A random displacement method for reservoir media in carbon dioxide geological storage

Abstract

The present invention discloses a random displacement method for reservoir media in carbon dioxide geological storage. The method includes: determining a theoretical rock physics model and a seismic forward modeling model using actual logging data and seismic data to construct a forward modeling framework; performing forward modeling simulation according to the fluid substitution theory and the Gassmann equation; optimizing the existing algorithms during the seismic forward modeling simulation of reservoir parameters, adding a random process of the content and proportion of the media participating in displacement, and providing a more complete numerical simulation scheme for the underground model; further modifying and optimizing the fluid substitution theory formula; using the actual physical property parameters of the underground reservoir as input, and finally realizing the estimation of high-reliability elastic parameters and seismic records. The present invention can better predict the different situations of the medium composition ratio in different reservoir models obtained in different work areas, and provide a larger and more real data set for the subsequent seismic inversion of the underground reservoir model.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic exploration for fire, and particularly to a method for random displacement of reservoir media in carbon dioxide geological storage. Background Art

[0002] Carbon dioxide capture and storage (CCS) is widely recognized worldwide as one of the fastest and most effective technologies for reducing carbon dioxide concentration. By finely describing the reservoir and monitoring the migration of carbon dioxide, it is ensured that the carbon dioxide storage site has stable geological conditions and suitable storage and trapping spaces, and the carbon dioxide is effectively stored. The safe storage of carbon dioxide requires stable geological conditions and suitable storage and trapping spaces, so that the carbon dioxide can be stored in the ground for a long time and effectively after injection. Therefore, before carbon dioxide storage, it is necessary to optimize the carbon dioxide storage site to ensure that the storage site has good reservoir space, suitable pressure, stable tectonic development, etc.

[0003] In the existing research on seismic forward modeling of reservoir parameters, the methods used are often based on the existing fluid substitution theory. By using some basic physical property parameters obtained from field drilling in the work area, approximate forward numerical simulation of the underground reservoir model is carried out, while ignoring the composition of the actual logging reservoir media. In the process of seismic forward modeling of reservoir parameters, only a rough simulation and approximation are made for the actual content and proportion of the reservoir media participating in the displacement during the carbon dioxide storage process, resulting in a large difference between the finally obtained numerical simulation results and the actual situation in the work area. In practical applications, it is often difficult to obtain a large number of real underground model parameters, and the prediction results have non-physical consistency, which limits the data-driven method to obtain better inversion results.

[0004] In summary, the existing research on seismic forward modeling methods for reservoir parameters has the following problems: A large number of approximate formulas and models are used in the process of seismic forward modeling of reservoir parameters, and there is non-physical completeness in the modeling process, resulting in limited accuracy of reservoir parameter prediction. At the same time, in the process of seismic forward modeling of reservoir parameters, the actual content and displacement ratio of the media participating in the displacement during the carbon dioxide geological storage process are often ignored, resulting in a large deviation between the finally obtained numerical simulation results and the actual logging situation. Summary of the Invention

[0005] In order to overcome the disadvantages and deficiencies of the existing technology, the present invention provides a method for random displacement of reservoir media in carbon dioxide geological storage.

[0006] The present invention effectively solves the problem that in the existing method, there is a large difference between the content and proportion in the numerical simulation of reservoir parameters involved in displacement and the content and proportion in the actual work area. As a result, the result obtained through seismic forward modeling of reservoir parameters can more truly reflect the actual situation of the reservoir model in the work area, obtain a more realistic underground model, explore more complete underground reservoir conditions for geological storage of carbon dioxide, provide guiding significance for adjusting the carbon dioxide storage plan, and further study fine detection methods for carbon dioxide storage monitoring. The method includes:

[0007] Step 101: Use actual logging data and seismic data to determine the specific parameters of the theoretical rock physics model and seismic forward modeling model. According to the fluid substitution theory and Wood's equation and Gassmann's equation in rock physics, establish the most basic underground reservoir model;

[0008] Step 102: According to the actual composition of the reservoir medium inside the well logging, correct the composition of the content and proportion of various media in the underground reservoir during the forward modeling of the underground reservoir model. The various media include: reservoir porosity, shale content, water saturation, oil saturation, and carbon dioxide saturation;

[0009] Step 103: Through the correction of the content and proportion of the media in the underground reservoir, optimize the process of calculating the reservoir elastic parameters in Gassmann's equation, correct the algorithms of seismic P-wave velocity, seismic S-wave velocity, and saturated rock density in the underground reservoir during the forward modeling process. Using the idea of random displacement, make the optimized Gassmann's equation more truly reflect the actual composition of the underground reservoir in the actual engineering situation;

[0010] Step 104: Compare and study the elastic parameters and physical properties parameters of the underground reservoir model obtained by forward modeling using the random displacement method of reservoir media in carbon dioxide geological storage (forward modeling is the process of obtaining seismic responses from known underground parameters) with those of the underground model in the actual work area, analyze the differences, and further optimize the random displacement algorithm to make the final result highly fitted with the result of the underground reservoir in the actual work area;

[0011] Step 105: On the premise of optimizing the random displacement algorithm, with the help of the elastic parameters obtained by the random displacement algorithm, use the AVO forward modeling theory, with the help of Zoeppritz equation, further conduct numerical simulation to obtain seismic records. The seismic records obtained by forward modeling with the elastic parameters obtained by the random displacement algorithm reflect the actual seismic records of the underground reservoir.

[0012] Furthermore, the theoretical rock physics model establishes a rock physics model through the fluid substitution theory of the Gassmann equation and the Zoeppritz equation; the parameters of the seismic forward modeling include: seismic P-wave velocity Vp, seismic S-wave velocity Vs, reservoir rock density Rho, and seismic records.

[0013] Establishing the rock physics model includes: for the known physical properties of the reservoir, namely porosity, shale content, water saturation, oil saturation, carbon dioxide saturation, and adjusting the corresponding content and ratio of the above physical properties using the random displacement algorithm. Elastic parameters are obtained through the fluid substitution theory of the Gassmann equation, namely seismic P-wave velocity Vp, seismic S-wave velocity Vs, reservoir rock density Rho, and seismic records are obtained using the Zoeppritz equation to complete the forward modeling process.

[0014] Furthermore, the expression of the random displacement algorithm includes:

[0015] ρ fl =S oil ρ oil +S H2O *[1 - {min + β%(max - min + 1)}]ρ H2O +S co2 ρ co2 (1)

[0016] In the formula, ρ fl represents the density of the fluid medium in the reservoir after being displaced by carbon dioxide. S oil and ρ oil respectively represent the oil saturation and density in the underground reservoir after being displaced by carbon dioxide. S co2 and ρ oil respectively represent the carbon dioxide saturation and density in the underground reservoir after being displaced by carbon dioxide. S H2O and ρ H2O respectively represent the water saturation and density in the underground reservoir after being displaced by carbon dioxide. β represents a random number related to the content of various media in the reservoir of the actual work area. max and min are the upper and lower limits of the specific parameter random process used to limit the media participating in the displacement in the reservoir in the random displacement algorithm.

[0017]

[0018] In the formula, ρ roc represents the density of the saturated rock in the reservoir after being displaced by carbon dioxide. represents the porosity of the reservoir, and ρ sub represents the average density of the rock matrix.

[0019] Further, through (1) and (2), the density of the saturated rock in the reservoir after carbon dioxide displacement obtained by the random displacement algorithm is obtained as one of the elastic parameters to be finally output, and then the following formula is derived:

[0020]

[0021] In the formula, V s represents the velocity of the seismic shear wave in the underground reservoir after carbon dioxide displacement, and μ satur represents the shear modulus of the saturated rock in the underground reservoir. Through formula (3), the velocity of the seismic shear wave in the reservoir after carbon dioxide displacement is obtained by the random displacement algorithm as one of the elastic parameters to be finally output;

[0022]

[0023] In the formula, K fl 、K oil 、K H2O 、K CO2 respectively represent the bulk moduli of the fluid, oil, water, and carbon dioxide in the reservoir after carbon dioxide displacement. The S ool 、S H2O 、S co2 involved in formula (4) are all the corresponding saturations obtained through the random displacement algorithm in formula (1);

[0024]

[0025] In the formula, K satur represents the bulk modulus of the saturated rock after carbon dioxide displacement, K dry represents the bulk modulus of the dry rock, and K sub represents the elastic modulus of the rock matrix. Substituting the bulk modulus of the fluid in the reservoir obtained from formula (4) into formula (5), the bulk modulus of the saturated rock after carbon dioxide displacement obtained by the random displacement algorithm is obtained;

[0026]

[0027] Substituting the bulk modulus of the saturated rock after carbon dioxide displacement calculated from formula (5) into formula (6), the elastic modulus M satur ;

[0028] Further, the expression of the random displacement algorithm further includes:

[0029]

[0030] In the formula, V pIt represents the velocity of the seismic longitudinal wave in the underground reservoir after carbon dioxide displacement; the required elastic parameters obtained by forward modeling of physical properties are obtained by synchronizing formulas (1)-(7), and all the obtained elastic parameters utilize the medium random displacement method in carbon dioxide geological storage. After that, the obtained elastic parameters are randomly displaced repeatedly until the elastic parameter results that tend to be stable and conform to the actual working area conditions are obtained.

[0031] Furthermore, by using the AVO forward modeling theory and with the help of the Zoeppritz equation, numerical simulation is further carried out to obtain seismic records. The AVO forward modeling theory refers to the phenomenon that the amplitude of seismic waves changes with the offset. This phenomenon is mainly caused by the inhomogeneity of the underground medium. The existence of the AVO effect causes changes in the displacement and amplitude of seismic waves in the underground reservoir. Therefore, this point should be considered when using the Zoeppritz equation to construct the underground seismic waveform curve. The following is an introduction to the process of obtaining seismic records by forward modeling with the Zoeppritz equation:

[0032]

[0033] The above formula is the Zoeppritz equation, where δ1, δ2, ε1, and ε2 represent the incident angle and transmission angle of the longitudinal wave, the reflection angle and transmission angle of the shear wave respectively. v p1 , v s1 , Rho1 and v p2 , v s2 , Rho2 represent the corresponding elastic parameters (longitudinal wave velocity, shear wave velocity, density) of medium 1 and medium 2 respectively. R pp , R ps , T pp , T ps represent the reflection and transmission coefficients respectively, and t represents time.

[0034] Based on the elastic parameters (Vp, Vs, Rho) obtained by forward modeling of physical properties, corresponding parameter corrections are made by combining the above formula with the AVO forward modeling theory, and the final seismic records can be obtained.

[0035] Beneficial effects:

[0036] The present invention provides a method for random displacement of reservoir media in geological carbon dioxide sequestration. This method optimizes the traditional seismic simulation of underground reservoir parameters, avoids the approximate treatment of reservoir media participating in displacement in the traditional method, can greatly improve the accuracy of numerical simulation, reduce the error in the simulation process, and obtain a more accurate underground model. This method further corrects the fluid replacement theory used in existing research, and randomly simulates the proportion of reservoir media participating in displacement, making the numerical simulation results based on the original fluid replacement theory more in line with the actual situation of the reservoir in the survey area. Through the random displacement method of media of the present invention, it is possible to better predict the different situations of the proportion of media composition in different reservoir models obtained in different work areas, and provide a larger and more real data set for the forward process of obtaining seismic records from elastic parameter forward modeling and seismic inversion of underground reservoir models in the subsequent stage. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the invention in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0038] Figure 1 is a flowchart of the method of the present invention;

[0039] Figure 2 is a diagram showing the difference in elastic parameter changes before and after underground reservoir displacement by the method of the present invention;

[0040] Figure 3 is a schematic diagram of elastic parameters obtained by numerical simulation by the method of the present invention;

[0041] Figure 4 is a schematic diagram of the optimal elastic parameter forward modeling result obtained by continuously repeating the random displacement process by the method of the present invention;

[0042] Figure 5 is a diagram showing the difference between the reservoir seismic record and the original seismic record obtained by the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will further describe the present application in detail with reference to the drawings and specific embodiments.

[0044] In view of the above problems existing in the traditional seismic forward modeling method for elastic parameters of underground reservoirs, such as the approximate and fuzzy treatment of the content and proportion of reservoir media participating in displacement, the certain error between the theoretical formula of fluid substitution used and the actual results, and the large error with the underground reservoir model in the actual work area, the purpose of the present invention is to provide a method for random displacement of media in carbon dioxide geological storage to achieve high-precision prediction of elastic parameters. The present invention is proposed based on the study of the following problems: 1. A large number of approximate formulas and models are used in the seismic forward modeling of reservoir parameters in existing research, and there is non-physical completeness in the modeling process, resulting in limited prediction accuracy of reservoir parameters. 2. In the process of seismic forward modeling simulation of reservoir parameters, the actual content and displacement ratio of the media participating in displacement in the carbon dioxide geological storage process are ignored, resulting in a large deviation between the final numerical simulation results and the actual well logging situation. 3. There is a certain error between the theoretical formula of fluid substitution used and the actual results. The present invention determines the theoretical rock physics model and seismic forward modeling model based on actual well logging data and seismic data, generates a forward modeling dataset, statistically analyzes the distribution laws of the corresponding elastic parameters and physical properties of rocks based on well data, and uses the actual well logging parameters as input to finally achieve the estimation of high-reliability elastic parameters and seismic data.

[0045] As Figure 1 shown, a method for random displacement of reservoir media in carbon dioxide geological storage specifically includes:

[0046] Step 101: Determine the specific parameters of the theoretical rock physics model and seismic forward modeling model based on actual well logging data and seismic data. According to the fluid substitution theory and the Wood equation and Gassmann equation in rock physics, establish the most basic underground reservoir model.

[0047] Step 102: Based on the actual composition of reservoir media inside the well logging, correct the composition of the content and proportion of various media in the underground reservoir during the forward modeling process of the underground reservoir model.

[0048] Step 103: Based on the correction of the content and proportion of media in the underground reservoir, optimize the process of calculating reservoir elastic parameters in the Gassmann equation, and correct the algorithms for seismic longitudinal wave velocity, seismic transverse wave velocity, and saturated rock density in the underground reservoir during the forward modeling process. Using the idea of random displacement, make the optimized Gassmann equation more truly reflect the actual composition of the underground reservoir in the actual engineering situation.

[0049] Step 104: Compare and study the elastic parameters and physical property parameters of the underground reservoir model obtained by forward modeling using the method for random displacement of reservoir media in carbon dioxide geological storage with those of the underground model in the actual work area, analyze the differences, and further optimize the random displacement algorithm to make the final result highly fitted with the results of the underground reservoir in the actual work area.

[0050] Step 105: On the premise of optimizing the random displacement algorithm, with the help of the elastic parameters obtained by the random displacement algorithm, using the AVO forward modeling theory and the Zoeppritz equation, further conduct numerical simulation to obtain seismic records. At this time, the seismic records obtained by forward modeling using the elastic parameters obtained by the random displacement algorithm can more realistically reflect the actual seismic records of the underground reservoir.

[0051] The present invention specifically adopts the following working steps to achieve the above invention: Determine the specific parameters of the theoretical rock physics model and the seismic forward modeling model based on actual logging data and seismic data. According to the fluid substitution theory and the rock physics equation, establish a basic underground reservoir model. Based on the actual composition of the reservoir medium inside the well logging, correct the composition of the content and proportion of various media in the underground reservoir during the forward modeling process of the underground reservoir model. Optimize the process of calculating the reservoir elastic parameters in the Gassmann equation, and correct the algorithms for the seismic P-wave velocity, seismic S-wave velocity, and saturated rock density of the underground reservoir during the forward modeling process, so that the optimized Gassmann equation can more realistically reflect the actual composition of the underground reservoir in the actual engineering situation. Compare and study the elastic parameters and physical properties parameters of the obtained underground reservoir model with those of the underground model in the actual work area, analyze the differences, and further optimize the random displacement algorithm. With the help of the elastic parameters obtained by the random displacement algorithm, using the AVO forward modeling theory and the Zoeppritz equation, further conduct numerical simulation to obtain seismic records, and output the final processing results, including reservoir elastic parameters, reservoir physical properties parameters, and seismic records. The invention and the working steps are described in detail as follows:

[0052] The present invention determines the specific parameters of the theoretical rock physics model and the seismic forward modeling model based on actual logging data and seismic data, establishes a theoretical rock physics analytical solution seismic forward modeling model, analyzes the error distribution law between the modeling results based on the theoretical physical model and the measured data, and establishes the most basic underground reservoir model according to the fluid substitution theory and the Wood equation and Gassmann equation in rock physics.

[0053] Investigate relevant materials, based on the composition of the reservoir medium inside the well logging, combined with the actual geological environment and the physical and chemical properties of the geological body in the work area, correct the composition of the content and proportion of various media in the underground reservoir during the forward modeling process of the underground reservoir model, so as to further clarify the upper and lower limits of the displacement range of the reservoir medium parameters by the random displacement algorithm.

[0054] Based on the correction of the medium content and proportion in the underground reservoir, the process of calculating reservoir elastic parameters in the Gassmann equation is optimized. Using the idea of random displacement, the algorithms for seismic P-wave velocity, seismic S-wave velocity, and saturated rock density in the underground reservoir during the forward modeling process are corrected. The optimized Gassmann equation can more realistically reflect the actual composition of the underground reservoir in actual engineering situations. To characterize the process of random displacement of reservoir media in carbon dioxide geological sequestration, the following random displacement algorithm is designed:

[0055] ρ fI =S oil ρ oil +S H2O *[1 - {min + β%(max - min + 1)}]ρ H2O +S co2 ρ co2 (1)

[0056] In the formula, ρ fl represents the density of the fluid medium in the reservoir after being displaced by carbon dioxide. S oil and ρ oil represent the oil saturation and density in the underground reservoir after carbon dioxide displacement respectively. S co2 and ρ oil represent the carbon dioxide saturation and density in the underground reservoir after carbon dioxide displacement respectively. S H2O and ρ H2O represent the water saturation and density in the underground reservoir after carbon dioxide displacement respectively. β represents a random number related to the content of various media in the reservoir of the actual work area. max and min are the upper and lower limits of the specific parameter random process used to limit the media participating in the displacement in the reservoir in the random displacement algorithm. It should be noted that the sum of S co2 , S oil , and S H2O is always 100% during the displacement process. That is, it is actually considered that only oil and water are the media participating in carbon dioxide displacement in the reservoir during the whole process. Therefore, only the water or oil in the reservoir needs to be used with the random displacement algorithm, and the saturations of the other two media can be obtained through the quantitative relationship among the three.

[0057]

[0058] In the formula, ρ roc represents the density of the saturated rock in the reservoir after carbon dioxide displacement, represents the porosity of the reservoir, and ρ sub represents the average density of the rock matrix.

[0059] Through (1) and (2), the density of the saturated rock in the reservoir after carbon dioxide displacement obtained by the random displacement algorithm can be obtained, which is one of the elastic parameters that need to be finally output. Thus, the following formula can be derived:

[0060]

[0061] In the formula, V s represents the velocity of the seismic shear wave in the underground reservoir after carbon dioxide displacement, and μ satur represents the shear modulus of the saturated rock in the underground reservoir. Through formula (3), the velocity of the seismic shear wave in the reservoir after carbon dioxide displacement obtained by the random displacement algorithm can be obtained, which is one of the elastic parameters that need to be finally output.

[0062]

[0063] In the formula, K fl , K oil , K H2O , K CO2 respectively represent the fluid bulk moduli of the fluid, oil, water, and carbon dioxide in the reservoir after carbon dioxide displacement. It should be noted that the S oil , S H2O , S co2 in the formula are all the corresponding saturations obtained through the random displacement algorithm of formula (1).

[0064]

[0065] In the formula, K satur represents the bulk modulus of the saturated rock after carbon dioxide displacement, K dry represents the bulk modulus of the dry rock, and K sub represents the elastic modulus of the rock matrix. Substituting the bulk modulus of the fluid in the reservoir obtained from formula (4) into formula (5), the bulk modulus of the saturated rock after carbon dioxide displacement obtained by the random displacement algorithm can be obtained.

[0066]

[0067] After that, substituting the bulk modulus of the saturated rock after carbon dioxide displacement calculated from formula (5) into formula (6), the elastic modulus M satur of the saturated rock after carbon dioxide displacement is obtained.

[0068]

[0069] In the formula, V p represents the velocity of the seismic compressional wave in the underground reservoir after carbon dioxide displacement.

[0070] Such asFigure 2 As shown, before and after carbon dioxide displacement, the elastic parameters of the underground reservoir have changed accordingly. On the curve graph, it is reflected that the corresponding seismic P-wave velocity curve, seismic S-wave velocity curve, and reservoir rock density curve before and after displacement do not coincide.

[0071] As Figure 3 shown, by using the random displacement algorithm, the content and proportion of each reservoir medium participating in the displacement are repeatedly corrected. Then, the elastic parameter curve closest to the actual situation can be obtained. Thus, the required elastic parameters obtained by forward modeling of physical properties are obtained, and all the obtained elastic parameters utilize the medium random displacement method in carbon dioxide geological storage. After that, the obtained elastic parameters can be further randomly displaced repeatedly until the elastic parameter results that tend to be stable and conform to the actual working area situation are obtained.

[0072] As Figure 4 shown, on the basis of Figure 3 , the optimal elastic parameter result graph under numerical simulation is obtained. The elastic parameters of the forward model obtained by using the random displacement algorithm are output and compared with the elastic parameters of the underground model in the actual working area to analyze the differences, and the random displacement algorithm is further optimized to make the final result highly fitted with the result of the underground reservoir in the actual working area.

[0073] As Figure 5 shown, Figure 5 (a) is the original seismic record obtained by further forward modeling of the elastic parameters before carbon dioxide displacement using the Zoeppritz equation. Figure 5 (b) is the seismic record after carbon dioxide displacement obtained by further forward modeling using the optimal elastic parameters after carbon dioxide displacement obtained by the random displacement algorithm. According to the elastic parameters obtained by the continuously optimized random displacement algorithm, using the AVO forward theory and relying on the Zoeppritz equation, numerical simulation is further carried out to obtain the seismic record. Finally, a relatively realistic seismic record of the underground reservoir is obtained.

[0074] Output the final results, including the original physical properties parameters of the reservoir, the elastic parameters obtained according to the reservoir parameter random displacement algorithm, and the seismic record obtained based on the elastic parameters obtained by the optimized random displacement algorithm.

[0075] The present invention has the following advantages: 1. The present invention optimizes the seismic simulation of traditional underground reservoir parameters, avoids the approximate treatment of the reservoir medium participating in displacement in the traditional method, can greatly improve the accuracy of numerical simulation, reduce the error in the simulation process, and obtain a more accurate underground model. 2. This technology further corrects the fluid substitution theory used in existing research, and randomly simulates the proportion of the reservoir medium participating in displacement, making the numerical simulation results based on the original fluid substitution theory more in line with the actual situation of the reservoir in the surveyed area. 3. Based on the random displacement method of the medium proportion of this technology, it can better predict the different situations of the medium composition proportion in different reservoir models obtained in different working areas, and provide a larger and more real dataset for the further seismic inversion of the underground reservoir model.

[0076] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any example given.

[0077] The embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

[0078] Although the embodiments of the present invention have been shown and described, it can be understood by those of ordinary skill in the art that various equivalent changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalent scope.

Claims

1. A random displacement method for reservoir media in carbon dioxide geological storage, characterized in that , The method includes: Step 101: Determine the theoretical rock physics model and seismic forward modeling parameters using actual logging data and seismic data. Based on the fluid substitution theory, Wood equation, and Gassmann equation in rock physics, establish an underground reservoir model; Step 102: According to the actual reservoir medium composition within the logging, correct the composition of the content and proportion of various media in the underground reservoir during the forward modeling process of the underground reservoir model; Step 103: Through the correction of the content and proportion of media in the underground reservoir, optimize the process of calculating reservoir elastic parameters in the Gassmann equation, correct the algorithms for seismic P-wave velocity, seismic S-wave velocity, and saturated rock density in the underground reservoir during the forward modeling process. Using the idea of random displacement, make the optimized Gassmann equation reflect the true composition of the underground reservoir under actual engineering conditions; Step 104: Compare and study the underground reservoir model obtained by forward modeling using the random displacement method of reservoir media in carbon dioxide geological storage with the elastic parameters and physical properties parameters of the underground model in the actual work area, analyze the differences, and further optimize the random displacement algorithm to make the final result fit the result of the underground reservoir in the actual work area; Step 105: On the premise of optimizing the random displacement algorithm, with the help of the elastic parameters obtained by the random displacement algorithm, use the AVO forward modeling theory, combined with the Zoeppritz equation, to further perform numerical simulation to obtain a seismic record. The seismic record obtained by forward modeling using the elastic parameters obtained by the random displacement algorithm reflects the actual seismic record of the underground reservoir; The theoretical rock physics model is established through the fluid substitution theory of the Gassmann equation and the Zeoppritz equation; the seismic forward modeling parameters include: seismic P-wave velocity Vp, seismic S-wave velocity Vs, reservoir rock density Rho, and seismic record; Establishing the rock physics model includes: for the known physical property parameters of the reservoir, namely porosity, shale content, water saturation, oil saturation, carbon dioxide saturation, and adjusting the corresponding content and proportion of the above physical property parameters using the random displacement algorithm. Through the fluid substitution theory of the Gassmann equation, obtain the elastic parameters, namely seismic P-wave velocity Vp, seismic S-wave velocity Vs, reservoir rock density Rho, and obtain the seismic record using the Zeoppritz equation to complete the forward modeling process; The random displacement algorithm, the expression includes: (1) In the formula, represents the density of the fluid medium in the reservoir after the underground reservoir is displaced by carbon dioxide, and represent the saturation and density of oil in the underground reservoir after carbon dioxide displacement, respectively, and represent the saturation and density of carbon dioxide in the underground reservoir after carbon dioxide displacement, respectively, and represent the saturation and density of water in the underground reservoir after carbon dioxide displacement, respectively, represents a random number, which is related to the content of various media in the reservoir of the actual work area. max and min are the upper and lower limits of the specific parameters of the random process that limit the media participating in the displacement in the reservoir in the random displacement algorithm; （2） In the formula, represents the density of the saturated rock in the reservoir after carbon dioxide displacement, represents the porosity of the reservoir, represents the average density of the rock matrix; Through (1)(2), obtain the density of the saturated rock in the reservoir after carbon dioxide displacement obtained by the random displacement algorithm, as one of the final elastic parameters to be output, and then introduce the following formula: (3) In the formula, represents the velocity of the seismic shear wave in the underground reservoir after carbon dioxide displacement, represents the shear modulus of the saturated rock in the underground reservoir. Through formula (3), the velocity of the seismic shear wave in the reservoir after carbon dioxide displacement is obtained using the random displacement algorithm and is used as one of the elastic parameters to be finally output; (4) In the formula, , , , respectively represent the fluid bulk moduli of the fluid, oil, water, and carbon dioxide in the reservoir after carbon dioxide displacement. The , , involved in Equation (4) are the corresponding saturations obtained through the random displacement algorithm of Equation (1); (5) In the formula, represents the bulk modulus of the rock saturated after carbon dioxide displacement, represents the bulk modulus of the dry rock, represents the elastic modulus of the rock matrix. Substitute the bulk modulus of the fluid in the reservoir obtained from Equation (4) into Equation (5) to obtain the bulk modulus of the rock saturated after carbon dioxide displacement obtained by the random displacement algorithm; (6) Substitute the bulk modulus of the carbon dioxide-displaced saturated rock calculated by Equation (5) into Equation (6) to obtain the elastic modulus of the carbon dioxide-displaced saturated rock ; The random displacement algorithm, the expression is: (7) In the formula, represents the velocity of the seismic longitudinal wave in the underground reservoir after carbon dioxide displacement; the required elastic parameters obtained by forward modeling of physical properties are obtained by synchronizing formulas (1)-(7), and all the obtained elastic parameters are subjected to multiple random displacements using the medium random displacement method in carbon dioxide geological storage, and then the obtained elastic parameters are repeatedly randomly displaced until the elastic parameter results that tend to be stable and conform to the actual working area conditions are obtained.

2. The random displacement method of reservoir medium in carbon dioxide geological storage according to claim 1, characterized in that The Zoeppritz equation, the expression is: (8) Among them, , , , respectively represent the incident angle and transmission angle of the longitudinal wave, and the reflection angle and transmission angle of the shear wave. , , and , , respectively represent the corresponding elastic parameters of medium 1 and medium 2. , , , respectively represent the reflection and transmission coefficients, and t represents time.

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