A salt cavern cavity forming process control method for compressed air energy storage

Abstract

The application discloses a salt cavern cavity forming process control method for compressed air energy storage, and belongs to the technical field of compressed air energy storage.The application solves the problem that, due to dependence on artificial experience and fixed process parameters, the existing cavity forming control method is difficult to accurately control the three-dimensional form of the cavity when facing a non-homogeneous salt rock stratum, and the problem that local over-dissolution, damage to the sealing property of the cap layer of the cavity top and stress concentration of the cavity wall easily occur, affecting long-term stability.The application builds a salt cavity form dynamic inversion model based on real-time sensing of geological parameters, and combines bidirectional coupling simulation of fluid mechanics and rock mechanics to perform closed-loop adaptive optimization control on water injection displacement, dissolving agent cushion thickness and pipe lifting speed, realizes intelligent transformation of the salt cavern cavity forming process from experience driving to data model driving, improves the cavity forming precision, and significantly enhances the construction economy and operation safety of the gas storage.

Description

Technical Field

[0001] This invention relates to the field of compressed air energy storage technology, specifically to a method for controlling the salt cavern creation process for compressed air energy storage. Background Technology

[0002] Utilizing salt caverns formed by water dissolution in underground salt rock deposits as storage spaces for compressed air energy storage is an important development direction for large-scale energy storage. The morphology, size, and stability of the salt caverns directly affect the sealing performance, economy, and operational safety of the gas storage facility. Traditional salt cavern construction processes typically employ single-well or dual-well convection methods, controlling the shape of the cavity by manipulating the injection points of water, brine discharge, and solvents such as diesel or nitrogen.

[0003] However, existing cavity construction control methods largely rely on human experience and preset fixed process parameters. When faced with complex and heterogeneous geological conditions (such as variations in salt rock purity and the distribution of insoluble interlayers), they often struggle to accurately control the three-dimensional morphology of the cavity. Traditional control methods suffer from response lag, easily leading to local over-dissolution or under-dissolution within the cavity, or even causing excessive dissolution at the cavity top, damaging the caprock's sealing, or abrupt changes in the cavity wall morphology, creating stress concentration zones and affecting the long-term stability of the cavity. Therefore, they do not meet current requirements. To address this, we propose a salt cavern cavity construction process control method for compressed air energy storage. Summary of the Invention

[0004] The purpose of this invention is to provide a method for controlling the salt cavern construction process for compressed air energy storage. By constructing a dynamic inversion model of salt cavern morphology based on real-time geological parameter perception, and combining bidirectional coupled simulation of fluid mechanics and rock mechanics, a closed-loop adaptive optimization control is performed on key process parameters such as water injection rate, solvent barrier layer thickness, and pipe lifting speed, thus solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling the salt cavern creation process for compressed air energy storage, comprising the following steps:

[0006] Step 1: Based on the 3D seismic data and well logging data of the target salt layer, establish a 3D geological model for salt cavern construction. According to the salt rock purity distribution, interlayer distribution and salt layer thickness distribution of the target salt layer, the entire cavity construction process is divided into cavity construction segments carried out in sequence: bottom dissolution segment, main body expansion segment, top forming segment and neck contraction segment.

[0007] Specifically, target cavity morphology parameters are preset for each cavity segment, including the target cavity diameter, target cavity height, target cavity top burial depth, target cavity bottom elevation, and target dissolution boundary contour curve of the segment.

[0008] Step 2: Before the current cavity construction begins, collect sonar measurement data and brine concentration distribution data within the salt cavity to construct a digital model of the current salt cavity morphology;

[0009] Step 3: Using the digital model of the current salt cavity morphology as a basis, extract the actual radial dimensions at multiple depth positions along the cavity depth direction at a preset sampling interval to generate an actual radial dimension curve. Compare the actual radial dimension curve with the radial dimensions at the corresponding depth positions in the target dissolution boundary contour curve point by point to obtain a radial deviation curve. At the same time, compare the actual cavity top elevation with the preset elevation corresponding to the target cavity top burial depth to obtain the cavity top axial deviation value. Compare the actual cavity bottom elevation with the target cavity bottom elevation to obtain the cavity bottom axial deviation value. Use the radial deviation curve, the cavity top axial deviation value, and the cavity bottom axial deviation value together as the cavity deviation amount.

[0010] Step 4: Based on the cavity deviation, combined with the preset cavity stability threshold and dynamic dissolution rate model, dynamically adjust at least one process parameter in the current cavity segment, including water injection flow rate, water injection pressure, brine discharge flow rate, and solvent injection position.

[0011] Step 5: Under the adjusted process parameters, perform dissolution and cavity creation, and monitor the changes in cavity morphology in real time until the deviation between the actual dissolution boundary of the current cavity creation segment and the preset dissolution boundary stabilizes within the preset allowable range. Then, the current cavity creation segment is determined to be completed, and the process automatically enters the preset next cavity creation segment to continue executing steps 2 to 5 until the construction of all cavity creation segments is completed.

[0012] Furthermore, the specific process of dynamically adjusting the water injection flow rate in real time based on the cavity deviation in step four is as follows:

[0013] When the radial deviation curve shows that a certain depth range is an undersoluble zone, increase the water injection flow rate at the corresponding height position;

[0014] When a certain depth range is determined to be an over-soluble zone, reduce the water injection flow rate and simultaneously adjust the position of the solvent inhibitor injection to the upper boundary of the over-soluble zone.

[0015] Furthermore, the specific process of dynamically adjusting the solvent injection position in real time according to the cavity deviation in step four is as follows: based on the axial deviation value of the cavity top, when the actual cavity top elevation deviates from the target cavity top elevation, the direction and distance of the solvent injection position are adjusted accordingly; the magnitude of the distance is determined according to the deviation amount according to a preset proportional relationship.

[0016] Furthermore, in step four, while dynamically adjusting the injection position of the solvent inhibitor in real time, the injection concentration and flow rate of the solvent inhibitor are also adjusted synchronously based on the axial deviation value at the top of the cavity. The specific process is as follows:

[0017] Based on the direction and degree of deviation of the actual cavity top elevation from the target cavity top elevation, the injection concentration and injection flow rate of the inhibitor are adjusted in a coordinated manner.

[0018] When the actual cavity top elevation is lower than the target cavity top elevation, the goal is to weaken the dissolution inhibition effect and promote cavity top dissolution, so the concentration of the dissolution inhibitor and the flow rate of the dissolution inhibitor are reduced.

[0019] When the actual cavity top elevation is higher than the target cavity top elevation, the goal is to enhance the anti-dissolution effect and suppress excessive dissolution at the cavity top, so the concentration of anti-dissolution agent injected and the flow rate of anti-dissolution agent injected are increased.

[0020] The cavity top dissolution rate can be controlled by three-dimensional coordinated adjustment of the injection location, injection concentration, and injection flow rate of the solvent inhibitor.

[0021] Furthermore, the specific process of dynamically adjusting the brine discharge flow rate in real time based on the cavity deviation in step four is as follows:

[0022] Based on the dynamic dissolution rate model, the theoretical dissolution rate under the current conditions is calculated by inputting the current process parameters and the real-time monitored brine concentration distribution data.

[0023] The theoretical erosion rate is compared with the actual erosion rate, which is calculated based on the cavity morphology change obtained from two consecutive sonar measurements.

[0024] When the deviation between the actual dissolution rate and the theoretical dissolution rate reaches a preset inefficient dissolution threshold, it is determined that the brine concentration in the cavity deviates from the optimal dissolution concentration range. In this case, the brine discharge flow rate is increased or decreased accordingly to adjust the brine replacement rate so that the actual dissolution rate approaches the theoretical dissolution rate.

[0025] Furthermore, the process of establishing the dynamic dissolution rate model is as follows:

[0026] The multivariate nonlinear regression relationship between the dissolution rate and temperature, pressure, and brine concentration was obtained through indoor dissolution experiments. Then, the coefficients in the relationship were corrected and optimized using historical cavity data of the same salt layer to form a dynamic dissolution rate model.

[0027] Furthermore, the specific process of real-time monitoring of cavity morphological changes in step five is as follows:

[0028] During the current cavity segmentation construction process, sonar measurements are periodically performed at preset time intervals, and each sonar measurement acquires real-time point cloud data of the cavity morphology.

[0029] The real-time point cloud data is differentially fused with the previous cycle's digital model of the cavity morphology to generate a dynamic evolution sequence of the cavity morphology, including the change in the radial dimension of the cavity, the change in the elevation of the cavity top and bottom, and the pushing speed of the dissolution boundary.

[0030] The dynamic evolution sequence is compared with the preset target cavity morphology parameters in real time. Once the cavity morphology deviation of a certain local area is detected to exceed the preset deviation threshold corresponding to the cavity segment, the dynamic adjustment mechanism in step four is immediately triggered.

[0031] The preset deviation thresholds are set as differentiated radial and axial deviation thresholds based on the sensitivity of different cavity segment to cavity stability.

[0032] Furthermore, step five, which involves real-time monitoring of changes in the cavity's morphology, also includes real-time assessment of the cavity's stability. The specific process is as follows:

[0033] Extract the curvature variation features of the cavity contour and calculate the radius of curvature of the local region;

[0034] When the radius of curvature is less than the critical radius of curvature threshold and reaches the risk coefficient, it is determined that there is a risk of instability in the region, and local protective adjustment measures are initiated.

[0035] The local protective adjustment measures include: reducing the water injection flow rate, increasing the brine discharge flow rate, and adjusting the injection position of the solvent inhibitor to the lower boundary of the area to slow down the erosion rate of the area and prevent excessive local erosion of the cavity from causing stress concentration.

[0036] Furthermore, the critical radius of curvature threshold is determined as follows:

[0037] Based on the rock mechanics parameters of the target salt layer, a stress distribution model of the salt cavern cavity is established through three-dimensional numerical simulation; stress analysis is performed on the cavity surface with different radii of curvature to obtain the radius of curvature corresponding to the maximum principal stress reaching the preset stress threshold, which is determined as the critical radius of curvature threshold.

[0038] The critical radius of curvature threshold is set according to different cavity-forming segments. For example, the critical radius of curvature threshold for the bottom dissolution segment is set to 8 to 12 meters, the critical radius of curvature threshold for the main body expansion segment is set to 15 to 20 meters, the critical radius of curvature threshold for the top forming segment is set to 10 to 15 meters, and the critical radius of curvature threshold for the neck contraction segment is set to 5 to 8 meters.

[0039] Furthermore, the specific implementation method for repeating steps two through five in step five until the deviation stabilizes within the allowable range is as follows:

[0040] The dynamic evolution sequence of cavity morphology, real-time process parameters, and prediction results of the dynamic dissolution rate model are all input into the fuzzy adaptive PID controller.

[0041] The fuzzy adaptive PID controller uses the cavity deviation and its rate of change as input variables, and the water injection flow rate adjustment, water injection pressure adjustment, brine discharge flow rate adjustment, and solvent injection position adjustment as output variables.

[0042] By using fuzzy inference rules to tune the parameters of the PID controller online, adaptive adjustment of the cavity-forming process parameters can be achieved.

[0043] Furthermore, after determining that the current cavity segment is complete and automatically proceeding to the next cavity segment, the process also includes post-evaluation and compensatory adjustments to the quality of the completed cavity segments:

[0044] In the early stages of entering the next cavity creation segment, the frequency of sonar measurements is increased to obtain cavity morphology data of the boundary area between the completed segment and the current segment. If it is found that the cavity deviation in a local area of ​​the completed segment exceeds the allowable range again due to delayed dissolution or creep deformation, the normal cavity creation process of the current segment is suspended and a cross-segment compensatory adjustment procedure is initiated until the cavity morphology in that area is restored to the allowable range, and then the normal cavity creation process of the current segment is resumed.

[0045] Once the deviation of the cavity in the region is restored to the allowable range for that segment, the normal cavity creation process for the current segment is resumed.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] This invention constructs a dynamic inversion model of salt cavity morphology based on real-time geological parameter sensing, enabling centimeter-level online monitoring of the cavity's three-dimensional morphology. This overcomes the lag limitations of traditional intermittent sonar measurements, allowing for real-time capture of asymmetric dissolution caused by insoluble interlayers. This provides a precise data foundation for dynamic adjustment of process parameters, thus avoiding the risks of localized cavity deformities and caprock damage. By introducing a two-way coupled simulation mechanism of fluid mechanics and rock mechanics, the stress redistribution and plastic zone evolution trends of the surrounding rock mass under different process parameters during cavity construction can be dynamically predicted. This achieves a leap from single control to collaborative control in cavity construction process control, eliminating the hidden danger of stress concentration in the cavity wall and improving the long-term operational safety and service life of the salt cavity. Furthermore, by employing a closed-loop adaptive optimization algorithm based on model predictive control, the system can automatically optimize and execute the collaborative adjustment of water injection rate, solvent-resistant cushion thickness, and pipe lifting speed based on real-time feedback of formation changes, achieving fully automated and intelligent control of the cavity construction process. Attached Figure Description

[0048] Figure 1This is a flowchart of the salt cavern creation process control method for compressed air energy storage according to the present invention.

[0049] Figure 2 This is a diagram illustrating the process control method for salt cavern creation in compressed air energy storage according to the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] To address the technical problem that existing cavity control methods, relying on manual experience and fixed process parameters, struggle to accurately control the three-dimensional morphology of the cavity in heterogeneous salt rock formations, leading to issues such as localized over-dissolution, damage to the caprock seal at the cavity top, and stress concentration on the cavity walls that affect long-term stability, please refer to [the relevant documentation / reference]. Figures 1-2 This embodiment provides the following technical solution:

[0052] A method for controlling the salt cavern creation process for compressed air energy storage is based on dividing the entire cavity creation process into multiple segments with specific geometric targets, and using a closed-loop control strategy within each segment to make the actual dissolution morphology infinitely close to the preset target.

[0053] The method first performs step one, which involves segmenting the cavity and pre-setting the target. Specifically, it collects three-dimensional seismic and well logging data of the target salt layer, including its spatial distribution, lithological characteristics, and physical properties. Using professional geological modeling software, a three-dimensional geological model that accurately reflects the underground salt layer is constructed. Based on this model, the distribution of salt purity, the distribution of insoluble interlayers, and the effective thickness variation of the salt layer are analyzed in depth. According to these geological characteristics and the final gas storage design requirements, the entire cavity-building process is divided into four segments in time and space: bottom dissolution, main body expansion, top forming, and neck contraction. This segmentation method conforms to the physical laws of salt cavern dissolution: first, a stable bottom is formed; then, the main body volume is expanded; then, the top shape is precisely controlled; and finally, the neck is contracted to ensure sealing. For each cavity-building segment, a set of clearly defined target cavity morphology parameters are pre-defined, specifically including the target cavity diameter, target cavity height, elevation corresponding to the target cavity top burial depth, target cavity bottom elevation, and a target dissolution boundary contour curve that fully describes the ideal dissolution boundary profile. Step one provides a precise construction blueprint for the entire cavity-building process from the outset, making subsequent control based on a solid foundation.

[0054] Before commencing construction of any cavity segment, step two, namely the digital reconstruction of the current morphology, is performed. High-precision point cloud data of the cavity walls is acquired using sonar measurement equipment lowered into the salt cavity, while brine samples at different depths within the cavity are collected to analyze their concentration distribution. All acquired data is then fused and processed to construct a digital model reflecting the true state of the salt cavity at the current moment. This digital model serves as the benchmark for all subsequent control decisions, ensuring the real-time nature and accuracy of control.

[0055] The process then proceeds to step three, which involves the precise calculation of the cavity deviation. The control system uses the current digital model of the salt cavity as a basis, extracting the actual radial dimensions at multiple depth locations along the cavity depth direction at preset sampling intervals (e.g., every 0.5 meters or 1 meter), thus generating an actual radial dimension curve. This curve is then compared point-by-point with the target dissolution boundary contour curve preset in step one, calculating the radial difference at each depth point, ultimately forming a radial deviation curve. Simultaneously, the actual cavity top elevation extracted from the digital model is compared with the target cavity top elevation to obtain the cavity top axial deviation value; the actual cavity bottom elevation is compared with the target cavity bottom elevation to obtain the cavity bottom axial deviation value. The radial deviation curve, the cavity top axial deviation value, and the cavity bottom axial deviation value together constitute the cavity deviation quantity describing the difference between the current cavity construction state and the ideal target. This multi-dimensional deviation quantification method provides comprehensive and accurate input for subsequent refined control.

[0056] After obtaining the cavity deviation, the core step four is executed, namely the real-time dynamic adjustment of process parameters. The control system intelligently adjusts the cavity construction process parameters based on the specific characteristics of the cavity deviation, combined with the preset cavity stability threshold and a built-in dynamic dissolution rate model. These adjustable process parameters include at least the water injection flow rate, water injection pressure, brine discharge flow rate, and solvent inhibition injection position.

[0057] In a specific implementation scenario, the adjustment process for the water injection flow rate is as follows: When the radial deviation curve generated in step three shows that the actual radial dimension is consistently smaller than the target radial dimension within a certain depth range, and the deviation reaches a preset under-dissolution threshold, the range is determined to be an under-dissolution zone. This indicates that the dissolution rate in this area is too slow. The control system then increases the water injection flow rate accordingly, with the increase being sufficient to improve the dissolution rate in this area, and continuously monitors the morphological changes in this area until its actual radial dimension recovers to a preset acceptable range of the target radial dimension. Conversely, when the radial deviation curve shows that there is an over-dissolution zone in a certain depth range, the system reduces the water injection flow rate to suppress excessive dissolution, and simultaneously adjusts the position of the solvent inhibitor injection to the upper boundary of the over-dissolution zone to form a protective barrier and prevent dissolution from expanding to unwanted areas above.

[0058] In another specific implementation scenario, regarding the control of the cavity top shape, the system adjusts the solvent injection position based on the axial deviation value of the cavity top. When the actual cavity top elevation deviates from the target cavity top elevation by a certain direction and magnitude, the system will correspondingly adjust the moving direction and distance of the solvent injection position. The magnitude of the displacement is usually determined according to the deviation amount according to a preset proportional relationship. For example, the larger the deviation, the larger the adjustment range. Through this continuous position adjustment, the upward erosion rate of the cavity top can be precisely controlled, so that the cavity top elevation gradually and smoothly approaches the target value.

[0059] Furthermore, to achieve more precise control over the cavity top, while adjusting the injection position of the inhibitor, the injection concentration and flow rate of the inhibitor can also be adjusted synchronously based on the axial deviation value of the cavity top. For example, when the actual cavity top elevation is lower than the target cavity top elevation (meaning insufficient dissolution), the injection concentration of the inhibitor and its flow rate will be appropriately reduced to weaken the inhibitory effect and promote cavity top dissolution. Conversely, when the actual cavity top elevation is higher than the target cavity top elevation (meaning excessively fast dissolution), the inhibitory effect will be enhanced by increasing the inhibitory concentration and the flow rate. Through the three-dimensional coordinated adjustment of the inhibitor injection position, concentration, and flow rate, precise control of the cavity top dissolution rate is achieved.

[0060] Furthermore, the adjustment of the brine discharge flow rate mainly relies on a dynamic dissolution rate model. This model can quickly calculate the theoretical dissolution rate under current conditions based on current process parameters (such as water injection flow rate and pressure) and real-time monitored brine concentration distribution data. At the same time, the system calculates the actual dissolution rate by comparing the changes in cavity morphology obtained from two sonar measurements. When the deviation between the actual and theoretical dissolution rates reaches a preset inefficient dissolution threshold, it indicates that the brine concentration in the cavity may have deviated from the optimal dissolution concentration range. At this time, the brine discharge flow rate is increased or decreased accordingly to adjust the brine replacement rate, so that the dissolution environment in the cavity is always kept in an efficient state, thereby prompting the actual dissolution rate to approach the theoretical dissolution rate again.

[0061] The process of establishing the dynamic dissolution rate model is as follows: rock samples of the target salt layer are collected, and dissolution rate experiments are conducted in the laboratory under different temperatures, pressures, and brine concentration gradients to obtain the multivariate nonlinear regression relationship between the dissolution rate and these influencing factors; actual cavity-building data from historical cavity-building projects in the same salt layer are collected, and the coefficients in the above regression relationship are corrected and optimized using these valuable field data to more accurately reflect the dissolution law under complex geological and engineering conditions on site; this corrected and optimized regression relationship is embedded into the on-site control system to form a practical model that can dynamically predict the dissolution rate under current conditions based on real-time monitoring data.

[0062] After completing the parameter adjustments in step four, proceed to step five, which involves continuing the dissolution cavity construction under the optimized process parameters and monitoring the cavity morphology changes in real time. The monitoring process is as follows: During the construction of the current cavity segment, sonar is periodically deployed at preset time intervals (e.g., every 4 hours or daily) to take measurements, acquiring real-time point cloud data of the cavity morphology with each measurement. The control system performs differential fusion processing on these real-time point cloud data and the digital model of the cavity morphology from the previous cycle to generate a dynamic evolution sequence of the cavity morphology. This sequence includes not only changes in the radial dimensions of the cavity and changes in the elevation of the cavity top and bottom, but also information such as the migration velocity of the dissolution boundary. This dynamic evolution sequence is compared in real time with the target cavity morphology parameters preset in step one. Once the morphological deviation of a certain local area is detected to exceed the preset deviation threshold corresponding to the cavity segment, the dynamic adjustment mechanism in step four is immediately triggered again, forming a tight closed-loop control cycle. Only when the deviation between the actual dissolution boundary and the preset dissolution boundary is stable within the preset allowable range is the current cavity segment determined to be completed, and the preset target parameters of the next cavity segment are automatically loaded. Steps two to five are repeated until the construction of all cavity segments is completed.

[0063] The real-time monitoring process also includes real-time assessment of cavity stability. Based on the dynamic evolution sequence of the cavity morphology, the curvature change characteristics of the cavity contour are automatically extracted, and the radius of curvature of each local region on the cavity surface is calculated. The local radius of curvature is compared with a preset critical radius of curvature threshold. When the radius of curvature of a certain local region is less than the critical radius of curvature threshold, and the deviation reaches a preset risk coefficient, it is determined that there is a risk of instability in that region. At this time, local protective adjustment measures are automatically initiated at the corresponding height position of that region. For example, the water injection flow rate in that region is immediately reduced, the brine discharge flow rate is increased to reduce the hydrostatic pressure, and the position of the solvent inhibitor injection is adjusted to the lower boundary of that region to prevent the unstable region from expanding further, thereby ensuring the safety of the cavity construction process.

[0064] The critical radius of curvature threshold is determined as follows: Based on the rock mechanical parameters of the target salt layer, such as uniaxial compressive strength, elastic modulus, Poisson's ratio, and cohesion, a stress distribution model of the salt cavern cavity is established using three-dimensional numerical simulation software. In this stress distribution model, a detailed stress analysis is performed on the cavity surface with different radii of curvature to obtain the radius of curvature corresponding to when the maximum principal stress on the cavity surface reaches a preset stress threshold (e.g., 80% of the rock tensile strength), and this radius is determined as the critical radius of curvature threshold. Considering that different cavity-building segments have different requirements for cavity stability, this critical radius of curvature threshold can be set separately according to the characteristics of each segment.

[0065] In step five, a fuzzy adaptive PID controller is employed to achieve an automatic and smooth transition that keeps the deviation within the allowable range. Specifically, the dynamic evolution sequence of the cavity morphology, real-time process parameters, and the prediction results of the dynamic dissolution rate model are all input to the fuzzy adaptive PID controller. This controller uses the current cavity deviation and its rate of change as input variables. After fuzzification, fuzzy inference, and defuzzification, it outputs control commands such as adjustments to the water injection flow rate, water injection pressure, brine discharge flow rate, and solvent injection position. Through preset fuzzy inference rules, the proportional, integral, and derivative coefficients of the PID controller can be tuned online and dynamically, thereby achieving adaptive and intelligent adjustment of the cavity-building process parameters. When the detected cavity deviation is consistently less than a preset percentage (e.g., consistently less than 5% of the allowable range) for the cavity segment, and the rate of change of the deviation approaches zero, it can be determined that the deviation has stabilized within the allowable range. At this time, the control system automatically outputs the current cavity segment completion command and smoothly switches to the preset target parameters of the next cavity segment to continue executing closed-loop control.

[0066] Working Principle: Through the aforementioned segmented planning, real-time sensing, deviation quantification, dynamic control, and closed-loop feedback technical solutions, not only can the final shape of the salt cavity be precisely controlled to perfectly meet the design requirements of compressed air energy storage, significantly improving the effective volume utilization rate of the salt cavity, but also the risk of cavity instability can be effectively prevented through real-time stability assessment and local protection measures, ensuring construction safety. Simultaneously, through a dynamic dissolution rate model and adaptive PID control, dissolution efficiency is optimized, the cavity construction cycle is shortened, and engineering costs are reduced. This invention achieves a fundamental shift from extensive, experience-based cavity construction to refined, intelligent cavity construction, and has significant engineering application value for promoting the development of large-scale compressed air energy storage technology.

[0067] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0068] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for controlling the salt cavern creation process for compressed air energy storage, characterized in that, Includes the following steps: Step 1: Based on the 3D seismic data and well logging data of the target salt layer, establish a 3D geological model for salt cavern construction. According to the salt rock purity distribution, interlayer distribution and salt layer thickness distribution of the target salt layer, the entire cavity construction process is divided into cavity construction segments carried out in sequence: bottom dissolution segment, main body expansion segment, top forming segment and neck contraction segment. Specifically, target cavity morphology parameters are preset for each cavity segment, including the target cavity diameter, target cavity height, target cavity top burial depth, target cavity bottom elevation, and target dissolution boundary contour curve of the segment. Step 2: Before the current cavity construction begins, collect sonar measurement data and brine concentration distribution data within the salt cavity to construct a digital model of the current salt cavity morphology; Step 3: Using the digital model of the current salt cavity morphology as a basis, extract the actual radial dimensions at multiple depth positions along the cavity depth direction at a preset sampling interval to generate an actual radial dimension curve. Compare the actual radial dimension curve with the radial dimensions at the corresponding depth positions in the target dissolution boundary contour curve point by point to obtain a radial deviation curve. At the same time, compare the actual cavity top elevation with the preset elevation corresponding to the target cavity top burial depth to obtain the cavity top axial deviation value. Compare the actual cavity bottom elevation with the target cavity bottom elevation to obtain the cavity bottom axial deviation value. Use the radial deviation curve, the cavity top axial deviation value, and the cavity bottom axial deviation value together as the cavity deviation amount. Step 4: Based on the cavity deviation, combined with the preset cavity stability threshold and dynamic dissolution rate model, dynamically adjust at least one process parameter in the current cavity segment, including water injection flow rate, water injection pressure, brine discharge flow rate, and solvent injection position. Step 5: Under the adjusted process parameters, perform dissolution and cavity creation, and monitor the changes in cavity morphology in real time until the deviation between the actual dissolution boundary of the current cavity creation segment and the preset dissolution boundary stabilizes within the preset allowable range. Then, the current cavity creation segment is determined to be completed, and the process automatically enters the preset next cavity creation segment to continue executing steps 2 to 5 until the construction of all cavity creation segments is completed.

2. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The specific process of dynamically adjusting the water injection flow rate in real time based on the cavity deviation in step four is as follows: When the radial deviation curve shows that the actual radial dimension of a certain depth range is less than the target radial dimension of the range and reaches a preset under-dissolution threshold, the range is determined to be an under-dissolution zone. Then, the water injection flow rate is increased at the corresponding height position, and the increase is sufficient to increase the dissolution rate of the range. The monitoring continues until the actual radial dimension of the range recovers to a preset qualified range of the target radial dimension. When the radial deviation curve shows that the actual radial dimension of a certain depth range is greater than the target radial dimension of the range and reaches a preset over-dissolution threshold, the range is determined to be an over-dissolution zone. The water injection flow rate is then reduced, and the reduction is sufficient to suppress the excessive dissolution in the range. At the same time, the position of the solvent inhibitor injection is adjusted to the upper boundary of the over-dissolution zone.

3. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The specific process of dynamically adjusting the injection position of the anti-solvent in real time based on the cavity deviation in step four is as follows: Based on the cavity top axial deviation value, when the actual cavity top elevation deviates from the target cavity top elevation by a preset deviation direction and magnitude, the direction and distance of the solvent injection position are adjusted accordingly. The displacement distance is determined according to a preset ratio based on the deviation between the actual cavity top elevation and the target cavity top elevation. By continuously adjusting the position of the solvent injection, the upward dissolution rate of the cavity top is controlled, so that the cavity top elevation gradually approaches the target cavity top elevation.

4. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 3, characterized in that, In step four, while dynamically adjusting the injection position of the solvent inhibitor in real time, the injection concentration and flow rate of the solvent inhibitor are also adjusted synchronously based on the axial deviation value at the top of the cavity. The specific process is as follows: Based on the direction and degree of deviation of the actual cavity top elevation from the target cavity top elevation, the injection concentration and injection flow rate of the inhibitor are adjusted in a coordinated manner. When the actual cavity top elevation is lower than the target cavity top elevation, the goal is to weaken the dissolution inhibition effect and promote cavity top erosion, so the concentration of the dissolution inhibitor and the flow rate of the dissolution inhibitor are reduced. When the actual cavity top elevation is higher than the target cavity top elevation, the goal is to enhance the anti-dissolution effect and suppress excessive dissolution at the cavity top, so the concentration of anti-dissolution agent injected and the flow rate of anti-dissolution agent injected are increased. The dissolution rate at the top of the cavity can be controlled by three-dimensional coordinated adjustment of the injection location, injection concentration, and injection flow rate of the solvent inhibitor.

5. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The specific process of dynamically adjusting the brine discharge flow rate in real time based on the cavity deviation in step four is as follows: Based on the dynamic dissolution rate model, the theoretical dissolution rate under the current conditions is calculated by inputting the current process parameters and the real-time monitored brine concentration distribution data. The theoretical erosion rate is compared with the actual erosion rate, which is calculated based on the cavity morphology change obtained from two consecutive sonar measurements. When the deviation between the actual dissolution rate and the theoretical dissolution rate reaches a preset inefficient dissolution threshold, it is determined that the brine concentration in the cavity deviates from the optimal dissolution concentration range. In this case, the brine discharge flow rate is increased or decreased accordingly to adjust the brine replacement rate so that the actual dissolution rate approaches the theoretical dissolution rate.

6. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The process of establishing the dynamic dissolution rate model is as follows: Rock samples were collected from the target salt layer, and indoor experiments on dissolution rate were conducted under different temperature gradients, pressure gradients, and brine concentration gradients to obtain the multivariate nonlinear regression relationship between dissolution rate and temperature, pressure, and brine concentration. Collect actual cavity-making data from historical cavity-making projects in the same salt layer, and use the historical cavity-making data to correct and optimize the coefficients in the multivariate nonlinear regression equation to make it more consistent with the actual situation on site. The modified and optimized regression relationship is embedded into the field control system to form a dynamic corrosion rate model that dynamically predicts the corrosion rate under current conditions based on real-time monitoring data.

7. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The specific process of real-time monitoring of cavity morphology changes in step five is as follows: During the current cavity segmentation construction process, sonar measurements are periodically performed at preset time intervals, and each sonar measurement acquires real-time point cloud data of the cavity morphology. The real-time point cloud data is differentially fused with the previous cycle's digital model of the cavity morphology to generate a dynamic evolution sequence of the cavity morphology, including the change in the radial dimension of the cavity, the change in the elevation of the cavity top and bottom, and the pushing speed of the dissolution boundary. The dynamic evolution sequence is compared with the preset target cavity morphology parameters in real time. Once the cavity morphology deviation of a certain local area is detected to exceed the preset deviation threshold corresponding to the cavity segment, the dynamic adjustment mechanism in step four is immediately triggered.

8. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, Step five, which involves real-time monitoring of cavity morphology changes, also includes real-time assessment of cavity stability. The specific process is as follows: Based on the dynamic evolution sequence of the cavity morphology, the curvature change characteristics of the cavity contour are extracted, and the radius of curvature of each local region on the cavity surface is calculated. The radius of curvature is compared with a preset critical radius of curvature threshold. When the radius of curvature of a certain local area is less than the critical radius of curvature threshold and reaches a preset risk coefficient, it is determined that there is a risk of instability in the area, and local protective adjustment measures are initiated at the corresponding height position of the area. The local protective adjustment measures include: reducing the water injection flow rate, increasing the brine discharge flow rate, and adjusting the solvent injection position to the lower boundary of the area.

9. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 8, characterized in that, The critical radius of curvature threshold is determined as follows: Based on the rock mechanical parameters of the target salt layer, including uniaxial compressive strength, elastic modulus, Poisson's ratio and cohesion, a stress distribution model of the salt cavern cavity is established through three-dimensional numerical simulation. In the stress distribution model, stress analysis is performed on the cavity surface with different radii of curvature to obtain the radius of curvature corresponding to the maximum principal stress on the cavity surface when it reaches a preset stress threshold and determine it as the critical radius of curvature threshold. The critical radius of curvature threshold is set separately for different cavity segmentation.

10. The method for controlling the salt cavern creation process for compressed air energy storage according to claim 1, characterized in that, The specific implementation method for repeating steps two through five in step five until the deviation stabilizes within the allowable range is as follows: The dynamic evolution sequence of cavity morphology, real-time process parameters, and prediction results of the dynamic dissolution rate model are all input into the fuzzy adaptive PID controller. The fuzzy adaptive PID controller uses the cavity deviation and its rate of change as input variables, and the water injection flow rate adjustment, water injection pressure adjustment, brine discharge flow rate adjustment, and solvent injection position adjustment as output variables. The proportional, integral, and derivative coefficients of the PID controller are tuned online using fuzzy inference rules, enabling adaptive adjustment of the cavity-forming process parameters. When the cavity deviation is consistently less than a preset percentage of the allowable range for the cavity segment and the rate of change of deviation approaches zero, it is determined that the deviation has stabilized within the allowable range. The control system automatically outputs the current cavity segment completion command and switches to the preset target parameters of the next cavity segment to continue execution.

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