Offshore platform natural gas processing platform online optimization method and system based on local dynamic simulation

Abstract

The invention belongs to the technical field of oil and gas field production platforms, and relates to an online optimization method and system for an offshore platform natural gas processing platform based on local dynamic simulation. Comprising the following steps: acquiring process data of each device of the offshore platform natural gas processing platform; according to the process data, judging whether the equipment has accumulated quantity, if not, carrying out steady-state simulation, and if yes, carrying out dynamic simulation; a steady-state simulation result is obtained by calculating the variance; obtaining a dynamic simulation result according to the opening degree of the field valve and the flow coefficient corresponding to each opening degree of the valve; and generating a platform optimization scheme according to the steady-state simulation result, the dynamic simulation result and the total energy consumption of the offshore platform natural gas processing platform. According to the invention, a stable / dynamic calculation method of unit equipment is determined through steady state detection, and the problem that data are inconsistent with a field is solved.

Description

Technical Field

[0001] The invention relates to an online optimization method and system for an offshore platform natural gas processing platform based on local dynamic simulation, belonging to the technical field of oil and gas field production platforms. Background Art

[0002] As a green, environmentally friendly, safe and efficient chemical energy, natural gas has occupied an increasingly important position in the global energy structure. Process simulation, as an important tool for process characteristic analysis, equipment design, optimization and control, is widely used in the modeling and simulation research of natural gas processing technology. In the simulation process of natural gas processing platform, there are two main methods: steady-state simulation and dynamic simulation. The disadvantage of steady-state simulation is that it is necessary to wait until the device operation is stable and the materials entering and leaving are conserved before steady-state simulation can be performed, and the device cannot be simulated in real time. The disadvantage of dynamic simulation is that it has a set of time and simulation data independent of the actual device, and it is impossible to access the real-time data on the site in real time. In addition, the existing simulation calculations on natural gas processing platforms only consider the problem of power consumption unilaterally. For offshore platform natural gas processing platforms, since the electricity of offshore platforms is produced by natural gas, special consideration is required in energy consumption analysis. Summary of the invention

[0003] In view of the above problems, the purpose of the present invention is to provide an online optimization method and system for an offshore platform natural gas processing platform based on local dynamic simulation. The steady-state detection determines the steady-state / dynamic calculation method of the unit equipment. The model no longer iterates the tear flow, so that the overall model converges, solves the problem of inconsistency between data and the site, and realizes online process simulation and device optimization with one platform.

[0004] To achieve the above-mentioned purpose, the present invention proposes the following technical scheme: an online optimization method for an offshore platform natural gas processing platform based on local dynamic simulation, comprising the following steps: obtaining process data of each device of the offshore platform natural gas processing platform; judging whether the equipment has accumulation according to the process data, and performing steady-state simulation if there is no accumulation, and performing dynamic simulation if there is accumulation; obtaining steady-state simulation results by calculating variance; obtaining dynamic simulation results according to the field valve opening and the flow coefficient corresponding to each valve opening; generating a platform optimization scheme according to the steady-state simulation results, the dynamic simulation results and the total energy consumption of the offshore platform natural gas processing platform.

[0005] Furthermore, after acquiring the process data, the process data is cleaned, and the cleaning method is as follows: determining the data status of the process data, and determining whether the number of bad data in a time window exceeds a threshold value based on the data status; if not, calculating the average value of the data in the time window, and marking the average value status as good data; if so, determining whether to replace the data; if the data replacement is successful, marking the average value status as Overrided; if the data replacement is unsuccessful, calculating the average value of the data in the time window, and marking the average value status as bad data.

[0006] Furthermore, the data status is good data, bad data and clamped data, and the method for judging the data status of the process data is: receiving historical data of the time window, obtaining data of the next node, obtaining the next site, judging whether the process data of the site exceeds the data limit, if so, judging whether it is clamped limit, if so, the data status is clamped data, if not, the data status is bad data; if there is no data exceeding the limit, judging whether the data is frozen, if so, the data status is bad data; if otherwise, judging whether the change rate exceeds the limit, if so, the data status is bad data, if otherwise, the data status is good data.

[0007] Further, the method for determining whether to replace data is as follows: determine whether to replace data, and if so, determine whether the previous data of the bad data is good data; if the bad data is replaced with good data, the replacement is successful; if not, determine whether the bad data can be replaced with a default value; if so, replace it, and the replacement is successful; otherwise, the replacement fails, and the average value status is marked as bad data.

[0008] Furthermore, the method for judging steady state is: first calculate the variance and mean square continuous difference of the data in the time window, and use the variance size and the ratio of the calculated variance to the mean square continuous difference as the standard for judging the steady state of the device; when the square of the variance is less than or equal to the stability threshold of the equipment, and the square of the variance divided by the square of the mean square continuous difference is greater than or equal to the preset value, it is steady state; otherwise, it is non-steady state.

[0009] Further, the calculation formula of the variance is:

[0010]

[0011] Among them, x t is the value at time t, x t-1 is the value at time t-1, x avg is the average value over a period of time, and k is the number of points taken.

[0012] Furthermore, the steady-state simulation uses a sequential module method to calculate each device in turn, and the dynamic simulation uses a simultaneous equation method.

[0013] Furthermore, the dynamic simulation results include liquid phase flow rate, and the calculation formula of the liquid phase flow rate is:

[0014]

[0015] Wherein, W[valve] is the liquid phase flow rate, Cv is the corresponding flow coefficient under the valve opening, ΔP=P[upstream]-P[downstream], P[upstream] is the operating pressure of the upstream equipment, P[downstream] is the operating pressure of the downstream equipment, and Rmass is the inlet flow rate of the equipment.

[0016] Furthermore, the calculation formula for the total energy consumption of the offshore platform natural gas processing platform is: total energy consumption = stripping gas consumption * unit natural gas market price + (pump power consumption + reboiler power consumption) * natural gas power generation converted electricity price; among which, natural gas power generation converted electricity price = amount of natural gas consumed to produce unit electricity * unit natural gas market price.

[0017] The present invention also discloses an online optimization system for an offshore platform natural gas processing platform based on local dynamic simulation, comprising: a data acquisition module, used to acquire process data of each device of the offshore platform natural gas processing platform; an accumulation determination module, used to determine whether the equipment has accumulation according to the process data, and to perform steady-state simulation if there is no accumulation, and to perform dynamic simulation if there is accumulation; a static simulation module, used to obtain steady-state simulation results by calculating variance; a dynamic simulation module, used to obtain dynamic simulation results according to the field valve opening and the flow coefficient corresponding to each valve opening; an optimization method generation module, used to generate a platform optimization plan according to the steady-state simulation results, the dynamic simulation results and the total energy consumption of the offshore platform natural gas processing platform.

[0018] The technical solution of the present invention has at least the following technical effects or advantages: The present invention determines the steady / dynamic calculation method of the unit equipment through steady-state detection, and the model no longer performs iterative calculations on the tear flow, so that the overall model converges, solves the problem of inconsistency between data and the site, and uses a platform to achieve online process simulation and device optimization. At the same time, for the offshore platform natural gas processing project, it proposes a method for natural gas power generation conversion, converts electricity costs into natural gas consumption costs, and optimizes the natural gas energy consumption of the entire device. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of an online optimization method for an offshore platform natural gas processing platform based on local dynamic simulation in one embodiment of the present invention;

[0020] Figure 2 is a flow chart of a method for cleaning process data in one embodiment of the present invention;

[0021] Figure 3 is an interface diagram of a device model of Simtech Simulator software in one embodiment of the present invention;

[0022] Figure 4 It is an interface diagram of total energy consumption optimization of Simtech Simulator software in one embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail through specific embodiments. However, it should be understood that the provision of specific embodiments is only for a better understanding of the present invention, and they should not be understood as limitations of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be understood as indicating or implying relative importance.

[0024] In order to solve the problems that static simulation in the prior art cannot simulate the device in real time, dynamic simulation cannot access the real-time data on site in real time, and the existing simulation calculations on natural gas processing platforms only consider the power consumption problem unilaterally, the present invention proposes an online optimization method and system for offshore platform natural gas processing platform based on local dynamic simulation. In order to simulate the offshore platform natural gas processing platform in real time, it is necessary to take steady-state simulation as the basis, determine whether the equipment has cumulative amount according to steady-state detection, and dynamically simulate the equipment with cumulative amount, such as towers and tanks, so as to simulate the fluctuation of the whole system after the valve adjusts the flow. According to the steady-state detection, it is divided into steady-state simulation and dynamic simulation to determine whether the equipment has cumulative amount, and modeling is performed on the same platform. For equipment with cumulative amount in towers and tanks, the product flow is calculated according to the on-site valve opening and valve Cv value, and local dynamic simulation is realized to solve the problem that the outlet valve of the regulating tank and tower cannot simulate the dynamic change of flow in steady-state simulation. For offshore platform natural gas processing projects, the present invention proposes a method for converting natural gas power generation, converting electricity charges into natural gas consumption costs, and optimizing the natural gas energy consumption of the entire device. The scheme of the present invention is described in detail by embodiments in conjunction with the accompanying drawings.

[0025] Embodiment 1

[0026] This embodiment discloses an online optimization method for an offshore natural gas processing platform based on local dynamic simulation. Figure 1 As shown, the following steps are included:

[0027] S1 obtains process data of various equipment on an offshore natural gas processing platform.

[0028] like Figure 2As shown in the figure, after obtaining the process data, due to the noise of some instruments on the equipment, the data obtained is unreasonable. Through the means of mathematical statistics, some unreasonable values ​​are excluded, and reasonable values ​​are selected as the process regulations of the model. Therefore, the process data needs to be cleaned. The cleaning method is: judge the data status of the process data, and judge whether the number of bad data in the time window exceeds the threshold according to the data status. If not, calculate the average value of the data in the time window, and mark the average value status as good data. If so, judge whether to replace the data. If the data is replaced successfully, mark the status of the average value as Overrided. If the data replacement is unsuccessful, calculate the average value of the data in the time window and mark the status of the average value as bad data.

[0029] The data status is good data, bad data and clamped data. The method for judging the data status of process data is: receive historical data of the time window, obtain data of the next node, obtain the next site, judge whether the process data of the site exceeds the data limit, if so, judge whether it is clamp limit, if so, the data status is clamped data, if not, the data status is bad data; if there is no data exceeding the limit, judge whether the data is frozen, if so, the data status is bad data; if otherwise, judge whether the change rate exceeds the limit, if so, the data status is bad data, if otherwise, the data status is good data.

[0030] The method for determining whether to replace data is as follows: determine whether to replace data, if so, determine whether the previous data of the bad data is good data; if the bad data is replaced with good data, the replacement is successful, if not, determine whether the bad data can be replaced with the default value, if so, replace it, and the replacement is successful, otherwise the replacement fails, and the average value status is marked as bad data.

[0031] S2 determines whether the equipment has accumulated amount based on the process data. If there is no accumulated amount, a steady-state simulation is performed; if there is accumulated amount, a dynamic simulation is performed.

[0032] The method for judging steady state is: first calculate the variance and mean square continuous difference of the data in the time window, and use the variance size and the ratio of the calculated variance to the mean square continuous difference as the standard for judging the steady state of the device; when the square of the variance is less than or equal to the stability threshold of the equipment, and the square of the variance divided by the square of the mean square continuous difference is greater than or equal to the preset value, it is steady state; otherwise, it is non-steady state.

[0033] In this embodiment, when σ2≤ε and When the unit data point is , the unit is in steady state. ε is the stability threshold of the device, which can be set by the user according to the operation of the device.

[0034] The formula for calculating variance is:

[0035]

[0036] Among them, x t is the value at time t, x t-1 is the value at time t-1, x avg is the average value over a period of time, and k is the number of points taken. If the unit is not in a steady state, a dynamic simulation is performed on the unit. The dynamic simulation calculates the flow rate by reading the control valve opening and the valve Cv value.

[0037] The method in this embodiment is implemented by Simtech Simulator software, and steady-state judgment is made on the software. For equipment without cumulative amounts, steady-state simulation can be used for calculation, such as pumps and heat exchangers; for equipment with cumulative amounts, dynamic simulation is used for calculation, such as towers and tanks. Two different types of models are built on a flow chart, and calculations are performed separately according to the equipment type. It should be noted that the Simtech Simulator software is preferably used in this embodiment, but it does not mean that it can only be implemented by this software.

[0038] S3 obtains steady-state simulation results by calculating variance; and obtains dynamic simulation results based on the on-site valve opening and the flow coefficient corresponding to each valve opening.

[0039] Steady-state simulation uses the sequential module method to calculate each device in turn, and only process data, including temperature, pressure, flow, composition, etc., are required. The dynamic simulation uses the simultaneous equation method. The dynamic model requires the size data of the tower and tank, the liquid level of the tank, the opening of the control valve, etc. In this embodiment, the liquid phase flow is mainly calculated based on the Cv value under the valve opening of the device, and then the pressure, temperature, and composition of the outlet are calculated using flash evaporation.

[0040] The dynamic simulation results include liquid phase flow rate, and the calculation formula of liquid phase flow rate is:

[0041]

[0042] Where W[valve] is the liquid flow rate, kg / hr; Cv valve opening corresponding to the flow coefficient, kg / hr; ΔP = P[upstream]-P[downstream], P[upstream] is the operating pressure of the upstream equipment, MPa, P[downstream] is the operating pressure of the downstream equipment, MPa, Rmass is the inlet flow of the equipment, kg / m 3 .

[0043] S4 generates a platform optimization plan based on the steady-state simulation results, dynamic simulation results and the total energy consumption of the offshore natural gas processing platform.

[0044] For offshore natural gas processing platforms, energy consumption comes from stripping gas consumption and electricity consumption. Since the electricity of offshore platforms is generated by natural gas, the electricity price needs to be converted according to the actual natural gas price. The calculation formula for the total energy consumption of offshore natural gas processing platforms is:

[0045] Total energy consumption = stripping gas consumption * unit natural gas market price + (pump power consumption + reboiler power consumption) * natural gas power generation converted electricity price;

[0046] Among them, the converted electricity price of natural gas power generation = the amount of natural gas consumed to produce unit electricity * the unit market price of natural gas.

[0047] The process optimization function of Simtech Simulator can optimize the total energy consumption as the objective function, and optimize the variables such as stripping gas consumption, lean TEG circulation volume, and dehydration tower inlet temperature to obtain the lowest cost based on process production requirements such as dry gas moisture content. During the implementation of the Deep Sea No. 1 project, Shengtai established a full-process model of the upper module of the Deep Sea No. 1 platform on the Advisor platform. The model covers production processes such as pressurization, dehydration, and regeneration. Figure 3 It is a flow chart of the equipment model. The model can determine the steady / dynamic calculation method of the unit equipment through steady-state judgment. The model will perform calculations for each operation of the valve by the operator and save the calculation results to the database in real time. The front-end interface obtains the calculation results from the database and presents them on the Web in the form of a flow chart. Users can view them through a web browser on any computer.

[0048] In this embodiment, the stripping gas price is the market price, and the electricity price is the converted electricity price calculated by the system. By setting the constraint condition of dry starting moisture content, the stripping gas consumption, lean TEG circulation volume, dehydration tower inlet temperature, etc. are optimized to obtain the best energy consumption, such as Figure 4 .

[0049] In this embodiment, the tear flow is no longer iterated to achieve device convergence; the basis of steady-state process simulation is mass conservation and energy conservation. Since this embodiment is based on steady-state simulation and adds the local dynamics of towers and tanks, the flow rate cannot meet the mass conservation required by steady state, so the tear flow cannot be converged and iterated. For towers, tanks and other equipment, due to the change in cumulative volume, the mass conservation and energy conservation of the equipment in and out cannot be met, so the mass balance and energy balance requirements of these equipment need to be relaxed.

[0050] Embodiment 2

[0051] Based on the same inventive concept, this embodiment discloses an online optimization system for an offshore platform natural gas processing platform based on local dynamic simulation, comprising:

[0052] A data acquisition module is used to obtain process data of various equipment on the offshore natural gas processing platform;

[0053] The accumulation amount determination module is used to determine whether the equipment has accumulation amount according to the process data. If there is no accumulation amount, a steady-state simulation is performed; if there is accumulation amount, a dynamic simulation is performed;

[0054] Static simulation module, used to obtain steady-state simulation results by calculating variance;

[0055] Dynamic simulation module, used to obtain dynamic simulation results according to the on-site valve opening and the flow coefficient corresponding to each valve opening;

[0056] The optimization method generation module is used to generate a platform optimization plan based on the steady-state simulation results, the dynamic simulation results and the total energy consumption of the offshore platform natural gas processing platform.

[0057] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not deviate from the spirit and scope of the present invention should be included in the protection scope of the claims of the present invention. The above content is only a specific implementation of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An online optimization method for an offshore natural gas processing platform based on local dynamic simulation, characterized in that: The following steps are involved: Obtain process data of each equipment on the offshore natural gas processing platform; According to the process data, determine whether the equipment has accumulated amount, if there is no accumulated amount, perform steady-state simulation, if there is accumulated amount, perform dynamic simulation; The steady-state simulation results are obtained by calculating the variance; According to the on-site valve opening and the flow coefficient corresponding to each valve opening, the dynamic simulation results are obtained; A platform optimization plan is generated based on the steady-state simulation results, the dynamic simulation results and the total energy consumption of the offshore platform natural gas processing platform.

2. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 1, characterized in that: After acquiring the process data, the process data is cleaned, and the cleaning method is as follows: determine the data status of the process data, and determine whether the number of bad data in the time window exceeds a threshold value based on the data status; if not, calculate the average value of the data in the time window, and mark the average value status as good data; if so, determine whether to replace the data; if the data is replaced successfully, mark the average value status as Overrided; if the data is replaced unsuccessfully, calculate the average value of the data in the time window, and mark the average value status as bad data.

3. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 2, characterized in that: The data status is good data, bad data and clamped data. The method for judging the data status of the process data is: receiving historical data of the time window, obtaining data of the next node, obtaining the next site, judging whether the process data of the site exceeds the data limit, if so, judging whether it is clamped limit, if so, the data status is clamped data, if not, the data status is bad data; if there is no data exceeding the limit, judging whether the data is frozen, if so, the data status is bad data; if otherwise, judging whether the change rate exceeds the limit, if so, the data status is bad data, if otherwise, the data status is good data.

4. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 2, characterized in that: The method for determining whether to replace data is as follows: determining whether to replace data, and if so, determining whether the previous data of the bad data is good data; if the bad data is replaced with good data, the replacement is successful; if not, determining whether the bad data can be replaced with a default value; if so, performing the replacement, and the replacement is successful; otherwise, the replacement fails, and the average value status is marked as bad data.

5. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 1, characterized in that: The method for judging steady state is: first calculate the variance and mean square continuous difference of the data in the time window, and use the variance size and the ratio of the calculated variance to the mean square continuous difference as the standard for judging the steady state of the device; when the square of the variance is less than or equal to the stability threshold of the device, and the square of the variance divided by the square of the mean square continuous difference is greater than or equal to the preset value, it is a steady state; Otherwise it is non-steady state.

6. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 5, characterized in that: The calculation formula of the variance is: Among them, x t is the value at time t, x t-1 is the value at time t-1, x avg is the average value over a period of time, and k is the number of points taken.

7. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 1, characterized in that: The steady-state simulation uses a sequential module method to calculate each device in turn, and the dynamic simulation uses a simultaneous equation method.

8. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to claim 7, characterized in that: The dynamic simulation results include liquid phase flow rate, and the calculation formula of the liquid phase flow rate is: Wherein, W[valve] is the liquid phase flow rate, Cv is the corresponding flow coefficient under the valve opening, ΔP=P[upstream]-P[downstream], P[upstream] is the operating pressure of the upstream equipment, P[downstream] is the operating pressure of the downstream equipment, and Rmass is the inlet flow rate of the equipment.

9. The method for online optimization of an offshore natural gas processing platform based on local dynamic simulation according to any one of claims 1 to 8, characterized in that: The calculation formula for the total energy consumption of the offshore natural gas processing platform is: Total energy consumption = stripping gas consumption * unit natural gas market price + (pump power consumption + reboiler power consumption) * natural gas power generation converted electricity price; Among them, the converted electricity price of natural gas power generation = the amount of natural gas consumed to produce unit electricity * the unit market price of natural gas.

10. An online optimization system for an offshore natural gas processing platform based on local dynamic simulation, characterized in that: include: A data acquisition module is used to obtain process data of various equipment on the offshore natural gas processing platform; An accumulation amount determination module is used to determine whether the equipment has accumulation amount according to the process data, and to perform steady-state simulation if there is no accumulation amount, and to perform dynamic simulation if there is accumulation amount; Static simulation module, used to obtain steady-state simulation results by calculating variance; Dynamic simulation module, used to obtain dynamic simulation results according to the on-site valve opening and the flow coefficient corresponding to each valve opening; The optimization method generation module is used to generate a platform optimization plan based on the steady-state simulation results, the dynamic simulation results and the total energy consumption of the offshore platform natural gas processing platform.

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