Method for dynamically predicting service life of tubular column based on corrosion logging detection

Abstract

The invention relates to the field of tubular column life dynamic prediction, in particular to a tubular column life dynamic prediction method based on corrosion logging detection, which comprises the following steps of: constructing target parameters influencing the corrosion rate of a test tubular column by utilizing a single parameter change test, and calculating the acid gas partial pressure, the liquid holdup and the fluid flow state of each monitoring point; the corrosion rate corresponding to the monitoring point is determined by adopting electromagnetic flaw detection logging, a corrosion rate prediction model is established by adopting a neural network prediction method, and future target prediction parameters are determined by predicting the gas production rate, the water production rate and the formation pressure of each year in the future; therefore, the corrosion rate of each year in the future is determined; calculating the residual wall thickness of the future year, determining an internal pressure resistance safety coefficient and an external extrusion resistance safety coefficient, determining the residual life of the to-be-predicted tubular column, and timely sending out early warning information; and transmitting the early warning information and the collected data to a terminal by using a wireless communication technology to monitor the tubular column in real time. Therefore, the dynamic performance of gas well life prediction is realized.

Description

Technical Field

[0001] The invention relates to the field of dynamic prediction of pipe string life, and in particular to a method for dynamic prediction of pipe string life based on corrosion logging detection. Background Art

[0002] In recent years, the gas produced from marine strata in the Sichuan Basin generally contains acidic gases such as H2S and CO2. Gas wells face serious risks of double corrosion failure. It is a common practice to use economical and applicable pipes to improve economic benefits under the premise of safety. The most widely used oil pipe material on site is high-sulfur-resistant carbon steel such as P110SS, which can better deal with stress corrosion cracking problems. However, there are still common problems of corrosion thinning and perforation. Subsequent treatment measures must be taken in a timely manner. Therefore, how to determine the service life of pipes in a specific block is a key technical issue to ensure safe and economic exploitation of gas wells. At present, there is no accurate, economical and applicable life prediction technology, and the existing methods are not adaptable.

[0003] The patent document of Chinese patent application publication number CN103206205A discloses a method for predicting the life of an oil pipe string, which includes: calculating the maximum stress of a new oil pipe string, where σ is the maximum stress of the new oil pipe string, L is the length of the oil pipe string, q is the weight of the oil pipe string per meter, Do is the outer diameter of the new oil pipe string, and Di is the inner diameter of the new oil pipe string; calculating the maximum stress of the oil pipe string at a certain time: Dtx=D i+2vt, where σt is the maximum stress of the tubing string at a certain time, Dtx is the inner diameter of the tubing string at a certain time, Di is the inner diameter of the new tubing, v is the corrosion rate, and t is time; the tensile safety factor of the new tubing string is calculated according to the following formula: where α is the tensile safety factor of the new tubing string, P is the tensile limit load of the new tubing string thread, and g is the acceleration of gravity; the tensile safety factor of the tubing string at a certain time is calculated based on the tensile safety factor of the new tubing string calculated above: where αt is the tensile safety factor of the tubing string at a certain time; when the tensile safety factor of the tubing string at a certain time is equal to the preset safety factor threshold, the decrease time of the tensile safety factor of the tubing string is the tensile safety life of the tubing string.

[0004] In the prior art, the remaining life is calculated based on known parameters of the oil tubing string without analyzing the dynamic prediction data, which has certain limitations in predicting the life of the tubing string. Summary of the invention

[0005] To this end, the present invention provides a method for dynamically predicting the life of a tubing string based on corrosion logging detection. By analyzing the key influencing factors of the dynamic parameters and the degree of corrosion in the production system, the tubing corrosion rate is efficiently and accurately obtained to solve the problem of effectively predicting the remaining life of the tubing string within fixed parameters.

[0006] To achieve the above object, the present invention provides a method for dynamically predicting the life of a pipe string based on corrosion logging detection, comprising:

[0007] A single parameter change test is used to construct several target parameters that affect the corrosion rate of the test string, wherein the target parameters include temperature, acid gas partial pressure, liquid holdup and fluid flow state;

[0008] Taking the wellhead as the starting point along the extension direction of the wellbore, a number of monitoring points are set at depth intervals, the temperature and pressure of each monitoring point are recorded, and the acid gas partial pressure at each monitoring point is determined according to the pressure and the acid gas proportion;

[0009] The gas-liquid mixture in the wellbore is transmitted using a test pipe string, and the gas-liquid flow rate at each monitoring point is calculated according to the inner diameter of the test pipe string, the wellhead pressure, and the total production of the gas-liquid mixture in the wellbore;

[0010] Determining the gas-liquid two-phase flow pattern of the gas-liquid mixture at the monitoring point according to the transmission position of the gas-liquid mixture in the test string;

[0011] Calculating the liquid holdup and fluid flow pattern of each monitoring point according to the gas-liquid flow rate and the gas-liquid two-phase flow pattern;

[0012] Using electromagnetic flaw detection and logging technology to determine the change rate of the wellbore wall thickness at each of the monitoring points to determine the corrosion rate corresponding to each of the monitoring points;

[0013] A corrosion rate prediction model is established using a neural network prediction method according to target parameters of each monitoring point and the corrosion rate;

[0014] A pipe string to be predicted is arranged in the gas well to be evaluated, wherein the pipe string to be predicted is used to transport the gas-liquid mixture in the gas well to be evaluated;

[0015] Predicting the gas production, water production and formation pressure in future years based on the current parameters of the gas well to be evaluated, so as to determine the target prediction parameters of the gas well to be evaluated in future years according to the pressure at each position of the gas well to be evaluated and the total production of gas-liquid mixture;

[0016] Determining the corrosion rate in each future year according to the target prediction parameter and the corrosion rate prediction model;

[0017] Determine the remaining wall thickness in future years at each location of the gas well to be evaluated based on the corrosion rates in future years;

[0018] Based on the minimum remaining wall thickness in any year and each of the target prediction parameters, calculate the safety factor against internal pressure and the safety factor against external collapse to determine the remaining life of the pipe string to be predicted and issue a warning message when the pipe string reaches its life;

[0019] A corrosion sensor, a stress sensor and a temperature sensor are installed on the pipe string, and the early warning information and collected data are transmitted to the terminal by wireless communication technology to monitor the pipe string in real time.

[0020] Furthermore, the process of constructing several target parameters that affect the corrosion rate of the test string using a single parameter change test includes:

[0021] Using high temperature and high pressure autoclave equipment, the weight loss corrosion test of the sample was carried out to determine the corrosion rate of the test column;

[0022] According to the corrosion rate, one target parameter is changed in the test string respectively, and the remaining target parameters are taken as the most extreme value within the research range. The influence of each target parameter on the corrosion rate is evaluated one by one, so as to determine the target parameter that affects the corrosion rate of the test string.

[0023] Furthermore, the process of determining the acid gas partial pressure at each monitoring point according to the pressure and the acid gas proportion includes:

[0024] Determine the molar percentage of the acid gas in the mixed gas by experiment or chemical analysis;

[0025] Using a pressure gauge to measure the total pressure of the mixed gas, multiplying the molar content percentage of the acidic gas by the total pressure to obtain the partial pressure of the acidic gas;

[0026] Repeat the above steps at each monitoring point in the extension direction of the wellbore to determine the acid gas partial pressure at each point.

[0027] Further, the process of calculating the liquid holdup and the fluid flow pattern of each monitoring point according to the gas-liquid flow rate and the gas-liquid two-phase flow pattern includes:

[0028] The flow rate of the gas-liquid mixture in the wellbore is measured by a flow meter, and the wellhead pressure is reduced, and the gas-liquid flow rate at each monitoring point is calculated according to the inner diameter of the pipe string;

[0029] By collecting the flow data of the gas-liquid mixture in the test column, analyzing the properties of the gas and liquid in the gas-liquid mixture, and measuring the ratio of the volume or mass of the gas phase to the volume or mass of the entire gas-liquid mixture according to the offline instrument, the ratio is used as the gas content;

[0030] Determine the gas-liquid flow pattern at the monitoring point according to the gas-liquid flow rate, fluid properties and gas content of the gas-liquid mixture in the column and with reference to the gas-liquid two-phase flow pattern diagram;

[0031] According to the gas-liquid flow rate and the gas-liquid flow pattern, the liquid holdup and fluid flow pattern of each monitoring point are calculated using multiphase flow PIPESIM software.

[0032] Furthermore, the process of determining the corrosion rate corresponding to each of the monitoring points includes:

[0033] Use electromagnetic flaw detection and logging technology to detect the remaining wall thickness of the wellbore and compare it with the wall thickness detected last time;

[0034] The corrosion rate corresponding to the monitoring point is determined according to the comparison result and the time interval between two detections.

[0035] Furthermore, the process of establishing a corrosion rate prediction model according to the target parameter of each monitoring point and the corrosion rate includes:

[0036] The corrosion target parameter values ​​of each monitoring point are evenly divided and used as training data and test data of the neural network model respectively;

[0037] A neural network prediction method is adopted, the corrosion target parameter value of each monitoring point is used as input, the corrosion rate corresponding to the monitoring point is used as output data, and the training data is used to complete the training of the neural network model;

[0038] The test data is input into the neural network model, and the predicted corrosion rate result output by it is compared with the actual corrosion rate in the test data to ensure that the error is within the standard range. Otherwise, the number of training samples is increased and the neural network model is retrained until the standard range requirements are met, thereby establishing a corrosion rate prediction model.

[0039] Furthermore, the process of determining the corrosion rate in each future year according to the target prediction parameter and the corrosion rate prediction model includes:

[0040] The target prediction parameters are input into the corrosion rate prediction model to determine the corrosion rate in each future year.

[0041] Further, the process of determining the remaining wall thickness in future years at each location of the gas well to be evaluated based on the corrosion rate in future years includes:

[0042] Based on the corrosion rates in the future years, determine the corroded wall thickness values ​​at the corresponding positions in the future;

[0043] According to the current wall thickness at each position of the gas well and the corroded wall thickness value at each corresponding position in the future, the future remaining wall thickness at each position is determined.

[0044] Furthermore, the process of calculating the safety factor against internal pressure and the safety factor against external collapse based on the minimum remaining wall thickness in any year and the target prediction parameters to determine the remaining life of the pipe string to be predicted and issuing early warning information in time when the pipe string reaches its life includes:

[0045] Determine the minimum remaining wall thickness in any year according to the future remaining wall thickness at each position and the corrosion rate in each future year;

[0046] Calculating a safety factor against internal pressure or a safety factor against external collapse according to the minimum remaining wall thickness;

[0047] When the safety factor against internal pressure or the safety factor against external collapse is lower than a target threshold, it is determined that the pipe string life is reached;

[0048] An early warning value is set according to a target threshold value, and an early warning message is triggered when the safety factor against internal pressure or the safety factor against external crushing is lower than the target threshold value.

[0049] Furthermore, the process of using wireless communication technology to transmit the warning information and collected data to the terminal for real-time monitoring of the pipe string includes:

[0050] The data acquisition system is used to collect sensor data, including corrosion degree, formation pressure and temperature;

[0051] Use wireless communication technology or LoRaWAN to transmit sensor data from the data acquisition system to a central server or cloud platform;

[0052] The collected data is stored for integration and analysis to view visual data charts and alarm information of the pipe string status.

[0053] Compared with the prior art, the beneficial effects of the present invention are that a single parameter change test is used to construct several target parameters that affect the corrosion rate of the test string, thereby enhancing the ability to predict the development trend of corrosion and providing a basis for preventive maintenance; a number of monitoring points are set along the extension direction of the wellbore with the wellhead as the starting point and Δh1 as the depth interval, the temperature and pressure of each monitoring point are recorded, and the acid gas partial pressure of each monitoring point is determined according to the pressure and the acid gas ratio, and the test string is used for transmission according to the gas-liquid mixture in the wellbore, and the liquid holdup and fluid flow state of each monitoring point are calculated to provide a more comprehensive corrosion influencing parameter analysis to ensure that all parameters affecting corrosion are considered; the corrosion rate corresponding to each monitoring point is determined by determining the change rate of the wellbore wall thickness of each monitoring point, which is helpful to promote the standardization of corrosion technology in the industry and provide a basis for establishing a corrosion rate prediction model; a corrosion rate prediction model is established according to the target parameters of each monitoring point and the corrosion rate, thereby reducing the need for on-site testing. The system can reduce the dependence on the test, reduce the cost and time consumption; predict the gas production, water production and formation pressure in the future years according to the current parameters of the gas well to be evaluated, determine the target prediction parameters of the gas well to be evaluated in the future years, and determine the corrosion rate of the predicted pipe string in the future years according to the corrosion rate prediction model, evaluate the corrosion risk in the future years, and take preventive measures in time; determine the remaining wall thickness of the gas well to be evaluated at each position in the future years based on the current parameters of the gas well to be evaluated and the corrosion rate in the future years, so as to predict the remaining wall thickness in advance, and then plan predictive maintenance to reduce the need for emergency maintenance; determine the safety factor against internal pressure and the safety factor against external collapse based on the minimum remaining wall thickness in any year and the target prediction parameters, predict the remaining life of the pipe string and issue early warning information in time, so as to effectively improve the accuracy of corrosion prediction; according to the sensors installed on the pipe string, use wireless communication technology to transmit the early warning information and collected data to the terminal for real-time monitoring of the pipe string, so as to realize the dynamic nature of gas well life prediction.

[0054] In particular, the corrosion rate of the test tubing was tested using a high-temperature and high-pressure autoclave, making the experimental results more valuable for practical applications. For the corrosion rate, one corrosion target parameter was changed in the test tubing respectively, and the remaining target parameters were taken as the most extreme values ​​within the research range. The influence of each target parameter on the corrosion rate was evaluated one by one. By identifying the parameters that affect the corrosion target, the corrosion rate can be predicted more effectively, providing data support for the experiment.

[0055] In particular, accurate temperature and pressure data are provided based on electromagnetic flaw detection and logging technology, which provides key parameters for calculating partial pressure bodies. The acid gas partial pressure at each monitoring point is determined by multiplying the molar content percentage by the pressure, which helps to accurately calculate the acid gas content and enhance the accuracy of the tubing string test.

[0056] In particular, by using a test string for transmission based on the gas-liquid mixture in the wellbore and calculating the liquid holdup and fluid flow pattern, the flow behavior and flow problems of the gas-liquid mixture in the string can be more accurately predicted, which helps to optimize production operation parameters.

[0057] In particular, by comparing the two test results, the corrosion rate can be quantified and the severity and development trend of corrosion can be evaluated.

[0058] In particular, a corrosion rate prediction model is established through the target parameters of each monitoring point and the corrosion rate to predict future corrosion rates and help formulate a preventive maintenance plan.

[0059] In particular, determining the corrosion rate in each future year based on the target prediction parameters and the corrosion rate prediction model will help formulate a preventive maintenance plan, improve response speed and flexibility, and enhance market competitiveness.

[0060] In particular, the remaining wall thickness in future years at each location of the gas well to be evaluated is determined based on current parameters and the corrosion rate in future years, so as to prevent corrosion problems in advance and reduce the risk of wellbore failure due to insufficient wall thickness.

[0061] In particular, the safety factor against internal pressure and the safety factor against external collapse are calculated based on the minimum remaining wall thickness in any year, the remaining life of the predicted pipe string is determined, and when the pipe string reaches its life, early warning information is issued in time, thereby ensuring the structural safety of the pipe string and reducing the risk of rupture or failure.

[0062] In particular, the early warning information and collected data are transmitted to the terminal according to the communication technology for real-time monitoring of the pipe string, which can realize the instant transmission of data, ensure that the status information of the pipe string can be received in real time, and respond to possible problems in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A schematic flow chart of a method for dynamically predicting pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0064] Figure 2 A schematic diagram of several target parameter flow charts of a method for dynamically predicting pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0065] Figure 3 A schematic flow chart of the acid gas partial pressure at each monitoring point of the method for dynamically predicting the pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0066] Figure 4 A schematic flow chart of the liquid holdup and fluid flow pattern at each monitoring point of the dynamic prediction method for pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0067] Figure 5 A schematic diagram of a flow chart of determining the corrosion rate corresponding to each monitoring point in a method for dynamically predicting the pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0068] Figure 6 A test result diagram of corrosion rate change of a method for dynamically predicting pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0069] Figure 7 A schematic diagram of a process for establishing a corrosion rate prediction model for a method for dynamically predicting pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0070] Figure 8 A schematic diagram of the process flow of the remaining wall thickness in future years of the method for dynamically predicting the pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0071] Fig. 9 A result diagram of the corrosion rate of a pipe string to be predicted in the method for dynamically predicting the pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0072] Fig.10 A graph of the remaining wall thickness results at various locations of a future gas well to be evaluated according to the method for dynamically predicting the pipe string life based on corrosion logging detection provided by an embodiment of the present invention;

[0073] Fig.11 A schematic diagram of a process of determining that the remaining life of a pipe string to be predicted reaches its life and issuing a warning message in a method for dynamically predicting the life of a pipe string based on corrosion logging detection provided by an embodiment of the present invention;

[0074] Fig.12 A schematic flow chart of a method for dynamically predicting the life of a tubular column based on corrosion logging detection provided in an embodiment of the present invention, which utilizes wireless communication to transmit early warning information and collected data to a terminal for monitoring the tubular column. DETAILED DESCRIPTION

[0075] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0076] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0077] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as a limitation on the present invention.

[0078] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0079] See also Figure 1 As shown, the present invention provides a method for dynamically predicting the life of a pipe string based on corrosion logging detection, the method comprising:

[0080] Step S100, constructing several target parameters that affect the corrosion rate of the test string by using a single parameter change test;

[0081] Step S200, setting a number of monitoring points at depth intervals with the wellhead as the starting point along the extension direction of the wellbore, recording the temperature and pressure of each monitoring point, and determining the acid gas partial pressure at each monitoring point according to the pressure and the acid gas proportion;

[0082] Step S300, calculating the liquid holdup and fluid flow pattern of each monitoring point according to the gas-liquid mixture in the wellbore being transmitted using a test string;

[0083] Step S400, using electromagnetic flaw detection and logging technology to determine the wellbore wall thickness change rate of each monitoring point to determine the corrosion rate corresponding to each monitoring point;

[0084] Step S500, establishing a corrosion rate prediction model using a neural network prediction method according to target parameters of each monitoring point and the corrosion rate;

[0085] Step S600, predicting the gas production, water production and formation pressure in future years according to the current parameters of the gas well to be evaluated, determining the target prediction parameters of the gas well to be evaluated in future years, and determining the predicted pipe string corrosion rate in future years according to the corrosion rate prediction model;

[0086] Step S700, determining the remaining wall thickness of the gas well to be evaluated in the future year at each position based on the current parameters of the gas well to be evaluated and the corrosion rate in the future year;

[0087] Step S800, calculating the safety factor against internal pressure and the safety factor against external collapse based on the minimum remaining wall thickness in any year and each of the target prediction parameters to determine the remaining life of the pipe string to be predicted and issuing a warning message when the pipe string reaches its life;

[0088] Step S900: Install a corrosion sensor, a stress sensor and a temperature sensor on the pipe string, and use wireless communication technology to transmit the warning information and collected data to the terminal to monitor the pipe string in real time.

[0089] Specifically, the embodiment of the present invention uses a single parameter change test to construct several target parameters that affect the corrosion rate of the test string, thereby enhancing the ability to predict the development trend of corrosion and providing a basis for preventive maintenance; a number of monitoring points are set along the extension direction of the wellbore with the wellhead as the starting point and Δh1 as the depth interval, the temperature and pressure of each monitoring point are recorded, and the acid gas partial pressure of each monitoring point is determined according to the pressure and the acid gas ratio, and the test string is used for transmission according to the gas-liquid mixture in the wellbore, and the liquid holdup and fluid flow state of each monitoring point are calculated to provide a more comprehensive corrosion influencing parameter analysis to ensure that all parameters affecting corrosion are considered; the wellbore wall thickness change rate of each monitoring point is determined to determine the corrosion rate corresponding to each monitoring point, which is helpful to promote the standardization of corrosion technology in the industry and provide a basis for establishing a corrosion rate prediction model; a corrosion rate prediction model is established according to the target parameters and the corrosion rate of each monitoring point, thereby reducing dependence on field testing, Reduce costs and time consumption; predict the gas production, water production and formation pressure in future years according to the current parameters of the gas well to be evaluated, determine the target prediction parameters of the gas well to be evaluated in future years, and determine the predicted pipe corrosion rate in future years according to the corrosion rate prediction model, evaluate the corrosion risk in future years, and take preventive measures in time; determine the remaining wall thickness of the gas well to be evaluated at each position in future years based on the current parameters of the gas well to be evaluated and the corrosion rate in future years, so as to predict the remaining wall thickness in advance and then plan predictive maintenance to reduce the need for emergency maintenance; determine the safety factor against internal pressure and the safety factor against external squeeze based on the minimum remaining wall thickness in any year and the target prediction parameters, predict the remaining life of the pipe and issue early warning information in time, so as to effectively improve the accuracy of corrosion prediction; according to the sensors installed on the pipe, use wireless communication technology to transmit the early warning information and collected data to the terminal for real-time monitoring of the pipe to achieve the dynamic nature of gas well life prediction.

[0090] See also Figure 2 As shown in FIG. 1 , the process of constructing several target parameters that affect the corrosion rate of the test string using a single parameter change test includes:

[0091] Step S110, using a high temperature and high pressure autoclave device to conduct a weight loss corrosion experiment on a sample to determine the corrosion rate of the test column;

[0092] Step S120, according to the corrosion rate, one target parameter is changed in the test string respectively, the remaining target parameters are taken as the most extreme value within the research range, and the influence of each target parameter on the corrosion rate is evaluated one by one, so as to determine that the target parameters that affect the corrosion rate of the test string are acid gas partial pressure, wellbore temperature, liquid holdup, and fluid flow state.

[0093] Specifically, the corrosion rate of the test string is tested using a high-temperature autoclave as described in the embodiment of the present invention, so that the experimental results have more practical application value. For the corrosion rate, one corrosion target parameter is changed in the test string respectively, and the remaining target parameters are taken as the most extreme value within the research range. The influence of each target parameter on the corrosion rate is evaluated one by one. By identifying the parameters that affect the corrosion target, the corrosion rate can be more effectively predicted, providing data support for the experiment.

[0094] See also Figure 3 As shown, the process of determining the acid gas partial pressure at each monitoring point according to the pressure and the acid gas proportion includes:

[0095] Step S210, determining the molar content percentage of the acid gas in the mixed gas according to experiments or chemical analysis;

[0096] Step S220, using a pressure gauge or measuring equipment to measure the total pressure of the mixed gas, converting the molar content percentage of the acid gas into a decimal form, and multiplying it by the total pressure to obtain the partial pressure of the acid gas;

[0097] Step S230, repeating the above steps at each monitoring point in the extension direction of the wellbore to determine the acid gas partial pressure at each point.

[0098] Specifically, the embodiment of the present invention provides accurate temperature and pressure data based on electromagnetic flaw detection and logging technology, provides key parameters for calculating the partial pressure body, and uses the molar content percentage multiplied by the pressure to determine the acid gas partial pressure at each monitoring point, which helps to accurately calculate the acid gas content and enhance the accuracy of the tubing string test.

[0099] See also Figure 4 As shown, the process of calculating the liquid holdup and fluid flow pattern of each monitoring point according to the gas-liquid flow rate and the gas-liquid two-phase flow pattern includes:

[0100] Step S310, using a flow meter to measure the flow of the gas-liquid mixture in the wellbore, and reducing the wellhead pressure, and calculating the gas-liquid flow rate at each monitoring point according to the inner diameter of the pipe string;

[0101] Step S320, by collecting the gas-liquid mixture flow data in the test string, analyzing the properties of the gas and liquid in the gas-liquid mixture, and measuring the ratio of the volume or mass of the gas phase to the volume or mass of the entire gas-liquid mixture by an offline instrument, the ratio is used as the gas content;

[0102] Step S330, determining the gas-liquid flow pattern at the monitoring point according to the gas-liquid flow rate, fluid properties and gas content of the gas-liquid mixture in the column and with reference to a gas-liquid two-phase flow pattern diagram;

[0103] Step S340, according to the gas-liquid flow pattern, the multiphase flow PIPESIM software is used to calculate the liquid holdup and fluid flow pattern of each monitoring point.

[0104] Specifically, the embodiments of the present invention use a test string to transmit the gas-liquid mixture in the wellbore, calculate the liquid holdup and fluid flow pattern, and more accurately predict the flow behavior and flow problems of the gas-liquid mixture in the string, which helps to optimize production operation parameters.

[0105] See also Figure 5 As shown, the process of determining the corrosion rate corresponding to each of the monitoring points includes:

[0106] Step S410, using electromagnetic flaw detection and logging technology to detect the remaining wall thickness of the wellbore and compare it with the wall thickness detected last time;

[0107] Step S420, determining the corrosion rate corresponding to the monitoring point according to the result comparison and the time interval between two detections.

[0108] Specifically, electromagnetic flaw detection and logging technology is used to obtain the current wellbore oil pipe wall thickness, and compared with the last wall thickness test result (one and a half years ago), the wall thickness loss rate at different wellbore depths is obtained according to the time interval between the two tests, that is, the corrosion rate. The data unit is mm / year. Starting from the wellhead depth 0, 1m is used as the depth interval (in m) to determine the wall thickness thinning value point and the corrosion rate value point. The corrosion rate is between 0.08-0.52mm / a, with an average of 0.29mm / a. The test results are as follows: Figure 6 .

[0109] Specifically, the embodiments of the present invention can quantify the corrosion rate and evaluate the severity and development trend of corrosion by comparing the results of two tests.

[0110] See also Figure 7 As shown, the process of establishing a corrosion rate prediction model according to the target parameters of each monitoring point and the corrosion rate includes:

[0111] Step S510, dividing the corrosion target parameter values ​​of each monitoring point into two groups, which are used as training data and test data of the neural network model respectively;

[0112] Step S520, using a neural network prediction method, taking the corrosion target parameter value of each monitoring point as input, taking the corrosion rate corresponding to the monitoring point as output data, and using the training data to complete the training of the neural network model;

[0113] Step S530, input the neural network model according to the test data, compare the predicted corrosion rate result output by it with the actual corrosion rate in the test data, ensure that the error is within the standard range, otherwise increase the number of training samples, retrain the neural network model until it meets the standard range requirements, thereby establishing a corrosion rate prediction model.

[0114] Specifically, the parameters of the main controlling factors of corrosion at different wellbore depths are divided into two parts, which are used as neural network training data and test data as shown in Tables 1 and 2.

[0115] Table 1 BP neural network model training samples

[0116]

[0117]

[0118] The main corrosion influencing parameters at different wellbore depths, gas partial pressure, wellbore temperature, liquid holdup, and flow state are used as input data. In this example, 14 groups of data are randomly selected, and the corrosion rate values ​​obtained by logging at the corresponding depths are used as output data. The data are input into the neural network model, and the BP neural network parameters are set to realize the training of data samples. The S-type function is used to establish the transformation function between units, and the nonlinear mapping relationship between the main corrosion influencing parameters and the corrosion rate values ​​at the corresponding depths is established to complete the training of all input data. The training sample results are shown in Table 1.

[0119] Table 2 BP neural network model test results

[0120]

[0121] The trained neural network model was verified using test data. The model parameters were continuously corrected until the expected prediction accuracy requirements were met. Five groups of corrosion main influencing parameter data were randomly selected at different wellbore depths as verification data and input into the trained BP neural network model. The model predicted corrosion rate results were compared with the actual corrosion rate of the test samples. The results are shown in Table 2. The error is within 20%, which meets the requirements of engineering applications. Otherwise, it is necessary to adjust the network parameters or further increase the number of training samples to retrain the neural network model until the accuracy requirements are met.

[0122] Specifically, in the embodiment of the present invention, a corrosion rate prediction model is established through the target parameters of each monitoring point and the corrosion rate to predict the future corrosion rate and help formulate a preventive maintenance plan.

[0123] Specifically, the embodiment of the present invention determines the corrosion rate in each future year by inputting the target prediction parameter into the corrosion rate prediction model.

[0124] Specifically, in the embodiment of the present invention, the corrosion rate of each future year is determined according to the target prediction parameter and the corrosion rate prediction model, which helps to formulate a preventive maintenance plan, improve response speed and flexibility, and enhance market competitiveness.

[0125] See also Figure 8 As shown, the process of determining the remaining wall thickness in the future years at each location of the gas well to be evaluated based on the corrosion rate in the future years includes:

[0126] Step S610, based on the corrosion rate in each future year, determining the corroded wall thickness value at each corresponding position in the future;

[0127] Step S620, determining the future remaining wall thickness of each position according to the current wall thickness of each position of the gas well and the corroded wall thickness value of each corresponding position in the future.

[0128] Specifically, the gas production, water production and formation pressure in the next 1-5 years are predicted based on the current parameters of the gas well to be evaluated, as shown in Table 3, and the values ​​of the main corrosion influencing factors of the gas well to be evaluated in the next 1-5 years, such as gas partial pressure, wellbore temperature, liquid holdup, and fluid flow state, are determined, and the corrosion rate prediction model is input to determine the predicted pipe string corrosion rate in 1-5 years, as shown in Table 3. Fig. 9 According to the predicted corrosion rate of the pipe column in 1-5 years, the corroded wall thickness value of each corresponding position in the future is determined. According to the wall thickness of each position of the gas well to be evaluated at present minus the corroded value of each corresponding position in the future, the remaining wall thickness of each position of the gas well to be evaluated is determined, such as Fig.10 .

[0129] Table 3 Parameter forecast for the next 1-5 years

[0130]

[0131] Specifically, in the embodiment of the present invention, the future remaining wall thickness of each position of the gas well to be evaluated is determined based on the current wall thickness of each position of the gas well to be evaluated minus the corrosion value of each corresponding position in the future.

[0132] Specifically, in the embodiment of the present invention, the remaining wall thickness in future years at each location of the gas well to be evaluated is determined according to the current parameters and the corrosion rate in future years, so as to prevent corrosion problems in advance and reduce the risk of wellbore failure due to insufficient wall thickness.

[0133] See also Fig.11 As shown, the process of calculating the safety factor against internal pressure and the safety factor against external collapse based on the minimum remaining wall thickness in any year and each of the target prediction parameters to determine the remaining life of the pipe string to be predicted and issuing an early warning message when the pipe string reaches its life includes:

[0134] Step S710, determining the minimum remaining wall thickness in any year according to the future remaining wall thickness at each position and the corrosion rate in each future year;

[0135] Step S720, calculating the safety factor against internal pressure or the safety factor against external collapse according to the minimum remaining wall thickness;

[0136] Step S730, when the safety factor against internal pressure or the safety factor against external collapse is lower than the target threshold of 1.5, it is determined that the pipe string life is reached;

[0137] Step S740, setting a warning value of 1.5 according to the target threshold, and triggering a warning message when the safety factor against internal pressure or the safety factor against external crushing is lower than the target threshold of 1.5.

[0138] Specifically, in the embodiment of the present invention, the internal pressure value of the pipe string and the internal pressure resistance strength of the pipe string are calculated to obtain the internal pressure resistance safety factor.

[0139] Column internal pressure value:

[0140]

[0141] Among them, p smax is the upper limit of the pressure in the pipe, in MPa; G is the specific gravity of natural gas; h v The vertical depth of the wellbore calculation point, in m; H is the vertical depth of the wellbore, in m.

[0142] Pipe string internal pressure resistance strength:

[0143]

[0144] Among them, [p i ] is the internal pressure strength, unit is MPa; k t The deviation coefficient of the wellbore wall thickness is taken as 0.875; f ymn is the minimum yield strength of the pipe material, in MPa; t cmin is the minimum remaining wall thickness, in mm; D cmax It is the maximum measured outer diameter in mm.

[0145] Safety factor against internal pressure:

[0146] S i =[p i ] / p i

[0147] Specifically, in the embodiment of the present invention, the absolute external extrusion pressure and the external extrusion resistance strength of the casing are calculated to obtain the external extrusion resistance safety factor.

[0148] Safety factor against external collapse:

[0149] S o =[p o ] / p o

[0150] Among them, S o is the safety factor against external collapse, [p o ] is the casing anti-external collapse strength, p o External extrusion pressure, which is divided into absolute external extrusion pressure and effective external extrusion pressure;

[0151] The absolute external extrusion pressure calculation formula is:

[0152] p o =p oh +0.00981ρ c h v

[0153] Among them, p o is the external extrusion pressure, unit: MPa, p oh is the annular pressure outside the wellbore, unit: MPa, ρ c is the density of the formation water outside the wellbore, taken as 1.05 g / cm 3

[0154] The calculation formula for the minimum operating pressure of the wellbore is:

[0155]

[0156] Among them, p i ' is the minimum pressure in the pipe, unit: MPa; p smin is the minimum operating pressure of the wellbore, in MPa;

[0157] The calculation formula of effective external pressure is:

[0158] p oe =p o -p′ i

[0159] Among them, p oe It is the effective external extrusion pressure, unit is MPa.

[0160] Specifically, in the embodiment of the present invention, the safety factor against internal pressure and the safety factor against external collapse are calculated based on the minimum remaining wall thickness in any year, the remaining life of the pipe string to be predicted is determined, and when the pipe string reaches its life, early warning information is issued in time, thereby ensuring the structural safety of the pipe string and reducing the risk of rupture or failure.

[0161] See also Fig.12 As shown, the process of using wireless communication technology to transmit the warning information and collected data to the terminal for real-time monitoring of the pipe string includes:

[0162] Step S810, using a data acquisition system to collect sensor data, the sensor data including corrosion degree, formation pressure and temperature;

[0163] Step S820, using wireless communication technology or LoRaWAN to transmit sensor data from the data acquisition system to a central server or cloud platform;

[0164] Step S830, storing the collected data for integration and analysis to view the visualized data chart and alarm information of the pipe string status.

[0165] Specifically, the embodiment of the present invention transmits the warning information and collected data to the terminal for real-time monitoring of the pipe string according to the communication technology, which can realize the instant transmission of data, ensure that the status information of the pipe string can be received in real time, and respond to possible problems in time.

[0166] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0167] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for dynamic prediction of pipe string life based on corrosion logging detection, characterized in that: include: A single parameter change test is used to construct several target parameters that affect the corrosion rate of the test string, wherein the target parameters include temperature, acid gas partial pressure, liquid holdup and fluid flow state; Taking the wellhead as the starting point along the extension direction of the wellbore, a number of monitoring points are set at depth intervals, the temperature and pressure of each monitoring point are recorded, and the acid gas partial pressure at each monitoring point is determined according to the pressure and the acid gas proportion; The gas-liquid mixture in the wellbore is transmitted using a test pipe string, and the gas-liquid flow rate at each monitoring point is calculated according to the inner diameter of the test pipe string, the wellhead pressure, and the total production of the gas-liquid mixture in the wellbore; Determining the gas-liquid two-phase flow pattern of the gas-liquid mixture at the monitoring point according to the transmission position of the gas-liquid mixture in the test string; Calculating the liquid holdup and fluid flow pattern of each monitoring point according to the gas-liquid flow rate and the gas-liquid two-phase flow pattern; Using electromagnetic flaw detection and logging technology to determine the change rate of the wellbore wall thickness at each of the monitoring points to determine the corrosion rate corresponding to each of the monitoring points; A corrosion rate prediction model is established using a neural network prediction method according to target parameters of each monitoring point and the corrosion rate; A pipe string to be predicted is arranged in the gas well to be evaluated, wherein the pipe string to be predicted is used to transport the gas-liquid mixture in the gas well to be evaluated; Predicting the gas production, water production and formation pressure in future years based on the current parameters of the gas well to be evaluated, so as to determine the target prediction parameters of the gas well to be evaluated in future years according to the pressure at each position of the gas well to be evaluated and the total production of gas-liquid mixture; Determining the corrosion rate in each future year according to the target prediction parameter and the corrosion rate prediction model; Determine the remaining wall thickness in future years at each location of the gas well to be evaluated based on the corrosion rates in future years; Based on the minimum remaining wall thickness in any year and each of the target prediction parameters, calculate the safety factor against internal pressure and the safety factor against external collapse to determine the remaining life of the pipe string to be predicted and issue a warning message when the pipe string reaches its life; A corrosion sensor, a stress sensor and a temperature sensor are installed on the pipe string, and the early warning information and collected data are transmitted to the terminal by wireless communication technology to monitor the pipe string in real time.

2. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 1 is characterized in that: The process of constructing several target parameters that affect the corrosion rate of the test string using a single parameter change test includes: Using high temperature and high pressure autoclave equipment, the weight loss corrosion test of the sample was carried out to determine the corrosion rate of the test column; According to the corrosion rate, one target parameter is changed in the test string respectively, and the remaining target parameters are taken as the most extreme value within the research range. The influence of each target parameter on the corrosion rate is evaluated one by one, so as to determine the target parameter that affects the corrosion rate of the test string.

3. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 2 is characterized in that: The process of determining the acid gas partial pressure at each monitoring point according to the pressure and the acid gas proportion includes: Determine the molar percentage of the acid gas in the mixed gas by experiment or chemical analysis; Using a pressure gauge to measure the total pressure of the mixed gas, multiplying the molar content percentage of the acid gas by the total pressure to obtain the partial pressure of the acid gas; Repeat the above steps at each monitoring point in the extension direction of the wellbore to determine the acid gas partial pressure at each point.

4. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 3 is characterized in that: The process of calculating the liquid holdup and fluid flow pattern of each monitoring point according to the gas-liquid flow rate and the gas-liquid two-phase flow pattern comprises: The flow rate of the gas-liquid mixture in the wellbore is measured by a flow meter, and the wellhead pressure is reduced, and the gas-liquid flow rate at each monitoring point is calculated according to the inner diameter of the pipe string; By collecting the flow data of the gas-liquid mixture in the test column, analyzing the properties of the gas and liquid in the gas-liquid mixture, and measuring the ratio of the volume or mass of the gas phase to the volume or mass of the entire gas-liquid mixture according to the off-line instrument, the ratio is used as the gas content; Determine the gas-liquid flow pattern at the monitoring point according to the gas-liquid flow rate, fluid properties and gas content of the gas-liquid mixture in the column and with reference to the gas-liquid two-phase flow pattern diagram; According to the gas-liquid flow rate and the gas-liquid flow pattern, the liquid holdup and fluid flow pattern of each monitoring point are calculated using multiphase flow PIPESIM software.

5. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 4 is characterized in that: The process of determining the corrosion rate corresponding to each of the monitoring points includes: Use electromagnetic flaw detection and logging technology to detect the remaining wall thickness of the wellbore and compare it with the wall thickness detected last time; The corrosion rate corresponding to the monitoring point is determined according to the comparison result and the time interval between two detections.

6. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 5 is characterized in that: The process of establishing a corrosion rate prediction model according to the target parameters of each monitoring point and the corrosion rate comprises: The corrosion target parameter values ​​of each monitoring point are evenly divided and used as training data and test data of the neural network model respectively; A neural network prediction method is adopted, the corrosion target parameter value of each monitoring point is used as input, the corrosion rate corresponding to the monitoring point is used as output data, and the training data is used to complete the training of the neural network model; The test data is input into the neural network model, and the predicted corrosion rate result output by it is compared with the actual corrosion rate in the test data to ensure that the error is within the standard range. Otherwise, the number of training samples is increased and the neural network model is retrained until the standard range requirements are met, thereby establishing a corrosion rate prediction model.

7. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 6 is characterized in that: The process of determining the corrosion rate in each future year according to the target prediction parameter and the corrosion rate prediction model includes: The target prediction parameters are input into the corrosion rate prediction model to determine the corrosion rate in each future year.

8. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 7 is characterized in that: The process of determining the future annual remaining wall thickness at each location of the gas well to be evaluated based on the future annual corrosion rates includes: Based on the corrosion rates in the future years, determine the corroded wall thickness values ​​at the corresponding positions in the future; According to the current wall thickness at each position of the gas well and the corroded wall thickness value at each corresponding position in the future, the future remaining wall thickness at each position is determined.

9. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 8, characterized in that: The process of calculating the safety factor against internal pressure and the safety factor against external collapse based on the minimum remaining wall thickness in any year and the target prediction parameters to determine the remaining life of the pipe string to be predicted and issuing early warning information in time when the pipe string reaches its life includes: Determine the minimum remaining wall thickness in any year according to the future remaining wall thickness at each position and the corrosion rate in each future year; Calculating a safety factor against internal pressure or a safety factor against external collapse according to the minimum remaining wall thickness; When the safety factor against internal pressure or the safety factor against external collapse is lower than a target threshold, it is determined that the pipe string life is reached; An early warning value is set according to a target threshold value, and an early warning message is triggered when the safety factor against internal pressure or the safety factor against external crushing is lower than the target threshold value.

10. The method for dynamic prediction of pipe string life based on corrosion logging detection according to claim 9, characterized in that: The process of using wireless communication technology to transmit the warning information and collected data to the terminal for real-time monitoring of the pipe string includes: The data acquisition system is used to collect sensor data, including corrosion degree, formation pressure and temperature; Use wireless communication technology or LoRaWAN to transmit sensor data from the data acquisition system to a central server or cloud platform; The collected data is stored for integration and analysis to view visual data charts and alarm information of the pipe string status.

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