Salt cavern carbon storage stability evaluation method and system based on multi-source data

Abstract

The invention discloses a salt cavern carbon storage stability evaluation method and system based on multi-source data, and belongs to the technical field of stability evaluation. Collecting geological survey data of an area where the salt cavern carbon storage library is located, and constructing a geological structure model; outputting a temperature and pressure change parameter range according to the historical meteorological data; extracting salt cavern operation pressure abnormal data; the temperature and pressure change parameter range and the operation pressure abnormal data are combined, and the action time length and the action depth range are set in combination with the cavity burial depth data; defining a disturbance input vector, and constructing a response evolution rate index; constructing response evolution strength based on the response evolution rate index; setting a dynamic risk value calculation function based on the response evolution strength; according to the method, the salt cavern stability is comprehensively evaluated from static structure analysis to dynamic evolution response, and the risk identification capability and decision-making efficiency in a complex environment and an extreme working condition are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of stability evaluation, and in particular to a salt cavern carbon storage stability evaluation method and system based on multi-source data. Background Art

[0002] Currently, salt caverns are primarily used for underground storage of energy sources such as natural gas and hydrogen. With the rise of carbon storage technology, their potential for carbon dioxide sequestration is becoming increasingly apparent. Furthermore, rock salt formations possess unique mechanical characteristics, such as creep, plasticity, and weak permeability. This makes the structural stability of salt caverns under disturbance conditions such as high-pressure injection and production a key issue for engineering safety. Related research has gradually focused on constructing detailed geological models, simulating multi-source disturbance scenarios, and evaluating rock mass response mechanisms. Various evaluation frameworks have been initially established, based on finite element simulation, discrete element analysis, and risk matrices. For example, the analytic hierarchy process (AHP) is used in conjunction with geological parameters (such as salt mine core data and interlayer distribution) for stability assessment, and FLAC3D software is used for long-term creep simulation of salt cavern gas storage (e.g., the stability analysis based on the Mohr-Coulomb model in the Zhaoji Salt Mine case). These frameworks provide technical support for engineering practice.

[0003] However, existing salt cavern carbon storage stability assessment methods commonly suffer from problems such as a single data dimension, idealized boundary settings, and a crude characterization of disturbance response mechanisms. For example, while the analytic hierarchy process (AHP) can achieve qualitative-to-quantitative transformation through multi-factor weight assignment, it lacks the ability to respond in real time to dynamic disturbances (such as sudden temperature and pressure changes and changes in injection and production frequency). Numerical tools such as FLAC3D, while capable of simulating long-term creep behavior, struggle to integrate multiple data sources (such as sudden meteorological changes and operational anomalies) for dynamic risk modeling. Most studies consider only a single dimension, namely, stratigraphic structure or injection and production parameters, lacking the ability to integrate multiple sources of information (such as meteorological data, historical operational data, and geological survey data). This makes it difficult to accurately reflect the nonlinear response of salt caverns under multiple disturbances in complex environments. Furthermore, existing methods often use idealized operating conditions for simulations of sudden temperature and pressure changes, lacking boundary construction mechanisms based on historical measured data, and are unable to dynamically evaluate the coupling between disturbance intensity and structural evolution. More critically, most current model evaluation metrics fail to incorporate attenuation controls for factors such as disturbance depth and temporal duration, resulting in limited risk warning accuracy. Summary of the Invention

[0004] The purpose of the present invention is to provide a salt cavern carbon storage stability evaluation method and system based on multi-source data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A salt cavern carbon storage stability evaluation method based on multi-source data comprises the following steps: step S1: collecting geological survey data of the area where the salt cavern carbon storage is located and constructing a geological structure model; step S2: outputting the temperature and pressure variation parameter range based on historical meteorological data; extracting salt cavern operating pressure anomaly data; combining the temperature and pressure variation parameter range with the operating pressure anomaly data, and setting the action time length and action depth range in combination with cavity burial depth data; step S3: defining a disturbance input vector and constructing a response evolution rate index; constructing a response evolution intensity based on the response evolution rate index; step S4: setting a dynamic risk value calculation function based on the response evolution intensity; presetting a threshold interval, analyzing, and performing stability warning.

[0007] As a preferred solution of the salt cavern carbon storage stability evaluation method based on multi-source data described in the present invention, geological exploration data of the area where the salt cavern carbon storage is located is collected. The geological exploration data includes salt mine core data, stratigraphic structure data, interlayer distribution data, cavity burial depth data, and stratigraphic inclination data. Based on the geological exploration data, a geological structure model is constructed. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer. Specifically, the following:

[0008] According to the salt mine core data, the lithology types at different depths are recorded and the preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratum structure data, the stratum structure profile is output;

[0009] In the rock layer structure section, a rock layer structure model including interlayer information is output based on the interlayer distribution data; based on the rock layer structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output;

[0010] Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the stratum dip data, a three-dimensional spatial structure diagram is constructed; in the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

[0011] As a preferred embodiment of the salt cavern carbon storage stability evaluation method based on multi-source data described in the present invention, based on historical meteorological data, temperature and pressure records with sudden changes are extracted, the change amplitude and change rate are recorded, and the temperature and pressure change parameter range is output; from the salt cavern operation history data, abnormal operating pressure data occurring within a short period of time is extracted, such as sudden increases in operating pressure or changes in injection and production frequency, and the corresponding operating condition change amplitude and duration are output;

[0012] The temperature and pressure change parameter range is combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions to reflect different types of temperature and pressure mutation scenarios; combined with the cavity burial depth data, the action time length and action depth range are set for each type of temperature and pressure mutation conditions as the boundary control basis for subsequent simulations; the temperature change, pressure change, action time and action depth are unified into an input parameter set.

[0013] As a preferred solution of the salt cavern carbon storage stability evaluation method based on multi-source data described in the present invention, the disturbance input vector is defined as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i shows the depth of the i-th disturbance event;

[0014] Construct the response evolution rate indicator as follows:

[0015]

[0016] Wherein, α and β represent the preset weighting factors of temperature change and pressure change, γ1 and γ2 represent the preset sensitivity factors (controlling the degree of nonlinear enhancement (such as the sensitivity of crack propagation to temperature or pressure changes)), λ represents the preset action time weighting factor, and μ represents the preset depth attenuation coefficient;

[0017] It should be noted that the first term in this formula represents the combined effects of thermal and pressure disturbances, and does not use linear weighting, but rather uses exponential amplification for nonlinear amplification. This reflects the fact that in high-temperature / high-pressure zones, effects such as material crack expansion and interface instability are more likely to occur and grow faster. The longer the middle term simulates the disturbance, the more destructive it is to the rock mass, but it will not increase indefinitely. This reflects the physical law that the cumulative response has a saturation upper limit, such as the gradual weakening of the time effect of material creep or damage. The last term is based on the mechanism of the gradual attenuation of thermal and pressure disturbances in actual underground structures. The deep response will be much smaller than the shallow response, which conforms to the basic laws of thermal diffusion and stress wave attenuation. The various parameters can be flexibly adjusted according to the different salt cavern geological structures, burial depths, and pressure / temperature histories. It has good versatility and adaptability and can be extended to different types of salt cavern carbon storage evaluation tasks.

[0018] Based on the response evolution rate indicator, the response evolution intensity is constructed as follows:

[0019]

[0020] Among them, w i represents the impact coefficient of the i-th disturbance event, and Λ represents the response evolution intensity under the current disturbance history.

[0021] As a preferred solution of the salt cavern carbon storage stability evaluation method based on multi-source data described in the present invention, a dynamic risk value calculation function is set based on the response evolution intensity Λ, as follows:

[0022] Ω=κ1·Λ+κ2·ΔT max +κ3·ΔP max

[0023] Where Λ represents the response evolution intensity under the current disturbance history, ΔT max Indicates the maximum temperature change in the current cycle, ΔP max represents the maximum pressure change in the current cycle, κ1, κ2, and κ3 represent the preset empirical control parameters, characterizing the contribution of each factor to stability, and Ω represents the dynamic risk value;

[0024] A risk threshold interval is preset, and if the dynamic risk value Ω is less than the minimum value within the risk threshold interval, it is determined that the structural stability of the salt cavern under continuous disturbance is excellent;

[0025] If the dynamic risk value Ω is within the risk threshold range, it is determined that the salt cavern is unstable under continuous disturbance. If the dynamic risk value Ω is greater than the maximum value within the risk threshold range, it is determined that the structural stability of the salt cavern is poor under continuous disturbance, and a stability warning is issued.

[0026] A salt cavern carbon storage stability evaluation system based on multi-source data includes: a data acquisition and model building module, a data acquisition and processing module, an index and strength calculation module, and a risk calculation, analysis and early warning module;

[0027] The data collection and model building module collects geological survey data of the area where the salt cavern carbon storage reservoir is located and builds a geological structure model;

[0028] The data acquisition and processing module outputs the temperature and pressure variation parameter range based on historical meteorological data; extracts abnormal operating pressure data of the salt cavern; combines the temperature and pressure variation parameter range with the abnormal operating pressure data, and sets the action time length and action depth range in combination with the cavern burial depth data;

[0029] The index and strength calculation module: defines a disturbance input vector and constructs a response evolution rate index; and constructs a response evolution intensity based on the response evolution rate index;

[0030] The risk calculation and analysis warning module: sets a dynamic risk value calculation function based on the response evolution intensity; presets a threshold interval, analyzes and issues stability warnings.

[0031] Furthermore, the data acquisition and model building module includes a data acquisition and model building unit;

[0032] The data acquisition and model building unit collects geological survey data of the area where the salt cavern carbon storage reservoir is located, including salt mine core data, stratigraphic structure data, interlayer distribution data, cavity depth data, and stratigraphic inclination data, and builds a geological structure model based on the geological survey data. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer, as follows:

[0033] According to the salt mine core data, the lithology types at different depths are recorded and the preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratum structure data, the stratum structure profile is output;

[0034] In the rock layer structure section, a rock layer structure model including interlayer information is output based on the interlayer distribution data; based on the rock layer structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output;

[0035] Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the stratum dip data, a three-dimensional spatial structure diagram is constructed; in the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

[0036] Furthermore, the data acquisition and processing module includes a data acquisition and processing unit;

[0037] The data acquisition and processing unit extracts temperature and pressure records with sudden changes based on historical meteorological data, records the magnitude and rate of change, and outputs the range of temperature and pressure change parameters. From the historical salt cavern operation data, it extracts abnormal operating pressure data that occurs within a short period of time, including sudden increases in operating pressure or changes in injection and production frequency, and outputs the corresponding operating condition change magnitude and duration.

[0038] The temperature and pressure change parameter range is combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions; combined with the cavity burial depth data, the action time length and action depth range are set for various temperature and pressure mutation conditions; the temperature change, pressure change, action time and action depth are unified into an input parameter set.

[0039] Furthermore, the index and strength calculation module includes an index calculation unit and a strength calculation unit;

[0040] The indicator calculation unit: defines the disturbance input vector, which is recorded as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i Indicates the depth of the i-th disturbance event; constructs the response evolution rate index;

[0041] The intensity calculation unit is configured to construct a response evolution intensity Λ based on the response evolution rate indicator.

[0042] Furthermore, the risk calculation and analysis warning module includes a risk calculation unit and an analysis warning unit;

[0043] The risk calculation unit sets a dynamic risk value calculation function based on the response evolution intensity Λ;

[0044] The analysis and early warning unit presets a risk threshold interval. If the dynamic risk value Ω is less than the minimum value within the risk threshold interval, the salt cavern is judged to have excellent structural stability under continuous disturbances. If the dynamic risk value Ω is within the risk threshold interval, the salt cavern is judged to be unstable under continuous disturbances. If the dynamic risk value Ω is greater than the maximum value within the risk threshold interval, the salt cavern is judged to have poor structural stability under continuous disturbances, and a stability warning is issued.

[0045] Compared with the existing technology, the beneficial effects achieved by the present invention are as follows: in the salt cavern carbon storage reservoir stability evaluation method and system based on multi-source data provided by the present invention, an accurate geological structure model is first constructed to provide a physical basis for subsequent stability simulation; by integrating historical meteorological data and salt cavern operation abnormality data, setting a variety of disturbance boundary conditions and considering the action time and depth, a comprehensive simulation of complex working conditions is achieved; further introducing disturbance input vectors and response evolution indicators, quantifying the disturbance intensity and capturing its spatiotemporal evolution characteristics, and establishing a cumulative characterization system for the historical impact of disturbances; finally, through the risk value calculation function and the graded threshold interval, a dynamic stability early warning mechanism is constructed. The overall technical solution not only realizes the comprehensive evaluation of salt cavern stability from static structural analysis to dynamic evolution response, but also significantly improves the risk identification ability and decision-making efficiency in complex environments and extreme working conditions, and has good engineering adaptability and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0047] Figure 1 This is a schematic diagram of the steps of a salt cavern carbon storage stability evaluation method based on multi-source data of the present invention;

[0048] Figure 2 It is a structural schematic diagram of a salt cavern carbon storage stability evaluation system based on multi-source data of the present invention. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] See also Figure 1 In this embodiment 1, a method for evaluating the stability of a salt cavern carbon storage reservoir based on multi-source data is provided, the method comprising the following steps:

[0051] Step S1: Collect geological survey data of the area where the salt cavern carbon storage reservoir is located and construct a geological structure model.

[0052] Specifically, geological survey data of the area where the salt cavern carbon storage reservoir is located is collected. The geological survey data includes salt mine core data, stratigraphic structure data, interlayer distribution data, cavity burial depth data, and stratigraphic dip data. Based on the geological survey data, a geological structure model is constructed. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer. The specific details are as follows:

[0053] Based on the salt mine core data, the lithology types at different depths are recorded, and preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratigraphic structure data, the rock structure profile is output. In the actual construction of salt cavern carbon storage, the lithology at different depths has a significant impact on the stability of the salt cavern. For example, in some areas of salt mines, the roof and interlayers are silty mudstone, which poses a risk of leakage when storing high-pressure CO2 gas. Therefore, it is crucial to accurately grasp the lithology distribution.

[0054] In the rock formation structure profile, a rock formation structure model containing interlayer information is output based on the interlayer distribution data; based on the rock formation structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output; for example, in the design process of a salt cavern gas storage reservoir, the relationship between the cavity and the surrounding rock is determined through the analysis of the interlayer distribution and the cavity burial depth, which provides a basis for subsequent stability evaluation.

[0055] Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the stratum dip data, a three-dimensional spatial structure diagram is constructed; in the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

[0056] In the present invention, by collecting multi-dimensional geological survey data including salt mine core data, stratigraphic structure data, interlayer distribution data, cavity burial depth data and stratigraphic inclination data, a detailed geological structure model is constructed, which realizes a comprehensive characterization of the rock salt layer structure, lithologic characteristics and mechanical differences around the salt cavern carbon storage reservoir. Furthermore, the model can be used to analyze the contact relationship and stress state between the cavity and the surrounding rock, and is particularly instructive for analyzing the stability and stress conduction path of the salt cavern. The implementation of this step provides a physical basis for the subsequent thermal and pressure disturbance response and risk analysis, improves the accuracy and credibility of the simulation boundary, and thus enhances the scientific nature of the overall stability evaluation.

[0057] Step S2: Output the temperature and pressure variation parameter range based on historical meteorological data; extract the salt cavern operating pressure anomaly data; combine the temperature and pressure variation parameter range with the operating pressure anomaly data, and set the action time length and action depth range in combination with the cavern burial depth data.

[0058] Specifically, based on historical meteorological data, extract temperature and pressure records with sudden change characteristics, record the change amplitude and change rate, and output the temperature and pressure change parameter range; in the salt cavern operation history data, extract the abnormal operating pressure data that occurred in a short period of time, and the abnormal operating pressure data includes a sudden increase in operating pressure or a change in injection and production frequency, and output the corresponding operating condition change amplitude and duration; for example, in the actual salt cavern operation process, there may be a sudden increase in operating pressure due to equipment failure, or a change in injection and production frequency due to production plan adjustment. These abnormal situations need to be considered in the evaluation.

[0059] The temperature and pressure variation parameter ranges are combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions to reflect different types of temperature and pressure mutation scenarios. Combined with the cavity depth data, the duration and depth range of each temperature and pressure mutation condition are set to serve as the boundary control basis for subsequent simulations. The temperature change, pressure change, duration, and depth are unified into a set of input parameters. In the actual operation of salt cavern carbon storage, cavities at different depths respond differently to temperature and pressure changes. For example, beyond 800 meters, the CO2 density does not change much with depth, but the impact of temperature and pressure changes on cavity stability persists. This step, by setting boundary conditions based on the cavity depth, is more realistic.

[0060] In the present invention, by combining external natural meteorological data (such as temperature and pressure mutation records) with internal operating conditions (such as pressure surges or changes in injection and production frequency), multiple simulation boundary conditions are generated, achieving coverage modeling of multiple real disturbance scenarios. Furthermore, the time and space range of the disturbance impact is set in combination with the cavity burial depth data, so that the simulation input has spatial hierarchy and time evolution. This step enables the model to not only reflect the stability under normal operating conditions, but also to evaluate the dynamic stability response under extreme conditions (such as heavy rain, extremely hot weather, and operational mutations), thereby significantly improving the adaptability and foresight of risk analysis.

[0061] Step S3: define a disturbance input vector and construct a response evolution rate index; based on the response evolution rate index, construct a response evolution intensity.

[0062] Specifically, define the perturbation input vector, denoted as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i shows the depth of the i-th disturbance event;

[0063] Construct the response evolution rate indicator as follows:

[0064]

[0065] Among them, α and β represent the preset weighting factors of the temperature change and pressure change, γ1 and γ2 represent the preset sensitivity factors (which control the degree of nonlinear enhancement (such as the sensitivity of crack propagation to temperature or pressure changes)), λ represents the preset action time weighting factor, and μ represents the preset depth attenuation coefficient. In the actual salt cavern carbon storage process, temperature and pressure changes will cause changes in the mechanical properties of salt rock. For example, the creep characteristics of salt rock are significantly affected by temperature and pressure. By introducing weighting factors and sensitivity coefficients, this formula comprehensively considers the impact of these factors on salt cavern stability.

[0066] Based on the response evolution rate indicator, the response evolution intensity is constructed as follows:

[0067]

[0068] Among them, w i represents the impact coefficient of the i-th disturbance event, and Λ represents the response evolution intensity under the current disturbance history.

[0069] In the present invention, this step quantifies the disturbance process into a disturbance input vector (including temperature change, pressure change, action time and action depth), introduces weight factors and sensitivity coefficients, and constructs a response evolution rate index of nonlinear enhancement characteristics. By integrating temperature and pressure factors with time and space dimensions, a mathematical expression that can measure the degree of disturbance impact is formed. Furthermore, the response evolution rate is integrated into the intensity of the historical impact of the disturbance, forming an indicator system that reflects the cumulative effect of multiple rounds of disturbances. This method innovatively links transient disturbances with long-term risks, provides quantitative support for risk trend prediction, thereby realizing the transition from single-point analysis to evolutionary analysis, and enhancing the ability to judge the long-term stability of salt caverns.

[0070] Step S4: Based on the response evolution intensity, set the dynamic risk value calculation function; preset the threshold range, analyze and perform stability warning.

[0071] Specifically, based on the response evolution intensity Λ, a dynamic risk value calculation function is set as follows:

[0072] Ω=κ1·Λ+κ2·ΔT max +κ3·ΔP max

[0073] Where Λ represents the response evolution intensity under the current disturbance history, ΔT max Indicates the maximum temperature change in the current cycle, ΔP max represents the maximum pressure change in the current cycle, κ1, κ2, and κ3 are preset empirical control parameters that characterize the contribution of each factor to stability, and Ω represents the dynamic risk value. In practical applications, different salt cavern carbon storage reservoirs have different stability requirements due to factors such as geological conditions and cavity structures. By setting the empirical control parameters κ1, κ2, and κ3, the evaluation requirements of different salt caverns can be more flexibly adapted.

[0074] A risk threshold interval is preset, and if the dynamic risk value Ω is less than the minimum value within the risk threshold interval, it is determined that the structural stability of the salt cavern under continuous disturbance is excellent;

[0075] If the dynamic risk value Ω is within the risk threshold range, it is determined that the salt cavern is unstable under continuous disturbance. If the dynamic risk value Ω is greater than the maximum value within the risk threshold range, it is determined that the structural stability of the salt cavern is poor under continuous disturbance, and a stability warning is issued.

[0076] It should be noted that, based on the existing evolution intensity, a dynamic risk value function containing multiple control parameters is established and compared with a preset risk threshold range to achieve the identification and early warning of the stability of the salt cavern structure under the current disturbance state. By integrating the maximum temperature and pressure disturbance parameters with the evolution intensity index, the dynamic risk value comprehensively reflects the risk level of the current state. This step not only achieves the quantitative output of risk but also realizes an automated and graded early warning mechanism by introducing threshold ranges. This improves the real-time and decision-making nature of the salt cavern carbon storage risk response, ensuring the safe and controllable operation of the carbon storage system.

[0077] See also Figure 2 In the second embodiment, a salt cavern carbon storage stability evaluation system based on multi-source data is provided, which includes a data acquisition and model building module, a data acquisition and processing module, an index and strength calculation module, and a risk calculation and analysis warning module.

[0078] The data collection and model building module collects geological survey data of the area where the salt cavern carbon storage reservoir is located and builds a geological structure model;

[0079] The data acquisition and processing module outputs the temperature and pressure variation parameter range based on historical meteorological data; extracts abnormal operating pressure data of the salt cavern; combines the temperature and pressure variation parameter range with the abnormal operating pressure data, and sets the action time length and action depth range in combination with the cavern burial depth data;

[0080] The index and strength calculation module: defines a disturbance input vector and constructs a response evolution rate index; and constructs a response evolution intensity based on the response evolution rate index;

[0081] The risk calculation and analysis warning module: sets a dynamic risk value calculation function based on the response evolution intensity; presets a threshold interval, analyzes and issues stability warnings.

[0082] Furthermore, the data acquisition and model building module includes a data acquisition and model building unit;

[0083] The data acquisition and model building unit collects geological survey data of the area where the salt cavern carbon storage reservoir is located, including salt mine core data, stratigraphic structure data, interlayer distribution data, cavity depth data, and stratigraphic inclination data, and builds a geological structure model based on the geological survey data. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer, as follows:

[0084] According to the salt mine core data, the lithology types at different depths are recorded and the preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratum structure data, the stratum structure profile is output;

[0085] In the rock layer structure section, a rock layer structure model including interlayer information is output based on the interlayer distribution data; based on the rock layer structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output;

[0086] Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the stratum dip data, a three-dimensional spatial structure diagram is constructed; in the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

[0087] Furthermore, the data acquisition and processing module includes a data acquisition and processing unit;

[0088] The data acquisition and processing unit extracts temperature and pressure records with sudden changes based on historical meteorological data, records the magnitude and rate of change, and outputs the range of temperature and pressure change parameters. From the historical salt cavern operation data, it extracts abnormal operating pressure data that occurs within a short period of time, including sudden increases in operating pressure or changes in injection and production frequency, and outputs the corresponding operating condition change magnitude and duration.

[0089] The temperature and pressure change parameter range is combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions; combined with the cavity burial depth data, the action time length and action depth range are set for various temperature and pressure mutation conditions; the temperature change, pressure change, action time and action depth are unified into an input parameter set.

[0090] Furthermore, the index and strength calculation module includes an index calculation unit and a strength calculation unit;

[0091] The indicator calculation unit: defines the disturbance input vector, which is recorded as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i Indicates the depth of the i-th disturbance event; constructs the response evolution rate index;

[0092] The intensity calculation unit is configured to construct a response evolution intensity Λ based on the response evolution rate indicator.

[0093] Furthermore, the risk calculation and analysis warning module includes a risk calculation unit and an analysis warning unit;

[0094] The risk calculation unit sets a dynamic risk value calculation function based on the response evolution intensity Λ;

[0095] The analysis and early warning unit presets a risk threshold interval. If the dynamic risk value Ω is less than the minimum value within the risk threshold interval, the salt cavern is judged to have excellent structural stability under continuous disturbances. If the dynamic risk value Ω is within the risk threshold interval, the salt cavern is judged to be unstable under continuous disturbances. If the dynamic risk value Ω is greater than the maximum value within the risk threshold interval, the salt cavern is judged to have poor structural stability under continuous disturbances, and a stability warning is issued.

[0096] 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.

[0097] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A salt cavern carbon storage stability evaluation method based on multi-source data, characterized in that: The method comprises the following steps: Step S1: Collect geological survey data of the area where the salt cavern carbon storage reservoir is located and construct a geological structure model; Step S2: Output the temperature and pressure variation parameter range based on historical meteorological data; extract the salt cavern operating pressure anomaly data; combine the temperature and pressure variation parameter range with the operating pressure anomaly data, and set the action time length and action depth range in combination with the cavern burial depth data; Step S3: defining a disturbance input vector and constructing a response evolution rate index; constructing a response evolution intensity based on the response evolution rate index; Step S4: Based on the response evolution intensity, set the dynamic risk value calculation function; preset the threshold range, analyze and perform stability warning.

2. The salt cavern carbon storage stability evaluation method based on multi-source data according to claim 1 is characterized in that: The specific implementation process of step S1 includes: Collect geological survey data on the area where the salt cavern carbon storage reservoir is located. The geological survey data includes salt mine core data, stratigraphic structure data, interlayer distribution data, cavity depth data, and stratigraphic dip data. Based on the geological survey data, construct a geological structure model. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer. The specific details are as follows: According to the salt mine core data, the lithology types at different depths are recorded and the preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratum structure data, the stratum structure profile is output; In the rock layer structure section, a rock layer structure model including interlayer information is output based on the interlayer distribution data; based on the rock layer structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output; Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the stratum dip data, a three-dimensional spatial structure diagram is constructed; in the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

3. The salt cavern carbon storage stability evaluation method based on multi-source data according to claim 2 is characterized in that: The specific implementation process of step S2 includes: Based on historical meteorological data, extract temperature and pressure records with sudden changes, record the change amplitude and rate, and output the temperature and pressure change parameter range; from the salt cavern operation history data, extract operating pressure anomaly data that occurred in a short period of time, such as sudden pressure increases or changes in injection and production frequency, and output the corresponding operating condition change amplitude and duration; The temperature and pressure change parameter range is combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions; combined with the cavity burial depth data, the action time length and action depth range are set for various temperature and pressure mutation conditions; the temperature change, pressure change, action time and action depth are unified into an input parameter set.

4. The method for evaluating the stability of salt cavern carbon storage based on multi-source data according to claim 3, characterized in that: The specific implementation process of step S3 includes: Define the perturbation input vector, denoted as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i shows the depth of the i-th disturbance event; Construct the response evolution rate indicator as follows: Wherein, α and β represent the preset weighting factors of temperature change and pressure change, γ1 and γ2 represent the preset sensitivity factors, λ represents the preset action time weighting factor, and μ represents the preset depth attenuation coefficient; Based on the response evolution rate indicator, the response evolution intensity is constructed as follows: Among them, w i represents the impact coefficient of the i-th disturbance event, and Λ represents the response evolution intensity under the current disturbance history.

5. The salt cavern carbon storage stability evaluation method based on multi-source data according to claim 4 is characterized in that: The specific implementation process of step S4 includes: Based on the response evolution intensity Λ, the dynamic risk value calculation function is set as follows: Ω=κ1·Λ+κ2·ΔT max +κ3·ΔP max Where Λ represents the response evolution intensity under the current disturbance history, ΔT max Indicates the maximum temperature change in the current cycle, ΔP max represents the maximum pressure change in the current cycle, κ1, κ2, and κ3 represent the preset empirical control parameters, characterizing the contribution of each factor to stability, and Ω represents the dynamic risk value; A risk threshold interval is preset, and if the dynamic risk value Ω is less than the minimum value within the risk threshold interval, it is determined that the structural stability of the salt cavern under continuous disturbance is excellent; If the dynamic risk value Ω is within the risk threshold range, it is determined that the salt cavern is unstable under continuous disturbance. If the dynamic risk value Ω is greater than the maximum value within the risk threshold range, it is determined that the structural stability of the salt cavern is poor under continuous disturbance, and a stability warning is issued.

6. A salt cavern carbon storage stability evaluation system based on multi-source data, which executes a salt cavern carbon storage stability evaluation method based on multi-source data according to any one of claims 1 to 5, characterized in that: The system includes: a data collection and model building module, a data acquisition and processing module, an indicator and intensity calculation module, and a risk calculation and analysis early warning module; The data collection and model building module collects geological survey data of the area where the salt cavern carbon storage reservoir is located and builds a geological structure model; The data acquisition and processing module outputs the temperature and pressure variation parameter range based on historical meteorological data; extracts abnormal operating pressure data of the salt cavern; combines the temperature and pressure variation parameter range with the abnormal operating pressure data, and sets the action time length and action depth range in combination with the cavern burial depth data; The index and strength calculation module: defines a disturbance input vector and constructs a response evolution rate index; and constructs a response evolution intensity based on the response evolution rate index; The risk calculation and analysis warning module: sets a dynamic risk value calculation function based on the response evolution intensity; presets a threshold interval, analyzes and issues stability warnings.

7. The salt cavern carbon storage stability evaluation system based on multi-source data according to claim 6, characterized in that: The data acquisition and model building module includes a data acquisition and model building unit; The data acquisition and model building unit collects geological survey data of the area where the salt cavern carbon storage reservoir is located, including salt mine core data, stratigraphic structure data, interlayer distribution data, cavity depth data, and stratigraphic inclination data, and builds a geological structure model based on the geological survey data. The geological structure model is used to reflect the mechanical differences and stress sensitivity characteristics of the rock salt layer, as follows: According to the salt mine core data, the lithology types at different depths are recorded and the preliminary lithology vertical distribution information is output. Based on the lithology vertical distribution information and combined with the stratum structure data, the stratum structure profile is output; In the rock layer structure section, a rock layer structure model including interlayer information is output based on the interlayer distribution data; based on the rock layer structure model and the cavity burial depth data, the depth interval where the cavity is located is marked, and the relationship between the cavity embedding position and the surrounding rock composition is output; Based on the relationship between the cavity embedding position and the surrounding rock composition, combined with the formation dip data, a three-dimensional spatial structure diagram is constructed; In the three-dimensional spatial structure diagram, corresponding lithology and structural parameters are set for different rock layers and interlayers to construct a geological structure model.

8. The salt cavern carbon storage stability evaluation system based on multi-source data according to claim 7, characterized in that: The data acquisition and processing module includes a data acquisition and processing unit; The data acquisition and processing unit extracts temperature and pressure records with sudden changes based on historical meteorological data, records the magnitude and rate of change, and outputs the range of temperature and pressure change parameters. From the historical salt cavern operation data, it extracts abnormal operating pressure data that occurs within a short period of time, including sudden increases in operating pressure or changes in injection and production frequency, and outputs the corresponding operating condition change magnitude and duration. The temperature and pressure change parameter range is combined with the operating pressure anomaly data to generate several sets of simulation boundary conditions; combined with the cavity burial depth data, the action time length and action depth range are set for various temperature and pressure mutation conditions; the temperature change, pressure change, action time and action depth are unified into an input parameter set.

9. The salt cavern carbon storage stability evaluation system based on multi-source data according to claim 8, characterized in that: The index and strength calculation module includes an index calculation unit and a strength calculation unit; The indicator calculation unit: defines the disturbance input vector, which is recorded as in, represents the comprehensive characteristics of the i-th disturbance event, ΔT i represents the temperature change of the i-th disturbance event, ΔP i represents the pressure change of the i-th disturbance event, τ i represents the action time of the i-th disturbance event, d i Indicates the depth of the i-th disturbance event; constructs the response evolution rate index; The intensity calculation unit is configured to construct a response evolution intensity Λ based on the response evolution rate indicator.

10. The salt cavern carbon storage stability evaluation system based on multi-source data according to claim 9, characterized in that: The risk calculation and analysis warning module includes a risk calculation unit and an analysis and warning unit; The risk calculation unit sets a dynamic risk value calculation function based on the response evolution intensity Λ; The analysis and early warning unit: presetting a risk threshold interval, if the dynamic risk value Ω is less than the minimum value within the risk threshold interval, then determining that the structural stability of the salt cavern under continuous disturbance is excellent; If the dynamic risk value Ω is within the risk threshold range, it is determined that the salt cavern is unstable under continuous disturbance. If the dynamic risk value Ω is greater than the maximum value within the risk threshold range, it is determined that the structural stability of the salt cavern is poor under continuous disturbance, and a stability warning is issued.

Images