1/84F8L2, G01F25/00A, G01N33/28E, G01F1/74Legal EventsDateCodeEventDescriptionNov 13, 2013FPAYFee paymentYear of fee payment: 8Nov 20, 2009FPAYFee paymentYear of fee payment: 4Jun 16, 2004ASAssignmentOwner name: INVENSYS SYSTEMS, INC., MASSACHUSETTSFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:MATTAR, WADE M.;HENRY, MANUS P.;DUTA, MIHAELA D.;AND OTHERS;REEL/FRAME:015466/0561;SIGNING DATES FROM 20040602 TO 20040609RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google