A method for effective monitoring of carbon dioxide storage leaks

Abstract

The application relates to the field of oil and gas geophysical prospecting engineering and discloses a method for effectively monitoring carbon dioxide storage leakage, which comprises the following steps: S1. establishing a geological model for carbon dioxide storage and performing reservoir simulation, and constructing a time-lapse synthetic model with different carbon dioxide saturations; S2. using rock physics theory, analyzing reservoir rock physics response characteristics under different carbon dioxide saturations, and deducing an elastic parameter model; S3. using a viscous-sound wave equation of a standard linear solid attenuation model to carry out seismic forward simulation, generating time-lapse seismic data, and performing reverse-time migration imaging; and S4. based on the reverse-time migration profile obtained in S3, using a frequency spectrum ratio method of an imaging domain to perform real-time monitoring on leakage conditions of carbon dioxide in early, middle and late stages after injection. The workflow provided by the application realizes comprehensive monitoring and prediction on carbon dioxide plume migration by integrating reservoir simulation, rock physics analysis and time-lapse seismic monitoring technology.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration engineering technology, specifically to an effective method for monitoring carbon dioxide sequestration leakage. Background Technology

[0002] With the increasing severity of global climate change, carbon capture and storage (CCS) technology has received widespread attention as an effective method to reduce carbon dioxide emissions. CCS technology for saline aquifers has become a research hotspot due to its enormous storage potential; however, the leakage risk during carbon dioxide injection cannot be ignored, requiring comprehensive monitoring. Time-lapse seismic monitoring is a proven and reliable method for large-scale carbon dioxide monitoring, successfully applied in several projects such as Sleipner, Otway, and Ketzin. However, while traditional time-lapse seismic monitoring methods can provide elastic properties such as P-wave velocity (Vp) and attenuation (Qp), they cannot directly quantify the saturation of the carbon dioxide plume. Reservoir simulation, while capable of predicting carbon dioxide distribution, lacks a direct link to the elastic properties in seismic data.

[0003] To address this issue, several studies have developed integrated workflows that combine reservoir, rock physics, and seismic data. A workflow for coal seam carbon dioxide sequestration was developed in 2010, simultaneously increasing coalbed methane production. A workflow for enhanced oil recovery (EOR) was established in 2020, combining simulation-to-seismic methods with seismic reservoir characterization. A workflow for detecting and quantifying P-wave velocity time-lapse anomalies using elastic full waveform inversion (FWI) was presented in 2017. However, these workflows are primarily applied to coal seams and EOR, with limited research specifically targeting saline reservoirs, and even fewer studies focusing on the attenuation effects after carbon dioxide injection.

[0004] To further quantify the attenuation effect caused by carbon dioxide injection, this invention proposes a novel integrated workflow. This workflow combines attenuation and spectral ratio methods, specifically applied to carbon dioxide sequestration monitoring in saline aquifers, with a focus on typical saline aquifers in the Pearl River Mouth Basin (PRMB) of the northern South China Sea. Based on field information from this region, we synthesized reservoir and seismic-related properties, established the relationship between carbon dioxide saturation and Vp and Qp using rock physics theory, and generated time-shifted seismic data. By analyzing the attenuation effect of carbon dioxide injection in the reservoir in the four-dimensional imaging domain using reverse time migration (RTM) and spectral ratio methods, this invention can more accurately predict the migration path of carbon dioxide plumes and their early-mid-late-stage leakage, providing technical support for the effective monitoring of offshore carbon dioxide sequestration projects. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an effective method for monitoring carbon dioxide sequestration leakage. It aims to utilize the SLS attenuation model and the spectral ratio method in the imaging domain to monitor plume leakage during the early, middle, and late stages of carbon dioxide sequestration, thereby providing a more comprehensive understanding and characterization of the migration and distribution of carbon dioxide in deep saline aquifers.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for effectively monitoring carbon dioxide sequestration leakage, comprising the following steps:

[0007] S1. Establish a geological model for carbon dioxide sequestration and perform reservoir simulation to construct time-shifted synthetic models with different carbon dioxide saturation levels;

[0008] S2. Using rock physics theory, analyze the characteristics of reservoir rock physical response under different carbon dioxide saturation levels, and deduce its elastic parameter model;

[0009] S3. Seismic forward modeling was performed using the viscous acoustic wave equation of the standard linear solid attenuation model to generate time-shifted seismic data, and then reverse time migration imaging was performed.

[0010] S4. Based on the reverse time-shifted profile obtained in S3, the leakage of carbon dioxide in the early, middle and late stages after injection is monitored in real time using the spectral ratio method in the imaging domain.

[0011] Preferably, a two-dimensional geological model for carbon dioxide sequestration is established based on geological properties, including a permeability model and a porosity model, and a two-dimensional velocity model and density model required for seismic processing in S2-S4 are established based on the provided well logging data.

[0012] Preferably, in step S2, the maximum inverse quality factor of the P-wave is used to calculate Qp, and the low-frequency compressibility modulus M0 and bulk density ρ are used to calculate the P-wave velocity Vp of the rock.

[0013]

[0014] Where M0 is the compression modulus at extremely low frequencies, and M ∞ This corresponds to the compression modulus at extremely high frequencies.

[0015] Preferably, in step S2, a fluid approximation method based on the longitudinal wave velocity (Vp) is used to calculate the low-frequency modulus:

[0016]

[0017] M s M is the compressive modulus of the mineral matrix. Dry Here, φ represents the compressive modulus of the rock skeleton, φ represents the total porosity, and K represents the total porosity.f The effective bulk modulus of the fluid in the rock is calculated using the harmonic average of water and carbon dioxide.

[0018] Preferably, in S2,

[0019]

[0020] The high-frequency compressive modulus is the compressive modulus M of wet rock. W And rock M containing only carbon dioxide G The harmonic mean, where K W and K g S represents the bulk modulus of water and carbon dioxide, respectively. W This represents water saturation.

[0021] Preferably, to calculate the longitudinal wave velocity Vp of the rock, the low-frequency compressibility modulus M0 and the bulk density ρ are used, as follows:

[0022]

[0023] Preferably, in step S3, the wave is attenuated when propagating in a carbon dioxide-induced attenuating medium. Forward modeling is performed using the viscous acoustic wave equation of a single SLS, and its expression is:

[0024]

[0025] Where, τ ε and τ σ These are the strain and stress relaxation times, respectively; r is the memory variable; ν p It's about speed.

[0026] Preferably, in the equation τ ε and τ σ The calculation expression is:

[0027]

[0028] Among them, Q p ω0 is the quality factor, used to characterize the intensity of seismic wave attenuation, and ω0 is the reference frequency.

[0029] Preferably, in step S4, the ratio method is used to calculate the ratio between the monitoring spectrum R2(k) and the baseline spectrum R1(k). This can be expressed as:

[0030] In[R2(k) / R1(k)]=ρ[k]+G0

[0031] Where k is the local wavenumber of the migration event, and ρ is calculated as follows:

[0032]

[0033] The integral is performed along the wave propagation path dl, which quantifies the cumulative attenuation on the time-shifted seismic image.

[0034] This invention provides an effective method for monitoring carbon dioxide sequestration leaks. It has the following beneficial effects:

[0035] The workflow proposed in this invention integrates reservoir simulation, rock physics analysis, and time-lapse seismic monitoring technologies to achieve comprehensive monitoring and prediction of carbon dioxide plume migration. Compared with existing technologies, this invention introduces the spectral ratio method of attenuation and imaging domain, which significantly improves the quantitative accuracy of the attenuation effect after carbon dioxide injection and enhances the safety and reliability of monitoring. At the same time, this workflow is optimized for the specific geological characteristics of the Pearl River Estuary Basin, and has stronger adaptability and timeliness, enabling timely identification of potential pre-, mid-, and late-stage leakage risks. Attached Figure Description

[0036] Figure 1 A flowchart illustrating the workflow of an effective method for monitoring carbon dioxide sequestration leaks before, during, and after the sequestration process, as provided in one embodiment of the present invention;

[0037] Figure 2 A two-dimensional porosity and permeability model provided as an embodiment of the present invention;

[0038] Figure 3 A two-dimensional initial velocity and density model provided as an embodiment of the present invention;

[0039] Figure 4 The carbon dioxide velocity variation and the decay variation of injected carbon dioxide are provided in one embodiment of the present invention;

[0040] Figure 5 Two-dimensional reverse time migration results provided in one embodiment of the present invention;

[0041] Figure 6 A spectrum diagram provided for one embodiment of the present invention;

[0042] Figure 7 Imaging results provided 100 years after carbon dioxide injection, as an embodiment of the present invention. Detailed Implementation

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Embodiments of the present invention: A method for effectively monitoring carbon dioxide storage leakage, such as... Figure 1 As shown, it includes the following steps:

[0045] S1. Establish a geological model for carbon dioxide sequestration and conduct reservoir simulation. Construct a time-shifted synthetic model with different carbon dioxide saturation levels. The establishment of the carbon dioxide sequestration model is the basis for quantifying the changes in reservoir properties under different carbon dioxide saturation levels.

[0046] S2, using rock physics theory, analyzes the rock physics response characteristics of reservoirs under different carbon dioxide saturation levels and derives their elastic parameter models. The correlation coefficient is calculated using the following method:

[0047] As seismic waves propagate through various layers of the Earth, their energy gradually attenuates. In this paper, we use the maximum inverse quality factor of P-waves to calculate Qp, and the low-frequency compressibility modulus M0 and bulk density ρ to calculate the P-wave velocity Vp of the rock.

[0048]

[0049] Where M0 is the compression modulus at extremely low frequencies, and M ∞ This corresponds to the compression modulus at extremely high frequencies.

[0050]

[0051] To calculate the low-frequency modulus, we use only a fluid approximation of the longitudinal wave velocity (Vp). s M is the compressive modulus of the mineral matrix. Dry Here, φ represents the compressive modulus of the rock skeleton, φ represents the total porosity, and K represents the total porosity. f The effective bulk modulus of the fluid in the rock is calculated using the harmonic average of water and carbon dioxide. The high-frequency compressive modulus is the compressive modulus M of wet rock. W And rock M containing only carbon dioxide G The harmonic mean. Where, K W and K g S represents the bulk modulus of water and carbon dioxide, respectively. W This represents water saturation.

[0052]

[0053] To calculate the longitudinal wave velocity Vp of the rock, we use the low-frequency compressibility modulus M0 and the bulk density ρ, as shown below:

[0054]

[0055] For this storage model, we utilized the extracted baseline velocity values. As for the quality factor Qp, the baseline value was set to 100,000, indicating no attenuation occurred within the seismic frequency range prior to carbon dioxide injection. We then conducted rock physics analysis of the reservoir after carbon dioxide injection under ambient temperature and pressure conditions. Figure 4 (a) shows the rate change after 25 years of carbon dioxide injection; (b) shows the rate decrease after 25 years of carbon dioxide injection; (c) shows the rate change after 100 years of carbon dioxide injection; and (d) shows the rate decrease after 100 years of carbon dioxide injection. Figure 4 (ad) shows the velocity change at year 25 after carbon dioxide injection, and (b) shows the decay change at year 25 after carbon dioxide injection; the velocity change at year 100 after carbon dioxide injection; and the decay change at year 100 after carbon dioxide injection. After carbon dioxide injection, the velocity at year 25 is significantly lower than the velocity at year 100. Meanwhile, continuous carbon dioxide injection from before injection to year 25 and then to year 100 leads to a gradual increase in the extent of the carbon dioxide plume within the reservoir. After injection ceases, the injected carbon dioxide further displaces water in the reservoir, expanding the extent of the carbon dioxide plume. Figure 4 d)

[0056] S3. Seismic forward modeling was performed using the viscous acoustic wave equation from the Standard Linear Solids (SLS) attenuation model to generate time-shifted seismic data, followed by reverse-time migration imaging. Waves are attenuated when propagating in a carbon dioxide-induced attenuating medium. To accurately describe the wave propagation characteristics in attenuating media, based on the Standard Linear Solids (SLS) theory, we used the viscous acoustic wave equation of a single SLS for forward modeling, the expression of which is:

[0057]

[0058] Where, τ ε and τ σ These are the strain and stress relaxation times, respectively; r is the memory variable; ν p It is velocity. τ in the equation ε and τ σ The calculation expression is:

[0059]

[0060] Among them, Q p ω0 is the quality factor, used to characterize the intensity of seismic wave attenuation, and ω0 is the reference frequency.

[0061] Figure 5 The results of the reverse time migration two-dimensional profile of the carbon dioxide sequestration model are shown. (a) is the reverse time migration profile without carbon dioxide injection; (b) is the reverse time migration profile after 25 years of carbon dioxide injection; and (c) is the reverse time migration profile after 100 years of carbon dioxide injection. Figure 5 The solid orange arrows indicate the leftward migration of the carbon dioxide plume at the fault, with the horizontal expansion 100 years later exceeding the migration range 25 years later. (Comparison...) Figure 5 (b) and Figure 5 (c) shows the result 100 years later. Figure 5 c) Due to the transport of carbon dioxide plumes, a more pronounced and widespread attenuation was observed. Furthermore, Figure 5 It also indicates that carbon dioxide injection leads to a decrease in seismic amplitude and a reduction in resolution. This phenomenon is caused by the significant attenuation resulting from the increased carbon dioxide saturation within the reservoir.

[0062] S4, based on the reverse time-shifted profile obtained in S3, uses the spectral ratio method in the imaging domain to monitor the leakage of carbon dioxide in the early, middle and late stages after injection in real time.

[0063] To more accurately investigate the impact of carbon dioxide plume distribution on time-lapsed seismic responses, we noted that carbon dioxide injection increases reservoir attenuation, leading to a significant reduction in amplitude and resolution, as well as phase distortion, thus causing misinterpretation of time-lapsed seismic data. A common method for quantifying the attenuation effect is to measure the spectral changes in seismic data caused by attenuation. To measure the attenuation effect from time-lapsed seismic imaging, we need to transform the equations from the frequency domain to the imaging domain. In this study, the spectral ratio method is used to calculate the ratio between the monitoring spectrum R2(k) and the baseline spectrum R1(k). This can be expressed as:

[0064] In[R2(k) / R1(k)]=ρ[k]+G0 (10)

[0065] Where k is the local wavenumber of the migration event, and ρ is calculated as follows:

[0066]

[0067] In equation (11), the integral is performed along the wave propagation path dl, which quantifies the cumulative attenuation on the time-shifted seismic image. Therefore, it can be well used to quantify the attenuation due to carbon dioxide injection over a given monitoring time range.

[0068] In addition, baseline data is used as a reference. Figure 6 (a) shows the difference between the offset profile results from year 25 of CO2 injection and the injection date; (b) shows the difference between the offset profile results from year 100 of CO2 injection and the injection date; (c) shows the difference only when providing... Figure 6 (a, b) Spectrum diagrams in attenuation region I; (d) Spectrum diagrams only providing... Figure 6 (a, b) Spectral ratio in attenuation region I; (e) For only providing Figure 6(a, b) Spectrum diagrams in attenuation region II; (f) for only providing Figure 6 (a, b) Spectral ratios in attenuation region II Figure 6 (ab) shows the baseline migration image and Figure 5 The difference between (b) and (c) is used to estimate the distribution of carbon dioxide. For example... Figure 6 As shown in (ab), the image differences clearly represent the carbon dioxide response in seismic imaging, proving that seismic imaging technology can effectively monitor the migration of carbon dioxide.

[0069] To better assess the attenuation effect, we calculated Figure 6 The wavenumber spectrum corresponding to the two black dashed boxes in the middle, such as Figure 6 As shown in (c) and (e), a significant attenuation effect appears in the spectrum 100 years after carbon dioxide injection. Notably, we observed a marked decrease in amplitude, particularly in the high-frequency range. However, the carbon dioxide plume spectrum in Region II, located near the carbon dioxide injection well, remained relatively stable over a monitoring period of 25 to 100 years, as... Figure 6 As shown in (c) and (e), this stability is primarily attributed to the cessation of carbon dioxide injection after 25 years.

[0070] To quantify the decay caused by carbon dioxide injection, we used the spectral ratio method with equation (9) to calculate the decay caused by injection at 25 and 100 years post-injection. Subsequently, we generated logarithmic plots of the slopes, revealing linear trends at different frequencies, such as... Figure 6 As shown in (d) and (f), these curves are generally linear, with each curve exhibiting a different negative slope, indicating a significant attenuation effect of carbon dioxide injection on the formation over 25 years. Furthermore, by calculating the quality factor (Qp), we can effectively quantify the spectral attenuation effect between 25-year and 100-year carbon dioxide injection. Figure 6 In (d), the calculated Qp values ​​are 23.98 and 19.32, respectively; Figure 6 In (f), the values ​​are 15.52 and 12.79, respectively. Based on the calculated Qp values, we observed that the attenuation effect becomes more significant as the carbon dioxide plume migrates.

[0071] like Figure 4-6 As shown, the method proposed in this paper effectively describes the quantitative characterization of carbon dioxide plumes caused by injected carbon dioxide. Therefore, our method provides an opportunity to predict carbon dioxide leakage using known reservoir characteristics. Furthermore, we can employ the image domain spectral ratio method to detect pre-, mid-, and post-leakage carbon dioxide leakage from seismic images, enabling us to monitor safety hazards based on time-delayed seismic datasets.

[0072] To monitor carbon dioxide leaks, we conducted reservoir simulations of leaking reservoirs and observed the migration of carbon dioxide plumes. Our workflow allows us to understand and predict how the characteristics of saline aquifers affect carbon dioxide leaks. Excessive permeability and caprock porosity, or fault reactivation, can lead to the formation of leak channels, increasing the risk of seismic activity or affecting reservoir safety, making them more susceptible to carbon dioxide leaks. We incorporated caprock permeability to simulate leaks and applied this new workflow to monitor their occurrence.

[0073] Similarly, using rock physics theory to obtain time-shifted seismic data and performing reverse time migration imaging, the imaging results 100 years after carbon dioxide injection are as follows: Figure 7 As shown in (a), (a) is the two-dimensional reverse time migration (RTM) imaging result 100 years after the leak occurred; (b) is the result of combining the seismic data monitored in the 100th year with... Figure 5 (a) The difference in reverse-time profiles between baseline seismic data prior to carbon dioxide injection; (c) The attenuation zone I, which provides information only about leakage occurring 100 years after carbon dioxide injection. Figure 6 (b) Spectral diagram of Region II (no leakage) at year 100; (d) Attenuation region I (leaking only carbon dioxide) at year 100. Figure 6 (b) Spectral ratio of Region II without leakage at year 100; (e) Attenuation ratio of Region II with leakage at year 100 for which only injected carbon dioxide was provided. Figure 6 (b) Spectral diagram of Region II without leakage at year 100; (f) Decay diagram of Region II with leakage at year 100, provided only with injected carbon dioxide. Figure 6 (b) Spectral ratio of Region II (no leakage) in year 100. By comparison Figure 6 (b) and Figure 7 (b) We observed that the RTM imaging results with carbon dioxide leakage showed a larger attenuation region than those without carbon dioxide leakage. This result was further validated in the imaging differences 7(b). Figure 7 (b) shows that the carbon dioxide plume attenuates beyond the caprock, highlighting the preliminary evidence of leakage effects from seismic imaging. To better illustrate the application of the proposed method in monitoring carbon dioxide leaks, we performed spectral analysis on the imaging results using the image domain spectral ratio method. Figure 6 Select two regions, I and II, at the same location, such as Figure 7 As shown in (b). Figure 7 (cd) and Figure 7 (ef) shows the spectra of region I and region II, respectively.

[0074] First, Region I Figure 7(c) shows a spectral comparison between leaky and leak-free conditions. Figure 7 (d) represents the corresponding spectral ratio. Figure 7 In (cd), we found that images without leakage showed results similar to the baseline imaging, while those with leakage showed a significantly attenuated spectrum. Furthermore, Figure 7 The spectral ratio in (d) shows a linear decreasing trend after the leak. This result indicates that a significant decrease in amplitude can be observed in the spectrum of the imaging results after a carbon dioxide leak.

[0075] Then, in Figure 7 In (ef), compared with the baseline imaging results, the spectra of both leaking and non-leaking imaging results showed attenuation. However, the spectral attenuation of leaking imaging results was stronger, and its spectral ratio showed a larger decreasing trend compared with non-leaking imaging results. Therefore, the above findings indicate that the proposed method can effectively characterize the state of carbon dioxide plumes, providing a potential possibility for monitoring carbon dioxide leakage.

[0076] In one specific embodiment:

[0077] I. Establishing a geological model:

[0078] Based on the geological characteristics of a typical saline aquifer in the northern South China Sea of ​​the Pearl River Mouth Basin (PRMB), a two-dimensional porosity and permeability model was constructed. The model size is 18km(x)×4km(y)×3km(z). The reservoir is characterized by anticline structure, which is conducive to the upward migration and storage of carbon dioxide over time. The model includes two main fault zones, each with a dip angle of 55°. The distance between the left and right faults is 40m and 30m, respectively. The injection well is located to the right of the 30m fault. The model boundary was set as a non-permeable boundary to reflect the actual reservoir conditions. Considering the long time required for the geochemical reaction between carbon dioxide and minerals, the simulation only observed the migration and distribution of carbon dioxide saturation over a period of 100 years.

[0079] II. Reservoir Simulation:

[0080] The migration of the carbon dioxide plume was dynamically predicted using Eclipse 300 (E300), a reservoir simulation software developed by Schlumberger. Single-well injection was carried out starting in 2024, with continuous carbon dioxide injection for 25 years, followed by 75 years of monitoring of the plume. It was assumed that the carbon dioxide was injected into the saline aquifer in a supercritical state, with a target injection depth of 1100m, a gas diffusion coefficient of 0.001, and a maximum bottomhole pressure of 600bar.

[0081] III. Rock Physical Response Analysis:

[0082] Based on the velocity and density values ​​extracted from well logging data, velocity and density models are constructed, such as... Figure 3 As shown, the physical response characteristics of reservoir rocks under different carbon dioxide saturation are analyzed, and their elastic parameter models are derived. Qp is calculated using the maximum inverse quality factor of P-wave, and the P-wave velocity of the rock is calculated using low-frequency compressive modulus and bulk density.

[0083] IV. Spectrum Analysis:

[0084] Based on the reverse time-shift profile obtained in S3, the leakage of carbon dioxide before, during and after injection is monitored in real time using the spectral ratio method in the imaging domain. The ratio between the monitored spectrum and the baseline spectrum is calculated to quantify the attenuation effect. A logarithmic plot of the slope is generated to reveal the linear trend at different frequencies, so as to evaluate the spectral attenuation effect between 25-year and 100-year carbon dioxide injection.

[0085] V. Leakage Monitoring and Verification:

[0086] By simulating different permeability conditions, the permeability of the caprock was increased to simulate leakage. The RTM imaging results under the conditions of leakage and no leakage were compared. It was observed that the imaging results under the condition of leakage showed a larger attenuation area. Furthermore, the spectral analysis of the imaging results was carried out using the image domain spectral ratio method, which verified the spectral attenuation caused by carbon dioxide leakage.

[0087] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method of effectively monitoring carbon dioxide sequestration leaks, characterized by, The method comprises the following steps: S1. Establishing a geological model for carbon dioxide storage and conducting reservoir simulation, and constructing a time-lapse synthetic model of different carbon dioxide saturations; S2. Analyzing the reservoir petrophysical response characteristics under different carbon dioxide saturations by using petrophysical theory, and deducing the elastic parameter model thereof; S3. Conducting seismic forward modeling by using the viscoacoustic wave equation of the standard linear solid attenuation model, generating time-lapse seismic data, and conducting reverse-time migration imaging, and the expression is: where, and are the strain and stress relaxation times, respectively, r is a memory variable, is the velocity, is the quality factor, used to characterize the strength of seismic wave attenuation, is the reference frequency; S4. Based on the reverse-time migration profile obtained in S3, and by using the frequency spectrum ratio method of the imaging domain, the pre-middle-post leakage conditions of the injected carbon dioxide are monitored in real time, and specifically comprising: The monitoring spectrum is calculated using the spectral ratio method. With baseline spectrum The ratio between them is expressed as: wherein, is the local wave number of the migration event, The calculation of is: 。 2. A method of effectively monitoring carbon dioxide storage leakage according to claim 1, characterized in that, According to the geological properties, a two-dimensional geological model for carbon dioxide storage is established, including a permeability model and a porosity model, and a two-dimensional velocity model and a density model required for seismic processing in S2-S4 are established according to the provided logging data.

3. The method of claim 1, wherein, In S2, Qp is calculated using the maximum inverse quality factor of P wave and the low-frequency compressional modulus and bulk density to calculate the P-wave velocity of the rock : wherein G is the compressive modulus at very low frequencies, and .

4. The method of claim 2, wherein, In the step S2, in order to calculate the low-frequency modulus, the fluid approximation replacement method of Vp is used: , the compressive modulus of the mineral matrix, the compressive modulus of the rock matrix, the total porosity, the effective bulk modulus of the fluids in the rock, calculated by the harmonic mean of water and carbon dioxide.

5. The method of claim 1, wherein, In the S2, High frequency compressional modulus is the compressional modulus of the wet rock and rock containing only carbon dioxide harmonic mean; wherein, and are the bulk modulus of water and carbon dioxide, respectively, is the water saturation, is the compressive modulus of the mineral matrix, is the compressive modulus of the rock skeleton, is the total porosity, is the effective bulk modulus of the fluids in the rock, calculated by the harmonic mean of water and carbon dioxide, .

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