Method and system for sealing carbon dioxide in saline water layer

Abstract

The invention discloses a method and system for sealing carbon dioxide in a salt water layer, and belongs to the field of carbon dioxide sealing, and the method comprises the following steps: capturing carbon dioxide and compressing the carbon dioxide into a liquid state or a supercritical state; injecting carbon dioxide into the platform by using a pipeline system; collecting geological parameters to construct a geological discrimination model; predicting a flowing path of carbon dioxide and judging leakage possibility, if not, taking as a carbon dioxide injection region, and if not, replacing the target region for re-detection; and acquiring parameters by using the acquisition equipment of the target subarea, monitoring the leakage condition of the carbon dioxide, and uploading leakage information to a monitoring terminal when the carbon dioxide leaks. The saline water layer is used for sealing the carbon dioxide, the geological condition of the injection target area is evaluated before injection, geological parameters are collected in real time after injection to monitor whether leakage occurs, and the leakage risk of the sealed carbon dioxide is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon dioxide storage, and in particular to a method and system for storing carbon dioxide in a saline layer. Background Art

[0002] Carbon dioxide storage is a technical measure to reduce the concentration of carbon dioxide in the atmosphere, aiming to mitigate global warming and climate change. Existing carbon dioxide storage is mainly geological storage: it compresses the captured carbon dioxide into liquid form and then injects it into geological structures deep underground, such as depleted oil and gas fields, deep salt water aquifers or unmineable coal seams. Geological storage technology has been applied to some commercial projects, such as the Sleipner project in the Norwegian North Sea, which has been in operation since 1996 and successfully injects carbon dioxide into geological structures, but geological storage may affect geological stability.

[0003] In addition, there are some applications that use mineral storage, namely mineralization storage, which involves reacting carbon dioxide with certain types of minerals (such as basalt or limestone) to produce stable carbonate minerals, thereby permanently fixing carbon dioxide. Although this method has broad prospects, it is still in the research and development and demonstration stage, and requires a large amount of mineral resources and specific geological conditions, and there are limited uses.

[0004] At present, carbon storage in saline aquifers has the advantages of being far away from surface water bodies and groundwater layers on which human beings depend for survival, higher safety and less environmental risks. However, the injection and storage of carbon in saline aquifers currently lacks reliable assessment methods before injection and real-time monitoring technology after injection, which poses a risk of carbon dioxide leakage. In addition, when carbon dioxide is captured using carbon dioxide capture chemical absorption technology, there is a risk of organic ammonia volatilization. Summary of the invention

[0005] To solve the above problems, the present invention provides a method and system for storing carbon dioxide in saline aquifers, which greatly reduces the risk of leakage of the stored carbon dioxide by evaluating the geological conditions of the target area before carbon dioxide injection and collecting geological parameters in real time after injection to monitor whether there is leakage.

[0006] To achieve the above object, the present invention provides a method for storing carbon dioxide in a saline layer, comprising the following steps:

[0007] S1. Using mixed amines as absorbent to capture carbon dioxide, and compressing the captured carbon dioxide into a liquid or supercritical state;

[0008] S2, injecting carbon dioxide into the platform using pipelines;

[0009] S3. Determine the leakage risk based on the geological discrimination model of the carbon storage layer and select the target injection area to inject carbon dioxide;

[0010] S31, obtaining geological parameters, and constructing a geological discrimination model based on the geological parameters;

[0011] S32, for multiple candidate injection well locations in the carbon storage target area, judging and selecting injection well locations that meet geological requirements according to the geological discrimination model;

[0012] S33. For the injection well locations in the selected carbon storage target area, use a partition monitoring method to predict the flow path of carbon dioxide and determine whether there is a risk of carbon dioxide leakage: if there is a risk of leakage, replace the injection well location and test again; if it is determined that there is no risk of leakage, use the target partition as the carbon dioxide injection area;

[0013] S34, injecting carbon dioxide into the target partition;

[0014] S4. Deploy collection equipment to the target area to collect injection parameters and geological parameters of carbon dioxide in real time, monitor carbon dioxide leakage, and upload leakage information to the monitoring terminal when carbon dioxide leakage occurs.

[0015] To achieve the above-mentioned object, the present invention also provides a system for storing carbon dioxide in a saline layer, comprising a carbon dioxide capture device, a carbon dioxide transport device and a carbon dioxide injection device;

[0016] The carbon dioxide capture device comprises a desulfurization tower, a gas heat exchanger, a wet dust collector, a heater and an absorption tower which are sequentially connected along the direction of the flue gas flow, and the carbon dioxide discharge port of the absorption tower is sequentially connected to the lean-rich liquid heat exchanger, the desorption tower and the compressor; the flue gas discharge port of the absorption tower is sequentially connected to the multi-stage water washing tower, the acid washing tower and the demister;

[0017] The carbon dioxide transfer equipment is a transfer vehicle or a pipeline system.

[0018] The carbon dioxide injection equipment includes an injection platform and an injection well. The injection platform is equipped with a monitoring terminal, which is a computer system or a cloud system.

[0019] The monitoring terminal is equipped with a processor and a memory. The memory is a combination of a non-volatile memory and a cache. The non-volatile memory stores an instruction set, which, when called and executed by the processor, can perform the following operations: construct a geological discrimination model for the carbon-sealed storage layer, determine the leakage risk based on the geological discrimination model for the carbon-sealed storage layer, and screen the target injection area.

[0020] According to the above technical scheme, the method for storing carbon dioxide in a saline layer proposed by the present invention has the following beneficial effects:

[0021] 1. The present invention achieves high efficiency in capturing carbon dioxide. The mixed amine is circulated and cooled by an interstage cooler to maintain the appropriate temperature conditions for the absorption reaction, further enhancing the absorption effect and ensuring that a large amount of carbon dioxide can be separated from the flue gas. Furthermore, in the flue gas treatment process after absorbing carbon dioxide, it is sequentially subjected to multi-stage water washing, acid washing and multi-stage purification by a demister. During the multi-stage water washing process, colloidal gas foam is introduced to enhance the removal effect of impurities, and acid washing can further neutralize the residual alkaline substances.

[0022] 2. The present invention evaluates the geological conditions of the target injection area before carbon dioxide injection, and judges and selects injection wells that meet geological requirements for multiple candidate injection wells in the carbon storage target area according to the geological discrimination model, thereby ensuring that the selected injection wells are located in areas with relatively stable geological conditions and low carbon dioxide leakage risks, thereby improving the safety and effectiveness of carbon dioxide injection; and after injection, geological parameters are collected in real time to monitor whether there is leakage, thereby greatly reducing the risk of leakage of stored carbon dioxide;

[0023] 3. A geological discrimination model is constructed by comprehensively considering the probability of occurrence of geological disasters, the probability of reaching the hazard-bearing body, the spatiotemporal probability of the hazard-bearing body, the vulnerability of the hazard-bearing body and the value of the hazard-bearing body. Through a multi-factor comprehensive evaluation, the possible risks in the carbon dioxide storage process are comprehensively considered. It not only focuses on the geological disasters themselves, but also combines them with the hazard-bearing bodies in the surrounding environment. It can more truly reflect the actual risk situation, understand the risk level in different regions, and provide a scientific basis for the reasonable selection of carbon dioxide injection areas, avoid injection operations in high-risk areas, and reduce the possibility of carbon dioxide leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 4 is a flow chart of a method for storing carbon dioxide in a saline aquifer according to an embodiment of the present invention.

[0025] Figure 2 is a flow chart of constructing a geological discrimination model according to an embodiment of the present invention.

[0026] Figure 3 is a flow chart for determining whether there is a risk of carbon dioxide leakage according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages disclosed in the embodiments of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] like Figure 1 , Figure 2 , Figure 3 The method for storing carbon dioxide in a saline layer of the embodiment shown comprises the following steps:

[0029] S1. Using mixed amines as absorbent to capture carbon dioxide and compressing the captured carbon dioxide into a liquid or supercritical state;

[0030] S2, injecting carbon dioxide into the platform using pipelines;

[0031] S3. Determine the leakage risk based on the geological discrimination model of the carbon storage layer and select the target injection area to inject carbon dioxide;

[0032] S31, obtaining geological parameters, and constructing a geological discrimination model based on the geological parameters;

[0033] S32, for multiple candidate injection well locations in the carbon storage target area, judging and selecting injection well locations that meet geological requirements according to the geological discrimination model;

[0034] S33. For the injection well locations in the selected carbon storage target area, use a partition monitoring method to predict the flow path of carbon dioxide and determine whether there is a risk of carbon dioxide leakage: if there is a risk of leakage, replace the injection well location and test again; if it is determined that there is no risk of leakage, use the target partition as the carbon dioxide injection area;

[0035] S34, injecting carbon dioxide into the target partition;

[0036] S4. Deploy collection equipment to the target area to collect injection parameters and geological parameters of carbon dioxide in real time, monitor carbon dioxide leakage, and upload leakage information to the monitoring terminal when carbon dioxide leakage occurs.

[0037] {Carbon dioxide capture}

[0038] As a further embodiment, in step S1, a mixed amine is used as an absorbent to capture carbon dioxide, and the captured carbon dioxide is compressed into a liquid or supercritical state. The mixed amine used includes N-methyldiethanolamine, and piperazine is used as an activator. Its reaction characteristics with carbon dioxide and circulating cooling through an interstage cooler in the absorption tower ensure the absorption effect and achieve efficient capture of carbon dioxide.

[0039] In the carbon dioxide capture design of the present invention, the flue gas is first desulfurized, then passed through a gas heat exchanger for cooling, then passed into a wet dust collector to remove aerosols, and steam is injected to increase the size of condensation nuclei. After being heated by a heater, it is passed into the bottom of an absorption tower, and mixed amines are sprayed on the top of the absorption tower to react with carbon dioxide in the flue gas to capture carbon dioxide. The rich liquid after absorbing carbon dioxide is processed by a series of subsequent heat exchangers, desorption towers and other equipment to achieve the release of carbon dioxide and the regeneration and recycling of mixed amines. Finally, the exhaust flue gas is further purified through multi-stage water washing, acid washing and demisters.

[0040] As an optional embodiment, the capture of carbon dioxide specifically includes the following steps:

[0041] S11, passing the flue gas after desulfurization into a gas heat exchanger for cooling, passing the cooled flue gas into a wet dust collector to remove aerosols in the flue gas, and injecting steam into the wet dust collector to increase the size of condensation nuclei;

[0042] S12, the flue gas containing condensation nuclei is heated by the heater and then passed into the bottom of the absorption tower, and the mixed amine is sprayed on the top of the absorption tower, and the mixed amine reacts with CO2 in the flue gas, and the mixed amine is circulated and cooled through the interstage cooler;

[0043] S13, the rich liquid that has absorbed CO2 is discharged from the bottom of the absorption tower, and after being heated by the lean-rich liquid heat exchanger, enters the desorption tower to be thermally decomposed to release CO2. The regenerated mixed amine is cooled by the lean-rich liquid heat exchanger and the lean liquid cooler, and then enters the absorption tower to circulate and absorb CO2;

[0044] S14. The flue gas is discharged after passing through multi-stage water washing, acid washing and demister in sequence, wherein colloidal gas foam is introduced during the multi-stage water washing process.

[0045] Preferably, the demister described in step S13 is one of a wire mesh demister, a blade demister, a Brown fiber demister, and any combination thereof.

[0046] Therefore, the method of the present invention reduces the emission of aerosols and reduces environmental pollution.

[0047] As mentioned above, the acid solution reacts quickly with alkaline gases such as NH3 in the pickling process. When sulfuric acid is used for pickling and pH < 5, ammonia emission is observed to be 4×10 -6 Down to 1×10 -6 The following, at the same time, the emissions of degradation products such as DMA, MA, EA, and DIEA are greatly reduced; combined with the wet electrostatic precipitator, ions are generated through internal corona discharge. After the aerosol collides with the ions and is charged, it separates from the flue gas in the electrostatic field and hits the electrode plate. When the wet electrostatic precipitator is arranged in front of the absorption tower, it can remove most of the aerosols in the flue gas (99.99%) and effectively reduce aerosol (MEA) emissions.

[0048] By injecting steam into the flue gas, the size of the condensation nuclei entering the absorber is increased so that they can be removed in conjunction with a demister or wet electrostatic precipitator, which can quickly reduce emissions by an order of magnitude.

[0049] Furthermore, colloidal gas foam (CGA) is passed during the multi-stage water washing process. Colloidal gas foam has the characteristics of large surface area, low viscosity and high bubble stability. A single CGA bubble can adsorb multiple aerosol droplets, and then the CGA is removed by water washing.

[0050] Combined with interstage cooling, the growth of aerosol particles can be reduced by lowering the MEA partial pressure in the absorption tower and the water scrubber. For flue gas with a CO2 concentration of 20%, the interstage cooling process can reduce MEA emissions to 1 / 5 to 1 / 10 of the original level.

[0051] As an optional embodiment, in step S2, the carbon dioxide compressed into a liquid or supercritical state is transported to the injection platform by using a pipeline system to prepare for subsequent injection.

[0052] It will be appreciated that long distance transport and transfer may be carried out by a transfer vehicle and then injected into the platform using pipe piles via a pipeline system.

[0053] Furthermore, carbon dioxide is injected into the selected target area, and the injection parameters and geological parameters of carbon dioxide are collected in real time to closely monitor carbon dioxide leakage. Once a leakage occurs, the information is uploaded to the monitoring terminal in a timely manner.

[0054] As an optional embodiment, in step S3, the leakage risk is judged based on the geological discrimination model of the carbon-sealed storage layer, the carbon-sealed target area is screened, and carbon dioxide is injected, including the following process:

[0055] S31, obtaining geological parameters, and constructing a geological discrimination model based on the geological parameters;

[0056] S32, for multiple candidate injection well locations in the carbon storage target area, judging and selecting injection well locations that meet geological requirements according to the geological discrimination model;

[0057] S33. For the injection well locations in the selected carbon storage target area, use a partition monitoring method to predict the flow path of carbon dioxide and determine whether there is a risk of carbon dioxide leakage: if there is a risk of leakage, replace the injection well location and test again; if it is determined that there is no risk of leakage, use the target partition as the carbon storage target area for carbon dioxide injection;

[0058] S34. Inject carbon dioxide into the target partition.

[0059] The above-mentioned embodiments are further described below with reference to the accompanying drawings.

[0060] {Constructing a geological discrimination model}

[0061] According to an embodiment of the present invention, Figure 2 As shown, the process of obtaining geological parameters in the aforementioned step S31 and constructing a geological discrimination model based on the geological parameters includes:

[0062] S311. Obtain logging data and seismic data of the carbon storage target area, and analyze and screen the geotechnical structural characteristics;

[0063] S312, clustering different rock and soil structural features to obtain geological disaster instance clusters corresponding to different rock and soil structural features, determining the instance data volumes of different clusters, and eliminating geological disaster instance clusters that do not meet the preset data volume standard;

[0064] S313, analyzing the spatiotemporal evolution of disasters in the selected geological disaster instance clusters, extracting the dominant factor sets of different geological disaster instance clusters, and selecting stability factors in the dominant factor sets using the Fisher algorithm;

[0065] S314. With the maximum geological disaster identification accuracy as the goal, determine whether the Pearson correlation coefficients between different dominant factors and stability meet the preset requirements, and obtain the dominant factors that meet the preset requirements as factors affecting the stability of the rock and soil mass;

[0066] S315. Based on the factors affecting the stability of rock and soil mass, the Monte Carlo method is used to obtain the probability of geological hazard instability in different rock and soil structural areas in the target area;

[0067] S316. Obtain the disaster-causing scope of the geological disaster, obtain the spatiotemporal probability of the disaster-causing body according to the time when the disaster-causing body is within the disaster-causing scope, and evaluate the vulnerability and value of the disaster-causing body according to the basic information and structural characteristics of the disaster-causing body;

[0068] S317. Construct a geological discrimination model based on a set of risk factors based on the probability of occurrence of geological disasters, the probability of reaching the disaster-prone body, the spatiotemporal probability of the disaster-prone body, the vulnerability of the disaster-prone body and the value of the disaster-prone body.

[0069] It should be understood that in S311, the logging data at different depths of the storage layer in the carbon storage target area can be further used to analyze the lithological parameters of the formation, such as stratification interface, stratification material, thickness, Poisson's ratio, elastic modulus, bottom, structural mechanical strength and other parameters, which are closely related to the stability of the formation rock and soil structure.

[0070] At the same time, the depth, continuity and other characteristics of the reflection interface can be analyzed and extracted from the seismic data to determine the stratified structure and fault conditions of the strata.

[0071] For example, based on the collected logging data at different depths of the carbon-sealed storage layer, the porosity of the carbon-sealed storage layer is calculated using density logging and acoustic logging data, and the permeability is further determined based on the porosity empirical model.

[0072] According to the seismic wave reflection data of the carbon sealing storage layer, the depth of the formation interface of the carbon sealing storage layer, the thickness of the formation, the reflection coefficient of the formation and its change are analyzed according to the travel time and amplitude of the reflected wave.

[0073] In step S312, clustering algorithms, such as K-means clustering, can be used to cluster geotechnical structural feature data points, calculate their distances from each cluster center, and assign data points to the cluster with the closest distance. The cluster center is then updated, and the above process is repeated until the cluster center no longer changes or the preset number of iterations is reached. In this way, different geotechnical structural feature clusters are obtained, and each cluster can be regarded as a geological hazard instance cluster.

[0074] Furthermore, the amount of instance data in each cluster is counted. A minimum data volume standard is preset, which can be determined based on the sample size requirements in statistics or the empirical value in geological research. Clusters with data volumes less than this standard are considered to be insufficiently representative and are removed from subsequent analysis to reduce the impact of noise data and abnormal clusters on the overall analysis and improve the reliability of the analysis results.

[0075] In a further embodiment, in step S313, a time factor is added, and for each retained geological disaster instance cluster, its change pattern in time and space is analyzed. For example, using matlab simulation, for the landslide disaster cluster, its occurrence frequency and scale changes in different seasons (time dimension), different terrain slopes and slope directions (spatial dimension) are studied. Further, the time and space factors closely related to the occurrence of disasters can be determined by a time and space distribution chart or a method of calculating the time and space autocorrelation coefficient.

[0076] From this, we further extract the set of factors that may affect geological disasters as the dominant factor set, such as the strength parameters of rock and soil, groundwater level changes, and earthquake activity frequency.

[0077] In an optional embodiment, the stability factor is selected in combination with the Fisher algorithm. The principle and core of the Fisher algorithm is to calculate the ratio of the between-class variance to the within-class variance.

[0078] Assume that there are m categories (geological hazard instance clusters) corresponding to each dominant factor of the ith type, and n categories of the jth type. j samples, and the sample mean is μ j , the overall mean is μ, then the between-class variance S can be further calculated b :

[0079]

[0080] Calculate the intra-class variance S w :

[0081]

[0082] Where x refers to category C j The samples in .

[0083] Furthermore, the Fisher ratio F of each dominant factor can be calculated: F = S b / S w .

[0084] The larger the ratio, the stronger the factor's ability to distinguish different categories (i.e., different stability states). The dominant factor with a larger Fisher ratio is selected as the stability factor.

[0085] In an optional embodiment, in step S134, the Pearson correlation coefficient is calculated for each dominant factor X and stability factor Y. By using a preset threshold of the Pearson correlation coefficient (which can be determined according to geological research and actual needs, for example, 0.5 indicates a strong correlation), if the absolute value of the calculated Pearson correlation coefficient of each dominant factor X and stability factor Y is greater than the threshold, it is considered that the factor has a significant correlation with the stability of the rock and soil mass, and is determined as a factor affecting the stability of the rock and soil mass, and is used as a key variable for the subsequent construction of a geological discrimination model.

[0086] In a further embodiment, in step S315, the Monte Carlo method is used to establish a mathematical model of the probability of geological hazard instability in combination with the key variables obtained in step S314, i.e., the factors affecting the stability of the rock and soil mass, to obtain the probability of geological hazard instability in different rock and soil structure areas in the target area.

[0087] For example, for the landslide instability model, the internal friction angle of the rock mass is involved. The instability probability model is established based on factors such as cohesion c, slope angle θ, groundwater level h, etc. Determine the probability distribution of each influencing factor. For example, the internal friction angle follows a normal distribution (its mean and standard deviation are obtained by fitting a large amount of geotechnical test data), and the cohesion follows a log-normal distribution.

[0088] Furthermore, a random number generator is used to generate a large number of random samples (eg, 1000-20000 groups of samples) according to the probability distribution of each factor. For each group of random samples, an instability probability value is calculated by substituting them into the instability probability model.

[0089] The distribution of instability probability values ​​is statistically analyzed to obtain the estimated values ​​of geological hazard instability probability in different geotechnical structural areas in the target area. For example, the characteristics of instability probability can be described by calculating the mean, median, quantile and other statistics of instability probability.

[0090] As an optional embodiment, in step S316, for different types of geological disasters (such as ground ruptures caused by earthquakes, accumulation range of landslides, etc.), the disaster range can be determined according to the scale of the geological disaster, energy release factors and geological and topographic conditions. For example, for earthquake disasters, the length and width of the surface rupture of the earthquake can be estimated by using empirical formulas (such as the relationship formula between earthquake rupture length and magnitude proposed by Wells and Coppersmith) based on parameters such as earthquake magnitude and fault rupture length, so as to determine the disaster range.

[0091] Furthermore, the temporal distribution of the disaster-prone body within the disaster-causing range is determined.

[0092] In the embodiment of the present invention, the spatiotemporal probability of a disaster-prone body is defined as the product of the time probability and the spatial probability of the disaster-prone body within the disaster-causing range. ST It can be expressed as P ST =P T *P S , where P T P represents the time probability of the disaster-prone body in the dangerous time period, S It represents the spatial probability that the hazard-prone body is within the disaster-causing spatial range. For example, it can be obtained by analyzing the spatial relationship between the hazard-prone body and the disaster-causing range through the Geographic Information System (GIS).

[0093] For the vulnerability assessment of disaster-prone objects, vulnerability curves or assessment models can be established based on factors such as the type of disaster-prone objects (such as brick-concrete structures, steel-structured bridges, etc.), structural characteristics (such as the number of floors of the building, the span of the bridge, etc.), and the year of construction. For example, for buildings, a damage probability model under different earthquake intensities can be established based on their structural type and seismic design standards as a basis for vulnerability assessment.

[0094] As an optional embodiment, for the disaster-bearing body of the engineering structure, a structural mechanics analysis model is used to evaluate its vulnerability. Furthermore, a coupling model can be established while considering the interaction between the disaster-bearing body and the rock and soil body. For example, for a building built on a soft soil foundation, when evaluating the vulnerability of the structure to damage caused by foundation settlement, factors such as the compressibility of the foundation soil and the type of building foundation (such as pile foundation) need to be considered. A numerical model of foundation-foundation-structure interaction is established to simulate the changes in the internal forces of the disaster-bearing body during the settlement process. Based on the allowable deformation and internal force limit values ​​of the structure, the probability of destruction of the building under different settlement amounts is determined to quantify its vulnerability.

[0095] As an optional embodiment, for disasters such as landslides and ground sliding, the vulnerability of the disaster-bearing body can be quantified by a vulnerability curve that shows the probability of the disaster-bearing body suffering different degrees of damage under different disaster intensities. For example, the curve is constructed by obtaining data through laboratory simulation, field tests, or numerical simulation.

[0096] For the evaluation of the value of disaster-prone bodies, market value evaluation methods or cost replacement methods can be used, etc. The value is comprehensively evaluated by taking into account the construction cost, maintenance cost and regional impact.

[0097] In step S317, the risk factors are further constructed by combining the aforementioned probability of occurrence of geological disasters, probability of reaching the hazard-bearing body, spatiotemporal probability of the hazard-bearing body, vulnerability of the hazard-bearing body and value of the hazard-bearing body to collectively construct a geological discrimination model.

[0098] In the embodiment of the present invention, in step S317, the probability of occurrence of geological disasters P obtained in the previous step is GD , probability of reaching the disaster-bearing body P RC (For example, it is determined based on the relationship between the propagation path of geological hazards and the position of the hazard-bearing body, such as the probability of debris flow flowing to the hazard-bearing body), the spatiotemporal probability P of the hazard-bearing body ST , the vulnerability V of the hazard-bearing body (expressed using the probability of destruction) and the value C of the hazard-bearing body are quantitatively integrated.

[0099] Construct risk assessment indicators and use risk value R to represent: R = P GD *P RC *P ST *V*C.

[0100] In this embodiment, the risk value R is used to comprehensively reflect the risk level of geological disasters in different regions, which serves as the basis for constructing a geological discrimination model.

[0101] {Leakage risk identification}

[0102] Furthermore, in step S33, for the injection well locations in the screened carbon storage target area, a partition monitoring method is used to predict the flow path of carbon dioxide and determine whether there is a risk of carbon dioxide leakage: if there is a leakage risk, the injection well location is replaced and tested again; if it is determined that there is no leakage risk, the target partition is used as the target area for carbon dioxide injection.

[0103] In an embodiment of the present invention, in step S33, determining whether there is a risk of carbon dioxide leakage specifically includes the following steps:

[0104] S31, obtaining geological parameters, and constructing a geological discrimination model based on the geological parameters;

[0105] S321, dividing the geological monitoring area into a plurality of sub-monitoring areas according to the geological type;

[0106] S322, obtaining geological parameters of each sub-monitoring area;

[0107] S323, gridding the geological parameters, inputting the gridded geological parameters into the geological model, and obtaining three-dimensional block geological models of multiple sub-monitoring areas using geological modeling software;

[0108] S324, based on the three-dimensional block geological models of the multiple sub-monitoring areas, predicting the flow path and pressure partition of carbon dioxide according to the fracture information in the three-dimensional block geological models;

[0109] S325. Determine whether there is a risk of carbon dioxide leakage based on the flow path and pressure zone.

[0110] As an optional embodiment, in step S321, the different geological types existing are determined by conducting a comprehensive geological survey and analysis of the geological monitoring area. For example, by consulting existing geological data, geological maps, and previously acquired logging data, seismic data and other information, the major geological types contained in the area, such as sedimentary rock areas, magmatic rock areas, and metamorphic rock areas, are identified. At the same time, the distribution areas of different lithologies are further subdivided. For example, in the sedimentary rock area, the distribution areas of different lithologies, such as sandstone formations, shale formations, and limestone formations, are distinguished, because the pore structures, permeabilities, and mechanical properties of rocks of different lithologies are different, which will have different effects on the storage and migration of carbon dioxide.

[0111] On this basis, the sub-monitoring areas are divided according to the different geological types and lithology distributions identified above. In this embodiment, the geographic information system (GIS) software is used to define the scope of each sub-monitoring area according to the boundaries of the stratum lithology and the distribution of geological structures (such as faults, folds, etc.). For example, with a large fault as the boundary, one side of the fault is a stratum dominated by sandstone, and the other side is a stratum dominated by shale, then the two sides are divided into different sub-monitoring areas. For areas with large continuous distribution and relatively uniform lithology, if the area is too large to be conducive to subsequent refined monitoring, it can also be further subdivided according to certain rules (such as according to the longitude and latitude grid or equal area division principle) to ensure that the geological characteristics inside each sub-monitoring area are relatively consistent, so as to facilitate the subsequent targeted parameter acquisition and analysis work.

[0112] In step S322, various geological parameters are obtained for each sub-monitoring area, which can be obtained through historical data collection and analysis, geophysical survey, etc.

[0113] In an embodiment of the present invention, the collection of geological parameters includes:

[0114] The first is the rock physical properties, including rock porosity, permeability, density, elastic modulus, etc. Porosity affects the storage space of carbon dioxide in rock pores, permeability determines the ease of carbon dioxide migration in rocks, and density and elastic modulus are related to the mechanical stability of rocks, which will affect the deformation and possible rupture of the formation after carbon dioxide injection;

[0115] Second, the formation structure parameters, such as the thickness, dip and direction of the formation, are critical for analyzing the migration trend of carbon dioxide between different formations and whether it will leak along the weak links of the formation (such as the bedding direction of the inclined formation).

[0116] The third is the geological structure-related parameters, including the location of faults in the sub-monitoring area, fault distance, width of the fault fracture zone, and the morphology of folds (such as the amplitude and wavelength of anticlines and synclines), which are key channel factors for possible leakage of carbon dioxide or important factors affecting its migration path.

[0117] Furthermore, in step S323, the irregularly distributed geological parameter data is converted into data on a regular grid according to the grid size to implement grid processing.

[0118] For example, on the basis of determining the appropriate grid size, a suitable interpolation method is adopted. For example, for continuously changing parameters such as porosity and permeability, the Kriging interpolation method is used. Based on the spatial correlation and variation function of geological parameters, the values ​​on the grid nodes are estimated through the data of known sampling points, so that the gridded data can reasonably reflect the spatial distribution of geological parameters in the entire sub-monitoring area. For some discrete geological structural parameters (such as fault locations), they can be integrated into the gridding system by representing them as special grid attributes (such as marking the corresponding grid as having a fault). In this way, the gridding processing of the entire monitoring area is realized.

[0119] Then, the gridded geological parameter information is input into the existing geological model framework according to the corresponding spatial position. After the gridded data is input, the geological modeling software (such as Petrel) is used to construct a three-dimensional block geological model of each sub-monitoring area by tracking different stratigraphic levels and assigning gridded stratigraphic attributes, simulating the three-dimensional structure of the stratigraphic layer, changes in rock properties, and geological structure.

[0120] In the model, each grid unit represents a small cube in the actual geological body, which has corresponding rock property parameters, stratigraphic structure information, geological structural characteristics, etc., forming an intuitive, three-dimensional model containing rich geological information, which provides a basic platform for subsequent analysis of carbon dioxide flow path and pressure zoning.

[0121] In step S324, geological modeling software is used to extract fracture-related information from the three-dimensional block geological model, including fracture occurrence (i.e., strike, dip), fracture aperture (width), fracture density (the number of fractures per unit volume), and fracture connectivity, etc., reflecting possible fluid migration pathways in the formation.

[0122] For example, a group of fractures with roughly parallel orientations and good interconnectivity may guide CO2 to migrate preferentially in this direction; fractures with larger openings can allow more CO2 to pass through, while fracture areas with high density mean that CO2 has more migration options.

[0123] By counting and analyzing the fracture information at different locations and depths in the model, the overall characteristics of the fracture network in the entire sub-monitoring area are determined.

[0124] Furthermore, numerical simulation methods are used in combination with Darcy's law of fluid seepage in porous media. The fluid flow rate, permeability, water-passing cross-sectional area, hydraulic gradient and multiphase flow theory (after carbon dioxide is injected, it belongs to multiphase flow in the formation and interacts with formation water, etc.) are used. The porosity, permeability and fracture network characteristics of the formation are used as input parameters to simulate the underground seepage process of carbon dioxide and predict its possible flow path.

[0125] During the simulation process, the diffusion of carbon dioxide from the injection point to the surrounding formations under different pressure differences is considered, and it gradually extends along the areas with high permeability and good fracture connectivity, eventually forming a visual carbon dioxide flow trajectory, intuitively showing the areas and directions that carbon dioxide may flow through in each sub-monitoring area.

[0126] Based on the numerical simulation method, pressure zoning is performed according to the pressure changes at different locations during the injection of carbon dioxide. Near the injection point, the pressure is relatively high due to the continuous injection of carbon dioxide. As carbon dioxide diffuses and migrates to the surrounding formations, the pressure gradually decreases. Therefore, the pressure values ​​at different locations are calculated through simulation, and the sub-monitoring area is divided into different pressure zones according to a certain pressure range (the high-pressure zone is set to a pressure greater than a certain threshold, and the low-pressure zone is set to a pressure less than another threshold). There is a pressure difference between different pressure zones, and this pressure difference is one of the driving forces for the flow of carbon dioxide underground. The pressure zoning also reflects the enrichment of carbon dioxide in the formation and the possible high-risk leakage areas (such as excessive pressure may cause formation ruptures, increasing the risk of leakage).

[0127] In a further embodiment, in step S325, the leakage risk is determined by comprehensively considering the flow path and pressure partition of the carbon dioxide.

[0128] Among them, if the flow path points to an area close to the surface or has a trend leading to non-target storage areas such as shallow groundwater layers and soil layers, it is judged that there is a possibility of carbon dioxide leaking into the external environment and there is a risk of leakage of uncontrolled flow.

[0129] For example, when the predicted flow path shows that carbon dioxide may migrate upward along a fault or crack and eventually approach the surface soil layer, it is necessary to pay special attention because once it breaks through the surface, the carbon dioxide will be released into the atmosphere and cannot be effectively stored.

[0130] As an optional embodiment, if the pressure in some areas is too high and exceeds the fracture pressure threshold of the formation, it is judged that the formation may be fractured, forming a new leakage channel, allowing carbon dioxide to leak out. The fracture pressure threshold refers to the formation fracture pressure value of the carbon storage layer, which can be estimated through rock mechanics experiments and geological model analysis.

[0131] As an optional embodiment, it is also possible to combine the flow path and pressure zoning for a precise comprehensive analysis, comprehensively consider factors such as the distance the carbon dioxide reaches the surface or non-target area, the difference between the pressure and the formation fracture pressure, and perform an assessment by calculating the leakage risk value.

[0132] In this embodiment, the leakage risk value = distance weight * inverse of distance + pressure weight * ((pressure - rupture pressure) / rupture pressure), so as to calculate the specific leakage risk value. When the leakage risk value exceeds a certain set threshold, it is determined that there is a leakage risk, thereby providing a scientific basis for whether to select the sub-monitoring area as a carbon dioxide injection area in the future.

[0133] {System for the method of storing carbon dioxide in saline aquifers}

[0134] According to an embodiment of the present invention, a system for storing carbon dioxide in a saline layer is provided, comprising a carbon dioxide capture device, a carbon dioxide transport device and a carbon dioxide injection device. The carbon dioxide capture device comprises a desulfurization tower, a gas heat exchanger, a wet dust collector, a heater and an absorption tower which are sequentially connected along the direction of the flue gas flow, and the carbon dioxide discharge port of the absorption tower is sequentially connected to the lean-rich liquid heat exchanger, the desorption tower and the compressor; the flue gas discharge port of the absorption tower is sequentially connected to the multi-stage water washing tower, the acid washing tower and the demister.

[0135] The carbon dioxide transfer equipment is a transfer vehicle or a pipeline system.

[0136] The carbon dioxide injection equipment includes an injection platform and an injection well. The injection platform is equipped with a monitoring terminal, which is a computer system or a cloud system.

[0137] The monitoring terminal is equipped with a processor and a memory. The memory is a combination of a non-volatile memory and a cache. The non-volatile memory stores an instruction set, which, when called and executed by the processor, can perform the following operations (steps S31, S32, and S33): construct a geological discrimination model for a carbon-sealed storage layer, and determine leakage risks based on the geological discrimination model for a carbon-sealed storage layer, and screen target injection areas.

[0138] Therefore, the present invention adopts the above-mentioned method and system for storing carbon dioxide in saline layers, which can greatly reduce the risk of leakage of the stored carbon dioxide by evaluating the geological conditions of the target injection area before carbon dioxide injection and collecting geological parameters in real time after injection to monitor whether there is leakage.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for storing carbon dioxide in a saline layer, characterized in that: The following steps are involved: S1. Using mixed amines as absorbent to capture carbon dioxide, and compressing the captured carbon dioxide into a liquid or supercritical state; S2, injecting carbon dioxide into the platform using pipelines; S3. Determine the leakage risk based on the geological discrimination model of the carbon storage layer and select the target injection area to inject carbon dioxide; S31, obtaining geological parameters, and constructing a geological discrimination model based on the geological parameters; S32, for multiple candidate injection well locations in the carbon storage target area, judging and selecting injection well locations that meet geological requirements according to the geological discrimination model; S33. For the injection well locations in the selected carbon storage target area, use a partition monitoring method to predict the flow path of carbon dioxide and determine whether there is a risk of carbon dioxide leakage: if there is a risk of leakage, replace the injection well location and test again; if it is determined that there is no risk of leakage, use the target partition as the carbon dioxide injection area; S34, injecting carbon dioxide into the target partition; S4. Deploy collection equipment to the target area to collect injection parameters and geological parameters of carbon dioxide in real time, monitor carbon dioxide leakage, and upload leakage information to the monitoring terminal when carbon dioxide leakage occurs.

2. The method for storing carbon dioxide in a saline layer according to claim 1, characterized in that: The mixed amine includes N-methyldiethanolamine and uses piperazine as an activator.

3. The method for storing carbon dioxide in a saline layer according to claim 2, characterized in that: The method of capturing carbon dioxide using mixed amine as an absorbent comprises the following steps: S11, passing the flue gas after desulfurization into a gas heat exchanger for cooling, passing the cooled flue gas into a wet dust collector to remove aerosols in the flue gas, and injecting steam into the wet dust collector to increase the size of condensation nuclei; S12, the flue gas containing condensation nuclei is heated by the heater and then passed into the bottom of the absorption tower, and the mixed amine is sprayed on the top of the absorption tower, the mixed amine reacts with CO2 in the flue gas, and the mixed amine is circulated and cooled through the interstage cooler; S13, the rich liquid that has absorbed CO2 is discharged from the bottom of the absorption tower, and after being heated by the lean-rich liquid heat exchanger, enters the desorption tower to be thermally decomposed to release CO2. The regenerated mixed amine is cooled by the lean-rich liquid heat exchanger and the lean liquid cooler, and then enters the absorption tower to circulate and absorb CO2; S14. The flue gas is discharged after passing through multi-stage water washing, acid washing and demister in sequence, wherein colloidal gas foam is introduced during the multi-stage water washing process.

4. The method for storing carbon dioxide in a saline layer according to claim 3, characterized in that: The demister is one of a wire mesh demister, a blade demister, a Brown fiber demister, and any combination thereof.

5. The method for storing carbon dioxide in a saline layer according to claim 1, characterized in that: In step S31, the geological parameters are obtained and a geological discrimination model is constructed based on the geological parameters, including the following steps: S311. Before carbon sequestration, collect well logging data and seismic data in the target area of ​​carbon sequestration, and analyze and screen the geotechnical structural characteristics; S312, clustering different rock and soil structural features to obtain geological disaster instance clusters corresponding to different rock and soil structural features, determining the instance data volumes of different clusters, and eliminating geological disaster instance clusters that do not meet the preset data volume standard; S313, analyzing the spatiotemporal evolution of disasters in the selected geological disaster instance clusters, extracting the dominant factor sets of different geological disaster instance clusters, and selecting stability factors in the dominant factor sets using the Fisher algorithm; S314. With the maximum geological disaster identification accuracy as the goal, determine whether the Pearson correlation coefficients between different dominant factors and stability meet the preset requirements, and obtain the dominant factors that meet the preset requirements as factors affecting the stability of the rock and soil mass; S315. Based on the factors affecting the stability of rock and soil mass, the Monte Carlo method is used to obtain the probability of geological hazard instability in different rock and soil structural areas in the target area; S316. Obtain the disaster-causing scope of the geological disaster, obtain the spatiotemporal probability of the disaster-causing body according to the time when the disaster-causing body is within the disaster-causing scope, and evaluate the vulnerability and value of the disaster-causing body according to the basic information and structural characteristics of the disaster-causing body; S317. Construct a geological discrimination model based on a set of risk factors based on the probability of occurrence of geological disasters, the probability of reaching the disaster-prone body, the spatiotemporal probability of the disaster-prone body, the vulnerability of the disaster-prone body and the value of the disaster-prone body.

6. The method for storing carbon dioxide in a saline layer according to claim 5, characterized in that: In step S311, based on the collected logging data at different depths of the carbon-sealed storage layer, the porosity of the carbon-sealed storage layer is calculated using density logging and sonic logging data, and the permeability is further determined based on a porosity empirical model.

7. The method for storing carbon dioxide in a saline layer according to claim 5, characterized in that: In step S311, seismic wave reflection data of the carbon sealing storage layer is obtained, and the depth of the formation interface of the carbon sealing storage layer, the thickness of the formation, and the reflection coefficient and its change of the formation are analyzed according to the travel time and amplitude of the reflected wave.

8. The method for storing carbon dioxide in a saline layer according to claim 1, characterized in that: In step S32, determining whether there is a risk of carbon dioxide leakage specifically includes the following steps: S321, dividing the geological monitoring area into a plurality of sub-monitoring areas according to the geological type; S322, obtaining geological parameters of each sub-monitoring area; S323, gridding the geological parameters, inputting the gridded geological parameters into the geological model, and obtaining three-dimensional block geological models of multiple sub-monitoring areas using geological modeling software; S324, based on the three-dimensional block geological models of the multiple sub-monitoring areas, predicting the flow path and pressure partition of carbon dioxide according to the fracture information in the three-dimensional block geological models; S325. Determine whether there is a risk of carbon dioxide leakage based on the flow path and pressure zone.

9. The method for storing carbon dioxide in a saline layer according to claim 2, characterized in that: In step S325, the leakage risk is determined based on the flow path and pressure partition of the carbon dioxide, including: Based on the distance of CO2 reaching the surface or non-target area, the difference between the pressure and the formation fracture pressure, the leakage risk value is calculated for evaluation: Leakage risk value = distance weight * inverse of distance + pressure weight * ((pressure - rupture pressure) / rupture pressure); When the leakage risk value exceeds a certain set threshold, it is determined that there is a leakage risk.

10. A system for storing carbon dioxide in a saline layer, characterized in that: Including CO2 capture equipment, CO2 transport equipment and CO2 injection equipment; The carbon dioxide capture device comprises a desulfurization tower, a gas heat exchanger, a wet dust collector, a heater and an absorption tower which are sequentially connected along the direction of the flue gas flow, and the carbon dioxide discharge port of the absorption tower is sequentially connected to the lean-rich liquid heat exchanger, the desorption tower and the compressor; the flue gas discharge port of the absorption tower is sequentially connected to the multi-stage water washing tower, the acid washing tower and the demister; The carbon dioxide transport equipment is a transport vehicle or a pipeline system. The carbon dioxide injection equipment includes an injection platform and an injection well. The injection platform is equipped with a monitoring terminal, which is a computer system or a cloud system. The monitoring terminal is equipped with a processor and a memory. The memory is a combination of a non-volatile memory and a cache. The non-volatile memory stores an instruction set, which, when called and executed by the processor, can perform the following operations: construct a geological discrimination model for the carbon-sealed storage layer, determine the leakage risk based on the geological discrimination model for the carbon-sealed storage layer, and screen the target injection area.

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