Oil and gas well production string service life prediction method, device, equipment and medium

Abstract

This application provides a method, apparatus, equipment, and medium for predicting the service life of production tubing in oil and gas wells. The method includes: acquiring downhole environmental parameters of the target oil and gas well, which includes a production tubing; calculating the temperature and pressure fields distributed along the well depth based on the downhole environmental parameters; calculating the triaxial stress state of the production tubing along the well depth using the temperature and pressure fields as boundary conditions and mechanical property parameters, wherein the triaxial stress state includes radial stress, circumferential stress, and axial stress; and inputting the temperature field, triaxial stress state, and corrosion characteristic parameters into a service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth. This improves the accuracy of predicting the service life of production tubing in complex operating environments.

Description

Technical Field

[0001] This application relates to the field of computer-aided engineering technology, and in particular to a method, apparatus, equipment and medium for predicting the service life of oil and gas well production tubing. Background Technology

[0002] In the development of high-temperature, high-pressure oil and gas fields containing carbon dioxide (CO2), the production tubing is a core component that ensures wellbore integrity and long-term safe production. Therefore, predicting the service life of the production tubing is particularly important.

[0003] Currently, the service life prediction of production tubing is based on empirical models. Corrosion rate is calculated using the operating parameters of the production tubing, and the corrosion rate is assumed to be constant or linearly changing. Then, the remaining service life of the tubing is predicted in combination with the initial wall thickness.

[0004] However, existing technologies only consider a single corrosion mechanism, resulting in low accuracy in predicting the service life of production tubing in complex service environments. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, and medium for predicting the service life of oil and gas well production tubing, in order to improve the accuracy of predicting the service life of production tubing in complex service environments.

[0006] In a first aspect, this application provides a method for predicting the service life of oil and gas well production tubing, including:

[0007] Obtain downhole environmental parameters of the target oil and gas well, wherein the oil and gas well includes a production tubing string;

[0008] Based on the downhole environmental parameters, the temperature field and pressure field distributed along the well depth of the oil and gas well are calculated;

[0009] Using the temperature field and pressure field as boundary conditions, the triaxial stress state of the production tubing along the well depth is calculated based on the mechanical property parameters. The triaxial stress state includes radial stress state, circumferential stress state and axial stress state.

[0010] The temperature field, the triaxial stress state, and the corrosion characteristic parameters are input into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

[0011] In one possible implementation, the step of calculating the temperature and pressure fields distributed along the well depth of the oil and gas well based on the downhole environmental parameters includes: establishing a temperature-pressure coupling model based on the wellbore heat transfer equation and multiphase flow theory; and solving the temperature-pressure coupling model using numerical methods based on the downhole environmental parameters to obtain the temperature and pressure fields distributed along the well depth of the oil and gas well.

[0012] In one possible implementation, the step of calculating the triaxial stress state of the tubing string along the well depth using the temperature and pressure fields as boundary conditions and based on mechanical property parameters includes: determining the load conditions of the production tubing string based on the temperature and pressure fields, wherein the load conditions include internal pressure, external pressure, and temperature load; establishing the mechanical equilibrium equation of the production tubing string based on the mechanical property parameters, wherein the mechanical property parameters include material properties and geometric dimensions; and solving the mechanical equilibrium equation based on the load conditions to obtain the triaxial stress state of the production tubing string distributed along the well depth.

[0013] In one possible implementation, the corrosion characteristic parameters include a dynamic corrosion rate determined based on the temperature field and pressure field; correspondingly, the determination of the dynamic corrosion rate includes: calculating the local temperature and carbon dioxide partial pressure at various points along the well depth on the inner wall of the production tubing based on the temperature field and pressure field; and calculating the dynamic corrosion rate using a preset corrosion kinetic model based on the local temperature and carbon dioxide partial pressure.

[0014] In one possible implementation, inputting the temperature field, the triaxial stress state, and corrosion characteristic parameters into a service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth includes: calculating the initial equivalent stress of the production tubing based on the triaxial stress state; determining the functional relationship of continuous thinning of wall thickness over time due to corrosion based on the corrosion characteristic parameters; establishing a coupling relationship in which the equivalent stress of the production tubing dynamically increases with the thinning of the corroded wall thickness; integrating the coupling relationship based on the initial equivalent stress to calculate the time required for the initial equivalent stress to increase to the material failure critical stress, thereby obtaining the service life distribution of the production tubing along the entire well depth.

[0015] In one possible implementation, after inputting the temperature field, the triaxial stress state, and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth, the method further includes: identifying the weak service life sections of the production tubing along the well depth based on the service life distribution; obtaining the location information and corresponding service life of the weak service life sections; and generating management recommendations for the production tubing based on the location information and the service life.

[0016] Secondly, this application provides an oil and gas well production tubing service life prediction device, comprising:

[0017] The acquisition module is used to acquire downhole environmental parameters of the target oil and gas well, wherein the oil and gas well includes a production tubing string;

[0018] The calculation module is used to calculate the temperature field and pressure field distributed along the well depth of the oil and gas well based on the downhole environmental parameters.

[0019] The calculation module is also used to calculate the triaxial stress state of the production tubing along the well depth based on the mechanical property parameters, using the temperature field and pressure field as boundary conditions, wherein the triaxial stress state includes radial stress state, circumferential stress state and axial stress state.

[0020] The input module is used to input the temperature field, the triaxial stress state, and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

[0021] Thirdly, this application provides an oil and gas well production string service life prediction device, including: a memory and a processor;

[0022] The memory stores computer-executed instructions;

[0023] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0024] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible embodiments of the first aspect.

[0025] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0026] The method, apparatus, equipment, and medium for predicting the service life of oil and gas well production tubing provided in this application acquire temperature and pressure field data through downhole environmental parameters; calculate the triaxial stress state based on mechanical property parameters; and obtain the service life distribution of the production tubing along the entire well depth through the triaxial stress state, temperature field, and corrosion characteristic parameters. By coupling the temperature field, pressure field, triaxial stress state, and corrosion characteristics for analysis, the limitations of single-parameter prediction are overcome, improving the accuracy of predicting the service life of production tubing in complex operating environments. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0028] Figure 1A schematic diagram illustrating a scenario for the method of predicting the service life of oil and gas well production tubing provided in this application embodiment;

[0029] Figure 2 A flowchart illustrating a method for predicting the service life of oil and gas well production tubing provided in one embodiment of this application;

[0030] Figure 3 A schematic diagram of another method for predicting the service life of oil and gas well production tubing provided in an embodiment of this application;

[0031] Figure 4 A well depth distribution map showing the pressure distribution inside and outside the production tubing string, provided for an embodiment of this application;

[0032] Figure 5 A temperature and corrosion rate distribution diagram along well depth for a production tubing string provided in this application embodiment;

[0033] Figure 6 A diagram showing the distribution of axial force along well depth in a production tubing string, provided as an embodiment of this application;

[0034] Figure 7 A diagram showing the service life distribution of a production tubing string along well depth, provided for an embodiment of this application;

[0035] Figure 8 A schematic diagram of the service life prediction device for oil and gas well production tubing provided in this application embodiment;

[0036] Figure 9 A schematic diagram of the structure of the oil and gas well production tubing service life prediction device provided in the embodiments of this application.

[0037] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0038] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0039] Currently, in the development of CO2-containing high-temperature and high-pressure oil and gas fields, the production tubing is a core component ensuring wellbore integrity and long-term safe production. These wells are typically located in deep oil and gas reservoirs, deep-sea oil and gas fields, or unconventional oil and gas resource development scenarios, where the downhole environment is significantly complex and extreme. Specifically, downhole temperatures can reach 120-200°C, pressures range from 30-100 MPa, and the fluids are rich in corrosive media. During long-term service, the production tubing not only needs to withstand internal and external pressures, axial forces, and thermal stress caused by temperature changes, but also suffers from wall thinning or even perforation failure due to electrochemical corrosion. This failure risk under the coupled effects of multiple factors directly relates to the operational reliability, maintenance costs, and environmental risks of oil and gas wells. Existing life prediction methods are based on empirical models, calculating corrosion rates using the operating parameters of the production tubing and assuming a constant or linearly changing corrosion rate, then combining this with the initial wall thickness to predict the remaining life of the tubing. However, these methods only consider a single corrosion mechanism, resulting in low accuracy in predicting the service life of the production tubing in complex operating environments.

[0040] The method for predicting the service life of oil and gas well production tubing provided in this application was developed by the inventors through analysis of multiple tubing failure cases. They discovered that existing methods suffer from prediction bias due to neglecting the coupling of multiple physical fields. This method obtains temperature and pressure field data based on downhole environmental parameters; calculates the triaxial stress state based on mechanical property parameters; and obtains the service life distribution of the production tubing along the entire well depth using the triaxial stress state, temperature field, and corrosion characteristic parameters. By coupling the temperature field, pressure field, triaxial stress state, and corrosion characteristics, the accuracy of predicting the service life of production tubing in complex operating environments is improved.

[0041] Figure 1 This is a schematic diagram illustrating a scenario for the method of predicting the service life of oil and gas well production tubing provided in the embodiments of this application, such as... Figure 1 As shown, the scene is a computer device, including: a receiving device 101, a processor 102 and a display device 103.

[0042] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the method for predicting the service life of oil and gas well production tubing. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or split some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0043] In the specific implementation process, the receiving device 101 can be an input / output interface or a communication interface, which can acquire the downhole environmental parameters of the target oil and gas well.

[0044] The processor 102 can process the downhole environmental parameters of the target oil and gas well to determine the service life distribution of the production tubing along the entire well depth.

[0045] The display device 103 can be used to display the service life distribution of the production tubing along the entire well depth.

[0046] The display device can also be a touch screen, used to receive user commands while displaying the above content, so as to achieve interaction with the user.

[0047] It should be understood that the aforementioned processor can be implemented by reading instructions from memory and executing those instructions, or it can be implemented through chip circuitry.

[0048] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0049] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0050] Figure 2 This is a flowchart illustrating a method for predicting the service life of an oil and gas well production tubing according to an embodiment of this application. The executing entity in this embodiment can be... Figure 1 The computer equipment shown is not specifically limited in this embodiment. Figure 2 As shown, the method includes:

[0051] S201: Obtain downhole environmental parameters of the target oil and gas well, which includes the production tubing.

[0052] Optionally, downhole environmental parameters may include: wellbore structure, production parameters, formation thermal conductivity, and downhole temperature-pressure profile, etc.

[0053] Optionally, production parameters may include: gas production, water production, and fluid properties, etc.

[0054] S202: Based on downhole environmental parameters, the temperature and pressure fields distributed along the well depth of the oil and gas well are calculated.

[0055] Optionally, based on downhole environmental parameters, the temperature and pressure fields distributed along the well depth of the oil and gas well are calculated, including: based on downhole environmental parameters, using the principles of fluid mechanics and heat transfer, establishing a set of coupled equations describing fluid flow and heat transfer within the wellbore; and using numerical methods to solve the set of coupled equations to obtain the temperature and pressure fields along the well depth.

[0056] Optionally, the temperature and pressure fields distributed along the well depth of the oil and gas well are calculated based on the downhole environmental parameters, including: establishing a temperature-pressure coupling model based on the wellbore heat transfer equation and multiphase flow theory; and solving the temperature-pressure coupling model using numerical methods based on the downhole environmental parameters to obtain the temperature and pressure fields distributed along the well depth of the oil and gas well.

[0057] Alternatively, the numerical method can be the finite difference method.

[0058] Optionally, the wellbore heat transfer equation is a differential equation describing the heat transfer between the wellbore fluid, tubing, annular fluid, casing, and formation.

[0059] Optionally, the temperature-pressure coupling model can refer to a mathematical model that simultaneously considers the mutual influence of fluid flow pressure drop and heat transfer.

[0060] By employing a temperature-pressure coupling model, the accuracy of temperature and pressure field predictions under complex multiphase flow conditions of high temperature and high pressure is ensured, providing reliable input for subsequent stress analysis and corrosion calculations, thereby improving the accuracy of predicting the service life of production tubing in complex service environments.

[0061] Alternatively, the calculation formula for the temperature-pressure coupling model can be:

[0062]

[0063] In the formula, d is the flow velocity of the hot fluid, in m / s; d is the inner diameter of the production tubing, in m; x is the well depth, in m. ρ is the fluid pressure, in MPa; ρ is the fluid density, in MPa. g is the acceleration due to gravity, with units of 1000 m / s. ; r is the formation thermal conductivity, in W / (m∙K); r0 is the outer diameter of the production tubing, in m; r t0 U represents the outer radius of the production tubing, in meters (m). T0 The overall heat transfer coefficient is expressed in W / (m²). 2 • K). θ is the angle between the production tubing axis and the horizontal direction, in degrees; f is the friction coefficient, dimensionless; W is the fluid mass flow rate, in kg / s; c pThe isobaric specific heat capacity of the fluid within the production string, expressed in J / (kg·K); c J T represents the Joule-Thomson coefficient of the fluid, which is dimensionless; ei0 The original formation temperature at the wellbore inlet is expressed in °C; g G This is the gas phase gravity correction factor, which is dimensionless.

[0064] S203: Using temperature and pressure fields as boundary conditions, the triaxial stress state of the production tubing along the well depth is calculated based on mechanical property parameters. The triaxial stress state includes radial stress state, circumferential stress state, and axial stress state.

[0065] Optionally, using temperature and pressure fields as boundary conditions, the triaxial stress state of the production tubing along the well depth is calculated based on mechanical property parameters. This includes: determining the load conditions of the production tubing based on the temperature and pressure fields, including internal pressure, external pressure, and temperature loads; establishing the mechanical equilibrium equations of the production tubing based on its mechanical property parameters, including material properties and geometric dimensions; and solving the mechanical equilibrium equations based on the load conditions to obtain the triaxial stress state of the production tubing distributed along the well depth.

[0066] By determining the load conditions, establishing the mechanical equilibrium equations, and substituting the loads to solve for the stress, the complex stress state of the production tubing downhole is accurately quantified, providing a reliable mechanical basis for life prediction and eliminating stress calculation distortion caused by single load analysis.

[0067] Optionally, the formula for calculating the mechanical equilibrium equation is:

[0068]

[0069] In the formula, σ r0 σ represents the radial stress before corrosion, in MPa. t0 σ represents the circumferential stress before corrosion, in MPa. z0 P represents the axial stress before corrosion, in MPa. o The external pressure of the production tubing is expressed in MPa; P i r represents the internal pressure at the i-th calculated depth point within the production tubing, in MPa. i F represents the inner diameter of the i-th calculated depth point of the production tubing, in meters. a The axial force at the i-th calculated depth point of the production tubing is expressed in N / m.

[0070] Optionally, the load conditions of the production tubing are determined based on the temperature and pressure fields, including: extracting the internal pressure, external pressure, and temperature load at each calculated depth point from the temperature and pressure fields to obtain the load conditions of the production tubing.

[0071] Optionally, the load conditions also include buckling effects.

[0072] Optionally, mechanical property parameters may include material properties and geometric dimensions.

[0073] Optionally, the geometric dimensions include: outer diameter, inner diameter, and wall thickness. Material properties include: elastic modulus, Poisson's ratio, coefficient of thermal expansion, and temperature-dependent yield strength.

[0074] S204: Input the temperature field, triaxial stress state and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

[0075] Optionally, corrosion characteristic parameters include dynamic corrosion rates determined based on temperature and pressure fields.

[0076] Accordingly, the determination of the dynamic corrosion rate includes: calculating the local temperature and carbon dioxide partial pressure at various points along the well depth on the inner wall of the production tubing based on the temperature and pressure fields; and calculating the dynamic corrosion rate using a pre-set corrosion kinetic model based on the local temperature and carbon dioxide partial pressure.

[0077] By calculating local temperature and CO2 partial pressure and substituting them into the corrosion kinetic model, the dynamic and accurate measurement of the corrosion rate of the tubing string was achieved, which closely matches the real-time changing characteristics of the downhole corrosion environment. The modeling of local temperature and pressure and CO2 partial pressure can match the differences in corrosion environment at different well depths and realize the dynamic iteration of corrosion rate.

[0078] Optionally, the preset corrosion kinetic model can be the De Waard-Milliams (DWM) model.

[0079] Optionally, the calculation formula for the corrosion kinetics model is:

[0080]

[0081]

[0082] In the formula, v cor The corrosion rate of the production tubing is expressed in mm / a; T is the temperature of the inner wall of the production tubing, expressed in K. The partial pressure of CO2 inside the production column is expressed in MPa; pH actual This represents the actual pH value of the corrosive liquid phase. t represents the pH value of a liquid phase consisting only of pure water under the same temperature and carbon dioxide partial pressure; t represents the temperature of the inner wall of the production tube, in °C.

[0083] Optionally, the temperature field, triaxial stress state, and corrosion characteristic parameters are input into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth. This includes: calculating the initial equivalent stress of the production tubing based on the triaxial stress state; determining the functional relationship of the continuous thinning of the wall thickness caused by corrosion over time based on the corrosion characteristic parameters; establishing the coupling relationship of the dynamic growth of the equivalent stress of the production tubing as the corrosion wall thickness thins; and integrating the coupling relationship based on the initial equivalent stress to calculate the time required for the initial equivalent stress to grow to the material failure critical stress, thereby obtaining the service life distribution of the production tubing along the entire well depth.

[0084] By calculating the initial equivalent stress, constructing the wall thickness reduction function relationship, establishing the stress-corrosion coupling relationship, and integrating to solve for the service life, a deep coupling between corrosion degradation and stress failure was achieved, the service life effect of the tubing was accurately quantified, and the prediction accuracy of the service life of the production tubing in complex service environments was improved.

[0085] Optionally, the formula for calculating the initial equivalent stress is:

[0086]

[0087] In the formula, σ m0 This represents the initial equivalent stress, expressed in MPa.

[0088] Optionally, the formula for the coupling relationship between the equivalent stress of the production string and the dynamic increase of the corrosion wall thickness is as follows:

[0089]

[0090] In the formula, σ m1 ρ represents the equivalent stress (Mises stress) under the influence of corrosion depth, in MPa; h represents the corrosion depth, in mm.

[0091] Optionally, from the coupling relationship formula, the formula for calculating the dynamic rate of change of equivalent stress is:

[0092]

[0093] In the formula, t0 represents time.

[0094] Optionally, the formula for the rate of change of the service life of the production tubing with respect to equivalent stress can be obtained from the formula for calculating the dynamic change rate of equivalent stress:

[0095]

[0096] In the formula, L c To predict service life; σ tfdenoted as the critical stress for material failure (i.e., the von Mises stress at which the production tubing fails, which can be taken as the yield strength of the production tubing); v0 is the rate of change of corrosion depth with time, v0=dh / dt0. .

[0097] Optionally, by integrating the formula for the rate of change of the service life of the production tubing with equivalent stress, the calculation formula for the service life of the production tubing under uniform corrosion conditions (i.e., the service life prediction integral model) is obtained as follows:

[0098]

[0099] The oil and gas well production string service life prediction method provided in this application obtains temperature and pressure field data based on downhole environmental parameters; calculates the triaxial stress state based on mechanical property parameters; and obtains the service life distribution of the production string along the entire well depth through the triaxial stress state, temperature field, and corrosion characteristic parameters. By coupling the temperature field, pressure field, triaxial stress state, and corrosion characteristics for analysis, the limitations of single-parameter prediction are overcome, improving the accuracy of service life prediction for the production string in complex service environments.

[0100] In one embodiment of this application, based on the above embodiment, after step S204, a process for generating management suggestions for the production tubing is further included, as detailed below:

[0101] Based on the service life distribution, identify the weak service life sections of the production tubing along the well depth.

[0102] Optionally, based on the service life distribution, weak sections of the production tubing along the well depth can be identified, including: comparing and analyzing the service life distribution data across the entire well depth to screen out the section with the shortest service life; and identifying the section with the shortest service life as the weak section.

[0103] Obtain the location information and corresponding service life of the well section with weak service life.

[0104] Optionally, the location information and corresponding service life of the weak well section can be obtained, including: extracting the specific well depth location and corresponding service life duration of the weak well section.

[0105] Based on location information and service life, management recommendations for production tubing are generated.

[0106] Optionally, management recommendations may include string inspection cycles, replacement timing, and protective measures.

[0107] The oil and gas well production string service life prediction method provided in this application identifies well sections with weak service life and generates management suggestions, thereby achieving precise positioning of string risks and refined management and control throughout the entire life cycle, and reducing the risk of downhole string failure.

[0108] In one embodiment of this application, another method for predicting the service life of oil and gas well production tubing is also provided, detailed below:

[0109] Step one involves establishing and solving a multi-field coupled model of the wellbore. This includes establishing a temperature-pressure coupled model based on the downhole environmental parameters of the target oil and gas well and combining fluid mechanics and heat transfer theories. By numerically solving the temperature-pressure coupled model, the temperature and pressure fields distributed along the well depth on the inner and outer walls of the production tubing under production conditions are obtained.

[0110] Optionally, this includes wellbore structure, production regime, and formation parameters.

[0111] Step two involves calculating the triaxial stress state of the production tubing. This includes establishing the mechanical equilibrium equations and deformation compatibility equations of the production tubing, taking temperature and pressure fields as boundary conditions and considering the internal pressure, external pressure, axial force, and contact constraints between the tubing and the wellbore. By solving these equations, the radial, circumferential, and axial stresses distributed along the well depth of the tubing are obtained, representing the triaxial stress state.

[0112] Optionally, the axial force includes self-weight, thermal stress caused by temperature effects, piston effect, and helical buckling effect.

[0113] Step 3: Determine the dynamic corrosion rate field. Based on the temperature and pressure fields, obtain the local temperature and CO2 partial pressure. Combined with the corrosion characteristics of the pipe material, determine the dynamic corrosion rate of the inner wall of the production tubing at each calculated depth along the well depth using a pre-set corrosion rate prediction module. This module outputs the corresponding corrosion rate based on the input local temperature and CO2 partial pressure, effectively reflecting the change in corrosion rate as temperature initially increases and then decreases, and as it increases non-linearly with CO2 partial pressure. The corrosion rate prediction module can be based on a DWM model. The dynamic corrosion rate determined in this step characterizes the wall thickness loss per unit time caused by electrochemical corrosion.

[0114] Alternatively, the partial pressure of CO2 can be calculated from the total pressure and the gas composition.

[0115] Step four involves constructing and solving an integral model for predicting service life. This includes establishing an integral model that uses multiaxial von Mises equivalent stress as a unified metric and dynamically couples the triaxial stress state of the tubing with the corrosion-induced wall thickness reduction process. This integral model directly transforms the continuous wall thickness loss caused by corrosion into a weakening of the tubing's load-bearing cross-section, leading to a dynamic redistribution of the tubing stress state and a continuous increase in equivalent stress. Service life is predicted by tracking the entire process of equivalent stress reaching the material failure threshold.

[0116] Optionally, the construction and solution process of the service life prediction integral model is as follows:

[0117] Based on the triaxial stress state, the initial equivalent stress of the tubular column is calculated. The failure threshold is defined as when the equivalent stress in the tubular wall increases to the material's yield strength.

[0118] Based on the dynamic corrosion rate, the corrosion depth is defined as a function of time, thus obtaining the instantaneous wall thickness that continuously thins over time.

[0119] The instantaneous wall thickness, which decreases continuously over time, is input into the stress analysis model of the tubing column to obtain the coupling relationship between the equivalent stress of the tube wall after corrosion and the corrosion depth (i.e., over time). This coupling relationship clearly expresses how the corrosion process leads to an increase in stress level.

[0120] Based on the coupling relationship, the dynamic rate of change of equivalent stress over time is obtained. The total time required for the initial equivalent stress to grow to the material's critical failure stress is calculated by integration; this time is the predicted service life. By solving this integral equation, a quantitative result of the service life can be obtained.

[0121] The oil and gas well production string service life prediction method provided in this application addresses the problem that existing methods cannot effectively couple complex downhole multi-physics fields, resulting in low prediction accuracy and weak engineering guidance. It creatively integrates triaxial stress analysis, dynamic corrosion process and service life prediction into a unified model, realizing a quantitative and refined assessment of the service life of the string based on conventional engineering parameters.

[0122] Figure 3 This is a schematic diagram illustrating another method for predicting the service life of an oil and gas well production string, provided in an embodiment of this application. Taking a high-temperature, high-pressure CO2-containing gas well (referred to as Well X) as an example, the service life is predicted. Figure 3 As shown, the method includes:

[0123] Step 1: Collect basic parameters of well X: well depth 4335m, production tubing is P110 steel, outer diameter 88.9mm, inner diameter 76mm.

[0124] Step 2: Based on the basic parameters, establish a wellbore temperature-pressure coupling model and solve it numerically to obtain the temperature field and pressure field distributed along the well depth of the oil and gas well. The pressure field can be the distribution of pressure inside and outside the production tubing along the well depth, and the temperature field can be the distribution of temperature of the production tubing along the well depth. Figure 4 A well depth distribution map showing the pressure distribution inside and outside the production tubing provided in this application embodiment, such as... Figure 4 As shown, the vertical axis represents pressure in MPa, and the horizontal axis represents well depth in meters. The figure illustrates the pressure inside the test tubing and the pressure in the wellbore. Figure 5A temperature and corrosion rate distribution diagram along well depth for a production tubing string is provided as an embodiment of this application, such as... Figure 5 As shown, the upper horizontal axis represents temperature in °C, and the lower horizontal axis represents corrosion rate in mm / a. The graph illustrates the relationship between corrosion rate and temperature. Figure 4 and Figure 5 It can be determined that the temperature at the bottom of the well is approximately 155.6°C, the internal pressure is approximately 36.9 MPa, and the external pressure is approximately 33.2 MPa.

[0125] The basic parameters include downhole environmental parameters and mechanical property parameters.

[0126] Step 3: Using the temperature and pressure field as input, and combining the self-weight of the production tubing, internal and external pressure, temperature effect, and the constraint of the packer fixed end, calculate the triaxial stress state of the production tubing along the well depth. Figure 6 This application provides an embodiment of an axial force distribution diagram along well depth for a production tubing string. The horizontal axis represents the axial force in kN, and the vertical axis represents the well depth in meters. Figure 6 It can be seen that the axial stress is the greatest near the wellhead, while the circumferential stress near the bottom of the well is significantly affected by the internal pressure.

[0127] Step 4: Calculate the dynamic corrosion rate using the DWM model. The results are as follows: Figure 5 As shown, the corrosion rate peaks at a depth of approximately 800-900 m (about 0.35 mm / year), consistent with the pattern that CO2 corrosion is most active in this temperature range.

[0128] Step 5: Define the critical stress for material failure as the von Mises stress reaching the yield strength of P110 steel. Based on the triaxial stress state and corrosion rate, establish an integral model for predicting service life.

[0129] Step 6: Input parameters such as triaxial stress and corrosion rate distributed along the well depth into the service life prediction integral model for numerical solution, and obtain the service life distribution curve of the production tubing along the well depth, such as... Figure 7 shown. Figure 7 This application provides a diagram showing the service life distribution of a production tubing string along well depth, with the horizontal axis representing safe service life in years (a) and the vertical axis representing well depth in meters (m). Figure 7 It is known that the shortest service life is about 4.9 years, located near a well depth of 280 m; the longest service life is about 6.4 years, located near a well depth of 3380 m. The service life of the 0-1000m section is generally short and is identified as a weak service life section or a high-risk corrosion section.

[0130] Figure 8 This is a schematic diagram of the structure of the oil and gas well production tubing service life prediction device provided in the embodiments of this application, as shown below. Figure 8As shown, the oil and gas well production tubing service life prediction device provided in this embodiment includes: an acquisition module 801, a calculation module 802, and an input module 803.

[0131] The acquisition module 801 is used to acquire downhole environmental parameters of the target oil and gas well, which includes a production tubing string.

[0132] The calculation module 802 is used to calculate the temperature field and pressure field distributed along the well depth of the oil and gas well based on the downhole environmental parameters.

[0133] The calculation module 802 is also used to calculate the triaxial stress state of the production tubing along the well depth based on the mechanical property parameters, using the temperature field and pressure field as boundary conditions. The triaxial stress state includes the radial stress state, the circumferential stress state and the axial stress state.

[0134] Input module 803 is used to input temperature field, triaxial stress state and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

[0135] In one possible implementation, the calculation module 802 is specifically used to: establish a temperature-pressure coupling model based on the wellbore heat transfer equation and multiphase flow theory; and solve the temperature-pressure coupling model numerically based on downhole environmental parameters to obtain the temperature and pressure fields distributed along the well depth of the oil and gas well.

[0136] In one possible implementation, the calculation module 802 is specifically used to: determine the load conditions of the production tubing based on the temperature field and pressure field, the load conditions including internal pressure, external pressure and temperature load; establish the mechanical equilibrium equation of the production tubing based on the mechanical property parameters of the production tubing, wherein the mechanical property parameters include material properties and geometric dimensions; and solve the mechanical equilibrium equation based on the load conditions to obtain the triaxial stress state of the production tubing distributed along the well depth.

[0137] In one possible implementation, the corrosion characteristic parameters include a dynamic corrosion rate determined based on temperature and pressure fields; correspondingly, the determination of the dynamic corrosion rate is specifically used to: calculate the local temperature and carbon dioxide partial pressure at various points along the well depth on the inner wall of the production tubing based on the temperature and pressure fields; and calculate the dynamic corrosion rate using a preset corrosion kinetic model based on the local temperature and carbon dioxide partial pressure.

[0138] In one possible implementation, the input module 803 is specifically used for: calculating the initial equivalent stress of the production tubing based on the triaxial stress state; determining the functional relationship of the continuous thinning of the wall thickness caused by corrosion over time based on corrosion characteristic parameters; establishing a coupling relationship in which the equivalent stress of the production tubing dynamically increases with the thinning of the corroded wall thickness; and integrating the coupling relationship based on the initial equivalent stress to calculate the time required for the initial equivalent stress to increase to the material failure critical stress, so as to obtain the service life distribution of the production tubing along the entire well depth.

[0139] In one possible implementation, the oil and gas well production string service life prediction device further includes:

[0140] The generation module is used to identify the weak service life sections of the production tubing along the well depth based on the service life distribution; obtain the location information and corresponding service life of the weak service life sections; and generate management suggestions for the production tubing based on the location information and service life.

[0141] The oil and gas well production tubing service life prediction device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0142] Figure 9 A schematic diagram of the structure of the oil and gas well production tubing service life prediction device provided in this application embodiment. Figure 9 As shown, the oil and gas well production tubing service life prediction device provided in this embodiment includes at least one processor 901 and a memory 902. Optionally, the device also includes a communication component 903. The processor 901, memory 902, and communication component 903 are connected via a bus 904.

[0143] In a specific implementation, at least one processor 901 executes computer execution instructions stored in memory 902, causing at least one processor 901 to perform the above-described method.

[0144] The specific implementation process of processor 901 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0145] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0146] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0147] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0148] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0149] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0150] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0151] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0152] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0153] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0155] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0156] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0157] Finally, it should be noted that other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and alterations may be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for predicting the service life of an oil and gas well production tubing string, characterized in that, include: Obtain downhole environmental parameters of the target oil and gas well, wherein the oil and gas well includes a production tubing string; Based on the downhole environmental parameters, the temperature field and pressure field distributed along the well depth of the oil and gas well are calculated; Using the temperature field and pressure field as boundary conditions, the triaxial stress state of the production tubing along the well depth is calculated based on the mechanical property parameters. The triaxial stress state includes radial stress state, circumferential stress state and axial stress state. The temperature field, the triaxial stress state, and the corrosion characteristic parameters are input into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

2. The method of claim 1, wherein, The calculation of the temperature and pressure fields distributed along the well depth of the oil and gas well based on the downhole environmental parameters includes: Based on the wellbore heat transfer equation and multiphase flow theory, a temperature-pressure coupling model is established; Based on the downhole environmental parameters, the temperature-pressure coupling model is solved numerically to obtain the temperature and pressure fields distributed along the well depth of the oil and gas well.

3. The method of claim 1, wherein, The calculation of the triaxial stress state of the oil and gas well tubing along the well depth, using the temperature and pressure fields as boundary conditions and based on mechanical property parameters, includes: Based on the temperature and pressure fields, the load conditions of the production tubing are determined, including internal pressure, external pressure, and temperature load. Based on the mechanical property parameters of the production tubing, a mechanical equilibrium equation for the production tubing is established, wherein the mechanical property parameters include material properties and geometric dimensions; Solve the mechanical equilibrium equations based on the load conditions to obtain the triaxial stress state of the production tubing distributed along the well depth.

4. The method of claim 1, wherein, The corrosion characteristic parameters include the dynamic corrosion rate determined based on the temperature field and pressure field; Accordingly, the determination of the dynamic corrosion rate includes: Based on the temperature and pressure fields, calculate the local temperature and carbon dioxide partial pressure at various points along the well depth on the inner wall of the production tubing; The dynamic corrosion rate is calculated using a preset corrosion kinetic model based on the local temperature and carbon dioxide partial pressure.

5. The method of claim 1, wherein, The step of inputting the temperature field, the triaxial stress state, and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth includes: Based on the triaxial stress state, the initial equivalent stress of the production tubing is calculated; Based on the corrosion characteristic parameters, the functional relationship of continuous thinning of wall thickness over time due to corrosion is determined; Establish the coupling relationship between the equivalent stress of the production tubing and the dynamic increase of the corrosion wall thickness; Based on the initial equivalent stress, the coupling relationship is integrated to calculate the time required for the initial equivalent stress to grow to the material failure critical stress, so as to obtain the service life distribution of the production tubing along the entire well depth.

6. The method according to any one of claims 1 to 5, characterized in that, After inputting the temperature field, the triaxial stress state, and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth, the method further includes: Based on the service life distribution, identify the weak service life sections of the production tubing along the well depth; Obtain the location information and corresponding service life of the well section with the weak service life; Based on the location information and the service life, management recommendations for the production tubing are generated.

7. An apparatus for predicting the service life of a production string of a hydrocarbon well, characterized in that, include: The acquisition module is used to acquire downhole environmental parameters of the target oil and gas well, wherein the oil and gas well includes a production tubing string; The calculation module is used to calculate the temperature field and pressure field distributed along the well depth of the oil and gas well based on the downhole environmental parameters. The calculation module is also used to calculate the triaxial stress state of the production tubing along the well depth based on the mechanical property parameters, using the temperature field and pressure field as boundary conditions, wherein the triaxial stress state includes radial stress state, circumferential stress state and axial stress state. The input module is used to input the temperature field, the triaxial stress state, and corrosion characteristic parameters into the service life prediction integral model to obtain the service life distribution of the production tubing along the entire well depth.

8. An apparatus for predicting service life of a production string of a hydrocarbon well, the apparatus comprising: include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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