Downhole oil casing laser cutting device

Abstract

The present invention discloses a downhole oil casing laser cutting device, belonging to the field of oil drilling technology. The device comprises: a laser cutting speed control system for dynamically controlling the laser cutting speed, comprising: a data acquisition module for acquiring material property data, beam quality data, and laser cutting state data; a material property analysis module for constructing a material property analysis model based on the material property data and outputting material property coefficients; a beam quality analysis module for constructing a beam quality evaluation model based on the beam quality data and outputting beam quality evaluation coefficients; a laser cutting state analysis module for constructing a laser cutting state model based on the laser cutting state data and outputting laser cutting state coefficients; and a speed optimization module for constructing a speed optimization model based on the laser cutting state coefficients and the current cutting speed and outputting a target cutting speed. The present invention can significantly improve cutting efficiency, precision, and adaptability in complex downhole environments.

Description

Technical Field

[0001] The invention belongs to the technical field of oil drilling, and in particular relates to a downhole oil casing laser cutting device. Background Art

[0002] Traditional downhole casing cutting mainly relies on mechanical cutting tools (such as milling cutters) or chemical cutting (such as shaped charge perforators), which have obvious defects:

[0003] Mechanical cutting: susceptible to the high temperature and high pressure environment downhole, the tool wear is severe, the service life is short, the efficiency is low when cutting thick-walled pipe (the speed is usually less than 10 mm / s), and the drill is prone to sticking. The cutting accuracy of multi-layer pipe strings is poor and the outer casing is easily damaged.

[0004] Chemical cutting: There is a risk of explosion, low safety, debris generated can easily clog the wellbore, subsequent cleanup costs are high, and the incision position cannot be precisely controlled.

[0005] Although existing laser cutting technology has been partially applied underground, it still has bottlenecks:

[0006] 1) Failure to consider the sudden change in reflectivity caused by the smoothness of the material surface, resulting in insufficient energy utilization;

[0007] 2) Ignoring the coupling effects of vibration and temperature and pressure fluctuations on beam quality, resulting in poor cutting stability;

[0008] 3) The focus position and power density are statically matched and cannot adapt to dynamic working conditions, making it difficult to control the cutting speed. Summary of the Invention

[0009] In view of the deficiencies in the prior art, the present invention provides a downhole oil casing laser cutting device to solve the above problems.

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions: A downhole oil casing laser cutting device, comprising:

[0011] Laser cutting speed control system, used to dynamically control laser cutting speed, including:

[0012] Data acquisition module, used to obtain material property data, beam quality data and laser cutting status data;

[0013] Material property analysis module, which builds a material property analysis model based on material property data and outputs material property coefficients;

[0014] The beam quality analysis module builds a beam quality evaluation model based on the beam quality data and outputs the beam quality evaluation coefficient;

[0015] Laser cutting state analysis module, which builds a laser cutting state model based on laser cutting state data and outputs laser cutting state coefficients;

[0016] The speed optimization module builds a speed optimization model based on the laser cutting state coefficient and the current cutting speed and outputs the target cutting speed.

[0017] On the basis of the above technical solutions, the present invention also provides the following optional technical solutions:

[0018] Further technical solution: The working steps of the laser cutting state analysis module are:

[0019] A speed optimization model is constructed based on the laser cutting state coefficient and the current cutting speed, and the laser cutting state coefficient and the current cutting speed are imported into the speed optimization model to output the target cutting speed;

[0020] If the target cutting speed , then adjust the current cutting speed to the target cutting speed;

[0021] If the target cutting speed , then adjust the current speed to the minimum cutting speed allowed by the material ;

[0022] If the target cutting speed , then adjust the current speed to the maximum cutting speed allowed by the material ;

[0023] The speed optimization model is expressed as:

[0024]

[0025] in, Indicates the target cutting speed, Indicates the maximum allowable cutting speed of the material. Represents the laser cutting state coefficient, represents the speed response coefficient, Indicates the current cutting speed.

[0026] Further technical solution: The material characteristic data includes material thickness, surface smoothness, and the angle between the incision and the normal of the section.

[0027] Further technical solution: The beam quality data includes the temperature fluctuation value of the cutting environment, the ambient air pressure, the ambient humidity and the vibration frequency of the laser generator, and the temperature fluctuation value refers to the difference between the current temperature and the standard temperature.

[0028] Further technical solution: The laser cutting status data includes power density, focus position and cutting speed.

[0029] Further technical solution: The working steps of the material property analysis module are as follows:

[0030] Perform maximum-minimum normalization processing on the material thickness and surface smoothness to obtain the material thickness index and surface smoothness index;

[0031] According to the thickness index, surface smoothness index and the angle between the cut and the normal line of the section, a material property analysis model is constructed to output the material property coefficient;

[0032] The material property analysis model is expressed as:

[0033]

[0034] in, represents the material characteristic coefficient, represents the material thickness index, represents the thickness attenuation coefficient, represents the thickness exponential factor, Material basic absorption coefficient, represents the material reflection suppression coefficient, represents the surface smoothness index, represents the smoothness attenuation coefficient, Indicates the angle between the cut and the normal of the cutting surface.

[0035] Further technical solution: The working steps of the beam quality analysis module are:

[0036] The maximum-minimum normalization method is used to normalize the vibration frequency, temperature fluctuation value, ambient pressure and ambient humidity to obtain the vibration frequency index, temperature fluctuation index, ambient pressure index and ambient humidity index;

[0037] Import the current vibration frequency index, current temperature fluctuation index, current ambient air pressure index, and current ambient humidity index into a preset beam quality analysis model to output a beam quality analysis factor;

[0038] The beam quality analysis model is expressed as:

[0039]

[0040] in, represents the beam quality analysis factor, Indicates the current vibration frequency index, Indicates the current temperature fluctuation index, Indicates the current ambient air pressure index. Indicates the reference ambient air pressure index, Indicates the current ambient humidity index. represents the weight and ;

[0041] The beam environment evaluation factor is introduced into the beam quality evaluation model to output the beam quality evaluation coefficient, which is expressed as:

[0042]

[0043] in, represents the beam quality evaluation coefficient, Represents the beam quality analysis factor.

[0044] Further technical solution: The working steps of the laser cutting state analysis module are:

[0045] Perform maximum-minimum normalization processing on the power density and the focal position to obtain the power density index and the focal position index;

[0046] Based on the current material characteristic coefficient and the power density index and focus position index under the beam quality evaluation coefficient, a laser cutting state model is constructed to output the laser cutting state coefficient;

[0047] The laser cutting state model is expressed as:

[0048]

[0049] in, Represents the laser cutting state coefficient, represents the beam quality evaluation coefficient, represents the power density index, represents the benchmark power density index, represents the material characteristic coefficient, represents the sensitivity coefficient, represents the focus position index, represents the optimal focus position, represents the focus tolerance parameter;

[0050] The obtained laser cutting state coefficient is compared with the laser cutting state coefficient threshold. If the laser cutting state coefficient is not within the laser cutting state coefficient threshold, the power density and focus position are adjusted until the laser cutting state coefficient is within the laser cutting state coefficient threshold.

[0051] The present invention provides a downhole oil casing laser cutting device, which has the following beneficial effects compared with the prior art:

[0052] 1. The beam quality evaluation model quantifies environmental interference, and the focus tolerance mechanism compensates for position offset and reduces the incision position error. The project optimizes the energy distribution of inclined cutting and reduces the roughness of the cut to increase the cutting accuracy and stability. The material property model integrates the nonlinear attenuation of thickness. Surface reflection suppression Adapt to rust / scaling pipe wall, and the pressure compensation item To offset the influence of downhole pressure fluctuations, the dynamic speed optimization model is used to combine the material property coefficient and the laser cutting state coefficient to achieve adaptive adjustment of the cutting speed to improve cutting efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0055] The specific implementation of the present invention is described in detail below with reference to specific embodiments.

[0056] Conventional downhole oil casing cutting relies on mechanical or chemical methods, which can lead to severe tool wear, low efficiency, and high safety risks. While existing laser cutting technology is partially used downhole, it has not effectively addressed the shortcomings of sudden changes in material surface reflectivity, coupled interference from environmental factors, and insufficient adaptability to dynamic operating conditions. This results in low energy utilization, poor stability, and imprecise speed control during the cutting process. For example, in high-temperature and high-pressure well conditions, changes in material surface smoothness can cause fluctuations in laser reflectivity, while vibration and changes in temperature and pressure can lead to deterioration in beam quality. Static parameter matching models are difficult to adapt to the dynamic demands of multi-layer pipe cutting.

[0057] See also Figure 1 , provided in one embodiment of the present invention, is a downhole oil casing laser cutting device, comprising:

[0058] Laser cutting speed control system, used to dynamically control laser cutting speed, including:

[0059] Data acquisition module, used to obtain material property data, beam quality data and laser cutting status data;

[0060] Material property analysis module, which builds a material property analysis model based on material property data and outputs material property coefficients;

[0061] The beam quality analysis module builds a beam quality evaluation model based on the beam quality data and outputs the beam quality evaluation coefficient;

[0062] Laser cutting state analysis module, which builds a laser cutting state model based on laser cutting state data and outputs laser cutting state coefficients;

[0063] The speed optimization module builds a speed optimization model based on the laser cutting state coefficient and the current cutting speed and outputs the target cutting speed.

[0064] Specifically, the data acquisition module collects material thickness, surface smoothness, and environmental temperature and pressure data in real time to provide input for each analysis module. The material property analysis module converts thickness and smoothness into an index through normalization processing, and calculates the material property coefficient in combination with the incision angle, effectively reflecting the material's absorption efficiency of laser energy. The beam quality analysis module standardizes parameters such as vibration frequency and temperature and pressure fluctuations, calculates the beam quality factor through weighted average, and then converts it into an evaluation coefficient through an exponential function to suppress the impact of environmental interference on beam stability. The laser cutting state analysis module normalizes the power density and focal position, combines the material property coefficient with the beam quality evaluation coefficient, calculates the focus offset effect through the Gaussian distribution function, and outputs a laser cutting state coefficient that reflects the current cutting stability. The speed optimization module uses an exponential decay model to dynamically adjust the target speed based on the laser cutting state coefficient and the current speed, and ensures that the speed is within the allowable range of the material through a boundary constraint mechanism, achieving a balance between cutting efficiency and stability.

[0065] Compared with existing technologies, existing laser cutting devices fail to establish a quantitative relationship between material surface smoothness and reflectivity, resulting in insufficient energy utilization. This solution, however, dynamically reflects changes in surface reflectivity through material property coefficients, improving energy absorption efficiency. Existing technologies ignore the coupled effects of vibration and temperature and pressure fluctuations, resulting in poor cutting stability. This solution quantifies environmental interference through a beam quality evaluation model to suppress beam quality degradation. Existing methods use a static parameter matching mode, which is difficult to adapt to dynamic working conditions. This solution dynamically adjusts the speed through real-time state coefficients and an exponential decay model, achieving precise adaptation of cutting parameters.

[0066] Through the above technical solution, this application solves the energy loss problem caused by sudden changes in material reflectivity, improves energy utilization by quantifying the impact of surface smoothness; reduces the coupling interference of environmental factors on beam stability, and enhances the robustness of the cutting process through a multi-parameter evaluation model; overcomes the adaptability defects of the static parameter matching mode under dynamic working conditions, and realizes dynamic optimization of the cutting speed through real-time feedback control.

[0067] Preferably, the material characteristic data include material thickness, surface smoothness, and an angle between the incision and the normal line of the cutting surface.

[0068] Material thickness refers to the radial dimension of the cut tube wall and can be measured in real time using a laser rangefinder or ultrasonic sensor. Surface smoothness is a quantitative indicator of the material's surface reflectivity to laser light. This can be achieved by collecting surface roughness data using an optical scattering sensor. This data is used to correct the reflection energy loss coefficient. The angle between the incision and the cut surface normal refers to the angle between the laser's incident direction and the line perpendicular to the cut surface. This data can be obtained using a 3D attitude sensor or image processing technology. This data is used to optimize the energy absorption efficiency of the beam's incident path.

[0069] Through the above technical solution, the present application can capture the sudden change state of the material surface reflectivity in real time, automatically compensate for the energy loss caused by changes in surface roughness, and at the same time optimize the energy absorption efficiency of the light beam incident path according to the incision angle, thereby achieving a dynamic balance of energy utilization during the cutting process.

[0070] Preferably, the beam quality data includes the temperature fluctuation value of the cutting environment, the ambient air pressure, the ambient humidity and the vibration frequency of the laser generator, and the temperature fluctuation value refers to the difference between the current temperature and the standard temperature.

[0071] Among them, the temperature fluctuation value refers to the difference between the current temperature and the standard temperature. Specifically, it can be achieved by using a temperature sensor array to collect the temperature data of the cutting area in real time, and calculating the difference with the preset standard temperature, which is used to quantify the impact of dynamic temperature changes on the laser transmission efficiency. Ambient air pressure refers to the gas pressure in the cutting operation area. Specifically, it can be achieved by using an air pressure sensor to periodically measure the downhole environmental pressure data, which is used to reflect the interference of the density change of the gas medium on the refractive index of the light beam. Ambient humidity refers to the air humidity of the operating environment. Specifically, it can be achieved by using a humidity sensor to continuously monitor the moisture content in the gas, which is used to evaluate the absorption and attenuation effect of water vapor on the laser energy. Vibration frequency refers to the vibration rate of the mechanical parts of the laser generator. Specifically, it can be achieved by using an accelerometer to collect data in real time, which is used to characterize the degree of beam path deviation caused by mechanical vibration.

[0072] Through the above technical solution, this application can perceive the composite interference of temperature, pressure, humidity and mechanical vibration in the complex underground environment in real time. By dynamically correcting the beam quality evaluation coefficient, it effectively suppresses the cutting path deviation and energy density fluctuation caused by environmental parameter fluctuations, and significantly improves the stability of the laser cutting process under high temperature, high pressure and multi-vibration conditions.

[0073] Preferably, the laser cutting state data includes power density, focus position (distance from the focus to the cutting surface) and cutting speed.

[0074] Among them, power density refers to the laser energy input per unit area, which can be achieved by adjusting the output power of the laser generator and the spot size. Its dynamic changes directly affect the material melting efficiency and provide an energy input benchmark for speed optimization.

[0075] Among them, the focal position refers to the focusing state of the laser beam on the surface of the material, which can be achieved through the position adjustment mechanism of the optical lens group. The offset determines the uniformity of energy distribution. Real-time monitoring can avoid the reduction of cutting quality due to defocusing.

[0076] Among them, cutting speed refers to the movement rate of the laser head relative to the material, which can be achieved through a servo motor drive system. As the feedback quantity of closed-loop regulation, it can reflect the dynamic balance state during the actual processing process.

[0077] Preferably, the working steps of the material property analysis module are:

[0078] Perform maximum-minimum normalization processing on the material thickness and surface smoothness to obtain the material thickness index and surface smoothness index;

[0079] According to the thickness index, surface smoothness index and the angle between the cut and the normal line of the section, a material property analysis model is constructed to output the material property coefficient;

[0080] The material property analysis model is expressed as:

[0081]

[0082] in, represents the material characteristic coefficient, represents the material thickness index, represents the thickness attenuation coefficient, represents the thickness exponential factor, Material basic absorption coefficient, represents the material reflection suppression coefficient, represents the surface smoothness index, represents the smoothness attenuation coefficient, Represents the angle between the incision and the normal line of the cutting surface, The larger the value, the easier the material is to cut.

[0083] Among them, the material thickness index refers to a dimensionless parameter that maps the actual thickness value to the standard range through the maximum-minimum normalization method. Specifically, the thickness value can be converted to the range of 0-1 by linear scaling to eliminate the interference of different thickness dimensions on the model operation. The surface smoothness index refers to a quantitative indicator of surface roughness processed by the same normalization method, which is used to characterize the dynamic influence of the material surface on the laser reflectivity. The angle between the incision and the normal of the section refers to the angle formed by the cutting trajectory and the perpendicular direction of the material surface. Specifically, it can be measured in real time by a three-dimensional attitude sensor to correct the influence of the laser incident angle on the energy absorption efficiency. The thickness attenuation coefficient characterizes the nonlinear attenuation intensity of the laser energy absorption efficiency caused by the increase in material thickness. The thickness attenuation coefficient and the thickness index factor can both be calibrated through expert experience or by using a material thickness-energy absorption rate calibration experiment. The steps of calibrating the two using the material thickness-energy absorption rate calibration experiment are as follows: select several groups of standard pipe samples to perform laser cutting experiments under standard working conditions, measure the actual energy absorption rate, and the actual energy absorption rate ( ) = theoretical energy required for tube melting / total laser input energy, the material thickness index is fitted with the actual energy absorption rate, and the fitting formula is: , solved based on the least squares method 、 .

[0084] Specifically, the material thickness index reflects the nonlinear attenuation effect of material thickness on energy absorption through a power function, while the surface smoothness index suppresses energy loss on highly reflective surfaces through an exponential attenuation term. The cosine function of the cut angle serves as a correction factor to dynamically adjust the effective energy absorption ratio. The reflection suppression coefficient and the basic absorption coefficient form a complementary relationship. When the surface smoothness is high, the reflection suppression term is enhanced to offset the energy loss caused by sudden changes in reflectivity. The thickness exponential factor adjusts the sensitivity of thickness to absorption efficiency, while the smoothness attenuation coefficient controls the response speed of reflection suppression to changes in surface state.

[0085] Compared with existing technologies, traditional methods only consider the inherent absorption characteristics of the material and ignore the dynamic impact of surface state changes on reflectivity, resulting in a sharp drop in energy utilization when cutting highly smooth surfaces. Existing technologies do not establish a correlation model between cutting angle and energy absorption efficiency, resulting in insufficient effective power density under bevel cutting conditions. This solution eliminates dimensional differences through normalization processing, constructs a multi-parameter coupling model to actively compensate for sudden changes in surface reflectivity, and introduces an angle correction factor to optimize energy transmission efficiency under bevel cutting conditions.

[0086] Through the above technical solution, this application can dynamically balance the combined effects of the material's inherent absorption characteristics and surface reflection characteristics on energy utilization, suppressing energy loss caused by high-reflectivity surfaces. The cutting angle correction factor can increase the effective power density under bevel cutting conditions and avoid insufficient cutting depth due to incident angle deviation. The complementary relationship between the reflection suppression coefficient and the basic absorption coefficient can adapt to the rapid switching of different surface states and maintain the stability of laser energy utilization.

[0087] Preferably, the working steps of the beam quality analysis module are:

[0088] The maximum-minimum normalization method is used to normalize the vibration frequency, temperature fluctuation value, ambient pressure and ambient humidity to obtain the vibration frequency index, temperature fluctuation index, ambient pressure index and ambient humidity index;

[0089] Import the current vibration frequency index, current temperature fluctuation index, current ambient air pressure index, and current ambient humidity index into a preset beam quality analysis model to output a beam quality analysis factor;

[0090] The beam quality analysis model is expressed as:

[0091]

[0092] in, represents the beam quality analysis factor, Indicates the current vibration frequency index, Indicates the current temperature fluctuation index, Indicates the current ambient air pressure index. Indicates the reference ambient air pressure index, Indicates the current ambient humidity index. represents the weight and ;

[0093] The beam environment evaluation factor is introduced into the beam quality evaluation model to output the beam quality evaluation coefficient, which is expressed as:

[0094]

[0095] in, represents the beam quality evaluation coefficient, represents the beam quality analysis factor, The larger the value, the better the beam quality.

[0096] The vibration frequency index refers to the value obtained by normalizing the laser generator's vibration frequency using the maximum-minimum normalization method. Specifically, this can be achieved by using an accelerometer or vibration sensor to collect real-time vibration frequency data, eliminating the influence of different dimensions on parameter analysis. The temperature fluctuation index is the normalized difference between the current temperature and the reference temperature. Specifically, this can be achieved by obtaining real-time temperature data from a temperature sensor, calculating the deviation from the reference temperature, and then performing a normalized conversion. This quantifies the impact of temperature changes on beam stability. The ambient pressure index is the normalized ambient pressure value. Specifically, this can be achieved by using a pressure sensor to collect data and converting it into a dimensionless parameter. It reflects the degree of interference caused by pressure fluctuations on the laser transmission path. The ambient humidity index is the normalized ambient humidity value. Specifically, this can be achieved by using a humidity sensor to obtain data. This index characterizes the absorption and attenuation effect of humidity on laser energy. The beam quality analysis factor is a composite index calculated by weighted average of the vibration frequency index, temperature fluctuation index, ambient pressure index, and ambient humidity index. It is used to comprehensively evaluate the coupled effects of multiple environmental factors on beam quality. The beam quality evaluation coefficient refers to the conversion of the beam quality analysis factor into a dimensionless evaluation parameter through an exponential function. Specifically, it can be mapped using an exponential decay model to quantify the overall degradation of the beam quality due to environmental factors.

[0097] Specifically, vibration frequency, temperature fluctuation, ambient pressure, and humidity are collected in real time by sensors and converted into dimensionless vibration frequency indices, temperature fluctuation indices, ambient pressure indices, and ambient humidity indices, respectively, using a maximum-minimum normalization method. These indices are then incorporated into the beam quality analysis model, where a beam quality analysis factor is generated by calculating the weighted sum of the squared vibration frequency index, the squared temperature fluctuation index, the absolute value of the ambient pressure index deviation, and the linear term of the ambient humidity index. The squared term enhances the nonlinear effects of high-frequency vibration and sudden temperature changes on beam stability, the absolute value term highlights the cumulative effect of pressure deviations from the standard value, and the humidity term directly reflects the absorption of laser energy by water vapor. Weighting coefficient constraints ensure the appropriate distribution of the contributions of the various environmental parameters. The beam quality analysis factor is further converted into a beam quality evaluation coefficient using an exponential function, resulting in an exponential decrease in the evaluation coefficient as the environmental parameters degrade, thereby dynamically reflecting the combined impact of environmental factors on beam quality.

[0098] Compared with existing technologies, traditional methods only consider a single environmental parameter or statically analyze beam quality, failing to establish a multi-parameter coupling model for vibration, temperature, air pressure, and humidity. This results in an inability to accurately assess the degree of quality degradation when beam stability is disturbed by the dynamic environment during the cutting process. This solution constructs a multi-dimensional analysis model that includes square terms, absolute value terms, and linear terms. In combination with weight allocation and exponential conversion mechanisms, it achieves a quantitative evaluation of the coupling effects of multiple factors in dynamic environments, resolving the problem of poor cutting stability caused by ignoring the interactive effects of environmental parameters in existing technologies.

[0099] Through the above technical solution, this application can monitor and quantitatively analyze in real time the comprehensive impact of vibration frequency, temperature fluctuations, air pressure deviation and humidity changes on beam quality. By dynamically adjusting the weight distribution and index conversion mechanism, it can accurately evaluate the degree of interference of environmental factors on laser cutting stability, thereby providing reliable beam quality parameter input for subsequent speed optimization, effectively reducing the cutting speed control error caused by environmental fluctuations, and improving cutting stability under complex working conditions underground.

[0100] Preferably, the working steps of the laser cutting state analysis module are:

[0101] Perform maximum-minimum normalization processing on the power density and the focal position to obtain the power density index and the focal position index;

[0102] Based on the current material characteristic coefficient and the power density index and focus position index under the beam quality evaluation coefficient, a laser cutting state model is constructed to output the laser cutting state coefficient;

[0103] The laser cutting state model is expressed as:

[0104]

[0105] in, Represents the laser cutting state coefficient, represents the beam quality evaluation coefficient, represents the power density index, represents the benchmark power density index, represents the material characteristic coefficient, represents the sensitivity coefficient, represents the focus position index, represents the optimal focus position, represents the focus tolerance parameter (standard deviation), And the larger the value, the better the match between the power density index and the focal position;

[0106] The obtained laser cutting state coefficient is compared with the laser cutting state coefficient threshold. If the laser cutting state coefficient is not within the laser cutting state coefficient threshold, the power density and focus position are adjusted until the laser cutting state coefficient is within the laser cutting state coefficient threshold.

[0107] Among them, the power density index refers to the parameter that maps the actual power density to a standardized interval through the maximum-minimum normalization method, which is used to eliminate the dimensional differences in power density under different working conditions.

[0108] The focus position index refers to the focus position parameter processed by the maximum-minimum normalization method, which is used to quantify the degree of deviation of the focus position from the theoretical optimal value.

[0109] Among them, the benchmark power density index refers to a pre-set standard power density reference value, which is used to calibrate the degree of matching between the current power density and the ideal state.

[0110] Among them, the sensitivity coefficient refers to the nonlinear adjustment parameter of the influence of material properties on power density, which is used to reflect the response intensity of different materials to power changes.

[0111] The optimal focus position refers to the best focus position parameter, which is used to establish a target benchmark for focus position adjustment.

[0112] The focus tolerance parameter refers to a standard deviation parameter, which is used to constrain the physically reasonable range of focus position adjustment.

[0113] Specifically, the power density and focal position are first converted into standardized indices so that parameters of different dimensions can be calculated collaboratively in a unified model. By introducing sensitivity coefficients, the model can dynamically reflect the nonlinear effects of material properties on power density. For example, high-reflectivity materials require higher power density compensation. The degree to which the focal position deviates from the optimal value is quantified by a Gaussian function, and the focus tolerance parameter controls the allowable range of the deviation. The laser cutting state coefficient is weighted by the beam quality evaluation coefficient and is generated by combining the dynamic relationship between power density and material properties and the exponential decay effect of the focus position deviation. When the coefficient exceeds the preset threshold, power density adjustment and focus position fine-tuning are triggered, for example, by adjusting the output power of the laser generator or adjusting the focusing lens position, until the cutting state returns to the stable range.

[0114] Compared to existing technologies, traditional laser cutting technology uses a fixed relationship between power density and focal position, making it unable to cope with dynamic conditions such as underground temperature fluctuations and changes in material reflectivity. This solution establishes a composite state model that incorporates material properties, beam quality, and focal position deviations, enabling dynamic coordinated adjustment of power density and focal position. For example, when the material surface smoothness suddenly changes, the power density is adjusted in real time to compensate for reflected energy loss, while the focal position is fine-tuned to maintain cutting accuracy.

[0115] Through the above technical solution, the present application solves the problem of uncontrolled cutting speed caused by static matching of focus position and power density in the prior art, and can automatically adjust laser parameters under complex working conditions underground. For example, when high temperature causes beam distortion, cutting stability is maintained by dynamically optimizing power density and focus position, thereby avoiding cutting interruptions or quality defects caused by parameter mismatch.

[0116] Preferably, the working steps of the speed optimization module are:

[0117] A speed optimization model is constructed based on the laser cutting state coefficient and the current cutting speed, and the laser cutting state coefficient and the current cutting speed are imported into the speed optimization model to output the target cutting speed;

[0118] If the target cutting speed , then adjust the current cutting speed to the target cutting speed;

[0119] If the target cutting speed , then adjust the current speed to the minimum cutting speed allowed by the material ;

[0120] If the target cutting speed , then adjust the current speed to the maximum cutting speed allowed by the material ;

[0121] The speed optimization model is expressed as:

[0122]

[0123] in, Indicates the target cutting speed, Indicates the maximum allowable cutting speed of the material. Represents the laser cutting state coefficient, represents the speed response coefficient, Indicates the current cutting speed.

[0124] Among them, the laser cutting state coefficient refers to a quantitative indicator that reflects the comprehensive influence of dynamic parameters such as power density and focus position in the current cutting process.

[0125] The speed response coefficient refers to a parameter that controls the cutting speed adjustment rate. Specifically, it can be obtained by using a preset empirical value or through historical data training, and is used to adjust the sensitivity of the target speed to changes in the current working conditions.

[0126] The minimum cutting speed allowed by the material refers to the minimum speed threshold to ensure the continuity of the cutting process, which is used to prevent cutting interruption caused by too low speed.

[0127] The maximum cutting speed allowed by the material refers to the highest speed threshold to avoid material overheating or beam energy loss, which is used to prevent cutting defects caused by excessive speed.

[0128] Specifically, the speed optimization model combines the laser cutting state coefficient with the speed response coefficient through an exponential function to dynamically adjust the target speed. When the laser cutting state coefficient increases, the model increases the weight of the material's maximum allowable speed, and vice versa, retains the inertia of the current speed. If the calculated target speed exceeds the material's allowable range, it is forcibly limited to the boundary value. For example, when the ambient temperature in the well suddenly changes, causing the beam quality to deteriorate, the laser cutting state coefficient decreases, and the model automatically reduces the weight of the maximum speed, prioritizing maintaining the current speed stability. When the cutting efficiency is improved after the focus position is optimized, the model achieves speed increase by increasing the weight of the maximum speed.

[0129] Compared to existing technologies, traditional methods use fixed speed parameters or rely solely on a single factor to adjust speed, making them unable to cope with dynamic conditions caused by sudden changes in material reflectivity or fluctuations in ambient temperature and pressure. This solution, by introducing a cutting state coefficient and a boundary constraint mechanism, achieves closed-loop speed control under the coupled influence of multiple parameters. For example, existing technologies fail to account for the nonlinear effects of focus position offset on speed adjustment, while this solution achieves dynamic compensation through the focus tolerance parameter in an exponential function.

[0130] Through the above technical solution, this application solves the problem of fluctuating cut quality caused by a mismatch between cutting speed and dynamic operating conditions, ensuring that speed adjustment always remains within the material's tolerance range. For example, when cutting highly reflective materials, a mandatory minimum speed limit prevents cutting interruptions caused by reflected energy loss; in high-temperature environments, a maximum speed constraint prevents thermal damage to the material. This enables adaptive control of cutting speed in complex underground environments, improving cutting efficiency and cut consistency.

[0131] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0132] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A downhole oil casing laser cutting device, characterized in that: include: Laser cutting speed control system, used to dynamically control laser cutting speed, including: Data acquisition module, used to obtain material property data, beam quality data and laser cutting status data; Material property analysis module, which builds a material property analysis model based on material property data and outputs material property coefficients; The beam quality analysis module builds a beam quality evaluation model based on the beam quality data and outputs the beam quality evaluation coefficient; Laser cutting state analysis module, which builds a laser cutting state model based on laser cutting state data and outputs laser cutting state coefficients; Speed ​​optimization module, which builds a speed optimization model based on the laser cutting state coefficient and the current cutting speed and outputs the target cutting speed; The speed optimization model is expressed as: in, Indicates the target cutting speed, Indicates the maximum allowable cutting speed of the material. Represents the laser cutting state coefficient, represents the speed response coefficient, Indicates the current cutting speed.

2. The downhole oil casing laser cutting device according to claim 1, characterized in that: The working steps of the laser cutting state analysis module are as follows: A speed optimization model is constructed based on the laser cutting state coefficient and the current cutting speed, and the laser cutting state coefficient and the current cutting speed are imported into the speed optimization model to output the target cutting speed; If the target cutting speed , then adjust the current cutting speed to the target cutting speed, Indicates the minimum cutting speed allowed for the material. Indicates the maximum cutting speed allowed by the material; If the target cutting speed , then adjust the current speed to the minimum cutting speed allowed by the material ; If the target cutting speed , then adjust the current speed to the maximum cutting speed allowed by the material .

3. The downhole oil casing laser cutting device according to claim 1 or 2, characterized in that: The material characteristic data include material thickness, surface smoothness, and the angle between the cut and the normal line of the cut surface.

4. The downhole oil casing laser cutting device according to claim 1 or 2, characterized in that: The beam quality data includes the temperature fluctuation value of the cutting environment, the ambient air pressure, the ambient humidity and the vibration frequency of the laser generator. The temperature fluctuation value refers to the difference between the current temperature and the standard temperature.

5. The downhole oil casing laser cutting device according to claim 1 or 2, characterized in that: The laser cutting status data includes power density, focus position and cutting speed.

6. The downhole oil casing laser cutting device according to claim 3, characterized in that: The working steps of the material property analysis module are: Perform maximum-minimum normalization processing on the material thickness and surface smoothness to obtain the material thickness index and surface smoothness index; According to the thickness index, surface smoothness index and the angle between the cut and the normal line of the section, a material property analysis model is constructed to output the material property coefficient; The material property analysis model is expressed as: in, represents the material characteristic coefficient, represents the material thickness index, represents the thickness attenuation coefficient, represents the thickness exponential factor, Material basic absorption coefficient, represents the material reflection suppression coefficient, represents the surface smoothness index, represents the smoothness attenuation coefficient, Indicates the angle between the cut and the normal of the cutting surface.

7. The downhole oil casing laser cutting device according to claim 4, characterized in that: The working steps of the beam quality analysis module are: The maximum-minimum normalization method is used to normalize the vibration frequency, temperature fluctuation value, ambient pressure and ambient humidity to obtain the vibration frequency index, temperature fluctuation index, ambient pressure index and ambient humidity index; Import the current vibration frequency index, current temperature fluctuation index, current ambient air pressure index, and current ambient humidity index into a preset beam quality analysis model to output a beam quality analysis factor; The beam quality analysis model is expressed as: in, represents the beam quality analysis factor, Indicates the current vibration frequency index, Indicates the current temperature fluctuation index, Indicates the current ambient air pressure index. Indicates the reference ambient air pressure index, Indicates the current ambient humidity index. represents the weight and ; The beam environment evaluation factor is introduced into the beam quality evaluation model to output the beam quality evaluation coefficient, which is expressed as: in, represents the beam quality evaluation coefficient, Represents the beam quality analysis factor.

8. The downhole oil casing laser cutting device according to claim 5, characterized in that: The working steps of the laser cutting state analysis module are as follows: Perform maximum-minimum normalization processing on the power density and the focal position to obtain the power density index and the focal position index; Based on the current material characteristic coefficient and the power density index and focus position index under the beam quality evaluation coefficient, a laser cutting state model is constructed to output the laser cutting state coefficient; The laser cutting state model is expressed as: in, Represents the laser cutting state coefficient, represents the beam quality evaluation coefficient, represents the power density index, represents the benchmark power density index, represents the material characteristic coefficient, represents the sensitivity coefficient, represents the focus position index, represents the optimal focus position, represents the focus tolerance parameter; The obtained laser cutting state coefficient is compared with the laser cutting state coefficient threshold. If the laser cutting state coefficient is not within the laser cutting state coefficient threshold, the power density and focus position are adjusted until the laser cutting state coefficient is within the laser cutting state coefficient threshold.

Images