Gas reservoir time-lapse seismic acquisition opportunity chart establishing method and system

Abstract

The invention relates to the technical field of seismic exploration, in particular to a method and system for establishing a gas reservoir time-lapse seismic acquisition opportunity chart, and the method comprises the steps: carrying out the experimental measurement of a rock core sample of a target gas field, and obtaining rock physical elastic parameters; acquiring and analyzing data of the target gas field, and constructing a geological model of the target gas field; performing rock physical modeling based on the rock physical elastic parameters and the target gas field geologic model to obtain a target rock physical model; carrying out time-lapse seismic forward modeling based on the target rock physical model and the White air pocket model; and obtaining a relationship among the pore pressure, the gas saturation change and the seismic response based on a simulation result, and drawing a gas reservoir time-lapse seismic acquisition opportunity chart. The gas reservoir time-lapse seismic acquisition opportunity chart established by the invention accurately maps actual gas reservoir characteristics, effectively guides the optimal selection of acquisition opportunities, and ensures the accuracy and reliability of seismic monitoring data.

Description

Technical Field

[0001] The present invention relates to the field of seismic detection technology, and in particular to a method and system for establishing a time-lapse seismic acquisition timing chart for a gas reservoir. Background Art

[0002] In the long-term development process of gas fields, with the gradual depletion of resources, many gas fields have entered the middle and late stages of development or even the final stages. In order to improve the development efficiency of gas fields, it is particularly important to accurately grasp the dynamic changes of gas reservoirs. This requires us to implement seismic monitoring of gas reservoirs, aiming to accurately predict the remaining gas volume, and adjust the production strategy accordingly to tap potential resources. Time-lapse seismic technology, as an effective method to monitor the dynamic changes of oil and gas reservoirs based on the change of seismic response over time, has gradually become a key technical means for oil and gas reservoir management and monitoring. However, before implementing time-lapse seismic research, conducting a detailed feasibility study is an indispensable step to ensure the applicability and effectiveness of the technology. In this context, the time-lapse seismic acquisition timing chart is particularly important. It provides a solid theoretical basis for feasibility studies and guides us on how to reasonably choose the acquisition timing of time-lapse seismic, thereby ensuring the accuracy and reliability of monitoring results. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for establishing a time-lapse seismic acquisition timing map of a gas reservoir in order to solve at least one of the above technical problems.

[0004] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0005] A method for establishing a gas reservoir time-lapse seismic acquisition timing chart comprises the following steps:

[0006] Conduct experimental measurements on core samples of the target gas field to obtain rock physical elastic parameters;

[0007] Acquire and analyze the data of the target gas field to construct a geological model of the target gas field;

[0008] Perform rock physics modeling based on the rock physics elastic parameters and the target gas field geological model to obtain a target rock physics model;

[0009] Conduct time-lapse seismic forward modeling based on the target rock physics model and White air bag model;

[0010] Based on the simulation results, the relationship between pore pressure, gas saturation changes and seismic response is obtained, and a time-lapse seismic acquisition timing chart for gas reservoirs is drawn.

[0011] Furthermore, experimental measurements are carried out on core samples of the target gas field, including:

[0012] Experimental measurement of rock physical elastic parameters of the core samples under different driving types, different development layers, and different temperature and pressure system conditions with variable pressure and pressure;

[0013] The rock physical elastic parameters include longitudinal wave velocity, shear wave velocity and density.

[0014] Furthermore, the velocity measurement principle is rock wave velocity = rock sample length / (sound wave arrival time - system base time); the density measurement principle is rock sample density = (dry sample mass + pore fluid mass) / total rock sample volume.

[0015] Furthermore, rock physics modeling is performed, specifically, the relationship between the rock physics elastic parameters and the gas reservoir characteristic parameters is matched with the existing rock physics model, and the rock physics model with the highest matching degree is selected as the target rock physics model.

[0016] Furthermore, the target gas field geological model includes a single factor model, a multi-factor model and an actual geological model;

[0017] The construction of the geological model of each target gas field needs to take into account the mechanism model and gas reservoir model of the target gas field.

[0018] Furthermore, based on the variation range of porosity, thickness, gas content and pressure of the gas field reservoir of the target gas field, a geological model of the target gas field is constructed.

[0019] Furthermore, the gas reservoir time-lapse seismic acquisition timing chart includes the following data: signal-to-noise ratio analysis results, gas content / pressure change rules inside the gas reservoir, spatial time-lapse seismic difference statistics results, time-lapse seismic spatial change rules, and target gas field acquisition timing analysis results.

[0020] A system for establishing a timing chart for time-lapse seismic acquisition of a gas reservoir, comprising:

[0021] The measurement module is used to conduct experimental measurements on core samples of the target gas field to obtain rock physical elastic parameters;

[0022] A model building module is used to acquire data of the target gas field for analysis and to build a geological model of the target gas field; the model building module is also used to perform rock physics modeling based on the rock physics elastic parameters and the geological model of the target gas field to acquire a target rock physics model;

[0023] The map generation module is used to carry out time-lapse seismic forward simulation based on the target rock physics model and the White gas bag model; obtain the relationship between pore pressure, gas saturation change and seismic response based on the simulation results and draw a gas reservoir time-lapse seismic acquisition timing map.

[0024] An electronic device, characterized in that it includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements any of the above methods for establishing a time-lapse seismic acquisition timing map for a gas reservoir.

[0025] A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, it implements any of the above methods for establishing a time-lapse seismic acquisition timing map of a gas reservoir.

[0026] The beneficial effects of the present invention are:

[0027] The present invention provides a method and system for establishing a time-lapse seismic acquisition timing map for gas reservoirs. Through laboratory measurement, geological model construction, rock physics modeling and time-lapse seismic forward simulation, the changing characteristics of the time-lapse seismic response of the gas field are clarified, and the acquisition timing of the gas field is analyzed by comprehensively considering various factors, providing a theoretical basis for the feasibility study of time-lapse seismic. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A method flow chart for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention Figure 1 ;

[0029] Figure 2 A schematic diagram of a method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention;

[0030] Figure 3 A method flow chart for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention Figure 2 ;

[0031] Figure 4 It is a schematic diagram of White's spherical model;

[0032] Figure 5 It is a schematic diagram of the White spherical model unit;

[0033] Figure 6 Comparison diagram of seismic forward modeling sections of wells connected at different times;

[0034] Figure 7 This is the difference profile of the forward seismic modeling of Lianjing in 2020 and 2010;

[0035] Figure 8 A time-lapse seismic response chart of a target gas field according to an embodiment of the present invention;

[0036] Fig. 9 A time-lapse seismic acquisition timing chart of a target gas field according to an embodiment of the present invention;

[0037] Fig.10 Establishing a system structure diagram for a gas reservoir time-lapse seismic acquisition timing chart according to one embodiment of the present invention;

[0038] Fig.11 This is a schematic diagram of the White air bag theoretical model adopted in the present invention;

[0039] Fig.12 This is the comparison result between the measured data and the model data;

[0040] Fig.13 This is the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing frequency;

[0041] Fig.14 This is the relationship between the P-wave velocity calculated by the White gas pocket model and the gas saturation under the condition of varying porosity;

[0042] Fig.15 This is the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing temperature;

[0043] Fig.16 This is the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing effective pressure;

[0044] Fig.17 Analysis of experimental and model data on the variation of P-wave velocity with gas saturation Figure 1 ;

[0045] Fig.18 Analysis of experimental and model data on the variation of P-wave velocity with gas saturation Figure 2 ;

[0046] Fig.19 P-wave velocity comparison between core measurement results and logging and model results Figure 1 ;

[0047] Fig. 20 P-wave velocity comparison between core measurement results and logging and model results Figure 2 ;

[0048] Fig.21 Comparison of shear wave velocity between core measurement results and logging and model results Figure 1 ;

[0049] Fig. 22 Comparison of shear wave velocity between core measurement results and logging and model results Figure 2 . DETAILED DESCRIPTION

[0050] The content of the present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only to enable those skilled in the art to better understand and thus implement the content of the present invention, rather than implying any limitation on the scope of the present invention.

[0051] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on.” The terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0052] Embodiment 1

[0053] Figure 1 A method flow chart for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention Figure 1 ; Figure 2 A schematic diagram of a method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention; Figure 3 A method flow chart for establishing a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention Figure 2 .like Figure 1-3 As shown, according to one embodiment of the present invention, a method for establishing a gas reservoir time-lapse seismic acquisition timing map includes the following steps:

[0054] Step S102, conducting experimental measurements on core samples of the target gas field to obtain rock physical elastic parameters;

[0055] Step S104, acquiring and analyzing data of the target gas field to construct a geological model of the target gas field;

[0056] Step S106, performing rock physics modeling based on rock physics elastic parameters and the target gas field geological model to obtain a target rock physics model;

[0057] Step S108, performing time-lapse seismic forward modeling based on the target rock physics model and the White air bag model;

[0058] Step S110, based on the simulation results, the relationship between the pore pressure, gas saturation change and seismic response is obtained and a time-lapse seismic acquisition timing chart of the gas reservoir is drawn.

[0059] In this embodiment, in step S102, the core samples of the target gas field are experimentally measured to obtain rock physical elastic parameters; starting from the rock physical experiment, the core samples in the production gas field (i.e., the target gas field) are sampled as samples, and the rock physical elastic parameters of the core samples are experimentally measured. In step S104, the data of the target gas field are obtained and analyzed to construct a geological model of the target gas field; starting from the analysis of basic data, the porosity, thickness, gas content and pressure of the gas field reservoir are clarified, and a theoretical model of the gas field (i.e., the geological model of the target gas field) is constructed in a variety of ways. Since the factors affecting the difference in time-lapse seismic are often not only the degree of change in gas saturation and pressure, but also related to the thickness, physical properties of the reservoir and the rock physical characteristics of the overlying strata; therefore, in order to reasonably explain the characterization significance of the difference in time-lapse seismic, it is necessary to start from the seismic response mechanism, so as to more accurately guide the interpretation of time-lapse seismic. In step S106, the optimization and calibration of the theoretical rock physics model are guided by the measured rock physics elastic parameter law, and the characteristic parameters of the gas reservoir (rock physics parameters under specific conditions) are accurately converted into rock physics elastic parameters to complete the rock physics modeling process. Due to the dispersion phenomenon of velocity, the White gas bag model considering the frequency effect is introduced for rock physics modeling, and finally the target rock physics model is generated. In step S108, the time-lapse seismic forward simulation study is carried out in combination with the time-lapse elastic parameters obtained by the rock physics forward modeling; in step S110, the rock physics elastic parameters are updated based on the changes in pore pressure and gas saturation, and the seismic response is obtained according to the updated rock physics elastic parameters, so as to analyze the correlation between the pore pressure, gas saturation changes and seismic response, and draw the timing chart of the time-lapse seismic acquisition of the gas reservoir.

[0060] In the process of rock physics modeling, the existing technology usually uses the Gassmann equation. Due to the dispersion of velocity, the Gassmann equation is only applicable to low-frequency elastic waves and cannot match the experimental measurement law, so rock physics modeling cannot be completed based on the experimental law. Therefore, the present invention introduces the white air bag model that takes into account the frequency effect for rock physics modeling.

[0061] White (1975) simulated the effect of patchy saturation on seismic waves by considering a porous rock that is saturated with formation water but contains spherical gas regions. The inhomogeneous saturation patches (spherical) are much larger than the grain scale but much smaller than the wavelength. Figure 4 This is a schematic diagram of the White spherical model. Figure 5 is a schematic diagram of the White spherical model unit. Figure 4 and Figure 5As shown in the figure, the middle sphere represents gas-saturated porous rock, and the surrounding cubes represent fully water-saturated porous rock. The ideal geometry of each unit includes a gas-filled sphere with radius a in the center and the surrounding cubes are abstracted as a spherical shell saturated with formation water with radius b. Adjacent units do not interact with each other. The gas saturation inner region is represented by subscript 1, and the outer shell is represented by subscript 2.

[0062] The complex bulk modulus K* of partially saturated porous rock, as a function of the angular frequency ω, is given by:

[0063]

[0064] The derivation process is as follows:

[0065]

[0066] α j =(iωη j / κ j K Ej ) 1 / 2

[0067]

[0068] Where: K is the bulk modulus; ω is the angular frequency; j = 1 or 2 represents two corresponding different regions; η is the fluid viscosity, Pa.s; K f ——bulk modulus, GPa; φ——porosity, %; κ——permeability, mD; K0——bulk modulus of solid mineral particles, GPa; K j ——saturation bulk modulus of region j, GPa; μ j ——Shear modulus of region j, GPa; K dryj ——bulk modulus of dry sample, GPa; μ dryj ——Dry sample shear modulus, GPa; K fj ——fluid bulk modulus, GPa; Sg——gas saturation, Sg=a 3 / b 3 , where a is the radius of the gas-filled sphere in the White spherical model, b is the outer radius of the formation water-saturated spherical shell in the White spherical model, b>a; K ∞ ——the bulk modulus in the high-frequency limit when there is no fluid flow between regions 1 and 2; ρ0——the effective density of the solid mineral, ρ f1 ——Effective density of fluid in region 1, ρ f2 ——effective density of the fluid in region 2; i——complex number; M r * ——longitudinal wave modulus of the real part; M i *——imaginary part of the longitudinal wave modulus; K i * ——effective complex bulk modulus; K 0j , K Aj ——First bulk modulus algebra, second bulk modulus algebra.

[0069] When the rock skeleton modulus of the two regions is the same, μ1=μ2=μ dry , because Gassmann predicts that fluid substitution does not change the shear modulus, in the high-frequency limit, when there is no fluid flow between regions 1 and 2, the bulk modulus is:

[0070]

[0071] P wave velocity V p * and the attenuation coefficient α p * From the complex P wave modulus M * and the effective density ρ * The form of:

[0072]

[0073] Where: * is the effective density; M * is the complex P-wave bulk modulus; μ * is the complex P-wave shear modulus; α p * is the attenuation coefficient; θ p * is the angle; V p * is the P-wave velocity.

[0074] When the White gas pocket model is developed for an actual gas field, the sample point calibration method is mainly used to repeatedly adjust the rock physics model parameters to complete the White model calibration (the rock physics parameters of the actual sample points are approximately consistent with the model parameters).

[0075] Combined with the time-lapse elastic parameters obtained from rock physics forward modeling, time-lapse seismic forward modeling research was carried out to obtain the seismic forward modeling profile that changes with time. Figure 6 The following are comparison diagrams of seismic forward modeling sections of wells at different times. Figure 6 As shown in the figure, by comparing and analyzing the differences, it is found that the seismic energy corresponding to each gas group in the target gas field gradually weakens over time. Figure 7 This is the difference profile of the forward seismic modeling of Lianjing in 2020 and 2010. Figure 7As shown, the forward seismic data of 2020 and 2010 (calculated by professional software under given rock physical parameters) are subtracted to obtain the time-lapse seismic difference profile; the difference profile can clarify when the difference reaches the maximum, guide the time-lapse seismic acquisition at the optimal time, thereby achieving the best effect, and facilitating subsequent gas field production research. Figure 7 The results show that the seismic energy decreases the most in the area of ​​gas-water replacement, and the rest of the area shows weak negative energy difference as a whole. The analysis shows that the target gas field is a strong edge water gas reservoir with limited pore pressure reduction, and the time-lapse seismic difference is mainly affected by the change of gas saturation. Figure 8 This is a time-lapse seismic response diagram of a target gas field in one embodiment of the present invention. Figure 8 As shown, the time-lapse seismic response characteristics of the target gas field geological model are analyzed to establish the time-lapse seismic response map of the target gas field.

[0076] The present invention introduces the White gas bag model that takes frequency influence into consideration for rock physics modeling, and combines it with time-lapse seismic forward simulation to successfully establish a time-lapse seismic acquisition timing chart for gas reservoirs, effectively solving the problem of inaccurate rock physics modeling caused by velocity dispersion in the prior art, providing a scientific basis for the optimal acquisition timing of time-lapse seismic, and facilitating subsequent gas field production research.

[0077] According to one embodiment of the present invention, step S102 includes:

[0078] Experimental measurement of rock physical elastic parameters of core samples under different driving types, different development layers, and different temperature and pressure system conditions with variable pressure and pressure;

[0079] Rock physical elastic parameters include longitudinal wave velocity, shear wave velocity and density.

[0080] Preferably, the velocity measurement principle is rock wave velocity = rock sample length / (acoustic wave arrival time-system base time); the density measurement principle is rock sample density = (dry sample mass+pore fluid mass) / total rock sample volume.

[0081] Rock physics acoustic measurement is a bridge between reservoir rock physics characteristics and seismic response, and oil and gas reservoir exploitation mainly causes changes in formation pressure and gas saturation. In this implementation, starting with rock physics experiments, experimental measurements of variable pressure and variable saturation rock physics elastic parameters (P-wave velocity, S-wave velocity, density) of cores in production gas fields (target gas fields) are carried out under different drive types, different development layers, and different temperature and pressure system conditions; the velocity measurement principle is rock wave velocity = rock sample length / (sound wave arrival time-system base time), and the density measurement principle is rock sample density = (dry sample mass + pore fluid mass) / total rock sample volume. The three elastic parameters of P-wave velocity, S-wave velocity and density of core samples are measured in the laboratory, and the remaining elastic parameters can be derived based on these three parameters.

[0082] There are dozens of commonly used rock physical parameters, but for a homogeneous isotropic medium, there are only three independent rock physical parameters, namely, P-wave velocity, S-wave velocity and density. Other parameters (such as the commonly used Poisson's ratio, Lame parameter, Young's modulus, bulk modulus, shear modulus, P-wave and S-wave impedance, etc.) can be derived. Therefore, the P-wave and S-wave velocities and density parameters are mainly measured in the laboratory, and other parameters are converted through these three parameters. After using the measurement system to measure the acoustic wave velocity and density parameters of the core, for example, they are calculated by the following formula:

[0083] Poisson's ratio:

[0084] Shear modulus: μ = ρV s 2

[0085] Bulk modulus:

[0086] Young's modulus: E = 3K (1-ν)

[0087] Wave impedance: Z = Vel*ρ

[0088] The present invention conducts experimental measurements of rock physical elastic parameters of core samples under different conditions with variable pressure and variable saturation, accurately obtains key parameters such as P-wave velocity, S-wave velocity and density, and provides reliable data support for building a bridge between reservoir rock physical characteristics and seismic response.

[0089] According to an embodiment of the present invention, step S106 specifically includes: matching the relationship between rock physical elastic parameters and gas reservoir characteristic parameters with the existing rock physical model, and selecting the rock physical model with the highest matching degree as the target rock physical model.

[0090] In this implementation, the optimization and calibration of the theoretical rock physics model are guided by the measured rock physics elastic parameter law, and the gas reservoir characteristic parameters (actual rock physics parameters of the gas reservoir under certain temperature and pressure conditions) are accurately converted into rock physics elastic parameters (rock physics parameters calculated by a certain theoretical model) to complete the rock physics modeling process. There are many theoretical rock physics models in the geophysical industry. According to the measured rock physics elastic parameter law, various theoretical models are constantly compared to find a theoretical model that is close to the measured law.

[0091] The present invention matches the measured rock physical elastic parameters with a variety of theoretical rock physical models, selects the model with the highest matching degree as the target rock physical model, realizes the accurate conversion of gas reservoir characteristic parameters to rock physical elastic parameters, and improves the accuracy and reliability of rock physical modeling.

[0092] According to an embodiment of the present invention, the target gas field geological model includes a single factor mode model, a multi-factor mode model and an actual geological model;

[0093] The construction of the geological model of each target gas field must take into account the mechanism model and gas reservoir model of the target gas field.

[0094] Preferably, a geological model of the target gas field is constructed based on the variation range of porosity, thickness, gas content and pressure of the gas field reservoir of the target gas field.

[0095] For time-lapse seismic, the difference in seismic reflection characteristics at different times is not only affected by the acquisition and processing, but the most important change is that the elastic modulus, density and other characteristics of the rock have changed. Usually, gas field development mainly leads to a decrease in the pore pressure and gas saturation of the reservoir, and the corresponding reservoir velocity and density change accordingly. Therefore, the seismic response formed by the reservoir and background mudstone will change with the continuous exploitation of the gas reservoir. In this implementation, starting with the analysis of basic data, the variation range of the porosity, thickness, gas content and pressure of the gas field reservoir is clarified, and the theoretical model of the gas field is constructed in three ways: single factor, multi-factor and reservoir model. Combining the three analysis methods of time-lapse seismic response, a time-lapse seismic response chart of the target gas field is established.

[0096] The factors that affect the difference in time-lapse seismic are often not only the degree of change in gas saturation and pressure, but also related to the thickness, physical properties of the reservoir and the rock physical characteristics of the overlying strata. Therefore, in order to reasonably explain the characterization significance of the difference in time-lapse seismic, it is necessary to start with the seismic response mechanism, so as to more accurately guide the interpretation of time-lapse seismic. In this implementation, the study of the time-lapse seismic response mechanism is mainly based on three forward models for analysis and research. The single-factor model is to establish a wedge model in combination with the actual situation of the gas field, and then assign a single change to the pore pressure and gas saturation respectively, and carry out forward simulation in combination with the rock physics forward modeling results. Finally, the influence of gas saturation, pore pressure and reservoir thickness changes on seismic response is analyzed. The multi-factor model uses the physical properties and gas saturation curves of the actual well to replace fluid and pore pressure, and then combines the production dynamic change law of the gas saturation and bottom hole pressure of the well to realize the time-lapse seismic forward simulation of the well point location. The actual reservoir model is based on the geological model and three-dimensional numerical model of the gas field, aiming to implement the spatial change law of time-lapse seismic.

[0097] The present invention constructs a variety of target gas field geological models including single-factor model, multi-factor model and actual geological model, and comprehensively considers the variation range of porosity, thickness, gas content and pressure of gas field reservoir, so as to more accurately reveal the mechanism of time-lapse seismic response, provide a scientific basis for the reasonable interpretation of time-lapse seismic differences, and effectively guide the interpretation of time-lapse seismic and subsequent gas field production research.

[0098] Fig. 9 This is a time-lapse seismic acquisition timing chart of a target gas field in one embodiment of the present invention. Fig. 9 As shown, according to one embodiment of the present invention, the gas reservoir time-lapse seismic acquisition timing map includes the following data: signal-to-noise ratio analysis results, gas content / pressure change rules inside the gas reservoir, spatial time-lapse seismic difference statistics results, time-lapse seismic spatial change rules, and target gas field acquisition timing analysis results.

[0099] The present invention constructs a gas reservoir time-lapse seismic acquisition timing chart that includes signal-to-noise ratio analysis results, gas reservoir internal gas content / pressure change rules, spatial time-lapse seismic difference statistics, time-lapse seismic spatial change rules and target gas field acquisition timing analysis results. The chart is intuitive and easy to understand, provides comprehensive and accurate data support for determining the optimal seismic acquisition timing, and effectively improves the efficiency and accuracy of gas reservoir monitoring and development.

[0100] The present invention provides a complete method for establishing a time-lapse seismic acquisition timing chart for gas reservoirs, laying a solid theoretical foundation for the feasibility study of time-lapse seismic. This method closely revolves around the actual challenges faced by production gas fields, and through meticulous laboratory measurements, systematically summarizes the changing laws of rock velocity under different temperature, pressure and gas saturation conditions. On this basis, a model that matches the dynamics of gas field development is constructed, and the White gas bag model considering the dispersion effect is optimized, and the dispersion effect is fully considered, successfully building a bridge for rock physics modeling between the ultrasonic frequency band and the seismic frequency band. The present invention can clearly reveal the time-lapse seismic response characteristics of the gas field, and deeply analyze its main controlling factors, including changes in dynamic data such as gas saturation and pressure; comprehensively consider multiple dimensions such as noise impact, time-lapse seismic change laws, gas reservoir dynamic data changes, and economic evaluation, scientifically and rationally analyze the acquisition timing of the gas field, and draw a gas reservoir time-lapse seismic acquisition timing chart. The chart is intuitive and easy to understand, and provides comprehensive and accurate data support for determining the optimal seismic acquisition timing, significantly improving the efficiency and accuracy of gas reservoir monitoring and development.

[0101] Embodiment 2

[0102] Fig.10 A system structure diagram is established for a gas reservoir time-lapse seismic acquisition timing chart according to an embodiment of the present invention, such as Fig.10 As shown, according to one embodiment of the present invention, a system for establishing a time-lapse seismic acquisition timing chart for a gas reservoir includes:

[0103] The measurement module 10 is used to perform experimental measurement on the core samples of the target gas field to obtain the physical elastic parameters of the rock;

[0104] The model building module 20 is used to obtain data of the target gas field for analysis and to build a geological model of the target gas field; the model building module 20 is also used to perform rock physics modeling based on rock physics elastic parameters and the geological model of the target gas field to obtain a target rock physics model;

[0105] The map generation module 30 is used to carry out time-lapse seismic forward simulation based on the target rock physics model and the White gas bag model; obtain the relationship between pore pressure, gas saturation change and seismic response based on the simulation results and draw a gas reservoir time-lapse seismic acquisition timing map.

[0106] According to one embodiment of the present invention, an electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, any method for establishing a time-lapse seismic acquisition timing map of a gas reservoir according to the present invention is implemented.

[0107] According to one embodiment of the present invention, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any method for establishing a time-lapse seismic acquisition timing map of a gas reservoir of the present invention is implemented.

[0108] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and media can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0109] Embodiment 3

[0110] In this embodiment, a gas field in the target area is used as the research area to illustrate the technical effect of the present invention. The gas field has been developed for more than ten years and has entered the middle and late stages of development as the development time increases. In order to predict the remaining gas in the middle and late stages of the gas field and adjust the potential to achieve the goal of efficient development of the gas field, it is necessary to conduct seismic monitoring of the gas reservoir. The establishment of a time-lapse seismic acquisition timing chart for the gas reservoir can provide a theoretical basis for the feasibility study of time-lapse seismic.

[0111] The sound wave frequency used in experimental rock physics measurements is 500KHz, while the Gassmann model, Xu-White model, etc. are only applicable to low-frequency seismic data, and the prerequisite for their establishment is that the fluid is evenly distributed inside the rock. Therefore, the above theoretical models are not suitable for studying experimental rock physics measurements. As an effective model for studying the change of sound wave properties with gas saturation, the White gas bag model has the advantages of not being restricted by pore shape, being able to study the influence of pore fluid distribution on sound wave properties, and being able to study the change of sound waves at different frequencies with different gas saturations. The present invention takes into account the influence of dispersion on velocity and introduces the White gas bag model as an effective model for studying the change of sound wave properties with gas saturation.

[0112] Fig.11 This is the principle diagram of the White air bag theoretical model adopted in the present invention. Fig.12 This is the comparison result between the measured data and the model data. Fig.13 This is the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing frequency. Fig.14 This is the relationship between the P-wave velocity calculated by the White gas bag model and the gas saturation under the condition of changing porosity. Fig.15 This is the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing temperature. Fig.16 The figure below shows the relationship between the P-wave velocity calculated by the White air bag model and the gas saturation under the condition of changing effective pressure. Figure 11-16 As shown in the figure, frequency has the most obvious influence on the inflection point of velocity variation with gas content, porosity has a greater influence on both the inflection point and the value, while temperature and effective pressure have a smaller influence on both the inflection point and the value of velocity variation with gas content.

[0113] Fig.17 Analysis of experimental and model data on the variation of P-wave velocity with gas saturation Figure 1 , Fig.18 Analysis of experimental and model data on the variation of P-wave velocity with gas saturation Figure 2 .like Fig.17 and Fig.18 As shown in the figure, the blue curve is the measurement result, the black curve is the Gassmann model result, and the red curve is the White air bag model result. From the data in the figure, it can be seen that the Gassmann model has a low degree of consistency with the actual measurement results, while the White air bag model has a high degree of consistency with the actual measurement results.

[0114] Fig.19 P-wave velocity comparison between core measurement results and logging and model results Figure 1 , Fig. 20 P-wave velocity comparison between core measurement results and logging and model results Figure 2 , Fig.21 Comparison of shear wave velocity between core measurement results and logging and model results Figure 1 , Fig. 22 Comparison of shear wave velocity between core measurement results and logging and model results Figure 2 .like Figure 19-22 As shown, through the measurement comparison of different cores, it can be seen that the blue dotted line in the figure is the difference ratio. From the comparison results, the difference ratio between the laboratory measurement data and the logging and model is within 20%, and the average error is within 10%.

[0115] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

[0116] It should be understood that the size of the serial numbers of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Claims

1. A method for establishing a time-lapse seismic acquisition timing chart for a gas reservoir, characterized in that: The following steps are involved: Conduct experimental measurements on core samples of the target gas field to obtain rock physical elastic parameters; Acquire and analyze the data of the target gas field to construct a geological model of the target gas field; Perform rock physics modeling based on the rock physics elastic parameters and the target gas field geological model to obtain a target rock physics model; Conduct time-lapse seismic forward modeling based on the target rock physics model and White air bag model; Based on the simulation results, the relationship between pore pressure, gas saturation changes and seismic response is obtained, and a time-lapse seismic acquisition timing chart for gas reservoirs is drawn.

2. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 1, characterized in that: Conduct experimental measurements on core samples from target gas fields, including: Experimental measurement of rock physical elastic parameters of the core samples under different driving types, different development layers, and different temperature and pressure system conditions with variable pressure and pressure; The rock physical elastic parameters include longitudinal wave velocity, shear wave velocity and density.

3. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 2, characterized in that: The principle of velocity measurement is rock wave velocity = rock sample length / (sound wave arrival time-system base time); the principle of density measurement is rock sample density = (dry sample mass + pore fluid mass) / total rock sample volume.

4. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 1, characterized in that: The rock physics modeling is performed, specifically, the relationship between the rock physics elastic parameters and the gas reservoir characteristic parameters is matched with the existing rock physics model, and the rock physics model with the highest matching degree is selected as the target rock physics model.

5. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 1, characterized in that: The target gas field geological model includes a single factor model, a multi-factor model and an actual geological model; The construction of the geological model of each target gas field needs to take into account the mechanism model and gas reservoir model of the target gas field.

6. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 1, characterized in that: Based on the variation range of porosity, thickness, gas content and pressure of the gas field reservoir of the target gas field, a geological model of the target gas field is constructed.

7. The method for establishing a gas reservoir time-lapse seismic acquisition timing chart according to claim 1, characterized in that: The gas reservoir time-lapse seismic acquisition timing chart includes the following data: signal-to-noise ratio analysis results, gas content / pressure change rules inside the gas reservoir, spatial time-lapse seismic difference statistics results, time-lapse seismic spatial change rules, and target gas field acquisition timing analysis results.

8. A system for establishing a time map of time-lapse seismic acquisition of gas reservoirs, characterized in that: include: The measurement module is used to conduct experimental measurements on core samples of the target gas field to obtain rock physical elastic parameters; A model building module is used to acquire data of the target gas field for analysis and to build a geological model of the target gas field; the model building module is also used to perform rock physics modeling based on the rock physics elastic parameters and the geological model of the target gas field to acquire a target rock physics model; The map generation module is used to carry out time-lapse seismic forward simulation based on the target rock physics model and the White gas bag model; obtain the relationship between pore pressure, gas saturation change and seismic response based on the simulation results and draw a gas reservoir time-lapse seismic acquisition timing map.

9. An electronic device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the method for establishing a time-lapse seismic acquisition timing map of a gas reservoir as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for establishing a time-lapse seismic acquisition timing map of a gas reservoir as described in any one of claims 1 to 7 is implemented.

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