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The invention embodiments relate to systems and methods for classifying multiphase fluid (MPF) flow in a pipe.

The simultaneous flow of two or more physical phases is referred to as multiple phase flow

<p dir="rtl">5 MPF) multiphase fluid flow. The behavior of MPF flow is more complex than that of single-phase flow patterns. The flow regime in an MPF ​​may depend on a number of factors, including, for example, the relative density ratio of one fluid to another, the difference in viscosity between the different fluids, and the velocity (slip) of each fluid. An MPF ​​may include any combination of two or more Phases such as solid, liquid, and gas For example, an MPF ​​may include sand, oil, and natural gas.</p>

<p dir="rtl">10 Accurate measurement and classification of MPF systems is critical to production optimization from hydrocarbon production wells and to determine the composition and quantity of production streams.</p>

Systems and methods have been proposed for the non-interfering measurement of MPF variables such as, flow regime, flow rate, presence of solids ratio, volume ratio and mass of individual phases with respect to each other. Active systems include those that transmit any or combination of acoustic and ultrasonic frequencies through the stream 15 and analyze the acoustic responses received.

Non-interfering systems and methods using emissions and acoustic signals to determine the different flow regimes and the presence of solids in the MPF use many variables of the flow acoustic data such as signal peak, root-mean-square (RMS) value, power, and basic frequency content. These systems and methods typically use consensus method templates. It is most important

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The problems with these existing systems and methods are the presence of continuous and random electrical and acoustic background noise in MPF ​​systems.

General description of the invention

5 The Applicant discloses a need for accurate and efficient measurement systems and methods for classifying multiphase fluid flow (MPF). 5 The Applicant also recognizes that the use of MPF calculations

Entropy approximations and methods with systems and methods of the present invention allow accurate real-time measurements and classification of MPF. The models of the present invention are non-radioactive, do not impede the flow in any way, and are computationally efficient. Embodiments of the present invention will allow non-interfering measurement of various MPF variables in one or a combination of a pipe, pipeline, casing, liner, and tubing, and will determine the presence of solid materials, such as

<p dir="rtl">10 sand, in mpf. Some of the models will allow small, non-intrusive, low-cost counters to measure and classify MPF systems and characteristics, which will improve monitoring, production, and reservoir management in hydrocarbon recovery applications.</p>

In addition, the applicant has been introduced to a statistical method that measures the short- and long-run complexity and randomness of MPF using conventional approximating entropy calculations. It will feature different

<p dir="rtl">15 MPF systems have different values ​​of statistical randomness, especially over shorter timescales. Principal component analysis is used for specific embodiment examples of the present invention.</p>

After realizing the deficiencies in existing systems and methods for measuring MPF, the sources of those deficiencies, and solutions to these deficiencies, the applicant discloses sample computer-implemented systems and methods, and a non-temporary computer-readable medium with computer programs stored to provide active and passive systems and methods.

<p dir="rtl">20 To classify the MPF and thus enhance the measurement and control of the flow regime in part of a pipe in hydrocarbon production processes. Hydrocarbon production processes may refer to any pre- or post-production of hydrocarbons in any form, including, but not limited to, crude oil, natural gas, natural gas condensate, liquefied petroleum gas, heavy products, light products, and distillates.</p>

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Embodiments of the invention may include a passive multiphase fluid flow (MPF) classification system to enhance the measurement and control of a flow regime in a section of a pipe for hydrocarbon production processes. The system includes an acoustic emission sensor located near the barrel portion and can be actuated to receive an acoustic emission from the MPF, as the barrel portion can carry the MPF in two physical phase hydrocarbon production processes

<p dir="rtl">5 At least, the acoustic emission sensor converts the received acoustic emission into an electrical signal. The system also includes a processing unit, which includes a processor, which receives the electrical signal and converts the electrical signal to MPF classification, and a processing unit in contact with and included in a non-temporary physical memory medium in contact with the processor with a set of stored instructions, where the stored set of instructions can be executed by the processor F. The processor performs the steps of dividing the signal</p>

<p dir="rtl">10 electrical into short-term, medium-term, and long-term time series, and assign positive real numbers to time series, where positive real numbers have larger and smaller values, where larger values ​​correspond to randomness of the process, and where smaller values ​​correspond to states of recognizable patterns in the electrical signal .</p>

The processor also performs the steps of classifying certain positive real numbers as odd values, and arithmetic

<p dir="rtl">15 Approximate short, medium, and long-term entropy values ​​of the MPF in response to the short-term, medium-term, and long-term time series of the electrical signal, and comparing the approximate short-term, medium-term, and long-term entropy values ​​of the MPF to the approximate short-term, medium-term, and long-term entropy values predetermined. The processor also performs the MPF characterization step in response to the similarities between the approximate short-term, medium-term, and long-term entropy values ​​of</p>

<p dir="rtl">20 MPF and predetermined approximate short-term, medium-term, and long-term entropy values. The processing unit also includes a user interface associated with the processing unit. The user interface accepts user input to control the processing unit, and displays MPF properties to the user.</p>

In some models, the system also includes a database with approximate short-term, medium-term, and long-term entropy values ​​predetermined for many MPF flow systems. In other models,

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The system also includes a preamplifier that is coupled to the otosensor and can be actuated to receive and amplify the electrical signal from the otosensor. In some embodiments, the system also includes a signal bandpass filter associated with the preamplifier, and the signal bandpass filter receives an amplified electrical signal from the preamplifier and also removes

<p dir="rtl">5 Acoustic background noise reports the audio information useful to the MPF contained in the amplified electrical signal, in response to cut-off frequencies programmed into the signal's bandpass filter derived from the operating frequency and bandwidth of the acoustic emission sensor.</p>

Also in other embodiments, the system includes an analog-to-digital converter associated with a bandpass filter, whereby the analog-to-digital converter operates on a reception from the signal's bandpass filter

<p dir="rtl">10 MPF useful audio information, converts the MPF useful audio information into a digital signal. In some embodiments of the system, the otosonic emission sensor includes a first otosonic emission sensor. The system also includes a second otosonic sensor located near the pipe section and can be actuated to receive an otosonic emission from the MPF. The second acoustic sensor converts the received otosonic emission into an electrical signal.</p>

<p dir="rtl">15 In some embodiments of the system, the second otosensor is placed at a distance D from the first otosensor, where D allows correlated MPF measurements in a substantially similar condition at both the first otosensor and the second otosensor, and where is obtained Precise measurement of the MPF flow velocity by dividing the distance D by the difference in time between the first time the MPF first EE sensor crosses and the second time it crosses</p>

<p dir="rtl">20 The second MPF sonic sensor.</p>

In other embodiments of the system, the processing unit also performs a set of instructions to perform principal component analysis on the system including steps to collect acoustic emission data under a set of flow variables in cases where an appropriate Reynolds number is known for the MPF that The data is collected for it, a time series of sound waveforms is formed, and an instantaneous transformation 25 is performed on the data, where the data is converted into measurements of sound energy as a function of frequency. Includes analysis

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The principal component also contains the steps for implementing a set of measurements using a test template that includes various MPF conditions that include at least one variable that is selected from the set of graduated values ​​for water droplet, graduated values ​​for total liquid flow, MPF systems, and post-processing of the data by applying principal component analysis to the data. To determine the frequencies that can be measured and related to identification

<p dir="rtl">5 MPF properties.</p>

Some system models also include an optimized otosensor, where the optimized otosensor receives frequencies that principal component analysis has determined are relevant to MPF characterization.

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An efficient multiphase fluid flow (MPF) classification system is also disclosed to enhance the measurement and control of a flow regime in a section of a pipe for hydrocarbon production processes. The system includes an audio receiver placed near the pipe part and can be operated to receive an audio signal to be sent through the MPF, and the part of the pipe can carry the MPF in the production of hidrocarbon which includes at least two physical phases, and the audio receiver converts the received electrical signal into an electrical signal. The system also includes an audio transmitter located near the pipe part and serves to deliver an audio signal through the MPF in hydrocarbon production processes, and also works to deliver the audio signal so that the audio signal can be received by the audio receiver. The system also includes a processing unit, which includes a processor, that receives the electrical signal and converts the electrical signal to MPF classification.

The processing unit is in contact with a non-temporary physical memory medium in connection with the processor 20 that has a set of stored instructions, where the stored instruction set can be executed by

The processor, which includes the steps of dividing the electrical signal into short-term, medium-term, and long-term time series and assigning positive real numbers to the time series, where the positive real numbers include larger values ​​and smaller values, where the larger values ​​correspond to the randomness of the process, and where the smaller values ​​correspond to states of possible patterns Recognize it in the electrical signal. Set includes

<p dir="rtl">25 The instructions also provide steps for classifying certain positive real numbers as odd values ​​and calculating values</p>

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Approximate short, medium, and long-term entropy of MPF by short-, medium-, and long-term time series of the electrical signal. The instruction set also includes steps for comparing the approximate short-term, medium-term, and long-term entropy values ​​of the MPF to the predetermined approximate short-term, medium-term, and long-term entropy values ​​and characterizing

<p dir="rtl">5 MPF in response to the similarities between the approximate short-, medium-, and long-term entropy values ​​of the MPF and the predetermined approximate short-, medium-, and long-term entropy values.</p>

The processing unit also includes a user interface associated with the processing unit, where the user interface operates

Accepts user input to control the processing unit, and displays MPF 10 properties to the user. In some embodiments, the active system also includes a database with predetermined approximate short-term, medium-term, and long-term entropy values ​​for several MPF flow systems. In some embodiments, the system also includes a preamplifier that is coupled to the audio receiver, and can be triggered to receive and amplify the electrical signal from the audio receiver. In other embodiments, the system also includes a signal bandpass filter associated with the preamplifier, the signal bandpass filter operating

<p dir="rtl">15 Receives an amplified electrical signal from the preamplifier, and also serves to remove the audio background noise from the MPF useful audio information contained in the amplified electrical signal, in response to cut-off frequencies programmed into the signal's bandpass filter derived from the audio receiver's operating frequency and bandwidth.</p>

On some models, the system also includes an analog-to-digital converter coupled to a bandpass filter

<p dir="rtl">20 For the signal, the analog-to-digital converter receives from the signal bandpass filter the useful audio information of the MPF, and converts the useful audio information of the MPF into a digital signal. In other embodiments, the system also includes an amplifier located near the audio transmitter and can be switched on to receive and amplify a drive signal to provide an amplified signal to the audio transmitter, where the amplifier is a high voltage amplifier whose voltage ranges from about 50 V (V) to</p>

<p dir="rtl">25 about 100 volts.</p>

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In some system models, the audio receiver includes a first audio receiver, and the system also includes a second audio receiver that is placed near a section of the pipe and can be switched on to receive an audio signal that is sent through the MPF, and the second audio receiver also converts the received electrical signal into a signal Electric, voice transmitter works

<p dir="rtl">5 The second position near the pipe portion delivers the audio signal through the MPF's operations</p>

Hydrocarbon production, and also works to connect the audio signal so that the audio signal can be received by the second audio receiver.

In some system embodiments, the second audio receiver is placed D distance from the first audio receiver, where D distance allows MPF measurements

<p dir="rtl">10 The bonded connectors are in a substantially similar condition for both the first audio receiver and the first audio receiver</p>

The second phonon, where an accurate measure of the MPF stream velocity is obtained by dividing the distance D by the difference in time between the first time the MPF crosses the first phonon and the second time the MPF crosses the second phonon.

In other models of an efficient system, the processing unit also executes a set of instructions

<p dir="rtl">15 To perform principal component analysis on the system that includes steps to collect the audio signal data</p>

Under a set of flux variables in cases where a suitable Reynolds number is known for the MPF for which the data is being collected, a time series of acoustic waveforms is generated, and an instantaneous transformation is performed on the data, whereby the data is converted into acoustic power measurements as a function of frequency , and perform set measurements using a test template that includes various MPF conditions that include a variable

<p dir="rtl">20 At least one is selected from the set of water droplet gradients, total liquid flow gradients, and MPF regimes, and a post-data processing by applying principal component analysis to the data to determine the measurable frequencies relevant to MPF characterization.</p>

In some system embodiments, the system also includes an optimized audio receiver, where the optimized audio receiver receives the frequencies identified by the component analysis

<p dir="rtl">25 The main one is related to setting MPF properties.</p>

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In addition, a method for multiphase fluid flow (MPF) classification is disclosed to enhance the measurement and control of the flow regime in a part of a pipe for hydrocarbon production processes. The method includes the steps of sensing the phonon emission from the MPF, whereby the pipe portion can carry the MPF in hydrocarbon production processes involving at least two physical phases and converts the phonon emission into

<p dir="rtl">5 electrical signal. The method also includes the steps of dividing the electrical signal into short-term, medium-term, and long-term time series, and assigning positive real numbers to the time series, where the positive real numbers include larger values ​​and smaller values, where the larger values ​​correspond to the randomness of the process, and where the smaller values ​​correspond to cases of patterns Recognizable in the electrical signal. The method also includes steps for classifying certain positive real numbers as outliers, and calculating values</p>

<p dir="rtl">10 Approximate short, medium, and long-term entropy of the MPF in response to the short-, medium-, and long-term time series of the electrical signal.</p>

The method also includes the steps of comparing the approximate short-term, medium-term, and long-term entropy values ​​of the MPF with the predetermined approximate short-term, medium-term, and long-term entropy values ​​and characterizing the MPF in response to the similarities between the approximate short-term entropy values,

<p dir="rtl">15 the medium-term, long-term MPF and approximate predetermined short-term, medium-term, and long-term entropy values.</p>

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In some embodiments, the method also includes the step of displaying the MPF properties on a user interface, where the user interface graphically represents at least one flow system. In some embodiments, the method also includes a step of pre-amplification of the electrical signal before the step of splitting the electrical signal. In other embodiments, the method includes a step of filtering the electrical signal, before splitting the electrical signal, in response to cut-off frequencies programmed into the signal bandpass filter derived from the operating frequency and bandwidth of the otometric sensor. In other embodiments, the method also includes the step of converting the electrical signal into a digital signal, before dividing the electrical signal.

In some embodiments of the method, the otosensing step includes a first otosensing step, and also includes a second otosensing step of the MPF, whereby

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Sensing the second otos at the same time as the first and at a distance of D from it. In other embodiments of the method, the method includes a precise measurement step of the MPF flow velocity in response to distance D, the first otosensing, and the second otosensing. Also in other embodiments, the method includes the step of performing a principal component analysis

<p dir="rtl">5 The main component consists of the steps of collecting acoustic emission data under a set of flux variables in cases where a suitable Reynolds number is known for the MPF for which the data is being collected and a time series of acoustic waveforms is generated.</p>

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Principal component analysis also includes the steps of performing a real-time conversion on the data, where the data is converted into acoustic power measurements as a function of frequency, and performing a set of measurements using a test template that includes various MPF conditions that include at least one variable chosen from the set of graduated values Water droplets, total liquid flow gradients, multiphase flow patterns, and post-processing of the data by applying principal component analysis to the data to determine the measurable frequencies relevant to MPF characterization. In some embodiments, the method also includes an optimization step by sensing an acoustic emission from the MPF to receive the frequencies that the principal component analysis has determined to be relevant to the MPF characterization.

In addition, a method for classifying a multiphase fluid flow (MPF) is disclosed to enhance the measurement and control of the flow regime in a part of a pipe for hydrocarbon production processes. The method includes the steps of transmitting an audio signal through the MPF, receiving the audio signal transmitted through the MPF, whereby the pipe part can carry the MPF in hydrocarbon production processes involving at least 20 physical phases, and converting the audio signal into an electrical signal. The method also includes division steps

the electrical signal to short-term, medium-term, and long-term time series, and assign positive real numbers to time series, where positive real numbers have larger and smaller values, where larger values ​​correspond to the randomness of the process, and where smaller values ​​correspond to states of recognizable patterns in The electrical signal, and the classification of certain positive real numbers as outliers.

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The method also includes the steps of calculating the approximate short, medium and long-term entropy values ​​of the MPF in response to the short-term, medium-term and long-term time series of the electrical signal, and comparing the short-term, medium-term and long-term approximate entropy values ​​of the MPF with the short-term and medium-term approximate entropy values predetermined long-term

<p dir="rtl">5 and characterizes the MPF in response to the similarities between the approximate short-term, medium-term, and long-term entropy values ​​of the MPF and the predetermined approximate short-term, medium-term, and long-term entropy values.</p>

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In some embodiments, the method also includes the step of displaying the MPF properties on a user interface, where the user interface graphically represents at least one flow system. In other embodiments, the method also includes a step of pre-amplification of the electrical signal before the step of splitting the electrical signal. Also in other embodiments, the method also includes a signal filtering step

The electrical, by pre-dividing the electrical signal, responds to cut-off frequencies programmed into the bandwidth filter of the signal derived from the operating frequency and bandwidth of the audio receiver. In some embodiments, the method also includes the step of converting the electrical signal into a digital signal, before dividing the electrical signal.

In some embodiments of the method, the reception step of an audio signal includes a first audio reception step, and also includes a second audio reception step transmitted through the MPF, wherein the second audio signal is received synchronously with and at a distance D from the first audio signal, and wherein the step includes Transmission of an audio signal has a first audio transmission step, which also includes a second audio transmission step through MPF, whereby the second audio signal is connected simultaneously with and at a distance D from the first audio signal.

Also in other embodiments of the method, the steps for calculating an accurate measurement of the MPF flow velocity in response to distance D, reception of the first acoustic signal, and reception of the second acoustic signal are included. Some models include the step of performing a principal component analysis, whereby the principal component analysis includes the steps of collecting the acoustic signal data under a set of flow variables in cases where a suitable 25 Reynolds number is known for the MPF for which the data is being collected and building a time series of Shapes

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sound wave. Principal component analysis also includes the steps of performing a real-time conversion on the data, where the data is converted into acoustic energy measurements as a function of frequency, carrying out a set of measurements using a test template that includes various MPF conditions that include at least one variable that is chosen from the set of graduated values ​​for a snapshot Water, total liquid flow graduated values, and flow patterns

<p dir="rtl">5 Polyphasic, post-processing of the data by applying principal component analysis to the data to determine the measurable frequencies related to MPF characterization.</p>

In some embodiments, the method also includes an example step of receiving an audio signal from the MPF to receive the frequencies that the principal component analysis has determined to be relevant for MPF characterization.

Brief description of the drawings

<p dir="rtl">10 These features, properties, and advantages of the present invention will become clear by looking at the following description, protections, and accompanying drawings. It should be noted that the drawings only show several models of the invention, and therefore are not considered restrictive to the field of invention, as they may include other models with the same effectiveness.</p>

Figure 1 is a schematic diagram of a passive system according to one of the embodiments of the present invention.

Figure 2 is a schematic diagram of a passive system according to one of the embodiments of the present invention.

<p dir="rtl">15 Figure 3 is a schematic diagram of an active system according to one of the embodiments of the present invention.</p>

Figure 4 is a schematic diagram of an active system according to one of the embodiments of the present invention.

Figure 5 is a graphical representation of multiphase fluid flow (MPF) systems, optionally for display on a user interface according to an embodiment of the present invention.

Figure 6 is a process flow diagram of a method according to one of the embodiments of the present invention.

20 Detailed description:

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The features and advantages of method models, systems, non-computer readable storage media with stored computer programs, etc., will be explained in more detail, and a more precise description will be given of models of methods, systems, non-computer readable storage media with stored computer programs which They have been briefly described by reference to their models, which will be explained in the accompanying drawings which form part of this description. However, it should be noted that the drawings only illustrate different models of road disclosures, non-temporary computer-readable media and systems that have computer programs stored according to the current disclosure and are therefore not considered to be restricted to road models, non-temporary computer-readable media and systems that have Computer programs stored according to the scope of the current invention and may include other effective models as well.

<p dir="rtl">10 Referring now to Fig. 1, a schematic diagram of a passive system based on 100 acoustic emissions, according to one of the embodiments of the present invention, is shown. In the embodiment of Figure 1, the passive system based on acoustic emissions 100 includes a pipeline 102 with at least one part 104 carrying a polyphase fluid flow (MPF). While Fig. 1 shows an MPF ​​vector in the Y1 direction, System 100 is capable of carrying an MPF ​​in either the Y1 or Y2 direction. emission is defined</p>

<p dir="rtl">15 Acoustic in MPF ​​is defined as a natural phenomenon that occurs within the surface of the MPF, and causes an instantaneous release of acoustic energy in a wide frequency range from 1 kHz to about 1 MHz.</p>

In some embodiments, the Y1 direction is the uphole direction in a well environment or the upstream direction in a pipeline environment. In some embodiments, the Y2 direction is the downhole direction in a well environment or is the downstream direction in a pipeline environment. A person of average skill in the field will realize that

<p dir="rtl">20 MPF may contain turbulent flows in reverse, but the flow generally travels toward or away from the surface in a well environment or toward or away from a pressure producing source, such as a pump, in a pipeline environment.</p>

The systems and methods of the present invention are compatible for use with any pipe or pipeline capable of carrying an MPF, including, but not limited to, above-ground pipelines, underground pipelines, underwater pipelines, pipelines inside a borehole,

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and closed pipelines, eg in a laboratory environment or pilot unit. The "pipes" or "pipes" within the wellbore may include any or a combination of conduits, jacketed flow conduits, coiled tubing, drill pipe, production line, completion casing, and drill casing.

Challenges facing current systems in pipelines include very low rates of

<p dir="rtl">5 signal-to-noise (SNR) and randomization of the acoustic emission signals. Furthermore, other disadvantages include interference of commercially available measurement systems, high power consumption, use of radioactive sources, high cost, high complexity, and large physical size. Due to these and other shortcomings in existing systems and methods, most of them are unable to provide accurate measurements and classifications of MPF in practical industrial scenarios. For example, one of these environments is a down environment</p>

<p dir="rtl">10 The well where many intervening factors affect MPF acoustics in a complex way. Also, existing systems and methods do not take into account the acoustic variations and the unstable nature of the AE acoustic emission signal.</p>

“Upstream Multiphase Flow Assurance in MPF ​​Monitoring Using Acoustic Emission Certain Properties are Described,” 2012 by Al-Lababidi, S.; Mba, D.;

<p dir="rtl">15 and Addali, A. Cranfield University, UK. The phonon emission from the MPF depends, in part, on the formation of gas bubbles and cavities, the discontinuity and coalescence of the system, and the interaction of the different phases within the MPF. These characteristics vary with different MPF systems, flow rates, as well as the amounts of liquid, gas/vapour, and solids in the MPF. In general, acoustic information is used in the embodiments of the present invention to classify MPF and determine flow characteristics. For example, can</p>

<p dir="rtl">20 The proposed systems and methods can be used in determining the MPF system (eg, mollusk flow), and can be used in determining the individual characteristics of the MPF (eg, mollusk flow frequency).</p>

Also with reference to Figure 1, System 100 includes an OE sensor 106 affixed to segment 104 of pipeline 102. In System 100, the OE sensor 106 is a non-energized means that is used to receive broadband otoacoustic emissions (usually in the order of several

<p dir="rtl">25 106 units of kilohertz (kHz) of the MPF. The OE sensor conducts one or more of the 106</p>

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Reception, storage, processing, and communication of MPF audio emissions 108. The audio emissions sensor 106 receives audio emissions at frequencies up to about 1MHz in order to monitor useful MPF audio emissions from the stream, such as the MPF audio emissions 108. The audio emissions sensor includes a microphone On some models, it includes a commercially available 5 otoacoustic emissions power sensor/transducer on some models.

For example, the AE1045S from Vallen Systems, located in Icking, Germany, can be used at a frequency ranging from about 100 kHz to about 1500 kHz. At the same time, or alternatively, an ordinary wideband EA sensor, such as this, can be used

Located at Princeton Junction, New Mistras Group Ltd. commercially provided by the company

<p dir="rtl">10 Jersey. A common type of wideband EA sensor is the WSA wideband sensor, which operates at an operating frequency of about 100 kHz to about 1000 kHz.</p>

In the embodiments of the passive systems of the present invention, such as Figures 1 and 2, the acoustic emission sensors, such as the acoustic emission sensor 106, are mounted outside the pipe or are mounted inside a hole

<p dir="rtl">15 Etched into the barrel, so that the surface of the OD sensor is in contact with the MPF. In some embodiments, the preferred design is to mount the OE sensor outside the pipe, as having the sensor outside the pipe may impede or negatively affect the flow. In some cases, if an otoacoustic sensor is placed in the flow path, the interaction of the MPF with the sensor will generate more unwanted otoacoustic emissions that are not representative of the MPF.</p>

<p dir="rtl">20 The frequency or frequencies received by the Acoustic Emission Sensor will not be adversely affected if the Emission Sensor is installed outside the tube. Alternatively, an acoustic emission sensor can characteristically be fitted into a hole drilled in the pipe if the MPF is not obstructed. The OD variables affected by the OD sensor location include signal peak (amplitude) and signal-to-noise ratio (SNR). If the sensor is installed in a hole drilled in the pipe, the</p>

<p dir="rtl">25 The acoustic emission received will have a larger amplitude and better SNR.</p>

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If the sensor is mounted on the outside of the pipe, the peak otoacoustic emissions that are received will be weak (as the emission will have to travel through the pipe wall). Also, with the OE sensor mounted outside the pipe wall, more noise may be transmitted through the pipe wall to the sensor It is not related to setting the MPF properties, however, as already mentioned

<p dir="rtl">5 To this end, the installation of the OE sensors outside the pipe creates a non-intrusive system. An otosensor may be clamped or coupled to a section of pipe by any suitable means known in the art, eg any or any combination of clips, adhesives, nails, screws, and tape.</p>

More than one acoustic emission sensor can be used in the systems and methods of the present invention, eg

<p dir="rtl">10 The example is as shown in Figure 2. In some embodiments, a coupler is required to couple an OE sensor in a suitable position with a pipeline. In the system shown in Figure 1, glycerol or a lubricant is used to appropriately position the OE sensor 106 on the outside of the part 104 to receive the MPF phonon emissions 108. When the OE sensor 106 receives the MPF phonon 108, the OE sensor 106</p>

<p dir="rtl">15 Converts the MPF 108 audio emissions into electrical signals. These electrical signals are analog electrical signals, suitable for later conversion to digital signals, in the embodiment of Figure 1. In other embodiments, these electrical signals from the OE sensor can be connected as a digital signal directly to a processing unit.</p>

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In some embodiments, when an otometric sensor is installed outside a pipe wall, a coupling is required to remove any air from the interface between the pipe wall and the sensor. Air can be introduced to the fine structure and surface roughness of two surfaces in contact with the surface between the acoustic emission sensor and the pipe wall. One reason to avoid air between the OD sensor and the pipe wall is that the acoustic obstruction of the air is less than (approximately five times) the surface of the pipe or the surface of the sensor. This low acoustic impedance allows very little energy to be transmitted from the wall of the tube onto the sensor without a coupling, because most of the energy is lost. Use of the coupling may greatly improve transmission

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Acoustic emission from the MPF, through the pipe wall, to the acoustic sensor. A thin coupling layer is placed between the surface of the tube wall and the surface of the sensor. Higher acoustic impedance couplers may provide better acoustic energy transmission and better SNR. Examples of such couplers include glycerol and propylene glycol.

<p dir="rtl">5 As shown in Figure 1, the phonon emission sensor 106 is coupled via connection 110 to a signal conversion module 112. Connection 110 may be a wired connection or a wireless connection, and the MPF phonon emissions 108 that are received and converted into electrical signals are connected by a sensor Acoustic emission 106 to signal conversion unit 112. The electrical signals generated by the MPF's acoustic emissions 108 are converted from the acoustic emission sensor 106 to the signal transducer 10 112 by any or any combination of a cloud storage medium, a wired connection, and a wireless connection.</p>

In the embodiment of Figure 1, the converter unit 112 includes a preamplifier 114, a bandpass filter for the signal 116, and an analog-to-digital converter 118. In other embodiments, the converter unit includes more or less number of converters. In other embodiments, the preamplifier, 15 bandpass filter, and analog-to-digital converter are not part of a single unit, such as the

Signal conversion 112. In some embodiments, the signal conversion unit includes hardware components and a non-buffered physical memory medium in contact with a processor that has a set of stored instructions.

The MPF acoustic emissions 108 detected by the acoustic emission sensor 106 are a combination of useful MPF acoustic information, which is used to classify the MPF streaming system, 20 and random acoustic background noise from the environment around the pipeline 102. The signal is amplified

The converted electrical produced by the otosensor 106 and transmitted to the preamplifier 114 by connection 110 via the preamplifier 114 to produce an amplified analog electrical signal. In some models, more than one amplifier is used. The amplified analog electrical signal is connected by connection 120 to the signal bandpass filter 116.

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As with connection 110, connection 120 may be a wired connection or a wireless connection, and the amplified electrical signal is connected to the bandpass filter of signal 116. The amplified electrical signal can be transmitted from the preamplifier to the signal's bandpass filter by any combination of Cloud storage, wired connection, and wireless connection.

<p dir="rtl">5 After the electrical analog signal is amplified by the preamplifier 114, the signal is filtered using a bandpass filter for the signal 116. The cut-off frequencies of the bandpass filter for the signal 116, in the Fig. 1 embodiment, depend on the operating frequency and bandwidth of the ED sensor 106. In other embodiments The cutoff frequencies of the signal's bandpass filter can be modulated by user input or modified according to MP stream conditions, MPF formulation, or other environmental conditions.</p>

<p dir="rtl">10 The signal bandpass filter 116 filters out or removes unwanted frequencies that are not useful in rating an MPF ​​system, such as noise from the environment around the pipeline 102.</p>

In some embodiments, a bandpass filter can be used to remove any unwanted noise signal and improve the SNR. For example, in active system designs, such as those shown in Figures 3 and 4 below, when a fixed-frequency audio signal is transmitted through an MPF, 15 bandpass filters are used to limit the received signal to the known transmitted frequency or frequencies and remove the remaining frequencies of the signal. Similarly, for passive system designs, such as those shown in Figures 1 and 2, the frequencies required for the acoustic emissions from the MPF must be in a given frequency range for a given application, with the remaining irrelevant frequencies removed. The values ​​of these frequencies are determined in the laboratory by experiments. Also, for passive designs, such as those shown in Figures 1 and 2, OE frequencies below about 20 kHz are usually removed.

In some embodiments, an off-the-shelf programmable integrated circuit can be used in the use of a bandpass filter, such as the 116 bandpass filter. Several such integrated circuits are commercially available, for example from Texas Instruments, located in Dallas, Texas. , or Analog Devices, located in Norwood, Massachusetts. Commercial 25 front end terminal solutions for signal transcoding modules, such as transcoding modules 112, 113, and signal filters are also available.

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Bandwidths 116, 117. The AFE5803 8-channel fully integrated analog front end from Texas Instruments is a commercial front end solution. These devices can be programmed through a serial interface by sending commands to a specific device from a personal computer, such as a PC or a telephone. Also, a special integrated circuit can be developed

to any or any combination of application specific integrated circuit (ASIC) 5 with a typical application

of signal transcoders 112, 113 and bandpass signal filters 116, 117.

After the amplified electrical-analog signal is filtered by the bandpass filter of signal 116, the filtered electrical-analog signal is transmitted from the bandpass filter of signal 116 to the analog-to-digital converter (ADC) 118 via connection 122. As is

<p dir="rtl">10 As with Connection 110 and Connection 120, Connection 122 may be a wired connection or a wireless connection, and the filtered electrical-analog signal is connected to the ADC 118. The electrical-analog signal filtered from the signal bandpass filter can be transferred to the ADC via a storage medium cloudy. In some embodiments, the analog-to-digital converter is a high-definition sigma-delta analog-to-digital converter. It can also</p>

<p dir="rtl">15 The use of any other suitable commercially available analog-to-digital converter in embodiments of the present invention.</p>

Also referring to Figure 1, after the electrical analog signal has passed through the transcoder 112, a digital electrical signal is connected through connection 124 to the processing unit 126. As with connections 110, 120, and 122, connection 124 may be a wired connection or A wireless connection, or any combination thereof, can deliver a digital electrical signal to the unit

<p dir="rtl">20 Processing 126. The digital electrical signal can be transmitted from the analog-to-digital converter 118 to the processing unit 126 by means of a cloud storage medium. The processing unit 126, in the embodiment shown, includes a signal processor 128, a battery 130, and a physical memory 132. The processing unit includes more or fewer units than in other models, it is not necessary that the components of the processing unit are physically coupled or very close and there may be as separate components.</p>

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In the embodiment shown, the signal processor includes a 128-person PC that is used in combination with a digital signal processor (DSP) and a processor. Alternatively, DSP can be used without a PC. The signal processor 128 is used to calculate the approximate entropy; processing, analyzing, and classifying audio signals; and saving

<p dir="rtl">5 Results for MPF properties, which include the MPF streaming system. Below will be presented more details of these accounts. In the form shown, the signal processor 128 includes a user interface 134. Raw data, measurement results, MPF ratings, and any other user input or signal processor output information are entered through and displayed to a user on the user interface 134. One or more flow regimes shown may appear In Figure 5, described below, the interface</p>

<p dir="rtl">10 User 134.</p>

The user interface 134 also accepts user input to control the CPU 126 and system 100. In some embodiments, the user interface includes audible or visual alerts and warnings in response to the rating of the MPF system. For example, if System 100 determines that the MPF is not in flow slug when slug flow is not acceptable to System 100, an audible alarm is provided

<p dir="rtl">15 visible to the user.</p>

The UI 134 displays a graphical classification of the flow type as shown in Figure 5. The system 100 accepts user input via the UI 134 to change the flow regime, for example by

control valves, actuators, and other devices in the pipeline 102. Alternatively, the system 100 may operate independently, that is, without simultaneous user input and based on preceding rules and programs

<p dir="rtl">20 Placed, to change the flow regime in the pipeline 102 if the current flow regime is unacceptable. The MPF flow pattern is changed by means of control valves, actuators, and other means (not shown) in the pipeline 102. For example, if System 100 determined that the MPF was in flow slug when it was not mass flow, then it is acceptable to System 100 based on established rules. Already, the System 100 will alter the MPF of the flow regime eg by means of control valves, actuators, and other means</p>

25 (not shown) in pipeline 102.

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Battery 130 is used to power the signal processor 128 and physical memory 132. In other models, more or less batteries are used. That is, raw data, calculations, measurement results, and MPF ratings can be saved in physical memory 132. Physical memory 132 can communicate with signal processor 128, and also store approximate entropy execution steps

<p dir="rtl">5 and running principal component analysis, each of which is discussed below. The processing unit has 126 connected</p>

Also with an optional external database 136, which may also include steps, executables, predefined values ​​for MPF systems, and any other input or output of the processing unit 126.

In the example of Figure 1, the signal processor 128 computes the approximate entropy of the MPF in response to the received digital signal. In statistics, approximate entropy is approximate entropy

<p dir="rtl">10 ApEn is a method used to quantify the regularity and unpredictability of fluctuations in time series data. ApEn was produced by Steven Pincus in 1991's Approximate.</p>

entropy as a measure of system complexity,” Proc. Natl. Acad. Sci. USA,

This method is used .Vol. 88, p. 2297-2301, March 1991, Mathematics

Statistical measurement of complexity in noise time series data. ApEn is powerful and non-existent

<p dir="rtl">15 Plane-sensitive or outlier, meaning that rare, small, very rare, and very large values ​​have little effect on the calculation of ApEn. ApEn assigns a positive integer to a time series of data, with larger values ​​corresponding to randomness or greater apparent process irregularity, and smaller values ​​corresponding to instances of more pronounced patterns in the data.</p>

The values ​​of randomness and current complexity will vary for different polyphasic flow patterns, especially on

<p dir="rtl">20 With short timescales, randomness and flow complexity values ​​are approximated using the ApEn method.</p>

In the example of Figure 1, the signal processor 128 in combination with the physical memory 132 performs the following steps. First, it divides the received digital signal into short-term, medium-term, and long-term time series. These time series of digital signals serve as inputs to the ApEn computational systems described below. Then, to use in equations 1 and 2, we are assigned a number

<p dir="rtl">25 positive integer for the time series, where positive real numbers have larger and smaller values,</p>

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Where larger values ​​correspond to process randomness, and where smaller values ​​correspond to states of recognizable patterns in the digital signal. Then, certain positive integers are classified as outliers. After the previous steps, using equations 1 and 2, the approximate short-term, medium-term, and long-term entropy values ​​of the MPF are calculated according to the short-term, medium-term, and long-term time series5 of the digital signal. For longer otoacoustic emissions measurements, values ​​of

Multiple ApEn to calculate average values ​​for short, medium, and long term ApEn.

The logarithmic system for calculating ApEn for time series data is known and described below. First, the time series of the data can be obtained, say from components 106 to 132 in Figure 1. That time series of the data can be represented by ( ) ,…,(2) ,(1), where the values ​​of

<p dir="rtl">10 Raw data at equidistant intervals. Then, an integer m is assigned, a positive integer r, where is the comparative run-length of the data, and r specifies the level of filtering. Then, the sequence of vectors (1 + - )^ ,…,(2)^ ,(1)^ in^{^} i , is specified</p>

Dimensional space - real m by [(1 - + ^),…,(1 + ^) ,(^)] = (^)^ ..

After these steps, the sequence (1 +- )^ ,…,(2)^ ,(1)^ is used to construct each ^,

<p dir="rtl">_{15 where 1+- ≥ ^ ≥ 1}&gt;[()^,(^)^] ^ℎ ℎ()^ ^_{= (^)}^ _{,, where}</p>

1+^- ^{^}

|(^)^∗ - (^)|_^^^ = [^∗^ ,^].

(^) are the numeric components of ^ . Here, d is the distance between vectors (^)^ and (^) , with

Consider the maximum difference in their corresponding numerical components.

Then, processing 1 is calculated using the previously described items.

20 ((^)^{^}^ ) Φ^{^}(^) = ( -+ 1)^-1∑^=^-1^{^+1}log (Equation 1)

After the previous steps, the classical entropy is calculated according to Equation 2.

<p dir="rtl">(^)^{1+^}Φ^{^}(^) - Φ = (Equation 2)</p>

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For ApEn-based MPF system measurements and classifications, a database of short-, medium-, and long-term ApEn values ​​representative of the respective MPF system at various flow rates is developed. This data can be gained from laboratory flow loops and actual field tests. Data gained from surface or downhole conditions can be used depending on the intended application. can develop

<p dir="rtl">5 Different databases for different model systems, such as the different models shown in Figures 1-4. The initial classification of the system of the present invention may occupy space in a flow loop rather than in a well or field application, but the flow loop data should ideally be representative of in-well MPF systems or field application.</p>

The MPF loop that is generally used in laboratory tests and measurements is the circuit

<p dir="rtl">10 closed (when a loop is present). Individual flow rates of water, brine, oil and gas may vary to produce representative flow conditions for different wells and fields. In some embodiments, a separator is used within the flow loop to separate the different phases. Flow loops may also operate at Higher temperature and pressure, and the actual gas field conditions can be doubled in the plant.</p>

After calculating the ApEn values ​​from the digital signal, these short, medium and long term values ​​of

<p dir="rtl">15 ApEn with previously computed short-, medium- and long-term ApEn values ​​in physical memory 132 and, optionally, values ​​in a database similar to precomputed values, such as the optional external database 136. Finally the MPF properties are determined in response to similarities between approximate short-term entropy values Computed short-term, mid-term, and long-term MPF of the digital signal and approximate entropy values ​​computed short-term, mid-term, and long-term computed in memory</p>

<p dir="rtl">20 Physical 132. After specifying the MPF flow regime, and other properties such as flow velocity (also described below for Figure 2), the calculations, results and flow classification are displayed on the UI 134, which accepts user input to control the processing unit, and displays the MPF properties on the System user or operator 100.</p>

In embodiments of the present invention, in order to classify the MPF in response to monitoring an acoustic emission, it is initially done

25 Classify a system, optionally in the lab, to develop a detailed database containing ApEn values

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for various flow systems. In certain embodiments of the present invention, in order to initiate MPF classification in the system, the following classification steps can be performed. These steps allow physical memory 132, or other databases that can communicate with the processing unit 126, to contain a complete series of values ​​that can be used to classify MPF streaming systems. The steps, in an embodiment, are as follows.

<p dir="rtl">5 First, at either or both of the plant or field site, different MPF designs are produced at</p>

Applicable pipeline design. For the various resulting MPF designs, different fractions of oil, water, gas, and solids must be used. These conditions are designed, in some embodiments, to closely resemble actual MPF designs expected during field applications in which the MPF must be classified according to the systems and methods of the present invention. Next, the test template where they differ is determined

<p dir="rtl">10 Oil, water (or brine), and gas rates accordingly. These conditions are designed, in some cases, to closely resemble actual MPF designs expected during field applications in which the MPF must be classified according to the systems and methods of the present invention. Test matrices may be produced With the following conditions: (1) graduated water drop values; (2) graduated values ​​of total liquid flow; and (3) different MPF flow patterns, as shown in Figure 5.</p>

<p dir="rtl">15 After these steps, ApEn is calculated for each data point in the test template. ApEn is calculated using the previous algorithms. In one embodiment, the following entropy values ​​can be calculated: (i) short-term (S): about 1-10 s; (ii) medium M) term: about 10-20 seconds; and (iii) long-term (L): about 2-10 min. For each given flow regime, at each test point in the test die, the resulting calculated MPF values ​​may be in</p>

<p dir="rtl">20 An image of a range of values, not necessarily a fixed number. By completing the initial flow classification steps, a data set of ApEn values ​​for various flow conditions is obtained and stored in a database, eg physical memory 132 in Figure 1.</p>

Referring now to Fig. 2, a schematic diagram of a passive system based on 200 correlation acoustic emissions is shown, according to one of the embodiments of the present invention. Certain items shown are also shown

<p dir="rtl">25 In Figure 2 and in Figure 1 the previous described. In Figure 2 model, plus an emission sensor</p>

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The acoustic sensor 106 is installed on the part 104 of the pipeline 102, and a second acoustic sensor 107 is installed on the part 104 of the pipeline 102. As shown, the second acoustic sensor art 107 follows the acoustic emission sensor 106 in the Y1 direction; However, in other embodiments the second acoustic sensor 107 may be placed prior to the acoustic emission sensor 106 in the Y2 direction at the 5-pipe segment 102 that operates on the MPF load.

In Figure 2, connection 111, converter 113, preamplifier 115, bandpass filter 117, analog-to-digital converter 119, and connections 121, 123, and 125 are shown. These modules are similar, respectively, to connection 110, transcoder 112, preamplifier 114, bandpass filter 116, analog-to-digital converter 118, and connections 120, 10 122, and 124 previously described. In some embodiments, components 113, 115, 117, must not be separated.

119, 121, 123, and 125 for components 112, 114, 116, 118, 120, 122, and 124.

For example, a connection 111 starting from the second acoustic sensor 107 may simply connect the second acoustic sensor 107 to the signal transducer 112 and the rest of the components.

In the embodiment of Fig. 2, the otosensor 106 and the second otosensor 107 are placed at a distance of D. More than two otosensors are used in other embodiments of the present invention. A pair of EERT sensors 106, 107 are used to measure the flow velocity through the pipe. Acoustic Emission Sensors 106 and 107 are placed relatively close together so that the MPF pattern is consistent or similar as it passes through both sensors. The relative affinity of the Acoustic Emission Sensors 106 and 107 to each other will vary, in part, depending on the pipeline geometry 20 102 and the physical fluid properties. The distance between the OE sensors may be 106, 107

Within 1 meter, it may be within 0.5 meters, or it may be within 5 meters. If more than two OE sensors are used, the distance between corresponding OD sensors may be the same or different. If one sensor is on the vertical part of the casing and the other is on the horizontal part of the casing, D will be the flow distance between both sensors, 25 and not the actual distance.

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When the MPF advances through segment 104 of the pipeline 102, each of the otoacoustic emissions 106, 107 receives the otoacoustic emissions of the MPF stream separated by a known distance D. If the MPF characteristics are compatible/substantially similar when measured at both otoacoustic sensors 106, 107, it calculates the time required for the fluid to move between

<p dir="rtl">5 EA Sensor 106, 107. For example, at a certain time MPF t1 passes</p>

With an acoustic emission sensor 106 and another set time t2, the MPF passes the second acoustic sensor 107. If the flow characteristics of the MPF are substantially the same at both points, then Δt is calculated to determine the velocity by t2-t2=Δt. In certain embodiments, by correlating the raw otoacoustic emissions received from each of the otoacoustic emissions sensors 106 and 107, and determining whether all 10 otoacoustic emissions are substantially the same, the fluid velocity is provided by the equation that

Velocity = Δt/D.

Therefore, the Acoustic Emission Sensors 106 and 107, when used in this manner, provide an accurate estimation of fluid velocity along with the measurement of the MPF system. The distance D must be selected carefully, because if this distance is too large or small, the OE sensors 106, 107 will not see the same

<p dir="rtl">15 physical characteristics in the MPF system, and the correlation between the OE sensors 106 and 107 will not provide reliable measurement results. Fluid velocity throughout part 104 is calculated by the processing unit 126 and displayed on UI 134. UI 134 displays real-time fluid flow properties including fluid velocity and displays graphs comparing past flow properties with current flow properties, such as flow velocity.</p>

<p dir="rtl">20 Referring now to Fig. 3, a schematic diagram of an efficient system based on acoustic emission 300 is shown, according to an embodiment of the present invention. Some of the components are numbered according to the pattern of Figure 1 and represent the same components described with reference to Figure 1 above. In the example of Figure 3, the audio transmitter 140 is mounted on pipeline 102 near section 104 and is largely in line with the audio receiver 150. In the models of Figures 3 and 4, the system designs are functional. in</p>

<p dir="rtl">25 In efficient system designs, one or more audio transmitters are used to transmit a signal</p>

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Fixed-frequency audio through MPF, and the audio signal is received by one or more audio receivers. Processing is then performed on the received electrical signal received by the audio receiver(s) to determine the MPF stream scheme and other characteristics.

In some embodiments of the active systems described, audio transmitters transmit an audio signal at a frequency

<p dir="rtl">5 My voice is fixed or within a narrow, predetermined band of frequencies. This fixed frequency (or a predetermined narrow band of frequencies) can be received by the audio receiver for one or more of the following: storage, transmission, processing. The audio transmitter(s) and audio receiver(s) of active systems have the characteristics of a transducer Similar, but not limited to, operating frequency, bandwidth, sensitivity, and beam angles.</p>

<p dir="rtl">10 In the system model shown in Figure 3 (and Figure 4), the voice transmitter 140 and voice receiver 150 are in direct contact with the MPF. The voice transmitter 140 and voice receiver 150 are installed in matching holes drilled in the section 104 of the pipeline 102, such that The transmitting surface of the audio transmitter 140 and the receiving surface of the audio receiver 150 are in direct contact with the MPF Components 140, 150 are installed in this design</p>

<p dir="rtl">15 So that the acoustic energy is effectively propagated from the audio transmitter 140 through the MPF of the audio receiver 150.</p>

The audio transmitter 140 and the audio receiver 150 operate at a fixed high frequency, ranging from about 0.5MHz to about 2MHz. The audio transmitter 140 and the audio receiver 150 operate at narrow beam angles, ranging from about 5o to about

<p dir="rtl">20 o15. In the embodiment of Figure 3, the processing unit 126 also includes a signal generator unit 142 within the signal processor 128. The signal generator unit 142 is operated and controlled via the user interface 134 to provide a management signal 144 to the audio transmitter 140. In some embodiments, the signal generator unit generates a signal It is a high frequency continuous sine wave, ranging from about 0.5MHz to about 2MHz. In other embodiments, however, other signals are produced by the signal generating unit.</p>

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The drive signal of the audio transmitter 140, in the form of Figures 3 and 4, can be modulated and may be a continuous sine wave or a square wave with a frequency equal to the operating frequency of the audio transmitter 140 and the audio receiver 150. The peak of the signal ranges from about 5 to about 10 volts (V) . The management signal can be generated using a built-in oscillator or any commercial digital signal processor

<p dir="rtl">5 DSP processor) or microcontroller (MCU).</p>

The management signal 144, in the embodiment shown, is amplified by an optional amplifier 146 before being connected to the audio transmitter 140. In other embodiments, the presence of the optional amplifier is not required. The op-amp 146 is a high-voltage amplifier that operates between about 50 volts to about 100 volts. The amplified signal is provided to manage the audio transmitter 140. When

<p dir="rtl">10 Audio transmitter 140 receives amplified management signal from operational amplifier 146, audio transmitter 140 converts electrical drive signal into audio signal 148. Audio signal 148 generated by audio transmitter 140 can be continuous signal. In some embodiments, the audio signal is of high frequency, from about 0.5MHz to about 2MHz.</p>

<p dir="rtl">15 The audio signal 148 travels from the audio transmitter 140 through the MPF in the pipeline segment 104 102 and is received by the audio receiver 150. The peak and power of the signal received at a given time depends on the actual composition of the MPF at that time. The audio receiver 150 receives the audio signal 148 and converts it into an electrical signal, in the form shown an analog electrical signal. As previously described for Figure 1, the received signal is pre-amplified by</p>

<p dir="rtl">20 The preamplifier route 114 is inside the signal transducer 112. The received signal consists of an actual signal as well as audio noise from the stream or pipeline. After the preamplifier 114, the signal passes through the signal bandpass filter 116, the analog-to-digital converter 118, and to the processing unit 126. The signal processing 128 calculates the power of the received signal (refer to Equation 3 below) and calculates the approximate entropy as previously described. Next, it analyzes The signal processor is 128 and classifies the signals</p>

<p dir="rtl">25 Acoustics to provide and display measurement results of MPF properties and flow system.</p>

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The calculated results, together with the raw data received by the audio receiver 150, are stored in physical memory 132 and displayed using the user interface 134. That is, the data within the processing unit 126 can be communicated, stored, and displayed at a remote location using any or any combination of wired connections And wireless internet like bluetooth wireless technology.

<p dir="rtl">5 Referring now to Fig. 4, it shows a connection diagram of an efficient system based on phonon emission 400, according to one of the embodiments of the present invention. Certain components shown in Figure 4 are shown in Figures 1-3 and previously described. In the embodiment of Figure 4, in addition to the audio receiver 150 installed on segment 104 of pipeline 102, a second audio receiver 151 is mounted on segment 104 of pipeline 102. As shown, the audio receiver</p>

<p dir="rtl">10 the second 151 follows the audio receiver 150 in the Y1 direction; However, in other embodiments the second voice receiver 151 may be placed before the voice receiver 150 in the Y2 direction at the segment of pipeline 102 where it carries the MPF.</p>

In Figure 4, connection 111, converter 113, preamplifier 115, bandpass filter 117, analog-to-digital converter 119, and connections 121, 123, and 125 are shown. This is amazing

<p dir="rtl">15 The modules are similar, respectively, to connection 110, converter 112, preamplifier 114, pass-band filter 116, analog-to-digital converter 118, and connections 120, 122, and 124 previously described. In some embodiments, components 113, 115, 117, 119, 121, 123, and 125 must not be separated from components 112, 114, 116, 118, 120, 122, and 124. For example, connection 111 traveling from the second audio receiver may simply connect 151</p>

<p dir="rtl">20 The second audio receiver 151 to the signal transducer 112 and the rest of the components.</p>

In the example of Figure 4, in addition to the audio transmitter 140 installed on segment 104 of pipeline 102, a second audio transmitter 141 is installed on segment 104 of pipeline 102. As shown, the second audio transmitter 141 follows the audio transmitter 140 in the Y1 direction ; However, in other models the 141 second audio transmitter can be placed before a device

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Voice transmission 140 in the Y2 direction at the portion of pipeline 102 where it operates as a load

.mpf

Audio Transmitters 140, 141 and Audio Receiver 150, 151 operate at a fixed high frequency, ranging from about 0.5MHz to about 2MHz. 140 audio transmitters,

<p dir="rtl">5 141 and audio receivers 150, 151 are operated at narrow beam angles, ranging from</p>

About o5 to about o15. In the embodiment of Figure 4, the processing unit 126 also includes a signal generator unit 142 within the signal processor 128. The signal generator unit 142 is operated and controlled via the user interface 134 to provide a management signal 144 for audio transmitters 140, 141. The signal generator unit 142 generates a waveform signal High-frequency continuous sinusoids, ranging from about 0.5MHz to

<p dir="rtl">10 about 2MHz. In other embodiments, however, the signal generating unit can generate other signals.</p>

The management signal 144 is amplified by an operational amplifier 146 and an optional second amplifier 147 before being connected to audio transmitters 140 and 141, respectively. In other models, optional amplifiers are not required. The optional amplifiers 146, 147 are high voltage amplifiers operating at about 50V to about 100V. The amplified signal is provided

<p dir="rtl">15 To manage the audio transmitters 140, 141. When the audio transmitters 140, 141 receive an amplified management signal from the operational amplifiers 146, 147, respectively, the audio transmitters 140, 141 convert the electrical signal into audio signals 148, 149. The audio signals are 148, 149 generated by audio transmitters 140, 141 are continuous signals. In some embodiments, the audio signals are of high frequency, from about 0.5MHz to about 2MHz</p>

<p dir="rtl">20 megahertz.</p>

Audio signals 148, 149 from audio transmitters 140, 141 travel through the MPF in segment 104 of pipeline 102 and are received by audio receivers 150, 151, respectively. The peak and power of the signals received at a given time depend on the actual MPF combination at that time. Audio receivers 150, 151 receive audio signals 148, 149 and convert them into a signal.

<p dir="rtl">25 analog electrical. As previously described for Figure 1, the received signals are amplified</p>

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Primarily via preamplifiers 114, 115 into signal transducers 112 and 113, respectively. The received signals consist of actual useful signal as well as audio noise from the MPF, the pipeline, and the environment surrounding the pipeline. After preamps 114, 115, the signal passes through signal bandpass filters 116, 117, and analog-to-digital converters

<p dir="rtl">5 118, 119, and to the processing unit 126. The signal processor 128 calculates the power of the received signals</p>

and calculate the approximate entropy as previously described. Then, the signal processor 128 analyzes and classifies the audio signals to provide and display the results of the MPF measurement of the stream characteristics and system.

The calculated results, together with the raw data received by the audio receivers 150, 151, are stored in physical memory 132 and displayed using the user interface 134. That is, data can be communicated

<p dir="rtl">10 within the Processing Unit 126, store it, and display it at a remote location using any or any combination of wired or wireless communications such as wireless internet, bluetooth technology.</p>

In the embodiment of Fig. 4, the audio receiver 150 and the second audio receiver 151 are placed D apart. Two audio receivers can be used in other embodiments of the present invention. A pair of audio receivers 150, 151 is used to measure the velocity of flow through the pipe. The audio receivers 150 and 151 are placed relatively close together

So that the MPF pattern matches or is the same as it passes through both sensors. The relative proximity of Voice Receivers 150 and 151 to each other will vary, in part, depending on the geometry of the pipeline 102 and the physical properties of the fluid. The distance D between the audio receivers 150, 151 may be within 1 meter, or about 0.5 meters, or about 5 meters. If one of the sensors is on the rc part of the

<p dir="rtl">20 casing and the other on a horizontal part of the casing, D will be the flow distance between each of the two sensors, not the actual distance.</p>

As the MPF progresses through segment 104 of pipeline 102, audio receivers 150 and 151 each receive audio signals 148 and 149 from audio transmitters 140 and 141, respectively, through the MPF stream. Audio receivers 150, 151 separated by the known distance D. If

<p dir="rtl">25 The MPF characteristics were largely similar when measured at both</p>

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Audio receivers 150, 151, then calculate the time required for the fluid to travel between audio receivers 150, 151. For example, at a certain time t1 the MPF passes the audio receiver 150 and at a certain time t2 the MPF passes the second audio receiver 151. So The flow properties of the MPF were quite similar at both points, Δt is calculated for velocity as t2 5 - Δt = t1. In certain embodiments, by linking the raw signals received at both audio receivers

150, 151 of the audio transmitters 140, 141, respectively, and to determine if both signals are substantially the same, the fluid velocity is obtained using the equation Velocity = D

.Δt/

Therefore, when the 150 and 151 audio receivers are used in this way, they provide an accurate estimate of

<p dir="rtl">10 For fluid velocity with the MPF measurement system. The distance D must be carefully selected, because if D is too large or small, receivers 150, 151 will not see the same physical characteristics in the MPF system, and correlation between receivers 150, 151 will not provide reliable measurement results. The fluid velocity through the segment 104 is calculated by the processing unit 126 and displayed on the user interface 134.</p>

<p dir="rtl">15 Referring now to Figs. 3 and 4, for the EE-based active system 300 and the EE-based active correlation system 400, the following steps are used, in an embodiment, to operate the systems for accurate measurement, calculation, and flow system characteristics of mpf. First, the audio transmitter 140 is activated along with the audio receiver 150. In the example of Figure 4, the second audio transmitter 141 and the second audio receiver 150 are activated</p>

<p dir="rtl">20 151. Next, the audio signal received by the audio receiver 150 is pre-amplified</p>

via the preamplifier 114, filtered by a bandpass filter of the signal 116 and converted to a digital signal by the analog-to-digital converter 118. In the example of Fig. 4, the audio signal received by the second audio receiver 151 is pre-amplified by the preamplifier 115, and filtered by the m-filter Bandwidth of the signal 117 and convert it into a digital signal by means of the converter

<p dir="rtl">25 Analog-digital 119.</p>

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Next, the digital signal is acquired by the processing unit 126 and the signal processor 128. The signal processor 128 can calculate the power Es of the received audio signal, x(n), using equation 3, as follows:

<p dir="rtl">²|()^| ∞^∞-∑ = equation (3)</p>

<p dir="rtl">5 For a finite number of N samples, equation 3 can be rewritten as equation 3a:</p>

<p dir="rtl">²|()^|0=∑ = (3a)</p>

In some embodiments, the power is calculated per 1000 cycles of the signal received. For example, if Systems 300 and 400, including audio transmitters and audio receivers, are operating at 1MHz, power is calculated every 1,000 cycles, which equals 1,000 power measurements every

<p dir="rtl">10 second. Using this example, if the received signal is sampled at the fs sampling frequency, then the number of samples N will be equal to equations 3b and 3c as follows:</p>

<p dir="rtl">^^ ^^ x x = (3b)</p>

^^^

1000× ×¹6 = (3c)

Signal processing 128 divides the sound energy signal(s) into short, medium, and long time series.

<p dir="rtl">15 and long-term. These time series signals will be inputs to the ApEn calculation system, as previously described for Fig. 1. ApEn values ​​are calculated for each time series. For longer otometric measurements, multiple ApEn values ​​will be calculated to average values ​​for short, medium, and long-term ApEn. The computed values ​​of short, medium, and long-term ApEn can be searched in the corresponding article 132 memory and external database(s), such as the</p>

<p dir="rtl">20 Optional external 136, which includes pre-calculated (pre-determined) MPF values ​​to provide the result of MPF measurements. In the embodiment shown in Figure 4, pairs of interconnected transceivers 140, 150 and 141 provide an estimate of fluid velocity through segment 104 and pipeline 102.</p>

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Referring now to the systems shown in Figures 3-4, in certain embodiments, modules such as audio receivers 150, 151 and audio transmitters 140, 141 can be interconnected on the outer side of the pipeline, such as pipeline 102, using a coupling between the module surfaces and the pipeline 102 Only interlocking components on the outside of the pipeline lead to a non-interrupting system. And at that

<p dir="rtl">5 system, some of the audio signals will propagate through the MPF, while some will propagate through the pipeline. The part of the audio signal that propagates through the pipeline is referred to as a carrier wave. Methods of signal processing are required to separate the load waves from the useful signal transmitted through the MPF. These processing methods can be implemented on the signal processor 128. The separated audio signal is processed using the same ApEn methods previously described.</p>

<p dir="rtl">10 In some embodiments, the passive systems of the present invention, such as those shown in Figures 1 and 2 and previously described, use acoustic emission sensors mounted on the inner or outer surface of a pipe to optionally create a non-intrusive classification system using a coupling. In some embodiments, the active systems of the present invention, such as those shown in Figures 3 and 4 and previously described, use audio transmitters and audio receivers in direct contact with the MPF. Transmitters are installed</p>

<p dir="rtl">15 The audio and audio receivers are in suitable holes drilled in a section of pipeline, such that the transmitting surface of the audio transmitters and the receiving surface of the audio receivers are in direct contact with the MPF. In some embodiments, components are built into this design so that the sound energy is actively propagated from the audio transmitters through the MPF to the audio receivers.</p>

In some embodiments, if the audio transmitter and audio receiver units are installed in contact

<p dir="rtl">20 With MPF, the received signal will be mathematically less processed, since there is no load wave received by the audio receiver. In some embodiments, if the audio transmitter and audio receiver are installed outside the pipe, a large part of the transmitted audio signals will propagate through the pipeline wall to the audio receiver without going through the MPF (carry wave). Signal processing methods must be used to separate the audio waves. The load is about the received waves that are transmitted through</p>

<p dir="rtl">25 MPF, which can increase the complexity of signal processing and calculation. The advantage of this system is that it does not</p>

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Intercalation of the audio transmitter and audio receiver modules, which can be deployed anywhere on the pipeline by just interfacing the audio transmitter and audio receiver on the pipeline with all electronic devices and processing units outside the pipeline.

Unwanted carrier waves can be treated as a continuous noise signal, due to which the audio signal is being transmitted

<p dir="rtl">5 The load wave noise signal will be at the same frequency as the actual signal, but with a different peak and phase, depending in part on the pipe wall through which it is traveling. The load wave noise signal (eg in a laboratory) can be classified and removed from The signal received into a processing unit, into a pass-band signal filter, or into an audio receiver by tuning to a specific frequency.</p>

<p dir="rtl">10 The systems shown in Figures 1-4 can be deployed on surface pipelines and facilities. The systems can be deployed on wellheads as well as downholes, and inside the wellbore to measure the MPF system from the wellbore. The systems may be part of a permanent intelligent completion, or a system that can be recovered in the parent bore or sidings. Permanent smart completions include permanent downhole sensors, flowmeters, and downhole flow control valves controlled from the surface, enabling monitoring, evaluation,</p>

<p dir="rtl">15 Active production (or injection) management in real time without any well interventions. Data is sent to the surface for local or remote monitoring. These systems are permanently deployed for the life of the well.</p>

A retrievable system is a wire or coil deployable tubing system that is lowered into the well for a specified length of time to perform certain measurements or logging operations. The system is restored from the well when the required 20 operation is completed.

In some embodiments of the systems shown in Figures 4-1, the systems can be combined with one or more measurement sensors (which include single or differential pressure measurements) to improve the accuracy of the MPF and data calculation. In addition, any or any combination of the sensor can be used. Temperature, pressure sensors, accelerometers, density meters, and flowmeters in systems and methods of invention

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Present. Measurements of those devices are provided by wired or wireless means to the processing unit 126 and displayed on the user interface 134.

In certain embodiments of the systems shown in Figures 1-4, electronic modules can be integrated such as, for example, otosensor 106, preamplifier 114, bandpass filter

<p dir="rtl">5 For signal 116, analog-to-digital converter 118, processing unit 126, signal processor 128, battery 130, physical memory 132, user interface 134 and any appropriate processing circuit needed in a single system in response to an Application Specific Integrated Circuit (ASIC) and system-on-chip methods SoC (System-on-Chip). In those models, for example, a very compact system can be deployed. Such a system with adequate protection may be appropriate</p>

<p dir="rtl">10 for the challenging environments encountered in downhole deployments.</p>

Referring now to Fig. 5, a graphical representation of MPF systems is shown, optionally for display on the user interface 134 in one of the embodiments of the present invention. While other flow systems are measured and classified by the systems shown in Figures 1-4, Figure 5 provides flow diagrams that are useful to the systems operator. Bubble flow is classified by small gas bubbles that flow along the top of the pipe.

<p dir="rtl">15 The elongated bubble flow is characterized by collisions between individual bubbles that increase in incidence with increasing gas flow rate and join in elongated 'clumps'. This is usually overlooked by mass flow. Smooth laminar flow is characterized by gas masses joining to produce a continuous gas flow along the top of the pipe with a smooth surface between gas and liquid typical of laminar flow at relatively low flow rates. Laminar wavy flow is characterized by the fact that the surface between gas and liquid is not smooth with the appearance of</p>

<p dir="rtl">20 Ripples on the surface of a liquid. In this model, the peak increases with increasing gas flow rate.</p>

A slug flow is characterized by a wave crest that travels along the surface of the liquid and becomes large enough to pass through the top of the pipe, and then the flow enters the slug flow system. In this model, the gas flows loosely and intermittently with small bubbles trapped in the liquid. The annular flow has a gas flow rate large enough to carry the liquid layer around the tube wall. and is transferred

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The liquid is like drops of art distributed through a continuous gas stream that flows in the middle of the pipe. The liquid layer is thicker along the bottom of the pipe due to the effect of gravity.

As already indicated, the acoustic emissions from the MPF depend, in part, on the formation of gas bubbles and cavities, system discontinuities, coalescence, and the interaction of different phases within the multiphase flow.

<p dir="rtl">5 These characteristics vary with different MPF systems, flow rates, as well as with different relative amounts of gas/vapour, and solids in the MPF. It is surprising and unexpected that the systems and methods of the present invention can accurately and effectively classify flow regimes, for example, those shown in Figure 5, by using ApEn calculations to remove unwanted acoustic noise and outlier measurements, which prevented the accuracy of those systems and methods.</p>

<p dir="rtl">10 In other models of the systems shown in Figures 1 and 2, principal component analysis (PCA) applies to the example systems. The systems shown in Figures 1 and 2 are inefficient, at least in part because there are no audio transmitters. Acoustic emissions received by OE Sensors 106, 107 will rise significantly from the MPF, pipeline 102, and the local environment surrounding OE Sensors 106, 107.</p>

<p dir="rtl">15 Initially, in the systems shown in Figures 1 and 2, the Acoustic Emission Sensors 106,</p>

<p dir="rtl">107 Wideband acoustic emission sensors collect data including broadband frequency emissions from the MPF, Pipeline 102, and the surrounding environment. The data acquired by these sensors is collected for broadband acoustic emissions in either or any combination of a field application, on site in a well or with a pipeline, and in the laboratory in a close flow loop with tightly controlled flow properties. In one embodiment, while that data is being collected, the appropriate Reynolds number is known to the MPF for which the data is being collected.</p>

Using the collected data, a time series is composed of the acoustic waveforms, and by performing a realtime transformation on the data, the data is converted into measurements of acoustic energy as a function of frequency. After converting an instantaneous set of measurements a test template is used covering 25 different MPF conditions that include, but are not limited to, Water Droplet Graduated Values, Total Liquid Flow Graduated Values,

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and different polyphasic flow patterns, such as, for example, those shown in Figure 5. When all the data are collected, the data is post-processed using PCA on the dataset. PCA is an ideal multivariate method for colinear manipulation, which is described in detail in

Norgaard, L. et al., “Principal Component Analysis and Near Infrared

<p dir="rtl">5 Spectroscopy,” A white paper from FOSS. In order to calculate the PCA model, several different computational methods can be used. Many of them are implemented in commercial software offering the ability to compute and display results from the PCA model.</p>

In other words, PCA allows knowledge of the most important variables for the accurate determination of the characteristics of a system. A pipeline, such as Pipeline 102, will emit different sound emissions at different frequencies with

<p dir="rtl">10 The passage of time, especially if there is an MPF ​​progressing through the pipeline 102. The OE sensor, such as the OE sensor 106, receives and records all such otopes in cases where the otosensor is a wideband otosensor. However, for some embodiments of the methods and systems described, not all acoustic emissions received by the acoustic emission device(s) are suitable for characterizing the MPF and stream system. For example,</p>

<p dir="rtl">15 Some system frequencies change, but the flow characteristics and the MPF flow system may not. In that case, the systems and methods of the present invention would not seek to explain that frequency change as having an effect on the characteristics of the MPF or its system.</p>

Therefore, when all the data has been collected from one or more wideband EA sensors, the data is post-processed by performing a PCA on the data. And in some models, it will

<p dir="rtl">20 PCA specifies the linear combination of key frequencies used to approximate the degree of correlation or values ​​of groups in discrete classifications. This will, in turn, identify the frequencies that are less important than others. In addition, this process allows PCA to optimize specific hardware components and reduce costs. For example, broadband acoustic emissions sensors can be replaced by an array of low-cost single-frequency tuned receivers where the frequencies are compatible with the values ​​generated by</p>

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PCA analysis. This can reduce system cost and incremental costs, because tuned receivers act as bandpass signal filters that only sound at obvious points of measurement.

To calculate the PCA model, several different computational methods can be used. Many of them are implemented in software that allows computation and display of results from the PCA model. In other models, it can be used

<p dir="rtl">5 system with a broadband receiver, then a series of individual signal filters in a solid component or using digital signal processing methods, tuned to the clear frequencies determined by the method</p>

.PCA

With reference to Figure 6, a process flow chart is provided for the system mode of operation model shown in Figure 4. Similar modes of operation can be used in other models of the systems shown. Starting with the step

<p dir="rtl">10 600, UI 134 can trigger one or more system users or operators</p>

400 To start the system 400. This trigger may include an audible and visual trigger, the user or operator may be asked to confirm that the system has started, or the system may start without a confirming response from the user or operator. An appropriate affirmative response from the user or operator may include operating one or a combination of buttons, switches, levers, touching a touch screen, and responding audibly to a user interface.

<p dir="rtl">15 that can accept voice commands. And UI 134 and CPU 126 can work</p>

Remote devices such as laptop computers and smart phones through wired or wireless networks, means or schemes of communication, as will become clear to those skilled in the field. Therefore, user or operator selection operations can be performed remotely.

At step 600, the flux may be introduced through pipeline 102, and may optionally flow easily into

<p dir="rtl">20 MPF system. In some embodiments, it does not enter the flow through the pipeline at system start-up and does not necessarily enter the flow through the pipeline at the same time as the system starts. Flow through Pipeline 102 may be stopped, started, increased, or decreased at any point in the mode of operation shown in Figure 6 by any or a combination of valves, baffles, actuators, and suitable means known in the art. In some embodiments the workflow of the operation method shown</p>

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In Figure 6 fully automated within processing unit 126 and step 600 is shown to initiate system 400 in response to system conditions 400, without simultaneous user input.

At step 602, the UI 134 may prompt the user or operator to activate either or both of the audio receiver 150 and the second audio receiver 151. At step 604, it may

<p dir="rtl">5 The user interface 134 prompts the user or operator to activate either or both of the audio transmitter 140 and the second audio transmitter 141. On certain System 400 models, one or more audio receivers and one or more audio transmitters are selected by the system 400 Respond to system characteristics, eg, pipeline and system design, operating conditions, flow conditions, and measurements of the previously recorded 400 system.</p>

<p dir="rtl">10 At step 606, system 400 detects if one or more audio transmitters 140, 141 has been activated. If system 400 determines that one or more audio transmitters 140, 141 has been activated, then at step 608 gives The user system or operator has the opportunity to select or modify the management signal 144. The signal generator unit 142 is operated and controlled via the user interface 134 to provide the management signal 144 to one or all of the audio transmitters 140, 141.</p>

<p dir="rtl">15 In some embodiments, the signal generator unit generates a high frequency continuous sine wave signal, eg from about 0.5 MHz to about 2 MHz. In other embodiments, however, other signals are generated at other frequencies than the signal generator unit after user or operator selection on the user interface.</p>

At step 610, System 400 begins collecting data at one or more receivers

<p dir="rtl">20 Voice activated by the user. It should be noted that Audio Receivers 150, 151 may receive frequencies from only Audio Transmitters 140, 141, from MPF only, or from both Audio Transmitters 140, 141 and MPF. This can be done using any or a combination of bandpass frequency cutoff and frequency specific signal filters.</p>

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After one or more audio receivers 150, 151 begins collecting data through one or more audio signals, one or more signals are pre-amplified at step 612, filtered at step 614, and converted from an analog electrical signal to a digital signal at step 616. These steps are optionally performed in signal transducers 112, 113, previously described.

<p dir="rtl">5 At step 618, the digital signal is processed in the processing unit 126, which includes the signal processor 128 and physical memory 132. The digital signal is processed to calculate the approximate entropy of the short-, medium-, and long-term data series collected from any or any combination of audio receivers 150 and 151. At step 620, the signal processor 128 determines if approximate entropy calculations are recognized or compared to previously computed or determined entropy approximations present in</p>

<p dir="rtl">10 Any or any combination of databases and physical memory 132. If the ApEn values ​​of the measured signal cannot be recognized, the system will not continue collecting data at audio receivers 150, 151.</p>

At step 622, the system decides if there is more than one voice receiver activated with more than one audio receiver receiving compatible data, or data indicating that the MPF pass-through is

<p dir="rtl">15 Similar characteristics to audio receivers. If this is not achieved, the user or operator is given the option to select the audio receiver again before the system calculates the flow velocity at step 624. If there is more than one audio receiver working, and the data retrieved at both sensors are compatible, then the Calculation of flow velocity within segment 104 of pipeline 102 at step 624.</p>

<p dir="rtl">20 Then, at step 626, System 400 determines the flow regime in response to the ApEn and flow velocity calculations. In other embodiments, the flow velocity is not required and is not used in determining the flow regime, for example, in the System 100 model in Figure 1 and System 300 in Figure 3. It is possible to specify the flow regime and approximate it to one of the flow regimes shown in Figure 5 and previously described , or it can be determined and approximated to a combination of any of these systems.</p>

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In other embodiments, the flow system is defined as another flow system in response to the audio signals received by the audio receivers. After the flow system is determined, the flow properties are displayed to the user or operator by UI 134 at step 628. While in the examples of Figures 1-4, UI 134 displays the limit of CPU components 126, and UI 134 may be

<p dir="rtl">5 A discrete unit associated with a wired or wired connection to the Processing Unit 126, such as a smartphone or laptop computer.</p>

Therefore, the user or operator may receive remotely displayed stream characteristics in real time, away from system 400. The user or operator may remotely control the systems by inputting into UI 134. At step 628, real-time data is also displayed on UI 10 134 and calculated in the 400 system, but obtained from other measures and means such as, metrics

Flowmeters, thermometers, density meters, accelerometers, and similar devices known in the art.

In the different invention models described, a person skilled in the art will realize that they can

Reading different types of memory by a computer, such as memory described with reference to computers

<p dir="rtl">15 And different servers, such as a computer, a computer server, a web server, or other computers with models of the current invention.</p>

Singular forms include references to the plural, unless the context expressly states otherwise.

Examples of computer readable media may include, but are not limited to, one or more fixed-encoded non-volatile media such as read-only memories.

<p dir="rtl">20 ROMs, CD-ROMs, read only memories (DVDs), Digital Versatile Discs, or read only memories</p>

electrically programmable read only memories

EEPROMs)); or recordable media such as floppy disks

<p dir="rtl">, hard disk drives, CD-R/RWs, DVD-RAMs, and DVD-ROMs</p>

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R/RWs, DVD+R/RWs, flash drives, memory sticks and other newer types of memory and transmission-type media such as analog and digital communication links. For example, such media may include operating instructions, as well as instructions regarding the systems and steps for methods described above and may operate on a computer.

<p dir="rtl">5 Those skilled in the art will recognize that such media may be in other locations instead of, or in addition to, the locations described for storing computer program products, such as software on them. Those skilled in the art will recognize that various software modules or electronic components previously described can be used and maintained using electronic hardware, software, or a combination thereof, and that such embodiments are included in embodiments of the present invention.</p>

<p dir="rtl">10 In the drawings and class, models of methods, systems, and a non-temporary computer-readable medium with stored computer programs of the present invention are disclosed. Although certain terms are used, the terms have been used in a descriptive sense and not to limit the scope of the invention. Methods and systems models, and a non-temporary computer-readable medium with stored computer programs of the present invention are described in detail with reference to those models shown. However, it is clear that it can</p>

<p dir="rtl">15 Making many modifications and changes in the scope of content and scope of models of models of methods and systems,</p>

And a non-temporary computer-readable medium with computer programs stored for the current invention as described in the previous description, and that these modifications and changes are considered equivalents and part of this invention.

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