An optimized method and system for pipeline descaling in oil and gas processing sites

Abstract

The application relates to the technical field of pipeline maintenance, in particular to an optimized oil and gas treatment station pipeline descaling method and system, which comprises the following steps: based on a pipeline scale sample, a plurality of organic and inorganic compounds are detected and identified by performing chemical component analysis on the sample, data of a plurality of components and contents are recorded, and sample component record data are generated.In the application, the chemical component analysis is performed on the pipeline scale sample, the composition of the plurality of organic and inorganic compounds of the scale is identified, targeted maintenance strategies are realized, the concentration and component of the cleaning agent are adjusted, the real-time monitoring of the flow and pressure data in the pipeline is combined, the analysis of the fluid chemical components is combined, the working state of the pipeline is evaluated in real time, the key factors causing the scale formation are identified, the scale formation position and speed are predicted, the flow pressure in the pipeline and the cleaning cycle are adjusted, the operation efficiency and safety of the pipeline system are improved, and the service life of the pipeline is prolonged.

Description

Technical Field

[0001] This invention relates to the field of pipeline maintenance technology, and in particular to an optimized method and system for descaling pipelines in oil and gas processing plants. Background Technology

[0002] Pipeline maintenance technology focuses on ensuring the efficiency, safety, and durability of oil and gas transmission pipeline systems. Through regular pipeline inspection, cleaning, and maintenance, it aims to prevent and resolve problems caused by corrosion, blockage, and wear. This includes physical and chemical cleaning, combined with intelligent monitoring systems for real-time status assessment, identifying potential defects or anomalies within the pipeline, and issuing timely alerts. This reduces the risk of accidental leaks or incidents, improves pipeline transport capacity, reduces maintenance frequency, extends pipeline service life, and ensures the reliability and economy of oil and gas transmission.

[0003] Among them, the descaling method for oil and gas processing plant pipelines focuses on solving the problem of scale buildup in pipelines of oil and gas processing plants, improving the operational efficiency and safety of pipelines, reducing scale formation in pipelines, improving the efficiency of oil and gas flow, and combining physical cleaning and chemical treatment methods to reduce blockage and corrosion caused by scale buildup in pipelines, improve the fluid dynamics characteristics in pipelines, reduce flow resistance and improve the efficiency of oil and gas transportation, reduce maintenance frequency and increase pipeline service life, reduce reliance on manual cleaning, reduce operating costs, reduce maintenance time, improve the overall safety and stability of pipelines, and achieve more sustainable oil and gas processing and transportation.

[0004] While traditional oil and gas processing plant pipeline descaling technologies have implemented various maintenance methods, including physical and chemical cleaning, they still have shortcomings in practical operation. Monitoring systems tend to focus on post-event treatment rather than real-time data analysis, limiting the ability to respond immediately to pipeline anomalies. When blockages or corrosion occur, problems can only be detected during regular inspections, increasing the difficulty of handling them and potentially leading to more serious equipment damage or safety accidents. Fixed cleaning cycles and chemical ratios are used for scale treatment, lacking the ability to dynamically adjust according to the actual pipeline conditions, resulting in low efficiency and unnecessary environmental burden due to the overuse of chemical cleaning agents. Long-term reliance on manual intervention also increases operational risks. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose an optimized method and system for descaling pipelines in oil and gas processing plants.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: an optimized method for descaling pipelines in oil and gas processing plants, comprising the following steps:

[0007] S1: Based on pipe scale samples, chemical composition analysis is performed on the samples to detect and identify various organic and inorganic compounds, record data on various components and their contents, and generate sample composition record data;

[0008] S2: Based on the sample composition data, the flow sensor is used to monitor the speed and pressure of the fluid flow inside the pipe in real time, and the chemical composition of the fluid inside the pipe is analyzed to generate fluid composition and flow information;

[0009] S3: Based on the fluid composition and flow rate information, analyze the correlation between various parameters such as flow rate, temperature, composition and scale formation, and evaluate the impact of scale on the fluid velocity in the pipeline, generating the analysis results of the causes of scale formation;

[0010] S4: Based on the analysis results of the formation causes, and based on the fluid flow rate at multiple locations within the pipe, predict multiple locations where scale will form, and assess the scale formation rate in multiple areas to generate scale formation prediction information;

[0011] S5: Based on the scale formation prediction information, the flow state inside the pipe is adjusted by increasing and decreasing the flow pressure inside the pipe to reduce the scale formation rate. Combined with real-time flow rate data, the effect of flow rate adjustment is evaluated, and a pressure adjustment operation record is generated.

[0012] S6: Adjust the operation record according to the pressure, adjust the concentration of the cleaning agent according to the chemical composition of the scale, adjust the cleaning cycle according to the scale formation rate, and generate a pipeline descaling record.

[0013] As a further aspect of the present invention, the sample component recording data includes organic compound type information, inorganic compound type information, and component content percentage dataset; the fluid component and flow information includes real-time flow velocity data, pressure measurement values, and fluid chemical composition change graphs; the formation cause analysis results include scale formation correlation analysis results, a list of key influencing factors, and scale impact on flow velocity assessment information; the scale formation prediction information includes scale formation location prediction results, predicted formation rate prediction data, and scale accumulation trend analysis results; the pressure adjustment operation record includes the adjusted pressure value, flow velocity change response results, and comparison data before and after pressure adjustment; and the pipeline descaling record includes the adjusted cleaning agent concentration, cleaning cycle adjustment results, and cleaning effect evaluation data.

[0014] As a further aspect of the present invention, based on pipe scale samples, the steps of performing chemical composition analysis on the samples to detect and identify various organic and inorganic compounds, and recording data on the composition and content of various components to generate sample composition recording data are as follows:

[0015] S101: Based on pipe scale samples, perform physical separation of the samples to isolate organic and inorganic components and generate sample separation results;

[0016] S102: Based on the sample separation results, perform qualitative and quantitative analysis on the organic and inorganic components in the sample, record the types and contents of various components, and generate chemical composition data;

[0017] S103: Based on the chemical composition data, combined with the sampling time and location information, record the chemical composition information of the target sample, including the content and proportion of various compounds, and generate sample composition record data.

[0018] As a further aspect of the present invention, based on the sample composition recording data, using a flow sensor to monitor the velocity and pressure of the fluid flow inside the pipe in real time, and analyzing the chemical composition of the fluid inside the pipe to generate fluid composition and flow information, the specific steps are as follows:

[0019] S201: Based on the sample composition data, use a flow sensor to monitor the flow rate and pressure of the fluid inside the pipe in real time, and generate real-time flow rate and pressure data;

[0020] S202: Based on the real-time flow rate and pressure data, collect temperature change data inside the pipeline in real time over multiple time periods to generate pipeline temperature data;

[0021] S203: Based on the pipeline temperature data, sample the fluid inside the pipeline, analyze and record the chemical composition of the fluid, and generate fluid composition and flow rate information.

[0022] As a further aspect of the present invention, the steps of analyzing the correlation between various parameters such as flow rate, temperature, composition, and scale formation based on the fluid composition and flow rate information, and evaluating the impact of scale on the fluid velocity in the pipeline to generate a result of the cause analysis are as follows:

[0023] S301: Based on the fluid composition and flow rate information, by analyzing the chemical composition of the scale, the relationship between the flow rate, temperature, pressure and chemical composition of the fluid inside the pipeline and the formation of scale is evaluated, and multi-factor influence assessment data is generated.

[0024] S302: Based on the multi-factor impact assessment data, calculate the correlation coefficient between multiple factors and scale formation, identify key factors, and generate key factor identification results;

[0025] S303: Based on the key factor identification results, by measuring and recording the flow velocity data of the scale accumulation area, analyze the impact of scale accumulation on the flow velocity, and generate the cause analysis results.

[0026] As a further aspect of the present invention, the specific formula for calculating the correlation coefficient between multiple factors and scale formation is as follows:

[0027]

[0028] in, Representative variable and The correlation coefficient between two variables indicates the degree of linear correlation between them. Representing the The values ​​of flow velocity, temperature, chemical concentration, or pressure observed each time reflect specific measurement data at a particular observation point. Indicates and The observed values ​​for the corresponding scale formation rate show the scale formation rate for each corresponding factor. It is all The average value provides the central tendency of the variable. It is all The average value also provides an average level of the rate of scale formation. This represents a specific observation instance index, used to identify each observation data item in the dataset.

[0029] As a further aspect of the present invention, based on the analysis results of the formation causes, and based on the fluid flow velocities at multiple locations within the pipe, the steps of predicting multiple locations where scale will form, evaluating the scale formation rate in multiple areas, and generating scale formation prediction information are as follows:

[0030] S401: Based on the analysis results of the formation cause, using the flow velocity monitoring data at multiple locations inside the pipe, analyze and predict the location of scale formation, and generate formation location prediction data;

[0031] S402: Based on the predicted location data, predict and calculate the scale formation rate at multiple locations, and generate a formation rate evaluation result;

[0032] S403: Based on the formation rate assessment results and combined with real-time flow rate monitoring data, analyze and verify the accuracy of the scale formation prediction results, and generate scale formation prediction information.

[0033] As a further aspect of the present invention, based on the scale formation prediction information, the flow state inside the pipe is adjusted by increasing and decreasing the flow pressure to reduce the scale formation rate, and the effect of the flow rate adjustment is evaluated by combining real-time flow rate data to generate a pressure adjustment operation record. The specific steps are as follows:

[0034] S501: Based on the scale formation prediction information, according to the internal flow velocity of the pipe and the predicted scale formation area information, analyze the pipe locations where fluid pressure needs to be adjusted, and generate adjustment demand assessment results.

[0035] S502: Based on the adjustment demand assessment results, adjust the fluid pressure in the pipeline according to the predicted scale formation rate information, and generate a real-time pressure adjustment record;

[0036] S503: Based on the real-time pressure adjustment record, monitor the flow rate and pressure data inside the pipeline after adjustment in real time, evaluate the impact of flow rate adjustment on the scale formation rate, verify the effectiveness of pressure adjustment, and generate a pressure adjustment operation record.

[0037] As a further aspect of the present invention, the steps of adjusting the concentration of the cleaning agent according to the chemical composition of the scale based on the pressure adjustment operation record, adjusting the cleaning cycle according to the scale formation rate, and generating a pipeline descaling record are as follows:

[0038] S601: Based on the pressure adjustment operation record, by analyzing the chemical composition of the scale in the pipeline, adjust the concentration, composition, and dosage of the cleaning agent to generate a cleaning agent adjustment record;

[0039] S602: Based on the cleaning agent adjustment record, combined with the scale formation rate, calculate and adjust the cleaning cycle and cleaning frequency, and generate a cleaning cycle adjustment list;

[0040] S603: Based on the cleaning cycle adjustment list, record the start and end times of multiple cleaning cycles, evaluate the cleaning effect, and generate a pipeline descaling record.

[0041] An optimized descaling system for oil and gas processing plant pipelines, the optimized oil and gas processing plant pipeline descaling system being used to perform the aforementioned optimized oil and gas processing plant pipeline descaling method, the system comprising:

[0042] The sample analysis module performs chemical analysis on the organic and inorganic compounds in the pipe scale sample, identifies the content of various compounds, and generates a list of scale chemical composition.

[0043] Based on the list of chemical components of the scale, the flow monitoring module uses a flow sensor to monitor the flow rate, pressure, and temperature in the pipeline in real time, and records the chemical composition of the fluid to generate flow rate and composition data.

[0044] Based on the flow and composition data, the cause analysis module analyzes the influence of pipe internal temperature, flow rate, and chemical composition on scale formation, identifies key factors in scale formation, and generates key factor identification results.

[0045] Based on the key factor identification results, the prediction and adjustment module predicts the location and speed of scale formation in the pipeline, and adjusts the pipeline pressure to slow down scale formation by combining real-time flow velocity data, thereby generating pipeline pressure adjustment results.

[0046] Based on the pipeline pressure adjustment results, the cleaning control module adjusts the concentration of the cleaning agent and the cleaning cycle according to the rate of scale formation, records the effect of the cleaning operation, and generates a pipeline descaling record.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0048] In this invention, chemical composition analysis of pipe scale samples is performed to identify the composition of various organic and inorganic compounds in the scale, enabling targeted maintenance strategies. These strategies include adjusting the concentration and composition of cleaning agents, real-time monitoring of flow and pressure data inside the pipe, analysis of fluid chemical composition, real-time assessment of the pipe's operating status, identification of key factors leading to scale formation, prediction of scale formation location and speed, and adjustment of internal flow pressure and cleaning cycle to improve the operating efficiency and safety of the pipeline system and extend the service life of the pipeline. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flowchart of S1 of the present invention;

[0051] Figure 3 This is a detailed flowchart of the S2 process of the present invention;

[0052] Figure 4 This is a detailed flowchart of the S3 process of the present invention;

[0053] Figure 5 This is a detailed flowchart of the S4 process of the present invention;

[0054] Figure 6 This is a detailed flowchart of S5 of the present invention;

[0055] Figure 7 This is a detailed flowchart of S6 of the present invention;

[0056] Figure 8 This is a system flowchart of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0059] Please see Figure 1 This invention provides a technical solution, an optimized method for descaling pipelines in oil and gas processing plants, comprising the following steps:

[0060] S1: Based on pipe scale samples, chemical composition analysis is performed on the samples to detect and identify various organic and inorganic compounds, record data on various components and their contents, and generate sample composition record data;

[0061] S2: Based on the sample composition data, using a flow sensor, the speed and pressure of fluid flow inside the pipeline are monitored in real time, and the chemical composition of the fluid inside the pipeline is analyzed to generate fluid composition and flow information;

[0062] S3: Based on fluid composition and flow information, analyze the correlation between various parameters such as flow rate, temperature, composition and scale formation, and evaluate the impact of scale on pipeline fluid velocity, generating the results of the scale formation cause analysis;

[0063] S4: Based on the analysis of the causes of scale formation, and based on the fluid flow rate at multiple locations within the pipeline, predict the multiple locations where scale will form, assess the scale formation rate in multiple areas, and generate scale formation prediction information.

[0064] S5: Based on the scale formation prediction information, the flow state inside the pipeline is adjusted by increasing and decreasing the flow pressure inside the pipeline to reduce the scale formation rate. Combined with real-time flow rate data, the effect of flow rate adjustment is evaluated, and a pressure adjustment operation record is generated.

[0065] S6: Adjust the operation record according to the pressure, adjust the concentration of the cleaning agent according to the chemical composition of the scale, adjust the cleaning cycle according to the scale formation rate, and generate a pipeline descaling record.

[0066] The sample composition records include information on organic compound types, inorganic compound types, and percentage data of component content. Fluid composition and flow information includes real-time flow velocity data, pressure measurements, and fluid chemical composition variation graphs. The formation cause analysis results include correlation analysis results of scale formation, a list of key influencing factors, and assessment information on the impact of scale on flow velocity. Scale formation prediction information includes predicted scale formation location, predicted formation rate, and analysis results of scale accumulation trends. Pressure adjustment operation records include adjusted pressure values, flow velocity change response results, and comparison data before and after pressure adjustment. Pipeline descaling records include adjusted cleaning agent concentration, cleaning cycle adjustment results, and cleaning effect evaluation data.

[0067] Please see Figure 2 Based on pipe scale samples, the chemical composition analysis of the samples is performed to detect and identify various organic and inorganic compounds, and data on the composition and content of various components are recorded. The specific steps for generating sample composition record data are as follows:

[0068] S101: Based on pipe scale samples, perform physical separation of the samples to isolate organic and inorganic components and generate sample separation results;

[0069] In sub-step S101, based on the pipe scale sample, the sample is initially processed using physical methods such as centrifugation and filtration. The high-speed rotation of the centrifuge separates heavier inorganic particles from lighter organic matter. Filtration refines the separation by passing the sample through filter paper with different pore sizes, effectively isolating inorganic and organic components. The process includes setting the centrifuge speed and running time, selecting filter paper with appropriate pore size, setting parameters based on the physical properties of the sample and the expected separation effect, and recording operating conditions such as centrifugation speed, time, and the type of filter paper used to ensure repeatability and accuracy. After separation, the separation effect is checked visually or under a microscope to ensure that inorganic and organic components are effectively isolated, generating the sample separation result.

[0070] S102: Based on the sample separation results, perform qualitative and quantitative analysis on the organic and inorganic components in the sample, record the types and contents of various components, and generate chemical composition data;

[0071] In sub-step S102, based on the sample separation results, chemical analysis of the organic and inorganic components in the sample is performed using gas chromatography-mass spectrometry (GC-MS) and X-ray fluorescence spectrometry (XRF). Qualitative and quantitative analyses of the organic and inorganic components are conducted separately. The process involves GC-MS analysis of organic components, including sample pretreatment, chromatographic condition setting, and mass spectrometry parameter optimization. Each component is accurately identified and measured using specific retention times and mass spectra. For inorganic components, XRF is used to determine the elemental types and contents in the sample through sample preparation, spectrometer calibration, and measurement parameter setting. Each step of the operation is recorded to ensure data accuracy and reliability, generating complete chemical composition data.

[0072] S103: Based on chemical composition data, combined with sampling time and location information, record the chemical composition information of the target sample, including the content and proportion of various compounds, and generate sample composition record data;

[0073] In sub-step S103, based on chemical composition data and combined with sampling time and location information, the chemical composition information in the target sample is recorded. Using geographic information system and time tagging technology, the geographical coordinates of the sampling point and the sampling time are recorded. Through the data management system, the chemical composition data and time and location information are integrated to record and analyze the content and proportion of various compounds in the sample, including data entry, error checking, data integration and processing. Statistical analysis software is used to analyze the data, identify the temporal and spatial distribution characteristics of the sample components, and display the sample component record data through data visualization tools such as charts and maps to ensure accurate recording and easy understanding of the information, resulting in the generated sample component record data.

[0074] Please see Figure 3 Based on sample composition data, using flow sensors to monitor the velocity and pressure of fluid flow inside the pipeline in real time, and analyzing the chemical composition of the fluid inside the pipeline to generate fluid composition and flow information, the specific steps are as follows:

[0075] S201: Based on sample composition recording data, using a flow sensor, the flow rate and pressure of the fluid inside the pipe are monitored in real time to generate real-time flow rate and pressure data;

[0076] The above content utilizes flow sensors to monitor the flow velocity and pressure of fluid inside the pipe, according to the formula... Calculate the flow rate;

[0077] In the formula, Represents the cross-sectional area of ​​the pipe. Represents flow rate, Represents traffic;

[0078] Detailed explanation of the formula and its calculation derivation:

[0079] Assuming the cross-sectional area of ​​the pipe The flow rate recorded by the flow velocity sensor is 0.05 square meters. Given a flow rate of 2 m / s, the fluid flow rate is calculated as follows:

[0080]

[0081] The result of 0.1 m³ / s indicates the flow rate of the fluid in the pipeline at the target time. The calculation process is used to monitor the dynamic flow state of the fluid in the pipeline, and the flow rate data is used to evaluate the operating efficiency of the system and analyze the factors affecting the flow rate.

[0082] S202: Based on real-time flow rate and pressure data, collect temperature change data inside the pipeline in real time over multiple time periods to generate pipeline temperature data;

[0083] In sub-step S202, temperature change data inside the pipeline is collected based on real-time flow rate and pressure data. Thermocouple temperature sensors are used to continuously monitor temperature changes over multiple time periods. The temperature sensors are optimized based on the thermodynamic conditions predicted by the flow rate and pressure data, including selecting appropriate measurement points and installation methods to obtain accurate temperature readings. The thermocouple data output is connected to a data logger to record temperature data in real time and synchronize it to the central monitoring system via wireless transmission. During operation, attention is paid to the thermal response time and measurement accuracy of the temperature sensors to ensure that the collected temperature data accurately reflects the temperature state inside the pipeline. The generated pipeline temperature data will be used to analyze the thermodynamic properties of the fluid, providing a scientific basis for fluid analysis and pipeline maintenance.

[0084] S203: Based on pipeline temperature data, sample the fluid inside the pipeline, analyze and record the chemical composition of the fluid, and generate fluid composition and flow information;

[0085] In sub-step S203, based on pipeline temperature data, the chemical composition of the fluid inside the pipeline is sampled and analyzed. An automatic sampling device is used, and the optimal sampling time is determined by combining flow and temperature data. The fluid sample is extracted from the pipeline by an extraction pump and quickly sealed to prevent changes in chemical properties. Sample analysis utilizes liquid chromatography-mass spectrometry (LC-MS) to analyze the chemical components in the fluid, including organic matter, inorganic salts, and trace elements. The operation steps include sample preparation, setting chromatographic conditions, and optimizing mass spectrometry detection parameters. The chromatographic and mass spectrometry data are processed by data analysis software to ensure that the content and proportion of each component are recorded. The analysis results are combined with flow and temperature data to generate fluid composition and flow information, providing a comprehensive diagnosis of the pipeline's operating status.

[0086] Please see Figure 4Based on fluid composition and flow rate information, the correlation between various parameters such as flow rate, temperature, composition, and scale formation is analyzed, and the impact of scale on pipeline fluid velocity is assessed. The specific steps for generating the analysis results of the causes of scale formation are as follows:

[0087] S301: Based on fluid composition and flow information, by analyzing the chemical composition of scale, assess the relationship between the flow rate, temperature, pressure and chemical composition of the fluid inside the pipeline and scale formation, and generate multi-factor impact assessment data;

[0088] In sub-step S301, the multi-factor relationship between fluid composition and flow rate information and scale formation is assessed by analyzing these factors. A multiple linear regression model using statistical analysis software is employed, combining flow rate, temperature, pressure, and chemical composition data for analysis. Fluid flow rate data, temperature readings, pressure values, and chemical composition records are collected and processed, then input into the analysis model. The statistical model is set with various fluid parameters as independent variables and scale formation frequency and severity as dependent variables. By establishing regression relationships, the impact of each parameter on scale formation is assessed. The process includes data standardization, model parameter estimation and validation, and the generation of multi-factor impact assessment data for predicting and controlling scale formation, thereby improving the efficiency and safety of pipeline management.

[0089] S302: Based on multi-factor impact assessment data, calculate the correlation coefficients between multiple factors and scale formation, identify key factors, and generate key factor identification results;

[0090] The specific formula for calculating the correlation coefficient between multiple factors and scale formation is as follows:

[0091]

[0092] in, Representative variable and The correlation coefficient between two variables indicates the degree of linear correlation between them. Representing the The values ​​of flow velocity, temperature, chemical concentration, or pressure observed each time reflect specific measurement data at a particular observation point. Indicates and The observed values ​​for the corresponding scale formation rate show the scale formation rate for each corresponding factor. It is all The average value provides the central tendency of the variable. It is all The average value also provides an average level of the rate of scale formation. This represents a specific observation instance index, used to identify each observation data item in the dataset.

[0093] formula:

[0094]

[0095] Detailed explanation of the formula and its calculation derivation:

[0096] The formula is used to calculate the Pearson correlation coefficient between two variables, assess the linear correlation between various operating conditions and scale formation rate, and provide a basis for adjusting pipeline operating conditions.

[0097] Parameter meanings and settings:

[0098] Let be the temperature value, assumed to be [18, 20, 22, 24, 26] °C, reflecting the temperature of the i-th observation. For all The average value, = 22 °C, reflecting the average temperature during the observation period;

[0099] Let [0.23, 0.22, 0.25, 0.24, 0.28] mm / h be the scale formation rate, reflecting the scale formation rate of the i-th observation. For all The average value, = 0.244 mm / h, reflecting the average rate of scale formation during the observation period.

[0100] Substitute the parameters into the formula to calculate:

[0101]

[0102]

[0103]

[0104]

[0105] result The study demonstrates a positive correlation between temperature and scale formation rate, indicating that scale formation rate increases with increasing temperature. This correlation coefficient is crucial for pipeline maintenance and operational adjustments.

[0106] S303: Based on the key factor identification results, by measuring and recording the flow velocity data of the scale accumulation area, analyze the impact of scale accumulation on flow velocity and generate the cause analysis results;

[0107] In sub-step S303, based on the key factor identification results, the impact of scale accumulation on flow rate is analyzed by measuring flow rate data in areas of scale accumulation. Flow rate sensors are used to measure flow rate in areas with known scale accumulation, including recording the time-series changes in flow rate. This involves selecting the sensor installation location, setting the data acquisition frequency, and configuring real-time data transmission. The flow rate data analysis employs an autoregressive moving average model based on time series analysis technology to identify the relationship between flow rate changes and scale accumulation. Through data analysis, the impact of scale on flow rate is understood, and the causes of scale formation are deduced based on actual measurement data, generating a cause analysis result. The result is crucial for developing cleaning and maintenance plans to ensure the effective operation and long-term stability of the piping system.

[0108] Please see Figure 5 Based on the analysis of the causes of scale formation, and considering the fluid flow velocities at multiple locations within the pipeline, the specific steps for generating scale formation prediction information are as follows:

[0109] S401: Based on the analysis of the causes of scale formation, the flow velocity monitoring data at multiple locations inside the pipeline is used to analyze and predict the location of scale formation, and generate formation location prediction data;

[0110] In sub-step S401, flow velocity monitoring data from multiple locations within the pipeline are used to analyze and predict the location of scale formation. This step employs Geographic Information System (GIS) technology and fluid dynamics simulation software, such as Computational Fluid Dynamics (CFD) models, to perform spatial distribution analysis of the flow velocity data. It integrates the pipeline's structural information with the flow velocity data, sets the boundary conditions and initial parameters of the CFD model, and runs the model to simulate fluid flow in the pipeline. By analyzing the flow characteristics of the fluid at different locations, including flow velocity changes at bends, joints, and narrow sections, the scale formation area is predicted. After the simulation results are verified, combined with real-time flow velocity monitoring data, predicted data on the location of scale formation is generated. This data is crucial for the subsequent pipeline maintenance and cleaning operation planning.

[0111] S402: Based on the formation location prediction data, predict and calculate the scale formation rate at multiple locations, and generate a formation rate assessment result;

[0112] In sub-step S402, based on the predicted location data, the scale formation rate at multiple locations is predicted and calculated. Using time series analysis, combined with historical scale formation records and current flow rate data, the scale formation rate at each predicted location is estimated. The process involves collecting historical scale data, current flow rate monitoring data, and the influence of environmental factors such as temperature and chemical composition at each location. By establishing statistical models, such as autoregressive moving average models, the scale formation rate is predicted, and the cumulative rate of scale at each location is calculated. The model parameters are obtained by fitting historical data to ensure the accuracy of the prediction, generating a scale formation rate assessment result to help pipeline operators optimize the allocation of time and resources for cleaning and maintenance.

[0113] S403: Based on the formation rate assessment results and combined with real-time flow rate monitoring data, analyze and verify the accuracy of the scale formation prediction results, and generate scale formation prediction information;

[0114] In the above content, based on the formation rate assessment results and combined with real-time flow rate monitoring data, error analysis methods were used to verify the accuracy of the scale formation prediction results. From the formula calculate;

[0115] In the formula, To account for the degree of error, This represents the predicted rate of scale formation. Represents the actual measured rate of scale formation;

[0116] Detailed explanation of the formula and its calculation derivation:

[0117] Assuming the predicted scale formation rate in the target pipe section The rate was 0.02 mm / day, but subsequent monitoring revealed the actual rate of scale formation. The error is 0.025 mm / day, according to the error calculation formula.

[0118]

[0119] The 20% error indicates that the prediction model needs further calibration and optimization to improve prediction accuracy. Analysis is crucial for understanding the limitations of the prediction model, improving the model and strategies, and ensuring the reliability and effectiveness of the prediction tool in practical applications.

[0120] Please see Figure 6 Based on the predicted fouling formation information, the flow state within the pipeline is adjusted by increasing and decreasing the flow pressure to reduce the fouling formation rate. The effect of the flow rate adjustment is evaluated by combining real-time flow velocity data, and the specific steps for generating a pressure adjustment operation record are as follows:

[0121] S501: Based on scale formation prediction information, and according to the internal flow velocity of the pipe and the predicted scale formation area information, analyze the pipe locations where fluid pressure needs to be adjusted, and generate adjustment demand assessment results.

[0122] In sub-step S501, based on the scale formation prediction information, the locations of pipelines requiring fluid pressure adjustment are analyzed. A fluid dynamics model is used to simulate the impact of different pressure settings on flow velocity and scale formation. Through computational fluid dynamics simulation, flow velocity data and scale formation area information are integrated to identify key areas where fluid pressure needs adjustment. Different operating scenarios are set during the simulation to evaluate the impact of different pressure settings on scale deposition trends. Based on the simulation results, pressure adjustment suggestions are proposed to optimize flow velocity distribution and reduce scale deposition. The data support of the dynamics simulation is evaluated, and adjustment requirement assessment results are generated to provide decision support for operators and achieve optimal operation of the pipeline system.

[0123] S502: Based on the adjustment demand assessment results and according to the predicted scale formation rate information, adjust the fluid pressure in the pipeline and generate a real-time pressure adjustment record;

[0124] In sub-step S502, based on the adjustment demand assessment results, the fluid pressure in the pipeline is adjusted. An automated control system is used to dynamically adjust the fluid pressure in the pipeline according to the predicted scale formation rate information. The control system automatically adjusts the valve opening or pump operating speed of each section of the pipeline according to the preset pressure adjustment strategy to change the fluid pressure. The process includes setting adjustment parameters, monitoring pressure changes in real time, and recording pressure adjustment data. The system makes fine adjustments based on real-time data feedback to ensure that the pressure adjustment achieves the expected effect and generates a real-time pressure adjustment record to ensure the stability of pipeline operation.

[0125] S503: Based on real-time pressure adjustment records, monitor the flow rate and pressure data inside the pipeline after adjustment, evaluate the impact of flow rate adjustment on the rate of scale formation, verify the effectiveness of pressure adjustment, and generate pressure adjustment operation records.

[0126] In sub-step S503, based on real-time pressure adjustment records, the flow rate and pressure data inside the pipeline after adjustment are monitored. Sensor technology is used to collect the adjusted flow rate and pressure data, assess the actual impact of the adjustment on the scale formation rate, and verify the effectiveness of the pressure adjustment. Statistical analysis methods and data visualization tools, such as scatter plots and regression analysis, are used in the analysis to identify the changing trend of scale formation rate before and after pressure adjustment, ensuring the completeness and accuracy of data collection. Through comparative analysis, a pressure adjustment operation record is generated. The record provides an evaluation of the effectiveness of the adjustment measures and helps optimize pressure management strategies to improve the efficiency and safety of the pipeline system.

[0127] Please see Figure 7The specific steps for generating pipeline descaling records are as follows: Adjusting the operation record based on pressure, adjusting the cleaning agent concentration based on the chemical composition of the scale, and adjusting the cleaning cycle based on the scale formation rate.

[0128] S601: Based on the pressure adjustment operation record, the concentration, composition, and dosage of the cleaning agent are adjusted by analyzing the chemical composition of the scale in the pipeline, and a cleaning agent adjustment record is generated.

[0129] In sub-step S601, based on the pressure adjustment operation record, the chemical composition of the scale in the pipeline is analyzed to adjust the concentration, composition, and dosage of the cleaning agent. Mass spectrometry and chemical analysis methods are used to identify the chemical composition and characteristics of the scale, select and adjust the chemical composition of the cleaning agent to enhance the cleaning effect. The concentration and dosage of the cleaning agent are adjusted according to the stubbornness and distribution range of the scale. A fluid dynamics model is used to predict the impact of different concentrations and dosages on the cleaning effect. The adjustment process involves small-scale laboratory experiments to verify the effectiveness of the cleaning agent composition and concentration, ensuring that the selected solution can effectively solve the scale problem. A cleaning agent adjustment record is generated to provide technical support and data backup for actual operation.

[0130] S602: Based on the cleaning agent adjustment record and combined with the scale formation rate, calculate and adjust the cleaning cycle and cleaning frequency, and generate a cleaning cycle adjustment list;

[0131] In sub-step S602, based on cleaning agent adjustment records and combined with the scale formation rate, the cleaning cycle and cleaning frequency are calculated and adjusted. Using historical data and predictive models, such as exponential smoothing and time series analysis, the rate of scale accumulation and the effectiveness of the cleaning agent are estimated, and the optimal cleaning cycle is determined. The parameters involved in the calculation process include the scale accumulation rate, the chemical properties of the cleaning agent, and the operating conditions of the pipeline. Based on the calculation results, the cleaning frequency is adjusted to maintain pipeline operation and prevent scale accumulation from reaching dangerous levels. Through comparative analysis of simulation and actual data, it is ensured that the adjusted cleaning cycle matches the actual scale formation rate. A cleaning cycle adjustment list is generated to optimize resource use and maintain the cleanliness and functionality of the pipeline.

[0132] S603: Based on the cleaning cycle adjustment list, record the start and end times of multiple cleaning cycles, evaluate the cleaning effect, and generate a pipeline descaling record.

[0133] In sub-step S603, based on the cleaning cycle adjustment list, the start and end times of multiple cleanings are recorded, and the cleaning effect is evaluated. The cleaning operation record includes the specific time of each cleaning, the type and amount of cleaning agent used, and the operating conditions, including the temperature and pressure settings of the pipeline. After cleaning, spectral analysis and sample testing methods are used to evaluate the residual scale and the removal effect of the cleaning agent. The process includes comparing the chemical composition and physical state of the pipeline inner wall before and after cleaning to ensure that each cleaning meets the predetermined cleaning standards. A pipeline descaling record is generated, which provides data support for subsequent maintenance cleaning and optimizes cleaning strategies and methods.

[0134] Please see Figure 8 An optimized oil and gas processing plant pipeline descaling system is provided for implementing the aforementioned optimized oil and gas processing plant pipeline descaling method. The system includes:

[0135] The sample analysis module performs chemical analysis on the organic and inorganic compounds in the pipe scale sample, identifies the content of various compounds, and generates a list of scale chemical composition.

[0136] The flow monitoring module uses a flow sensor to monitor the flow rate, pressure, and temperature in the pipeline in real time based on a list of scale chemical components, and records the chemical composition of the fluid to generate flow rate and composition data.

[0137] The cause analysis module analyzes the effects of internal pipe temperature, flow rate, and chemical composition on scale formation based on flow and composition data, identifies key factors in scale formation, and generates key factor identification results.

[0138] Based on the key factor identification results, the prediction and adjustment module predicts the location and speed of scale formation in the pipeline, and combines real-time flow velocity data to adjust the pipeline pressure to slow down scale formation and generate pipeline pressure adjustment results.

[0139] The cleaning control module adjusts the concentration of the cleaning agent and the cleaning cycle based on the pipeline pressure adjustment results and the rate of scale formation, and records the effect of the cleaning operation to generate a pipeline descaling record.

[0140] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An optimized method of descaling pipelines at oil and gas processing sites, characterized in that, The method comprises the following steps: Based on the pipeline scale sample, by analyzing the chemical composition of the sample, detecting and identifying a variety of organic and inorganic compounds, recording the data of a variety of components and contents, and generating sample composition record data; Based on the sample composition record data, using a flow sensor, real-time monitoring of the speed and pressure of the fluid flow inside the pipeline, and analyzing the chemical composition of the fluid in the pipeline, generating fluid composition and flow information; Based on the fluid composition and flow information, analyzing the correlation between flow rate, temperature, composition and scale formation, and evaluating the influence of scale on the flow rate of the pipeline, generating formation cause analysis results; According to the formation cause analysis results, according to the fluid flow rate at multiple positions in the pipeline, predicting multiple positions of scale formation, and evaluating the scale formation rate of multiple areas, generating scale formation prediction information; According to the scale formation prediction information, by increasing and reducing the flow pressure inside the pipeline, adjusting the flow state in the pipeline to reduce the scale formation rate, and combining with the real-time flow rate data, evaluating the effect of flow rate adjustment, generating pressure adjustment operation record; According to the pressure adjustment operation record, adjusting the concentration of the cleaning agent according to the chemical composition of the scale, and adjusting the cleaning period combined with the scale formation rate, generating pipeline descaling record; The sample composition record data includes organic compound type information, inorganic compound type information, and component content percentage data set. The fluid composition and flow information includes real-time flow rate data, pressure measurement value, and fluid chemical composition change graph. The formation cause analysis results include scale formation correlation analysis results, key influence factor list, and scale influence on flow rate evaluation information. The scale formation prediction information includes scale formation position prediction results, predicted formation speed prediction data, and scale accumulation trend analysis results. The pressure adjustment operation record includes adjusted pressure value, flow rate change response results, and pressure adjustment before and after comparison data. The pipeline descaling record includes adjusted cleaning agent concentration, cleaning period adjustment results, and cleaning effect evaluation data.

2. The optimized oil and gas processing field pipeline descaling method of claim 1, wherein, Based on the pipeline scale sample, by analyzing the chemical composition of the sample, detecting and identifying a variety of organic and inorganic compounds, recording the data of a variety of components and contents, and generating sample composition record data, the steps are as follows: Based on the pipeline scale sample, the sample is physically separated, and the organic and inorganic components are isolated to generate sample separation results; Based on the sample separation results, qualitative and quantitative analysis is performed on the organic and inorganic components in the sample, the types and contents of a variety of components are recorded, and chemical composition data is generated; Based on the chemical composition data, combined with the time and position information of the sample, the chemical composition information of the target sample is recorded, including the content and proportion of a variety of compounds, and sample composition record data is generated.

3. The optimized oil and gas processing field pipeline pigging method of claim 1, wherein, Based on the sample composition record data, using a flow sensor, real-time monitoring of the speed and pressure of the fluid flow inside the pipeline, and analyzing the chemical composition of the fluid in the pipeline, generating fluid composition and flow information, the steps are as follows: Based on the sample composition record data, the flow rate and pressure of the fluid inside the pipeline are monitored in real time by using a flow sensor to generate real-time flow rate and pressure data; Based on the real-time flow rate and pressure data, temperature change data inside the pipeline in multiple time periods are collected in real time to generate pipeline temperature data; Based on the pipeline temperature data, the fluid inside the pipeline is sampled, and the chemical composition of the fluid is analyzed and recorded to generate fluid composition and flow information.

4. The optimized oil and gas processing field pipeline pigging method of claim 1, wherein, Based on the fluid composition and flow information, the correlation between flow rate, temperature, composition and scale formation is analyzed, and the influence of scale on the flow rate of the pipeline is evaluated to generate a formation cause analysis result. The specific steps are as follows: Based on the fluid composition and flow information, the relationship between the flow rate, temperature, pressure and chemical composition of the fluid inside the pipeline and scale formation is evaluated by analyzing the chemical composition of the scale to generate multi-factor influence evaluation data; Based on the multi-factor influence evaluation data, the correlation coefficient between multiple factors and scale formation is calculated, and the key factors are identified to generate a key factor identification result; Based on the key factor identification result, the influence of scale accumulation on flow rate is analyzed by measuring and recording flow rate data in the scale accumulation area to generate a formation cause analysis result.

5. The method of claim 4, wherein, The specific formula for calculating the correlation coefficient between multiple factors and scale formation is: in, Representative variable and The correlation coefficient between two variables indicates the degree of linear correlation between them. Representing the The values ​​of flow velocity, temperature, chemical concentration, or pressure observed each time reflect specific measurement data at a particular observation point. Indicates and The observed values ​​for the corresponding scale formation rate show the scale formation rate for each corresponding factor. It is all The average value provides the central tendency of the variable. It is all The average value also provides an average level of the rate of scale formation. This represents a specific observation instance index, used to identify each observation data item in the dataset.

6. The optimized oil and gas processing field pipeline pigging method of claim 1, wherein, According to the formation cause analysis result, the fluid flow rate at multiple positions in the pipeline is used to predict the positions of scale formation and evaluate the scale formation rate in multiple areas to generate scale formation prediction information. The specific steps are as follows: Based on the formation cause analysis result, the flow rate monitoring data at multiple positions inside the pipeline is used to analyze and predict the positions of scale formation to generate formation position prediction data; Based on the formation position prediction data, the scale formation rate at multiple positions is predicted and calculated to generate a formation speed evaluation result; Based on the formation speed evaluation result, the accuracy of the scale formation prediction result is analyzed and verified by combining real-time flow rate monitoring data to generate scale formation prediction information.

7. The optimized oil and gas processing field pipeline pigging method of claim 1, wherein, According to the scale formation prediction information, the flow state in the pipeline is adjusted by increasing and decreasing the flow pressure inside the pipeline to reduce the scale formation rate, and the effect of flow rate adjustment is evaluated by combining real-time flow rate data to generate a pressure adjustment operation record. The specific steps are as follows: Based on the scale formation prediction information, the pipeline position that needs to be adjusted based on the flow rate and predicted scale formation area information inside the pipeline is analyzed to generate an adjustment demand evaluation result; Based on the adjustment demand evaluation result, the fluid pressure in the pipeline is adjusted according to the predicted scale formation speed information to generate a real-time pressure adjustment record; Based on the real-time pressure adjustment record, the flow rate and pressure data inside the adjusted pipeline are monitored in real time to evaluate the influence of flow rate adjustment on scale formation rate and verify the effectiveness of pressure adjustment to generate a pressure adjustment operation record.

8. The optimized oil and gas processing field pipeline pigging method of claim 1, wherein, According to the pressure adjustment operation record, the concentration of the cleaning agent is adjusted according to the chemical composition of the scale, and the cleaning cycle is adjusted according to the scale formation rate to generate a pipeline descaling record. The specific steps are as follows: Based on the pressure adjustment record, by analyzing the chemical composition of the scale in the pipeline, the concentration, composition and dosage of the cleaning agent are adjusted to generate a cleaning agent adjustment record; Based on the cleaning agent adjustment record, combined with the scale formation rate, the cleaning period and cleaning frequency are calculated and adjusted to generate a cleaning period adjustment list; Based on the cleaning period adjustment list, the time of multiple cleaning starts and ends is recorded, and the cleaning effect is evaluated to generate a pipeline descaling record.

9. An optimized oil and gas processing site pipeline descaling system, characterized by, The optimized oil and gas processing station pipeline descaling method according to any one of claims 1-8, the system comprises: The sample analysis module performs chemical analysis on organic and inorganic compounds in the sample based on the pipeline scale sample, identifies the content of multiple compounds, and generates a scale chemical composition list; The flow monitoring module uses flow sensors to monitor the flow rate, pressure and temperature in the pipeline in real time based on the scale chemical composition list, and records the chemical composition of the fluid to generate flow and composition data; The cause analysis module analyzes the influence of the internal temperature, flow rate and chemical composition of the pipeline on scale formation based on the flow and composition data, identifies the key factors of scale formation, and generates a key factor identification result; The prediction adjustment module predicts the location and speed of scale formation in the pipeline based on the key factor identification result, adjusts the pipeline pressure to slow down scale formation combined with real-time flow rate data, and generates a pipeline pressure adjustment result; The cleaning control module adjusts the concentration and cleaning period of the cleaning agent according to the scale formation rate based on the pipeline pressure adjustment result, and records the effect of the cleaning operation to generate a pipeline descaling record.

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