A method and system for time-lapse seismic monitoring of sensitive attribute parameters for CO2 oil flooding

Abstract

The present invention belongs to the technical field of CO2 plume monitoring, and discloses a method and system for time-lapse seismic monitoring sensitive attribute parameters during CO2 flooding. The method selects a sandstone reservoir with high porosity and high permeability as the target layer; based on the selected sandstone reservoir, rock physics modeling is carried out, and the rock physics modeling is equivalent to rock matrix, rock skeleton, pore filler and saturated rock; based on the obtained rock physics modeling, different concentrations of CO2 are injected into the reservoir, and the corresponding velocity and density values are calculated by using the modified Batzle-Wang formula; after calculating the corresponding velocity and density values, the AVO response is calculated by using the Shuey formula. The present invention analyzes the influence of injecting CO2 under in-situ conditions on the elastic properties of saturated reservoir rocks, and helps to improve the accuracy of using seismic methods for CO2 plume monitoring.

Description

Technical Field

[0001] The present invention belongs to the technical field of CO2 plume monitoring, and in particular relates to a method and system for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring. Background Art

[0002] Continental sedimentary basins are the main geological storage space for CO2. The strong heterogeneity of the reservoir makes it more difficult to capture the differences in seismic responses caused by CO2 injection into the formation. Geophysical methods, especially seismic detection technology, are effective monitoring methods for CO2 migration and leakage throughout the life cycle of CO2 geological storage projects. High-pressure CO2 injection into reservoir rocks will change the density of the reservoir rocks, thereby affecting the propagation characteristics of seismic waves. Therefore, seismic waves can be used to detect the movement of CO2 waves and front edges and the distribution characteristics of CO2.

[0003] CO2 displacement oil and gas technology can not only improve oil and gas recovery rates, but also permanently store CO2 in underground rock pores, which can greatly reduce CO2 emissions. Since the 1960s, existing technologies have begun to carry out research on CO2 oil recovery enhancement (CO2-EOR), which has made a huge contribution to large-scale rapid CO2 emission reductions. The most famous CO2-EOR project is the Weyburn-Midale CO2 Monitoring and Storage Project (Weyburn Project for short) started by the IEA Greenhouse Gas Research and Development Program (IEAGHG) in 2000. Between 2000 and 2016, more than 30 million tons of CO2 were injected cumulatively (https: / / sequestration.mit.edu / tools / projects / weyburn.html). Many scholars have used this as a prototype to conduct extensive research on the principles, methods and techniques of four-dimensional seismic monitoring (Ma and Morozov, 2010; Moradi and Lawton, 2013; Verdon and James, 2016; Maurya et al., 2018; Meng et al., 2023). Limited by geological background and actual data, CO2 storage monitoring technology focuses on studying the seismic response of marine reservoirs (Rostron and Whittaker, 2011; Verdon and James, 2016; Hannis et al., 2017; Daley et al., 2019; Jenkins, 2020; Popik et al., 2020; Gasperikova et al., 2022; GCCSI, 2023). For low-porosity, low-permeability, and highly heterogeneous reservoirs in widely developed continental sedimentary basins, CO2 is injected into underground reservoirs and displaces oil and gas, causing changes in the elastic characteristics of the formation. Whether the differences in seismic wave field response characteristics caused by these changes can be captured is directly related to the feasibility of using four-dimensional seismic to monitor CO2 plume migration under complex continental sedimentary conditions. Considering that CO2 offshore storage has a higher safety factor than onshore storage, offshore basins will be the most important geological storage space for CO2 in the future.

[0004] Through the above analysis, the problems and defects of the existing technology are as follows: when analyzing the changes in geophysical response characteristics caused by CO2 injection into the reservoir, the existing technology calculates two key parameters of CO2 (pseudo-critical temperature and pseudo-critical pressure), but in actual scenarios, these two key parameters are not the laboratory parameters of real CO2, but the parameters of hydrocarbons of the same mass as CO2. Therefore, the changes in elastic parameters caused by CO2 injection into the reservoir are very different from the changes in real CO2. This difference has low accuracy in monitoring the main risks in the effectiveness and safety of CO2 geological storage using geophysical technology. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the disclosed embodiments of the present invention provide a method and system for CO2 oil recovery time-lapse seismic monitoring of sensitive attribute parameters.

[0006] The technical solution is as follows: A method for CO2 oil flooding time-lapse seismic monitoring of sensitive attribute parameters, comprising the steps of:

[0007] S1, select sandstone reservoir with high porosity and high permeability as the target layer;

[0008] S2, rock physics modeling is performed based on the selected sandstone reservoir, and the rock physics modeling is equivalent to rock matrix, rock skeleton, pore filling and saturated rock;

[0009] S3, based on the obtained rock physics modeling, inject different concentrations of CO2 into the reservoir and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula;

[0010] S4, after calculating the corresponding velocity and density values, the Shuey formula is used to calculate the AVO response.

[0011] In step S2, the rock physics modeling is equivalent to the rock matrix, including: using Voigt-Reuss-Hill average to calculate the equivalent rock matrix bulk modulus and shear modulus , calculation formula:

[0012] ;

[0013] In the formula, is the Voigt upper limit, is the Reuss lower bound, is the average rock matrix elastic modulus, For the The volume fraction of the mineral components, For the The elastic modulus of the mineral components, is the number of all mineral components.

[0014] In step S2, rock physics modeling is equivalent to rock skeleton, including: using DEM model to calculate the elastic modulus of dry rock skeleton, for which the bulk modulus and shear modulus of the filler are respectively and , then the coupled form of the differential equations of the DEM model is simplified to:

[0015] ;

[0016] ;

[0017] In the formula, Compute intermediate variables for differentiation, is the differential bulk modulus function, is the differential shear modulus function, are all differential functions, not separate variables, are coefficients of differential functions;

[0018] from arrive Integrate and satisfy the initial conditions ,make ,in, are all differential initial conditions, , respectively represent the equivalent rock matrix bulk modulus and shear modulus ; Get the dry rock skeleton modulus of single pore structure:

[0019] ;

[0020] ;

[0021] In the formula, is the bulk modulus of the dry rock skeleton, is the shear modulus of the dry rock skeleton, is the total porosity of the rock, is a geometric factor related to the pore shape.

[0022] In step S2, the rock physics modeling is equivalent to saturated rock, including: calculating the density of fluid-saturated rock, calculating the bulk modulus of fluid-saturated rock, and calculating the longitudinal and transverse wave velocity values ​​of fluid-saturated rock;

[0023] The calculated fluid saturated rock density is obtained by weighted average of the rock matrix density and the pore fluid density in volume proportion. Based on the target layer being filled with oil and water, the average formula of the two-phase mixed fluid is used for calculation:

[0024] ;

[0025] ;

[0026] In the formula, is the pore fluid density, is the fluid-saturated rock density, is the density of oil, is the rock matrix density, is the water saturation, is the density of water.

[0027] Furthermore, the bulk modulus of saturated rock was calculated using the Biot-Gassmann equation;

[0028] Calculate the P-wave and S-wave velocity values ​​of fluid-saturated rock by using the P-wave and S-wave velocity formulas;

[0029] ;

[0030] ;

[0031] In the formula, is the longitudinal wave velocity, is the shear wave velocity, is the shear modulus of fluid-saturated rock, is the bulk modulus of fluid-saturated rock, is the density of fluid-saturated rock.

[0032] In step S3, the corresponding velocity and density values ​​are calculated using the modified Batzle-Wang formula, including:

[0033] The modified Batzle-Wang formula is:

[0034] ;

[0035] ;

[0036] ;

[0037] In the formula, is Young's modulus, is the pressure under in-situ conditions, is the gravity of CO2, is the density, is the pseudo-critical pressure, All are coefficients, calculated by the following formula:

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] In the formula, is the pseudo-critical temperature;

[0043] It is calculated by the average geothermal gradient of the depression under actual reservoir conditions, 3.3°C;

[0044] ;

[0045] ;

[0046] The effect of CO2 injection into the formation on the seismic response characteristics of the rock is studied using the modified form of the Batzle-Wang equation;

[0047] ;

[0048] In the formula, For compressibility, For volume.

[0049] In step S4, the Shuey formula is used to calculate the AVO response, which is expressed as:

[0050] ;

[0051] In the formula, is the reflection coefficient, is the reflection coefficient at zero angle of incidence, is the second derivative of the wave impedance, is the angle of incidence.

[0052] Furthermore, the sandstone layer was used as the target reservoir to simulate the AVO change curve during CO2 injection. Before CO2 injection, according to the well logging curve, the average parameters of the target reservoir included different P-wave velocities, S-wave velocities, and density of mudstone and sandstone.

[0053] Based on the average parameters of the target reservoir, a reservoir velocity model was constructed, and the interface between the caprock mudstone and sandstone was selected. The fluid replacement formula with different CO2 saturations was used to calculate the P-wave and S-wave velocities and density values, and the Shuey formula was used to calculate the AVO response.

[0054] Furthermore, in the calculation of the AVO response using the Shuey formula, it is included:

[0055] The amplitude of the CO2 parameters calculated using the modified Batzle-Wang equation at zero offset is negative. As the incident angle increases from 30 degrees to 45 degrees, the absolute value of the reflection coefficient gradually decreases. When the CO2 saturation increases from 0% to 40%, the AVO response changes significantly.

[0056] Another object of the present invention is to provide a system for time-lapse seismic monitoring of sensitive attribute parameters for CO2 oil recovery, which implements the method for time-lapse seismic monitoring of sensitive attribute parameters for CO2 oil recovery, and comprises:

[0057] Sandstone reservoir selection module, used to select sandstone reservoirs with high porosity and high permeability as target layers;

[0058] The rock physics modeling module is used to perform rock physics modeling based on the selected sandstone reservoir, and to equate the rock physics modeling to rock matrix, rock skeleton, pore filling and saturated rock;

[0059] The velocity and density value calculation module is used to inject different concentrations of CO2 into the reservoir based on the obtained rock physical modeling, and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula;

[0060] The AVO response calculation module is used to calculate the AVO response using the Shuey formula after calculating the corresponding velocity and density values.

[0061] In combination with all the above technical solutions, the beneficial effects of the present invention are as follows: the present invention will use the seismic and logging data of an oil field for analysis, analyze the changes in the elastic properties of rocks caused by CO2 injection under in-situ conditions through fluid replacement and rock physics modeling, and analyze the sensitivity of seismic attributes to pore fluids through seismic forward simulation, clarifying the ability of time-lapse seismic detection of CO2 plumes in continental sedimentary basins. The present invention analyzes the impact of CO2 injection on the elastic properties of saturated reservoir rocks under in-situ conditions, and helps to improve the accuracy of CO2 plume monitoring using seismic methods. The present invention analyzes the differences caused by traditional practices and clarifies that this difference is the main risk in using geophysical technology to monitor the effectiveness and safety of CO2 geological storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings herein are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description, serve to explain the principles of the present disclosure;

[0063] Figure 1 It is a flow chart of a method for time-lapse seismic monitoring of sensitive attribute parameters of CO2 oil recovery provided by an embodiment of the present invention;

[0064] Figure 2 1 is a comparison diagram of rock physics modeling and measured seismic wave velocity provided by an embodiment of the present invention, wherein the blue solid line represents the result of rock physics modeling calculation, and the red dotted line represents the result of actual measurement; wherein (a) is a P-wave velocity diagram at different depths, (b) is a S-wave velocity diagram at different depths, (c) is a P-wave velocity error diagram at different depths, and (d) is a S-wave velocity error diagram at different depths;

[0065] Figure 3It is a diagram of reservoir parameter changes at different CO2 saturations under the original Batzle-Wang formula provided by an embodiment of the present invention; wherein (a) is a P-wave velocity diagram at different depths under the original Batzle-Wang formula, (b) is an S-wave velocity diagram at different depths under the original Batzle-Wang formula, (c) is a density diagram of different waves at different depths under the original Batzle-Wang formula, and (d) is a ratio of longitudinal and transverse wave velocities at different depths under the original Batzle-Wang formula;

[0066] Figure 4 It is a diagram of reservoir parameter changes at different CO2 saturations under the modified Batzle-Wang formula provided by an embodiment of the present invention; wherein (a) is a modified P-wave velocity diagram at different depths, (b) is a modified S-wave velocity diagram at different depths, (c) is a modified density diagram of different waves at different depths, and (d) is a modified ratio of longitudinal and transverse wave velocities at different depths;

[0067] Figure 5 is the AVO response diagram of different CO2 saturations under the original Batzle-Wang formula provided in the embodiment of the present invention, wherein S CO2 Indicates the saturation of CO2;

[0068] Figure 6 It is an AVO response diagram of different CO2 saturations under the modified Batzle-Wang formula provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific implementation disclosed below.

[0070] The innovation of the present invention is that the terrestrial sedimentary basin is the main CO2 geological storage space in China, and the strong heterogeneity of the reservoir and other characteristics make it more difficult to capture the differences in seismic responses caused by the injection of CO2 into the formation. Geophysical methods, especially seismic detection technology, are effective monitoring methods for CO2 migration and leakage throughout the life cycle of CO2 geological storage projects. The injection of high-pressure CO2 into reservoir rocks will change the density of the reservoir rocks, thereby affecting the propagation characteristics of seismic waves. Therefore, seismic waves can be used to detect the movement of CO2 waves and fronts and the distribution characteristics of CO2. The effect of CO2 injection on the elastic properties of saturated reservoir rocks under in-situ conditions is studied, and AVO response analysis is performed to establish a method and system for sensitive attribute parameters of CO2 oil recovery time-lapse seismic monitoring, which will help improve the accuracy of CO2 migration path monitoring using seismic methods.

[0071] Embodiment 1, the technical features related to the present invention include:

[0072] 1. Anisotropic fluid substitution theory for porous media.

[0073] 1.1 Physical properties of CO2. The main goal of the CO2-EOR project is to inject CO2 into underground oil reservoirs, bury the CO2 used to displace oil underground while increasing oil recovery. The injection of CO2 causes changes in the geophysical properties of reservoir rocks. At present, driven by the urgent need for geological storage of CO2, a large number of mature reservoir numerical simulation software are widely used to study the seepage characteristics after CO2 is injected into the formation due to the storage space and displacement methods are similar to those of oil and gas. In these software, the calculation of CO2 physical properties is mostly completed using the Batzle-Wang (1992) equation. The original intention of developing this equation was to study the geophysical properties of rocks under real reservoir conditions based on the hydrocarbon generation evolution history of source rocks. It is mainly suitable for studying the influence of the presence of hydrocarbons in pores on rock properties. It is based on the gas specific gravity (G) and pseudo-critical temperature ( ) and pressure ( ), a method for calculating pseudo-critical temperature and pressure based on the statistical average value of natural gas specific gravity is given:

[0074] (1)

[0075] (2)

[0076] Among them, the unit of P is MPa, and the unit of T is K.

[0077] Initially, CO2 was considered a gas like hydrocarbons, and its physical properties were calculated using the pseudo-critical temperature and pressure calculated using the formula. The pseudo-critical temperature and pressure of CO2 calculated using the above formulas (1) and (2) are 624 psi (4.3 MPa) and 83.7 °C, respectively, while the critical pressure and temperature of CO2 measured in the laboratory are 1072 psi (7.4 MPa) and 31.1 °C. This difference will undoubtedly lead to people's misunderstanding of the physical properties of CO2. Xu (2006) compared the difference between core experiments and numerical simulations. This difference made the CO2 properties calculated using Batzle-Wang (1992) differ from the laboratory data of Wang and Nur (1989) by as much as 300%.

[0078] The Batzle-Wang equation was modified for CO2 based on laboratory measurement results to describe the physical properties of CO2 under in-situ conditions, so as to better simulate the seismic response characteristics after CO2 injection into the formation. The modified Batzle-Wang equation can be expressed as:

[0079] ;

[0080] ;

[0081] ;

[0082] in:

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] J / g-mole deg (gas constant)

[0088] Among them, G is the gravity of CO2, E is Young's modulus, is the in-situ absolute temperature, which is calculated based on the average geothermal gradient of 3.3℃ in the Bozhong Sag under actual reservoir conditions:

[0089] (3)

[0090] in, is compressibility, P is the pressure under in-situ conditions, and V is the volume.

[0091] (4)

[0092] In the present invention, the influence of CO2 injection into the formation on the seismic response characteristics of the rock will be studied using a modified form of the Batzle-Wang equation.

[0093] (5)

[0094] 1.2 Physical properties of mixed fluid saturated rock. After CO2 is injected into underground reservoirs, it will cause changes in pore fluid composition, saturation and pore pressure, which have an important impact on the rock physical properties of the reservoir. Of course, the injected CO2 will also dissolve in the pore fluid or react with the rock skeleton, but from the experience of monitoring early CCUS projects such as Sleipner, In Salah and Snøhvit, this chemical reaction occurs slowly and relatively rarely, and almost all injected CO2 remains as an independent phase after the injection stops. Wilkinson et al. (2009) found in their analysis of a CO2-rich natural gas field that after tens of millions of years, 70-95% of CO2 still exists in the form of a free phase, and only about 2.4% of CO2 will be mineralized, while a similar amount of CO2 is dissolved in the pore water.

[0095] Therefore, this paper mainly analyzes the impact of changes in pore fluid on reservoir rock physical characteristics in the early stage of CO2 injection project when the rock skeleton does not change. This is a typical fluid replacement problem. Although the properties of pore fluid change with its composition, pressure and temperature, the change is systematic and can be characterized by geophysical methods.

[0096] The determined relationship between pores and pore fluids and rock elasticity is based on the use of seismic wave inversion of the three-phase properties of solid rock skeleton-CO2-oil (gas)-brine (in actual CO2 flooding projects, it is mainly the fluid CO2 that replaces the oil storage pores, and the oil recovery rate is usually 90%, and the state at the end of oil recovery is usually two-phase. CO2 and water are used later. The three phases are too complicated, and after displacement, it is basically CO2 and water) and the movement of pore fluids in rocks is estimated. Under in situ conditions, the fluids commonly encountered in CO2 geological storage projects include brine, oil and gas. The present invention calculates the influence of mixed fluids on the elastic properties of porous medium rocks by assuming the volume fractions of different component fluids. The Gassmann-Biot equation defines the relationship between the bulk modulus of fluid-saturated rock and the elastic properties of the rock skeleton and pore fluid, thereby establishing a theoretical basis for elastic wave propagation in porous media. Bulk modulus of fluid-saturated porous rock Dry modulus and skeleton modulus related

[0097] (6)

[0098] (7)

[0099] in, is the porosity, are the effective bulk moduli of saturated rock, rock skeleton and pore mixed fluid, respectively. is the bulk modulus of the minerals that make up the rock, are the shear moduli of saturated rock and rock skeleton, respectively, and are independent of fluid composition and saturation.

[0100] 2. If Figure 1 As shown, the method for sensitive attribute parameters of CO2 oil recovery time-lapse seismic monitoring provided by the embodiment of the present invention includes:

[0101] S1, select sandstone reservoir with high porosity and high permeability as the target layer;

[0102] S2, performing rock physical modeling based on the selected sandstone reservoir, and equating the rock physical modeling to rock matrix, rock skeleton, pore filling and saturated rock;

[0103] S3, based on the obtained rock physics modeling, inject different concentrations of CO2 into the reservoir and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula;

[0104] S4, after calculating the corresponding velocity and density values, the Shuey formula is used to calculate the AVO response.

[0105] In step S1, it includes: data foundation.

[0106] In this study, a well with relatively complete logging curves in an oil field was selected for numerical simulation. After drilling, the P-wave acoustic time difference, S-wave acoustic time difference, density, neutron and natural gamma data were measured.

[0107] According to the interpretation of single well logging, the effective thickness of a single layer is generally 1-5m, with an average of 2.6m. According to the physical properties of the oil field reservoir, the thicker sandstone reservoir with high porosity and high permeability layers was selected, and the sandstone depth range is 1217.8284m-1224.6864m. Later, the sandstone reservoir will be selected as the target layer, and rock physical modeling, fluid replacement after different concentrations of CO2 are injected into the reservoir, and the corresponding AVO response analysis will be carried out for this layer.

[0108] In step S2, rock physics modeling is included.

[0109] In order to analyze the impact of CO2 injection on reservoir parameters, it is first necessary to accurately model the reservoir in rock physics. Rock physics modeling is equivalent to four parts: rock matrix, rock skeleton, pore filling and saturated rock.

[0110] Based on the petrological characteristics of the Guantao Formation in an oil field, the mineral composition of the rock is known, and the equivalent matrix modulus is calculated using the Voigt-Reuss-Hill average and shear modulus , calculation formula:

[0111] (8)

[0112] In the formula, is the Voigt upper limit, is the Reuss lower bound, is the average rock matrix elastic modulus, For the The volume fraction of the mineral components, For the The elastic modulus of the mineral components, is the number of all mineral components.

[0113] As for the calculation of the elastic modulus of the dry rock skeleton, a certain study area is a medium-high porosity and medium-high permeability reservoir with relatively more primary pores and relatively uniform distribution of pore fluids. The DEM (Differential Effective Medium) model is more suitable for its high porosity. For the dry rock skeleton, the bulk modulus and shear modulus of the filler are and , then the coupled form of the differential equations of the DEM model is simplified to:

[0114] (9)

[0115] (10)

[0116] In the formula, Compute intermediate variables for differentiation, is the differential bulk modulus function, is the differential shear modulus function, are all differential functions, not separate variables, are coefficients of differential functions;

[0117] For formula (9) and formula (10), arrive Integrate and satisfy the initial conditions ,make ,in, are all differential initial conditions, , respectively represent the equivalent rock matrix bulk modulus and shear modulus ; Get the dry rock skeleton modulus of single pore structure:

[0118] (11)

[0119] (12)

[0120] In the formula, is the bulk modulus of the dry rock skeleton, is the shear modulus of the dry rock skeleton, is the total porosity of the rock, is a geometric factor related to the pore shape.

[0121] The fluid-saturated rock density is obtained by weighted average of the rock matrix (constituent minerals) density and the pore fluid density in volume proportion. Based on the target area's target layer being filled with oil and water, the average formula of the two-phase mixed fluid is used for calculation:

[0122] ;

[0123] ;

[0124] In the formula, is the pore fluid density, is the fluid-saturated rock density, is the density of oil, is the rock matrix density, is the water saturation, is the density of water.

[0125] Finally, the bulk modulus of saturated rock is calculated using the Biot-Gassmann equation. The above is the main part of rock physics modeling. Finally, the P-wave and S-wave velocity values ​​are calculated using the P-wave and S-wave velocity formulas.

[0126] ;

[0127] ;

[0128] In the formula, is the longitudinal wave velocity, is the shear wave velocity, is the shear modulus of fluid-saturated rock, is the bulk modulus of fluid-saturated rock, is the density of fluid-saturated rock.

[0129] Compare the velocity values ​​calculated by rock physics modeling with the measured velocities, such as Figure 2Comparison between rock physics modeling and measured seismic wave velocity. Figure 2 It can be concluded that there is almost no error between the rock physics modeling and the measured P-wave velocity, and the error range of the S-wave is also controlled within a certain fluctuation.

[0130] Exemplarily, in step S3, the effect of CO2 saturation changes on reservoir velocity parameters is included.

[0131] After verifying the accuracy of the rock physics modeling process in step 2, different concentrations of CO2 were further injected into the reservoir, and the corresponding velocity and density values ​​were calculated to analyze the AVO response under different CO2 saturations.

[0132] The modified Batzle-Wang formula and the original Batzle-Wang formula were used to calculate the bulk modulus and density at different pressures. According to the proposed optimal injection pressure of 26 MPa in the continuous gas injection experiment, the results obtained under this pressure condition are shown in Table 1. The CO2 attribute parameters in Table 1 are substituted into the fluid replacement formula to further calculate the reservoir velocity and density for subsequent reservoir AVO response calculations and to evaluate the sensitivity of the seismic AVO method to CO2 saturation changes.

[0133] As mentioned in step 1.1, the modified Batzle-Wang formula is more consistent with laboratory data. is the density, All are coefficients, calculated by the following formula:

[0134] ;

[0135] ;

[0136] in,

[0137] ;

[0138] ;

[0139] ;

[0140] ;

[0141] J / g-mole deg (gas constant)

[0142] Therefore, the present invention adopts the CO2 parameter calculated by this formula.

[0143] Table 1 CO2 property parameters at a pressure of 26 MPa

[0144]

[0145] Figure 3 This is a diagram showing the changes in reservoir parameters at different CO2 saturations under the original Batzle-Wang formula, showing the CO2 parameters calculated using the original Batzle-Wang formula. Figure 4 The diagram of reservoir parameter changes at different CO2 saturations under the modified Batzle-Wang formula shows the CO2 parameters calculated using the modified Batzle-Wang formula. Different concentrations of CO2 were injected into the reservoir, and the changes in reservoir parameters, including P-wave velocity, S-wave velocity, density and aspect ratio, were observed.

[0146] After CO2 is injected, the oil in the reservoir is gradually replaced, and this process changes the fluid properties of the reservoir. Since the bulk modulus of CO2 is usually lower than that of oil, it will lead to a decrease in seismic wave velocity. With the increase of CO2 saturation (different dotted line colors represent different CO2 saturations, the black solid line represents the value of the rock physics model, and the others are CO2 saturations of 0.1 to 0.7), the longitudinal wave velocity shows a gradual downward trend, and the shear wave velocity remains almost unchanged. On the contrary, if the bulk modulus of CO2 is higher than that of oil, CO2 with a high bulk modulus is more difficult to compress, which will lead to an increase in the seismic wave velocity.

[0147] exist Figure 3 In the original Batzle-Wang equation, the CO2 parameters calculated have a high bulk modulus, and its bulk modulus is higher than that of oil, which means that after CO2 is injected into the reservoir, the rigidity of the reservoir is enhanced due to the difficulty in compressing the high bulk modulus CO2. Figure 3 In the , the P-wave velocity is relatively high, and as the CO2 concentration increases, the P-wave velocity gradually increases. According to Table 1, the CO2 density calculated using the original Batzle-Wang equation is lower than the density of oil, resulting in Figure 3 There is a significant drop in the density curve.

[0148] exist Figure 4 In the data, the CO2 bulk modulus calculated by the modified Batzle-Wang equation is lower, which means that CO2 is more compressible, thereby reducing the overall rigidity of the reservoir. As the CO2 saturation increases, the P-wave velocity curve continues to decline. This phenomenon is particularly evident in reservoir areas with larger porosity and higher oil content, especially in the depth range of 1220-1222 meters. According to Table 1, the CO2 density calculated using the modified Batzle-Wang equation is only slightly lower than the density of oil. Figure 4The density curve in the stratum therefore shows a small decrease. In contrast, CO2 has a smaller effect on the shear wave velocity after replacing the oil, and the compressional wave velocity usually decreases more, so the Vp / Vs ratio shows a downward trend. Since the Vp / Vs ratio is the most sensitive to parameter changes, its downward trend can better reflect the process of CO2 gradually replacing the oil in the reservoir. Figure 3 and Figure 4 The difference reflects the different effects of CO2 physical properties on reservoir seismic response, which has important academic significance for subsequent reservoir monitoring and fluid property analysis.

[0149] Table 2 Parameters of sandstone medium model of a certain well

[0150]

[0151] Exemplarily, in step S4, the AVO response after different concentrations of CO2 are injected into a typical reservoir is included.

[0152] Taking a certain well as the target sandstone layer, the AVO change curve during CO2 injection is simulated. Before CO2 injection, according to the well logging curve, the average parameters of the target reservoir are shown in Table 2.

[0153] Based on Table 2, a reservoir velocity model was constructed, and the interface between the caprock mudstone and sandstone was selected. The fluid replacement formula with different CO2 saturations was used to calculate the P-wave and S-wave velocities and density values, and the AVO response was calculated using the Shuey formula. Assuming that under the original formation pressure, the reservoir contains three-phase fluids of water, oil and CO2 after oil displacement, and further assuming that the CO2 saturation gradually increases from 0% to 70%, the AVO response results are finally obtained as follows: Figure 5 AVO response diagram for different CO2 saturations under the original Batzle-Wang formula and Figure 6 The AVO response diagram for different CO2 saturations under the modified Batzle-Wang formula is shown in the figure.

[0154] Figure 5 The AVO response curve after CO2 injection into the reservoir is shown using the original Batzle-Wang equation. Figure 6 The figure shows the AVO response curve after calculating the CO2 parameters using the modified Batzle-Wang equation. The different color curves in the two figures represent different CO2 saturations, and both figures show Class IV AVO response.

[0155] exist Figure 5In the case of CO2 parameters calculated using the original Batzle-Wang equation, the amplitude at zero offset is negative, and as the incident angle increases, the absolute value of the reflection coefficient decreases sharply. As the CO2 saturation increases, the AVO curve rises as a whole, but the amplitude change is maintained within 0.005, and the curve changes are not obvious. Figure 6 In the study, the amplitude of the CO2 parameters calculated using the modified Batzle-Wang equation at zero offset is stronger and negative. As the incident angle increases, the absolute value of the reflection coefficient gradually decreases, and when the CO2 saturation increases from 0% to 40%, the change in AVO response is more significant. After CO2 displaces oil, the reflection amplitude of the seismic wave increases, especially at large offset angles (30 to 45 degrees). This shows that after CO2 displaces oil, these characteristics become important signs of changes in fluid properties in the reservoir. The research results further prove that the CO2 parameters calculated using the modified Batzle-Wang equation are more accurate, and the reservoir parameters and AVO response characteristics obtained after injection into the reservoir are more significant, which is helpful for subsequent fluid property monitoring and analysis.

[0156] Embodiment 2, the present invention provides a CO2 oil recovery time-lapse seismic monitoring sensitive attribute parameter system, comprising:

[0157] Sandstone reservoir selection module, used to select sandstone reservoirs with high porosity and high permeability as target layers;

[0158] A rock physics modeling module is used to perform rock physics modeling based on the selected sandstone reservoir, and to equate the rock physics modeling to rock matrix, rock skeleton, pore filling and saturated rock;

[0159] The velocity and density value calculation module is used to inject different concentrations of CO2 into the reservoir based on the obtained rock physical modeling, and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula;

[0160] The AVO response calculation module is used to calculate the AVO response using the Shuey formula after calculating the corresponding velocity and density values.

[0161] The present invention constructs a rock physics model based on the petrological characteristics of an oil field in a certain study area and the analysis of its logging data. The DEM model is used to calculate the dry rock skeleton modulus mainly for the characteristics of high porosity. The rock physics modeling calculated value of the longitudinal wave velocity is compared with the measured value, and the rock physics modeling of the target area is established.

[0162] Before and after the modification of the Batzle-Wang equation, the results show that the bulk modulus and density of CO2 have a significant effect on the P-wave velocity and Vp / Vs ratio of the reservoir, and these effects are more obvious in reservoirs with high porosity and high fluid saturation. Figure 3 and Figure 4 The comparative analysis further reveals the different effects of CO2 physical properties on reservoir rigidity and seismic response, which provides an important reference for reservoir monitoring and fluid property analysis after CO2 injection.

[0163] The AVO response curve results show that the modified Batzle-Wang equation can provide more accurate reservoir parameters, and the AVO response characteristics are more significant with the increase of CO2 saturation. In particular, the significant change of reflection amplitude at larger offset angles highlights the importance of this modification method in enhancing the monitoring and analysis of fluid properties in CO2-injected reservoirs.

[0164] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for time-lapse seismic monitoring of sensitive attribute parameters for CO2 oil recovery, characterized in that: The method comprises the steps of: S1, select sandstone reservoir with high porosity and high permeability as the target layer; S2, rock physics modeling is performed based on the selected sandstone reservoir, and the rock physics modeling is equivalent to rock matrix, rock skeleton, pore filling and saturated rock; S3, based on the obtained rock physics modeling, inject different concentrations of CO2 into the reservoir and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula; S4, after calculating the corresponding velocity and density values, the AVO response is calculated using the Shuey formula; In step S3, the corresponding velocity and density values ​​are calculated using the modified Batzle-Wang formula, including: The modified Batzle-Wang formula is: ； In the formula, is Young's modulus, is the pressure under in-situ conditions, is the gravity of CO2, is the density, is the pseudo-critical pressure, All are coefficients, calculated by the following formula: ； In the formula, is the pseudo-critical temperature; It is calculated by the average geothermal gradient of the depression under actual reservoir conditions, 3.3°C; ； The effect of CO2 injection into the formation on the seismic response characteristics of the rock is studied using the modified form of the Batzle-Wang equation; ； In the formula, For compressibility, For volume.

2. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 1, characterized in that: In step S2, the rock physics modeling is equivalent to the rock matrix, including: using Voigt-Reuss-Hill average to calculate the equivalent rock matrix bulk modulus and shear modulus , the calculation formula is: ； In the formula, is the Voigt upper limit, is the Reuss lower bound, is the average rock matrix elastic modulus, For the The volume fraction of the mineral components, For the The elastic modulus of the mineral components, is the number of all mineral components.

3. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 2, characterized in that: In step S2, rock physics modeling is equivalent to rock skeleton, including: using DEM model to calculate the elastic modulus of dry rock skeleton, for which the bulk modulus and shear modulus of the filler are respectively and , then the coupled form of the differential equations of the DEM model is simplified to: ； In the formula, Compute intermediate variables for differentiation, is the differential bulk modulus function, is the differential shear modulus function, are all differential functions, are coefficients of differential functions; from arrive Integrate and satisfy the initial conditions , ,make ,in, are all differential initial conditions, are the equivalent rock matrix bulk moduli and shear modulus ; Get the dry rock skeleton modulus of single pore structure: ； In the formula, is the bulk modulus of the dry rock skeleton, is the shear modulus of the dry rock skeleton, is the total porosity of the rock, is a geometric factor related to the pore shape.

4. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 3 is characterized in that: In step S2, the rock physics modeling is equivalent to saturated rock, including: calculating the density of fluid-saturated rock, calculating the bulk modulus of fluid-saturated rock, and calculating the longitudinal and transverse wave velocity values ​​of fluid-saturated rock; The calculated fluid saturated rock density is obtained by weighted average of the rock matrix density and the pore fluid density in volume proportion. Based on the target layer being filled with oil and water, the average formula of the two-phase mixed fluid is used for calculation: ； In the formula, is the pore fluid density, is the fluid-saturated rock density, is the density of oil, is the rock matrix density, is the water saturation, is the density of water.

5. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 4, characterized in that: The bulk modulus of saturated rock is calculated using the Biot-Gassmann equation; Calculate the P-wave and S-wave velocity values ​​of fluid-saturated rock by using the P-wave and S-wave velocity formulas; ； In the formula, is the longitudinal wave velocity, is the shear wave velocity, is the shear modulus of fluid-saturated rock, is the bulk modulus of fluid-saturated rock, is the density of fluid-saturated rock.

6. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 1, characterized in that: In step S4, the Shuey formula is used to calculate the AVO response, which is expressed as: ； In the formula, is the reflection coefficient, is the reflection coefficient at zero angle of incidence, is the second derivative of the wave impedance, is the angle of incidence.

7. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 6, characterized in that: Taking the sandstone layer as the target reservoir, the AVO change curve during CO2 injection is simulated. Before CO2 injection, according to the well logging curve, the average parameters of the target reservoir include different P-wave velocities, S-wave velocities and density of mudstone and sandstone; Based on the average parameters of the target reservoir, a reservoir velocity model was constructed, and the interface between the caprock mudstone and sandstone was selected. The fluid replacement formula with different CO2 saturations was used to calculate the P-wave and S-wave velocities and density values, and the Shuey formula was used to calculate the AVO response.

8. The method for sensitive attribute parameters of CO2 oil flooding time-lapse seismic monitoring according to claim 7, characterized in that: In the calculation of AVO response using Shuey formula, it includes: The amplitude of the CO2 parameters calculated using the modified Batzle-Wang equation at zero offset is negative. As the incident angle increases from 30 degrees to 45 degrees, the absolute value of the reflection coefficient gradually decreases. When the CO2 saturation increases from 0% to 40%, the AVO response changes significantly.

9. A CO2 oil flooding time-lapse seismic monitoring sensitive attribute parameter system, characterized in that: The method for time-lapse seismic monitoring of sensitive attribute parameters of CO2 oil recovery according to any one of claims 1 to 8 is implemented, and the system comprises: Sandstone reservoir selection module, used to select sandstone reservoirs with high porosity and high permeability as target layers; The rock physics modeling module is used to perform rock physics modeling based on the selected sandstone reservoir, and to equate the rock physics modeling to rock matrix, rock skeleton, pore filling and saturated rock; The velocity and density value calculation module is used to inject different concentrations of CO2 into the reservoir based on the obtained rock physical modeling, and calculate the corresponding velocity and density values ​​using the modified Batzle-Wang formula; The AVO response calculation module is used to calculate the AVO response using the Shuey formula after calculating the corresponding velocity and density values.

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