阅读说明：本技术 用于实时发现和解决湿气文丘里流量计问题的系统和方法 (System and method for real-time discovery and resolution of wet gas venturi meter problems ) 是由 ***·伊德里斯 默罕默德·A·阿勒-阿特维 于 2019-02-07 设计创作，主要内容包括：用于发现并解决一个或多个气井场中的湿气文丘里流量计的问题的系统和方法,所述系统包括：一个或多个气井场,其被配置为向气厂供应气体,每个气井场包括：连接到管道的气井、安装在管道上的一个或多个阀门、一个或多个压力传感器、一个或多个温度传感器、被配置为测量管道中的气体的压差的一个或多个文丘里流量计以及一个或多个可编程的逻辑控制器,所述一个或多个可编程的逻辑控制器被配置为：从压力传感器、温度传感器和文丘里流量计接收测量的数据；接收一个或多个文丘里流量计的多个尺寸；接收多个流体属性值；以及确定井场中的每一个的第一气体速率和第一冷凝物速率。(A system and method for discovering and addressing problems with wet gas venturi meters in one or more gas wellsites, the system comprising: one or more gas wellsites configured to supply gas to a gas plant, each gas wellsite comprising: a gas well connected to a pipeline, one or more valves mounted on the pipeline, one or more pressure sensors, one or more temperature sensors, one or more venturi meters configured to measure a pressure differential of the gas in the pipeline, and one or more programmable logic controllers configured to: receiving measured data from the pressure sensor, the temperature sensor, and the venturi flow meter; receiving a plurality of sizes of one or more venturi meters; receiving a plurality of fluid property values; and determining a first gas rate and a first condensate rate for each of the wellsites.)

1. A system, comprising:

one or more gas wellsites configured to supply gas to a gas plant, each gas wellsite comprising: a gas well connected to a pipeline, one or more valves mounted on the pipeline, one or more pressure sensors configured to measure a pressure of gas in the pipeline, one or more temperature sensors configured to measure a temperature of gas in the pipeline, one or more venturi meters configured to measure a pressure differential of gas in the pipeline, and one or more programmable logic controllers configured to:

receiving measured data from the pressure sensor, the temperature sensor, and the venturi flow meter;

receiving a plurality of sizes of the one or more venturi meters;

receiving a plurality of fluid property values; and

determining a first gas rate and a first condensate rate for each of the wellsites;

one or more server sites for storing measured data for each of the wellsites, a size of the venturi meter, the fluid property values, the gas rate, and the condensate rate; and

one or more processors and a non-transitory computer-readable medium in communication with the one or more processors and having a set of instructions stored thereon that, when executed, cause the one or more processors to perform operations comprising:

receiving measured data from the one or more server sites;

receiving, from the one or more server sites, a plurality of sizes of the one or more venturi meters;

receiving the plurality of fluid property values from the one or more server sites;

determining a second gas rate and a second condensate rate for each of the wellsites;

comparing the second gas rate to the first gas rate and the second condensate rate to the first condensate rate; and

one or more problems associated with one or more venturi meters in one or more gas wellsites are identified.

2. The system of claim 1, wherein the plurality of dimensions of the one or more venturi meters comprise an inner diameter of a venturi conduit and an inner diameter of a venturi throat.

3. The system of any of claims 1-2, wherein the plurality of fluid property values includes at least two of a gas density (pg), a condensate density (pc), a Condensate Mass Fraction (CMF), a Gas Conversion Factor (GCF), and a Condensate Conversion Factor (CCF).

4. The system of any of claims 1-3, wherein the plurality of fluid property values are calculated using a correlation as a function of pressure and temperature, wherein the correlation is generated by analysis of a particular reservoir at a predetermined Condensed Gas Ratio (CGR).

5. The system of any one of claims 1-4, wherein the one or more processors are further configured to:

receiving actual total gas production after a process of separating gas and liquid from all gas wells of the gas plant; and

evaluating an accuracy between a total gas rate of the venturi flow meter and a total gas rate measured at the gas plant.

6. The system of any one of claims 1-5, wherein the one or more processors are further configured to:

if one or both values do not match because of an incorrect throat or pipe size or fluid property correlation, the data is classified as incorrect or erroneous.

7. The system of any one of claims 1-6, wherein the one or more processors are further configured to:

determining that the measured data from the one or more server sites is outside a predetermined threshold range; and

generating a device calibration or device replacement requirement.

8. The system of any one of claims 1-7, wherein the one or more processors are further configured to:

classifying the well as a problematic well if the determined gas rate or the determined condensate rate is outside a predetermined threshold range of the 3-phase separator test values; and

corrective action is generated to change the fluid property correlation with lower or higher CGR values and/or calibrate the P-T-dP level gauge transmitter.

9. The system of any one of claims 1-8, wherein the one or more processors are further configured to:

generating a list of the identified problematic wells; and

the list is sent to a maintenance group to perform corrective action.

10. The system of any one of claims 1-9, wherein the one or more processors are further configured to:

evaluating rate accuracy by looking at the overall performance of a venturi flow meter from all of the gas wells and comparing the total gas production between the venturi flow meter and a slug catcher at the gas plant; and

generating an alert if the rate difference or error is greater than a predetermined percentage.

11. A method for discovering and addressing problems with wet gas venturi meters in gas wells, the method comprising:

receiving, by one or more processors, measured data from one or more server sites;

receiving, from the one or more server sites, a plurality of sizes of one or more venturi meters on one or more gas wellsites;

receiving a plurality of fluid property values from the one or more server sites;

determining a second gas rate and a second condensate rate for each of the gas wellsites;

comparing the second gas rate to a first gas rate determined by the wellsite and comparing the second condensate rate to a first condensate rate determined by the wellsite; and

one or more problems associated with one or more venturi meters in one or more gas wellsites are identified.

12. The method of claim 11, further comprising:

receiving actual total gas production after a process of separating gas and liquid from all gas wells of the gas plant; and

evaluating an accuracy between an overall total gas rate of the venturi flow meter and a total gas rate measured at the gas plant.

13. The method according to any one of claims 11-12, further comprising:

if one or both values do not match because of an incorrect throat or pipe size or fluid property correlation, the data is classified as incorrect or erroneous.

14. The method according to any one of claims 11-13, further comprising:

determining that the measured data from the one or more server sites is outside a predetermined threshold range; and

generating a device calibration or device replacement requirement.

15. The method according to any one of claims 11-14, further comprising:

classifying the well as a problematic well if the determined gas rate or the determined condensate rate is outside a predetermined threshold range of the 3-phase separator test values; and

corrective action is generated to change the fluid property correlation with lower or higher CGR values and/or calibrate the P-T-dP level gauge transmitter.

16. The method according to any one of claims 11-15, further comprising:

generating a list of the identified problematic wells; and

the list is sent to a maintenance group to perform corrective action.

17. The method according to any one of claims 11-16, further comprising:

evaluating rates by looking at the overall performance of a venturi meter from all of the gas wells and comparing the total gas production between the venturi meter and a slug catcher at the gas plant; and

generating an alert if the rate difference or error is greater than a predetermined percentage.

18. A system, comprising:

one or more processors and a non-transitory computer-readable medium in communication with the one or more processors and having a set of instructions stored thereon that, when executed, cause the one or more processors to perform operations comprising:

receiving measured data from the one or more server sites;

receiving, from the one or more server sites, a plurality of sizes of the one or more venturi meters;

receiving a plurality of fluid property values from the one or more server sites;

determining a second gas rate and a second condensate rate for each of the wellsites;

comparing the second gas rate to a first gas rate determined by the wellsite and comparing the second condensate rate to a first condensate rate determined by the wellsite; and

one or more problems associated with one or more venturi meters in one or more gas wellsites are identified.

19. The system of claim 18, wherein the plurality of dimensions of the one or more venturi meters comprise an inner diameter of a venturi conduit and an inner diameter of a venturi throat.

20. The system of any of claims 18-19, wherein the plurality of fluid property values includes at least two of a gas density (pg), a condensate density (pc), a Condensate Mass Fraction (CMF), a Gas Conversion Factor (GCF), and a Condensate Conversion Factor (CCF).

Technical Field

Example embodiments relate generally to automation in gas wells, and more particularly, to a method and system for discovering and addressing wet gas venturi flow meter problems in gas wells.

Background

Determining the flow rate of fluids flowing within a well is important for monitoring and controlling the movement of fluids in the well and reservoir. For example, by monitoring the flow rates of both oil and water from each zone of the well, the water production of the entire well can be controlled by reducing the flow from those zones that produce the highest water cut (i.e., the ratio of the water flow rate to the total flow rate), allowing the reservoir to be more completely cleared over the life of the well.

One common method for determining the velocity of a fluid in a flow path involves positioning a turbine blade within the flow path and measuring the rotational speed of the turbine blade. In single phase flow conditions, the rotational speed of the turbine blades is related only to the speed of the flow path. Unfortunately, however, under multiphase flow conditions (such as mixed oil and water flow conditions), the response of the turbine can be very complex and the results may not be interpretable. Another method of determining the fluid velocity in a flow path involves injecting a tracer material into a selected fluid phase (oil or water) and measuring the time it takes for the tracer material to travel a known distance in the flow path. The known distance and travel time may then be used to calculate the velocity. One disadvantage of this method for permanent downhole use is the need for reservoirs of tracer material and mechanical tracer injectors. Since the reservoir and injector are permanently located downhole, the number of velocity measurements is limited by the quality of the tracer material, and the injector is prone to sticking and failure.

Another method of determining the velocity of a fluid in a flow path involves the use of local capacitance or resistance sensors. However, this method is only applicable to a flow pattern in which one phase is dispersed in the form of droplets in another continuous phase. When a droplet passes one of the sensors, a signal is generated for a duration related to the velocity of the droplet. Where the droplet size is known by other means, the velocity of the droplet and hence the fluid flow can be derived. One disadvantage of this method is that it does not work at all in the stratified flow regime, since it relies on the presence of bubbles.

Another method of determining the fluid flow rate in the flow path involves measuring the total volumetric flow rate using a venturi meter. A venturi flow meter is a flow measuring instrument: which uses converging sections of tubing to increase the flow rate and produce a corresponding pressure drop so that the flow rate can be deduced. They have been in common use for many years, particularly in gas wells. Venturi flow meters are widely used to measure gas flow rates, including single phase gas flow rates of natural gas recovered from gas reservoirs. These instruments can provide accurate gas flow measurements early in the life of a gas well when the well is producing dry gas with a small amount of liquid (such as less than 5% by volume). However, as the reservoir becomes mature, the well begins to "produce" (cut) with gas or produce more liquid (such as water or other condensate). This may occur as reservoir temperature and pressure drop with production. The presence of liquid in the gas affects the accuracy with which the venturi meter measures the flow rate of the gas. Recovering other liquids in natural gas leads to inaccurate production monitoring, distribution, and reservoir engineering and management decisions.

Almost all existing gas producing wells are equipped with venturi meters to measure the gas flow rate. However, the use of multiple venturi meters to correct inaccuracies caused by increased liquid production is expensive and requires extensive infrastructure modifications to existing and new piping systems. Existing methods of correcting for increased fluid production are expensive and require many modifications and additions to existing systems and require frequent calibration.

Disclosure of Invention

Accordingly, there is a need to provide an improved system for discovering and addressing problems associated with wet gas venturi meters in gas wells in real time.

Accordingly, example embodiments relate to a comprehensive process for calculating flow rates of gas and condensate in a gas well. The exemplary embodiments provide significant enhancements in finding problems with gas venturi measurements and providing a field maintenance team with an appropriate list of actions to address the problem. As a result, the reliability and accuracy of the gas venturi meter is improved. The use of new processes and systems is important in maintaining the reliability and accuracy of gas velocity measurements using venturi flow meter systems.

One example embodiment is a system, comprising: one or more gas wellsites configured to supply gas to a gas plant, each gas wellsite comprising: a gas well connected to the pipeline, one or more valves mounted on the pipeline, one or more pressure sensors configured to measure a pressure of the gas in the pipeline, one or more temperature sensors configured to measure a temperature of the gas in the pipeline, one or more venturi meters configured to measure a pressure differential of the gas in the pipeline, and one or more programmable logic controllers configured to receive measured data from the pressure sensors, the temperature sensors, and the venturi meters, receive a plurality of dimensions of the one or more venturi meters, receive a plurality of fluid property values, and the wellsite determines a first gas rate and a first condensate rate for each of the wellsites; one or more server sites for storing measured data for each of the wellsites, a size of the venturi meter, fluid property values, a gas rate, and a condensate rate; and one or more processors and a non-transitory computer readable medium in communication with the one or more processors and having a set of instructions stored thereon that, when executed, cause the one or more processors to perform operations comprising receiving measured data from one or more server sites, receiving a plurality of dimensions of one or more venturi meters from the one or more server sites, receiving a plurality of fluid property values from the one or more server sites, determining a second gas rate and a second condensate rate for each of the wellsites, comparing the second gas rate to the first gas rate and the second condensate rate to the first condensate rate, and identifying one or more problems associated with one or more venturi meters in the one or more gas wellsites.

Another example embodiment is a method for discovering and addressing problems with one or more wet gas venturi meters in one or more gas wellsites. The method comprises the following steps: receiving, by one or more processors, the measured data from one or more server sites; receiving, from one or more server sites, a plurality of sizes of one or more venturi meters on one or more gas wellsites; receiving a plurality of fluid property values from one or more server sites; determining a second gas rate and a second condensate rate for each of the gas wellsites; comparing the second gas rate to a first gas rate determined by the wellsite and comparing the second condensate rate to a first condensate rate determined by the wellsite; and identifying one or more problems associated with one or more venturi meters in one or more gas wellsites.

Another example embodiment is a system comprising one or more processors and a non-transitory computer-readable medium in communication with the one or more processors and having stored thereon a set of instructions that, when executed, cause the one or more processors to perform operations comprising: the method may include receiving measured data from one or more server sites, receiving a plurality of sizes of one or more venturi meters from one or more server sites, receiving a plurality of fluid property values from one or more server sites, determining a second gas rate and a second condensate rate for each of the wellsites, comparing the second gas rate to a first gas rate determined by the wellsite and the second condensate rate to a first condensate rate determined by the wellsite, and identifying one or more problems associated with one or more venturi meters in one or more gas wellsites.

Drawings

So that the manner in which the features, advantages and objects of the invention, as well as others which may become apparent, are attained and can be understood in more detail, more particular description of the invention briefly summarized above may be had by reference to the embodiments thereof which are illustrated in the appended drawings, which drawings form a part of this specification. It is to be noted, however, that the appended drawings illustrate only example embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.

FIG. 1 is a schematic diagram of an intelligent system for discovering and addressing problems with wet gas venturi meters in gas wells in accordance with one or more example embodiments of the present disclosure.

FIG. 2 shows example steps in a method for discovering and solving problems of a wet gas venturi meter in a gas well according to one or more example embodiments of the present disclosure.

Fig. 3 is an example listing of problematic wells identified by an intelligent system in accordance with one or more example embodiments of the present disclosure.

FIG. 4 is a result of venturi meter calibration work performed on the data shown in FIG. 3 by an intelligent system according to one or more example embodiments of the present disclosure.

FIG. 5 is an exemplary graph illustrating values of actual gas rates determined using a 3-phase separator test versus values determined using a venturi flow meter of an intelligent system according to one or more example embodiments of the present disclosure.

FIG. 6 is a schematic block diagram of a data processing system for discovering and addressing problems with wet gas venturi meters in gas wells in accordance with one or more example embodiments of the present disclosure.

FIG. 7 shows example steps in a method for discovering and solving problems of a wet gas venturi meter in a gas well according to one or more example embodiments of the present disclosure.

Detailed Description

The methods and systems of the present disclosure may now be described more fully hereinafter with reference to the accompanying drawings, in which embodiments are shown. The methods and systems of the present disclosure may be in many different forms and should not be construed as limited to the illustrated embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Like reference numerals refer to like elements throughout.

Turning now to the drawings, FIG. 1 is a schematic diagram of an intelligent system 100 for discovering and addressing problems with wet gas venturi meters in gas wells, according to one or more example embodiments of the present disclosure. As shown in this figure, the system 100 may include one or more wellsites 10, which may be configured to supply gas to a gas plant 25. Each wellsite 10 may include a gas well 12, one or more valves 14, one or more pressure sensors 16, one or more temperature sensors 18, one or more venturi flow meters 20, and one or more differential pressure sensors 22, all of which may be operatively connected to a Programmable Logic Controller (PLC) in a Remote Terminal Unit (RTU) 24. A venturi flow meter is a flow measuring instrument: which uses converging sections of tubing to increase the flow rate and produce a corresponding pressure drop so that the flow rate can be deduced. They have been in common use for many years, particularly in gas wells. There are three main actual measurement readings for the gas well 10 that can be used to calculate the gas condensate flow rate. These readings are flow line or venturi pressure (P), flow line or venturi temperature (T), and venturi meter differential pressure (dP), each of which may be measured using one or more pressure sensors 16, one or more temperature sensors 18, and one or more venturi meters 20, respectively. These three flow parameters may be transmitted in real time to a Programmable Logic Controller (PLC) within a Remote Terminal Unit (RTU)24 at the field or well site.

In some embodiments, the flow rate calculations may be processed within the PLC-RTU 24 for each individual gas well field 10. The size of the venturi meter may be defined by the inner diameters of the venturi conduit (DP) and the throat (DT). The correlations as a function of pressure and temperature are used to calculate desired fluid property values such as gas density (ρ g), condensate density (ρ c), Condensate Mass Fraction (CMF), Gas Conversion Factor (GCF) and Condensate Conversion Factor (CCF). This correlation results from PVT analysis of a particular reservoir at a particular Condensed Gas Ratio (CGR). The following sections of this section provide general equations or formulas that may be applied to the calculation process. Finally, the results of this calculation are the gas rate (Qg) and the condensate rate (Qc).

The results of the gas condensate rate from the calculation process are transmitted in real time to a supervisory control and data acquisition (SCADA) server 26 along with the main actual measurement readings. The SCADA server may include one or more servers 28, which include one or more databases and one or more database management systems (not shown). This information can be used by field operators to monitor gas production and make remote gas rate adjustments for all gas wells. The same reading in the SCADA server may be sent to the Plant Information (PI) server 30. The PI servers may include one or more servers 32 that include one or more databases and one or more database management systems (not shown). The data may be used for further production data analysis, such as production monitoring and evaluation of the well by production or reservoir engineers.

The intelligent system 100 may also include an inventive production monitoring tool 34 for discovering and addressing problems with wet gas venturi meters in gas wells in accordance with one or more example embodiments of the present disclosure. An inventive production monitoring tool (CPMT)34, which may include one or more processors 36, may be operatively connected to the PI server 30 to receive data therefrom and perform the operations explained in more detail with respect to fig. 2 and 7.

FIG. 2 shows example steps in a method 200 for discovering and solving problems with wet gas venturi meters in gas wells in accordance with one or more example embodiments of the present disclosure. At step 210, the inventive production monitoring tool 34 receives data from the PI server. At step 212, the data input parameters for each individual gas well consist of two (2) categories, which may include real-time readings, such as readings that may be retrieved in real-time from a SCADA server by a PI server. These parameters may include P, T, dP and FWHP as actual measurements from individual gas wells. The first three variables can be used directly to calculate the gas flow rate in a CPMT processing system. The FWHP readings are used to determine the flow conditions of a well that is shut-in or flowing. Q_g-PLCAnd Q_c-PLCIs the result of a calculation process from the PLC-RTU of a single gas well that can be used for rate verification. Q_{gGas Plant}Refers to the actual total gas production following the process of separating gas and liquids from all gas wells of a gas plant. This value can be used to evaluate the accuracy between the total gas rate (well flow) of the venturi meter and the total gas rate measured at the gas plant. For example, the fixed data input may include the size of the venturi flow meter, such as information from the inner diameter of the throats and pipes of all gas wells. The parameters may also include fluid property correlations, such as correlations that may be a function of pressure and temperature, which may be used to determine the density of the gas and condensate phases and may also know the condensate mass fraction from the total mass. The correlation is also used to convert the flow rate to a standard condition.

After receiving the data in step 212, the process in step 214 applies the same equation or formula already used in the PLC-RTU system. The detailed equations are provided in the latter part of this section. At step 216, the system performs a rate verification process that verifies the results, i.e., Q, of the PLC-RTU for each individual gas well_g-PLCAnd CGR_PLC. If one or both values do not match the results of the CPMT processing, the system may place the data under the "wrong/incorrect data entry" category, slightly due to incorrect throat-to-tube size or fluid property correlationAnd then stated in step 228 of the process. At step 218, the system executes problem identification logic, where an impractical reading of the P-T-dP measurement (such as a negative, too low or too high value that may be out of range of the instrument) may be classified as "requiring device calibration or replacement," to be stated later in step 230 of the process. However, it should be noted here that in certain cases, the excessive size of the throat diameter may affect the accuracy of the venturi measurement.

In step 220, the system checks for infrequent information. For example, in the case where any well has been capacity tested using a 3-phase separator test and the results of the gas condensate rate show significant differences from the venturi meter readings, then that well may be added to the list of wells in question in step 222. The type of corrective action required is to change the fluid property correlation with a lower or higher CGR value and/or calibrate the P-T-dP level gauge transmitter. In step 222, the system generates a list of wells that have been identified as having problems. Wells that have been identified as having problems from step 216-220 may be sent to a maintenance team for corrective action. At step 224, execution of the correction job may be performed. For example, after receiving the list of wells in question, the maintenance team may perform the necessary corrective action for each well as required in step 222. The completed work may be reported to a production engineer for further validation. At step 226, a calibration job verification may be performed. For example, a problematic well that has been repaired by a maintenance team may be verified by a production engineer. If the work originally completed is not accepted by the production engineer, the maintenance team may need to re-order the corrective work. Finally, at step 232, a rate accuracy evaluation may be performed by the system. The final step is to check the overall performance of the venturi meters for all gas wells. This check can compare the total gas production between the venturi flow meter and the slug flow trap at the gas plant. If the rate difference (error) is greater than 10%, the process may return to step 218 until the error is less than 10%.

Fig. 3 is an example listing of problematic wells identified by an intelligent system according to one or more example embodiments of the present disclosure, and fig. 4 is the result of venturi meter calibration work performed on the data shown in fig. 3 by the intelligent system according to one or more example embodiments of the present disclosure. As can be seen from these figures, the venturi flow meter of the present intelligent system 100 has proven to be a reliable and accurate meter that can provide adequate gas flow rate readings for gas/condensate fields in a cost effective manner.

FIG. 5 is an example graph 500 illustrating values of actual gas rates determined using a 3-phase separator test versus values determined using a venturi flow meter of an intelligent system according to one or more example embodiments of the present disclosure. In graph 500, line 510 is a 1:1 fit line, line 520 is a-10% error line, and line 530 is a + 10% error line. As can be seen from the graph, the gas velocity determined by the Venturi meter of the present intelligent system is nearly along the 1:1 fit line 510, which demonstrates that the Venturi meter provides an accurate gas velocity measurement with less than 10% error. The range of data used for comparison is:

CGR 12-420stb/MMscf

WGR 1-9stb/MMscf

in the case of gas wells that produce large amounts of water from a formation reservoir, for example, WGR>10stb/MMscf, which may affect the accuracy of the venturi meter's gas flow rate. The process of calculating gas flow rate using a venturi meter measurement system includes three (3) key groups, e.g., including fluid properties (ρ)_g、ρ_cCMF, GCF and CCF) which can be determined by correlation as a function of pressure and temperature. It is generated by PVT test analysis of multiple fields and reservoirs at certain CGR values in various fields. These fluid property correlations are referred to as PVT tables, for example. The key group may also include the basis of the flow equation, which may use the main equation provided in ISO 5167-4: 2003. The key group may include moisture correction using the Rick de Leeuw correlation available in the North Sea Flow Meter (NSFM) seminar paper 21-1997, selected for moisture correction or overreading factor. Since liquid is present in some cases, the correction factor may beAnd the measurement error of the Venturi flowmeter is reduced.

An example of a flow calculation formula:

if Frg <1.5 → n ═ 0.41

Frg≥1.5→n＝0,606*[1－10^-0.746*Frg]

The uniform PVT table or fluid property correlations are:

1.ρ_g＝a₁+(b₁*T)+(c₁*P)+(d₁*T²)+(e₁*P²)+(f₁*T*P)+(g₁*T³)+(h₁*P³)+(i₁*T*P²)+(j₁*T²*P)

2.ρ_c＝a₂+(b₂*T)+(c₂*P)+(d₂*T²)+(e₂*P²)+(f₂*T*P)+(g₂*T³)+(h₂*P³)+(i₂*T*P²)+(j₂*T²*P)

3.CMF＝a₃+(b₃*T)+(c₃*P)+(d₃*T²)+(e₃*P²)+(f₃*T*P)+(g₃*T³)+(h₃*P³)+(i₃*T*P²)+(j₃*T²*P)

4.

5.

the constants a, b, c, d, e, f, g, h, i, j, k are specific to each field and reservoir at different CGR values for each gas well. There are multiple sets of PVT tables that have been used to determine fluid properties in the gas flow calculation process.

Wherein:

turning now to fig. 6, a data processing system, such as the CPMT 34, is schematically illustrated in fig. 6, which may include a master node 120 of a CPU 122 and a set of processors or worker nodes 124 operating as network exploration and production data. As can be set forth, the data processing system 34 processes gas production data with a controllable specified quality of service (QoS) for a process application. The data processing system 34 operates in accordance with the processing techniques schematically illustrated in fig. 2 and 7. Thus, in the event of a failure, the processing of the gas production data is performed without affecting or losing processing time.

Considering now a data processing system according to the present invention as shown in fig. 6, a data processing system 34 is provided as a processing platform for processing data. Data processing system 34 includes one or more central processing units or CPUs 122. The one or more CPUs 122 are associated with a memory or database 126 for general input parameters, the memory or database 126 having types and attributes according to the gas production data to be processed.

A user interface 128, operatively connected to CPU 122, includes a graphical display 130 for displaying images, a printer or other suitable image forming mechanism, and user input devices 132 to provide user access to manipulate, access and provide output forms of processing results, database records and other information. The memory or database 126 is typically in the memory 134 of an external data storage server or computer 138. The database 126 contains data including the structure, location and organization of cells in the reservoir model, which may be described below, data typically input parameters and survey and production data to be processed.

The CPU or computer 122 of the data processing system 34 includes a master node 120 and an internal memory 140, the internal memory 140 being coupled to the master node 120 to store operational instructions, control information, and to act as a storage or transmission buffer as needed. The data processing system 34 includes program code 142 stored in memory 140. The program code 142 according to the present invention is in the form of computer operable instructions that cause the master node 120 and the processor node 124 to transmit gas production data and control instructions back and forth in accordance with the DDS interworking technique as may be set forth.

It should be noted that program code 142 may be in the form of microcode, programs, routines, or symbolic computer operable language that provides a particular set of ordered operations that control the functionality of and direct the operation of data processing system 34. The instructions of program code 142 may be stored in memory 140, or in a computer floppy disk, magnetic tape, conventional hard drive, electronic read-only memory, optical storage, or other data storage device having a computer usable medium stored thereon. Program code 142 may also be embodied on a data storage device as a computer readable medium.

The processor node 124 is a general purpose programmable data processing unit programmed to perform the processing of survey and production data according to the present invention. The processor node 124 operates under the control of the master node 120 and then compiles the obtained processing results in a memory 134, providing data in the memory 134 to form with the user interface 128 of the output display to form a data record for analysis and interpretation.

Although the present invention is independent of the particular computer hardware used, the exemplary embodiment of the present invention is preferably based on the master node 120 and processor node 124 of the HP Linux cluster computer. However, it should be understood that other computer hardware may also be used.

FIG. 7 shows example steps in a method 700 for discovering and solving problems with wet gas venturi meters in gas wells in accordance with one or more example embodiments of the present disclosure. One example embodiment is a system 34 for discovering and solving problems with wet gas venturi meters in gas wells according to one or more example embodiments of the present disclosure. The system 34 includes one or more processors 122, 124 and a non-transitory computer-readable medium 140 in communication with the one or more processors 122, 124 and having a set of instructions 142 stored thereon, which, when executed 142, cause the one or more processors 122, 124 to perform operations, including, for example, the steps shown in fig. 2 and 7. In some embodiments, a system may include: one or more gas wellsites configured to supply gas to a gas plant, each gas wellsite comprising a gas well connected to a pipeline, one or more valves mounted on the pipeline, one or more pressure sensors configured to measure a pressure of the gas in the pipeline, one or more temperature sensors configured to measure a temperature of the gas in the pipeline, one or more venturi meters configured to measure a pressure differential of the gas in the pipeline, and one or more programmable logic controllers configured to receive measured data from the pressure sensors, the temperature sensors, and the venturi meters, receive a plurality of dimensions of the one or more venturi meters, receive a plurality of fluid property values, and determine a first gas rate and a first condensate rate for each of the wellsites. The system may also include one or more server sites for storing the measured data for each of the wellsites, the size of the venturi meter, the fluid property values, the gas rate, and the condensate rate.

The system may also include one or more processors and a non-transitory computer-readable medium in communication with the one or more processors and having stored thereon a set of instructions that, when executed, cause the one or more processors to perform operation 702 and 708, operation 702 and 708 comprising: the method includes receiving measured data from one or more server sites, receiving a plurality of sizes of one or more venturi meters from one or more server sites, receiving a plurality of fluid property values from one or more server sites at step 702, determining a second gas rate and a second condensate rate for each of the wellsites at step 704, comparing the second gas rate to the first gas rate and the second condensate rate to the first condensate rate at step 706, and identifying one or more problems associated with one or more venturi meters in one or more gas wellsites at step 708.

The method may also include receiving actual total gas production after the process of the gas plant separating gas and liquid from all gas wells and evaluating the accuracy between the total gas rate of the venturi meter and the gas rate measured at the gas plant. The method may further comprise: if one or both values do not match due to an incorrect throat or pipe size or fluid property correlation, the data is classified as incorrect or erroneous. The method may also include determining that the measured data from the one or more server sites is outside a predetermined threshold range and generating a device calibration or device replacement requirement. The method may further comprise: classifying the well as a problematic well if the determined gas rate or the determined condensate rate is outside a predetermined threshold range of the 3-phase separator test values; and generating a corrective action to change the fluid property correlation with the lower or higher CGR value and/or calibrate the P-T-dP level gauge transmitter. The method may also include generating a list of wells where problems were identified and sending the list to a maintenance group for performing corrective work. The method may further comprise: rate accuracy is evaluated by looking at the overall performance of the venturi meters from all gas wells and comparing the total gas production between the venturi meters and slug traps at the gas plant; and generating an alert if the rate difference or error is greater than a predetermined percentage.

The specification, including the summary, brief description of the drawings, and detailed description of the invention, and the appended claims, refers to particular features of the disclosure (including processes or method steps). The skilled person will appreciate that the invention includes all possible combinations and uses of the specific features described in the specification. Those skilled in the art will understand that the present disclosure is not limited to or by the descriptions of the embodiments given in the specification.

Those of ordinary skill in the art also understand that the terminology used in describing particular embodiments does not limit the scope or breadth of the present disclosure. In interpreting both the specification and the appended claims, all terms should be interpreted in the broadest possible manner consistent with the context of each term. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

As used in the specification and the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. The verb "comprise" and its conjugations should be interpreted as referring to elements, components or steps in a non-exclusive manner. The referenced elements, components or steps may be present, utilized or combined with other elements, components or steps not expressly referenced. "optionally," and its various forms, means that the subsequently described event or circumstance may or may not occur. The description includes instances where the event or circumstance occurs and instances where it does not.

Conditional language (such as "can," "might," or "may," etc.) is generally intended to convey that certain embodiments may include, while other embodiments do not include, certain features, elements, and/or operations, unless expressly stated otherwise or understood otherwise in the context of the usage. Thus, such conditional language is not generally intended to imply that one or more embodiments require features, elements and/or operations in any way or that one or more embodiments must include provisions for deciding whether there is user input or prompting that such features, elements and/or operations are included or are to be performed in any particular embodiment.

Thus, the system and method described herein are well adapted to carry out the objects and attain the ends and advantages mentioned, as well as others inherent therein. While exemplary embodiments of the systems and methods have been presented for purposes of disclosure, numerous changes exist in the details of procedures for accomplishing the desired results. These and other similar modifications may readily suggest themselves to those skilled in the art, and are intended to be encompassed within the spirit of the systems and methods disclosed herein and the scope of the appended claims.