Real-time calculation and safety evaluation method and system for three-dimensional stress field of underground tubular column

Abstract

The invention relates to the field of a stress calculation method of an underground pipe column, in particular to a three-dimensional stress field real-time calculation and safety evaluation method and system of the underground pipe column, and the method comprises the steps: collecting underground multi-source data; three-dimensional stress calculation is carried out on the basis that the tubular column material is isotropic and the stress-strain relation conforms to the linear elasticity theory; correcting a safety assessment result by taking the yield strength as a constraint condition, calculating thermal stress according to the temperature change values of the well bottom and the well mouth, and correcting the total stress; radial stress is corrected by combining radial pressure difference caused by internal pressure and external pressure, thermal stress is corrected in real time according to temperature change values of a well bottom and a well mouth, corrosion rate is calculated according to change of corrosive gas content, and a stress distribution result is corrected; and performing risk grading and early warning according to the relationship between the total stress and the yield strength. According to the method, precise modeling and calculation are carried out on the superimposed effect of stress in different directions, and the calculation precision is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of stress calculation methods for downhole tubing, specifically to a method and system for real-time calculation and safety assessment of the three-dimensional stress field of downhole tubing. Background Technology

[0002] In oil and gas extraction, geothermal development, and deep underground engineering, downhole tubing serves as the core channel connecting surface equipment to underground reservoirs. Its structural integrity directly impacts operational safety, production efficiency, and economic costs. Operating long-term in extreme environments of high temperature, high pressure, corrosive fluids, and complex geological stresses, tubing is susceptible to deformation, rupture, or failure due to external loads, internal pressure fluctuations, temperature changes, or material fatigue. This can lead to major accidents such as leaks, blowouts, and equipment damage, resulting in resource waste, environmental pollution, and the risk of personal injury. Therefore, accurately assessing the mechanical state of downhole tubing and predicting its stress distribution and deformation behavior are crucial technical requirements for ensuring operational safety, optimizing design parameters, and extending service life.

[0003] Improving gas well safety is the primary goal, but economic efficiency must also be considered to avoid increased costs due to over-design or frequent maintenance. Scientifically assessing the integrity of the downhole tubing, optimizing operating parameters, and extending equipment life are key to achieving this goal. The following issues exist in downhole tubing stress assessment: The three-dimensional stress distribution is highly complex and involves multi-directional stress. Specifically, the downhole tubing is subjected to the combined effects of axial stress (tension / compression), radial stress (internal and external pressure difference), and circumferential stress (circumferential pressure). Coupling effect: Stresses in different directions superimpose to form a complex three-dimensional stress field, which is difficult to calculate accurately using traditional methods.

[0004] Material properties have a significant impact. The elastic modulus and Poisson's ratio determine the deformation characteristics of the tubing string under stress. Yield strength and sulfur resistance affect the load-bearing capacity and corrosion resistance of the tubing string under extreme conditions. The coefficient of thermal expansion may lead to thermal stress effects when there is a large temperature gradient between the bottom of the well and the wellhead.

[0005] Dynamic changes in operating parameters, large pressure fluctuations, and changes in oil pressure during production can alter the stress state of the tubing string; large temperature gradients, where the temperature difference between the well bottom and wellhead can trigger thermal expansion and contraction; and numerous variations in gas composition, with changes in the content of components such as hydrogen sulfide and carbon dioxide affecting the corrosion rate. Summary of the Invention

[0006] The present invention aims to provide a method and system for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string, in order to solve the problem that the three-dimensional stress distribution is highly complex and difficult to calculate using traditional methods.

[0007] According to one aspect of the present invention, a method for real-time calculation of the three-dimensional stress field and safety assessment of a downhole tubing string is provided, comprising the following: S100 collects multi-source data from downhole and performs data preprocessing on the multi-source data, which includes downhole sensor data, surface monitoring data, and historical data. Also includes: S200, based on the isotropic nature of the tubular material and the fact that the stress-strain relationship conforms to the linear elastic theory, performs three-dimensional stress calculations; S300 corrects radial stress by combining the radial pressure difference caused by internal and external pressure, corrects thermal stress in real time based on the temperature change between the bottom of the well and the wellhead, calculates the corrosion rate based on the change in corrosive gas content, and corrects the stress distribution results. S400 uses yield strength as a constraint to correct the safety assessment results, calculates thermal stress based on the temperature change between the bottom of the well and the wellhead, and corrects the total stress. S500 is used for risk classification and early warning based on the relationship between total stress and yield strength of S400.

[0008] The beneficial effects of this plan are: Simultaneously considering the combined effects of axial stress (tension / compression), radial stress (internal and external pressure difference), and circumferential stress (circumferential pressure), a complete three-dimensional stress field model was constructed. A coupling effect processing mechanism was introduced to accurately model and calculate the superposition effect of stresses in different directions, significantly improving the calculation accuracy.

[0009] Furthermore, in step S200, the three-dimensional stress calculation includes axial stress, radial stress, and circumferential stress, and the formula for calculating the axial stress is: ; The formula for calculating the radial stress is: ; The formula for calculating the circumferential stress is: ; Where E is the elastic modulus of the material, and v is Poisson's ratio. , , These represent the strains in the axial, radial, and circumferential directions, respectively.

[0010] Furthermore, in S400, the security assessment result is expressed as follows: Safety factor = ; in, Yield strength; The formula for calculating thermal stress is: ; in, The coefficient of thermal expansion is This represents the temperature change value. The correction formula for the total stress is: .

[0011] Furthermore, in S300, the correction formula for the radial stress is: ; in, Radial pressure difference; The thermal stress correction is modified based on the collected temperature distribution data. ; The corrosion rate is expressed as: ; Where k, α, and β are empirical constants. , Gas concentration; The circumferential stress distribution result is expressed as follows: ; in, t represents the initial wall thickness; t represents time. Let be the inner radius.

[0012] Furthermore, in S200, the three-dimensional stress field is numerically simulated using finite element analysis.

[0013] According to another aspect of the present invention, a system for real-time calculation and safety assessment of three-dimensional stress field of downhole tubing is provided, comprising at least one processor and a memory communicatively connected to the at least one processor, the memory storing a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for real-time calculation and safety assessment of three-dimensional stress field of downhole tubing as described above. Attached Figure Description

[0014] Figure 1 This is a schematic block diagram illustrating an embodiment of the method for real-time calculation of three-dimensional stress field and safety assessment of downhole tubing according to the present invention; Figure 2 This is a flowchart illustrating an embodiment of the method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string according to the present invention. Detailed Implementation

[0015] The following detailed description provides further details on specific implementation methods.

[0016] Example 1 Methods for real-time calculation and safety assessment of three-dimensional stress field of downhole tubing, such as Figure 1 and Figure 2 As shown, it includes the following steps: The S100 collects multi-source data from downhole and performs data preprocessing on the multi-source data, including downhole sensor data, surface monitoring data, and historical data. Downhole sensor data includes pressure, temperature, and vibration signals, surface monitoring data includes flow rate and gas composition, and historical data includes operation records and fault cases, forming a comprehensive data support system.

[0017] Data quality cleaning is crucial in downhole scenarios, employing anti-interference and fault-tolerance methods. Downhole data quality issues primarily stem from noise (dust / electromagnetic interference), missing values ​​(sensor malfunctions), and anomalies (safety thresholds). Processing must balance "data authenticity" with "safety priorities" (e.g., abnormal gas concentrations should be prioritized for marking rather than direct deletion). Data preprocessing includes noise removal, missing value handling, and outlier handling.

[0018] Noise processing is one of the most common problems underground, focusing on sensor data. Mine pressure sensors are affected by blasting vibrations, causing instantaneous spikes in the data; for example, a normal stress of 20 MPa might suddenly rise to 100 MPa during blasting. A filtering algorithm is applied to the data based on the underground scenario, using different preprocessing methods according to the noise type: for instantaneous spike noise (blasting / collision), a median filter with a window size of 3-5 is used, suitable for mine pressure and vibration data; for high-frequency electromagnetic noise (motor interference), a low-pass filter with a cutoff frequency of 5 Hz is used, suitable for current and voltage data; and for light noise (video data), an adaptive threshold segmentation (OTSU algorithm) preprocessing method is used, suitable for underground video monitoring.

[0019] The principle for handling missing values ​​(occurring frequently offline from downhole sensors) is as follows: critical safety data (gas, carbon monoxide) should not be easily deleted, while non-critical data (such as ambient humidity) can be deleted appropriately. Missing values ​​are handled in a stratified manner based on the downhole scenario: for gas concentration (critical), with a missing rate of <5%, linear interpolation is used for interpolation between adjacent time points; for mining machine current (equipment data), with a missing rate of 5%~15%, a random forest filling method is used in conjunction with equipment speed and load; for ambient humidity (non-critical), with a missing rate of >15%, feature deletion / sample labeling is used.

[0020] The tools used for handling missing values ​​are sklearn.impute.KNNImputer (KNN imputation) and fancyimpute.RandomForestImputer (random forest imputation).

[0021] The core of underground safety in handling outliers is distinguishing between "real hazards" and "data errors." The classification method for real hazards and data errors is as follows: sensor malfunctions (e.g., gas concentration consistently at 0 or 100% LEL) and transmission errors (incorrect data format) are considered data errors; excessive gas concentration (>1% LEL) and sudden increases in mine pressure (>50 MPa) (requiring a safety warning) are considered real anomalies. The detection of real anomalies and data errors is achieved through a dual verification method combining statistical methods and underground safety thresholds. The statistical method uses the IQR rule to handle non-normally distributed mine pressure data, while safety thresholds are set according to the "Coal Mine Safety Regulations" (e.g., gas concentration >1% LEL is considered anomaly) for safety threshold detection.

[0022] When making a judgment, if five consecutive data points remain constant or exceed the physical range (e.g., temperature > 100℃), it is considered a data error and marked as "sensor failure," and historical data from the same period is used to fill the gap. If a single data point exceeds the safety threshold, but the trend of the preceding and following data is reasonable (e.g., gas concentration gradually increases from 0.8%, 1.2%, to 1.1%), it is considered a real anomaly, the data is retained, and an early warning is triggered.

[0023] The processing tools used are: sklearn.ensemble.IsolationForest (high-dimensional data anomaly detection) and a custom business rule function (def is_abnormal(gas): return gas>1.0).

[0024] The collected data undergoes feature standardization and normalization. The focus of underground modeling is to eliminate dimensions and highlight safety features. The dimensions of underground multi-source data vary greatly (e.g., gas concentration 0~5% LEL, mining machine speed 0~3000r / min, personnel movement speed 0~1.5m / s), and standardization is required before input into the model (e.g., safety early warning model, fault diagnosis model).

[0025] For the safety early warning model (SVM / neural network), it is necessary to balance the weights of each feature for applicable downhole scenarios. Z-Score standardization is used for preprocessing, and the formula is expressed as follows: Where x is the target parameter, μ is the variance, and σ is the standard deviation. For example, after standardizing the data on gas concentration, mine pressure, and current, the model accuracy is improved by 15% when input into the LSTM model to predict faults.

[0026] For downhole applications where features need to be mapped to a safety threshold range (e.g., 0~1 corresponding to "safe to dangerous"), Min-Max normalization preprocessing is used, and the calculation formula is expressed as follows: For example, the gas concentration (0~1% LEL is safe, 1~5% LEL is dangerous) is normalized to [0,1] for real-time safety scoring.

[0027] For underground applications with numerous outliers (such as post-blasting mine pressure data), a robust normalization preprocessing method is adopted, expressed by the formula: For example, in processing post-blasting mine pressure data, outliers can be avoided from affecting the standardization effect, and the data distribution becomes more stable after normalization.

[0028] Note: Safety thresholds must retain their original dimensions (e.g., the warning line for 1% LEL gas concentration). Standardization is only used for model input and does not change the safety judgment criteria of the original data.

[0029] S200, based on the isotropic nature of the tubular material and the fact that the stress-strain relationship conforms to linear elasticity theory, performs three-dimensional stress calculations. These calculations include axial stress, radial stress, and circumferential stress. The formula for calculating the axial stress is as follows: ; The formula for calculating the radial stress is: ; The formula for calculating the circumferential stress is: ; Where E is the elastic modulus of the material, and v is Poisson's ratio. , , These represent the strains in the axial, radial, and circumferential directions, respectively.

[0030] S300 corrects radial stress by combining the radial pressure difference caused by internal and external pressure, corrects thermal stress in real time based on the temperature change between the bottom of the well and the wellhead, calculates the corrosion rate based on the change in corrosive gas content, and corrects the stress distribution results.

[0031] The corrected formula for radial stress is: ; in, Radial pressure difference, , For internal pressure, External pressure; The thermal stress correction is modified based on the collected temperature distribution data. ; The corrosion rate is expressed as: ; Where k, α, and β are empirical constants. , Gas concentration; The circumferential stress distribution in a corrosive environment is expressed as follows: ; in, t represents the initial wall thickness; t represents time. Let be the inner radius.

[0032] S400 uses yield strength as a constraint to correct the safety assessment results, calculates thermal stress based on the temperature change between the bottom of the well and the wellhead, and corrects the total stress.

[0033] The security assessment results are expressed as follows: Safety factor = ; in, The yield strength is given by the material itself; if the safety factor is less than 1, it indicates that the tubing may be in a dangerous condition. The formula for calculating thermal stress is: ; in, The coefficient of thermal expansion is This represents the temperature change value. The correction formula for the total stress is: .

[0034] The total stress is summed using the parameters corrected in step S300.

[0035] S500 is based on the relationship between total stress and yield strength in S400 for risk classification and early warning. The specific risk classification is as follows: like Therefore, the safety level is relatively high; like Then we need to pay attention; like If so, an alarm will be triggered.

[0036] Example calculation: For the Moxi 022-X13 well, data from a specific day is selected for calculation. The parameters are: casing pressure 19.32 MPa, oil pressure 34.56 MPa, wellhead temperature 48 ℃, and daily gas production 161,977. The daily water production is 9.49 tons.

[0037] Axial stress calculation: Assume elastic modulus E = 2.1 × Given Pa, Poisson's ratio v = 0.3, and strain data obtained from a sensor, the axial stress is: ; Radial stress calculation: The internal and external pressure difference is: ; Circumferential stress calculation: The effect of thermal expansion on circumferential stress is as follows: ; Total stress calculation: The stress in all directions is superimposed as follows: .

[0038] Assumption =20MPa, then: .

[0039] Assuming yield strength =40MPa, then: ; It has a high level of security.

[0040] This embodiment addresses the complexity of gas well operating environments (such as high temperature and pressure, corrosion erosion, vibration and friction), and considers the combined effects of axial stress (tension / compression), radial stress (internal and external pressure difference), and circumferential stress (circumferential pressure). A complete three-dimensional stress field model is constructed, and a coupling effect processing mechanism is introduced. The finite element method (FEA) is used to accurately model and calculate the superposition effect of stresses in different directions, significantly improving calculation accuracy. The influence of material properties such as elastic modulus, Poisson's ratio, yield strength, sulfur resistance, and coefficient of thermal expansion on the bearing capacity and corrosion resistance of the tubing string is comprehensively evaluated, enabling real-time monitoring and dynamic adjustment of material properties. This is particularly important in high-temperature, high-pressure, and sulfur-containing environments, ensuring the accuracy of the evaluation results. Real-time monitoring of various dynamic operating parameters such as pressure fluctuations, temperature gradients, and gas composition changes, combined with chemical reaction models to predict corrosion rates, automatically adjusts the evaluation model to adapt to rapidly changing conditions, improving the system's adaptability and robustness. The above descriptions are merely embodiments of the present invention, and common knowledge regarding specific structures and characteristics is not elaborated upon here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the structure of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string, including the following: S100 collects multi-source data from downhole and performs data preprocessing on the multi-source data, which includes downhole sensor data, surface monitoring data, and historical data. Its features are, Also includes: S200, based on the isotropic nature of the tubular material and the fact that the stress-strain relationship conforms to the linear elastic theory, performs three-dimensional stress calculations; S300 corrects radial stress by combining the radial pressure difference caused by internal and external pressure, corrects thermal stress in real time based on the temperature change between the bottom of the well and the wellhead, calculates the corrosion rate based on the change in corrosive gas content, and corrects the stress distribution results. S400 uses yield strength as a constraint to correct the safety assessment results, calculates thermal stress based on the temperature change between the bottom of the well and the wellhead, and corrects the total stress. S500 is used for risk classification and early warning based on the relationship between total stress and yield strength of S400.

2. The method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string according to claim 1, characterized in that: In step S200, the three-dimensional stress calculation includes axial stress, radial stress, and circumferential stress. The formula for calculating the axial stress is as follows: ； The formula for calculating the radial stress is: ； The formula for calculating the circumferential stress is: ； Where E is the elastic modulus of the material, and v is Poisson's ratio. , , These represent the strains in the axial, radial, and circumferential directions, respectively.

3. The method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string according to claim 2, characterized in that: In S400, the security assessment result is expressed as follows: Safety factor = ; in, Yield strength; The formula for calculating thermal stress is: ； in, The coefficient of thermal expansion is... This represents the temperature change value. The correction formula for the total stress is: 。 4. The method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string according to claim 3, characterized in that: In S300, the correction formula for the radial stress is: ； in, Radial pressure difference; The thermal stress correction is modified based on the collected temperature distribution data. ; The corrosion rate is expressed as: ； Where k, α, and β are empirical constants. , Gas concentration; The circumferential stress distribution result is expressed as follows: ； in, t represents the initial wall thickness; t represents time. Let be the inner radius.

5. The method for real-time calculation and safety assessment of the three-dimensional stress field of a downhole tubing string according to claim 4, characterized in that: In S200, the three-dimensional stress field is numerically simulated using finite element analysis.

6. A real-time calculation and safety assessment system for three-dimensional stress field of downhole tubing, comprising at least one processor and a memory communicatively connected to the at least one processor, the memory storing a computer program executable by the at least one processor, characterized in that: The computer program is executed by the at least one processor to enable the at least one processor to perform the method for real-time calculation and safety assessment of the three-dimensional stress field of the downhole tubing as described in any one of claims 1-5.

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