Method, system, equipment and medium for constructing velocity-temperature model of oil and gas reservoir

Abstract

The invention discloses a construction method, system, equipment and medium of an oil and gas reservoir velocity-temperature model, and particularly relates to the technical field of model construction, and the technical key points are as follows: obtaining environmental thermodynamic parameters of an underground oil and gas reservoir medium and sound pressure components of seismic waves; constructing a thermal-acoustic coupling medium seismic wave propagation model based on an elastic theory and an acoustic approximation theory; based on a thermal-acoustic coupling medium seismic wave propagation model, forward modeling is carried out by using a staggered grid finite difference method, and a simulated sound pressure component of a seismic wave is obtained through simulation; acquiring an actual seismic sound pressure component, and constructing a target function by minimizing an error between the actual seismic sound pressure component and the simulated sound pressure component; implementing full-waveform inversion by using a gradient descent method, and solving an objective function to obtain an optimal model parameter; and performing parameter updating on the thermal-acoustic coupling medium seismic wave propagation model by using the optimal model parameters to obtain an updated oil and gas reservoir velocity-temperature model.

Description

Technical Field

[0001] This invention relates to the field of model building technology, specifically to a method, system, equipment, and medium for constructing a velocity-temperature model of an oil and gas reservoir. Background Technology

[0002] Currently, oil and gas exploration has entered the realm of "two deeps" (deep strata and deep waters), and high temperature and high pressure have become important factors restricting these potential oil and gas reservoirs. In particular, temperature parameters not only affect the propagation characteristics of seismic waves, creating false reservoir identification, but also pose significant challenges to the safety and success rate of drilling and production. Accurately identifying temperature anomalies and finding associated geothermal resources near these oil and gas reservoirs can further promote the achievement of the "dual carbon" target.

[0003] Currently, various geophysical methods are commonly used in geothermal and oil and gas exploration to infer underground temperature or geothermal gradients. Typical methods include magnetic methods and resistivity methods. Magnetic methods utilize the temperature-dependent changes in the magnetic susceptibility of ferromagnetic minerals in rocks to locate underground Curie isotherms or magmatic activity zones. Resistivity methods, based on the effect of temperature changes on the resistivity of the medium, are currently the most widely used method in geothermal exploration. Although these methods have advantages such as low cost, minimal topographical requirements, and simple operation, they also have drawbacks such as large detection scales and limited accuracy.

[0004] Seismic exploration technology, especially active-source seismic exploration, has demonstrated excellent resolution capabilities in oil and gas exploration. Based on the theory of full-wavelength inversion (FWI), detailed subsurface velocity structures can be obtained, thereby enhancing the imaging capabilities of subsurface structures and geological bodies. In recent years, the application of full-wavelength inversion technology in geothermal exploration has also made progress. For example, researchers have combined distributed acoustic sensor (DAS) arrays with full-wavelength inversion to achieve geothermal reservoir imaging, or used converted waves and hybrid optimization algorithms to estimate subsurface P-wave velocity models, and obtained high-resolution velocity structures in geothermal areas based on seismic noise tomography FWI. Furthermore, multi-parameter full-wavelength inversion methods have been used to detect complex structures such as lava conduits beneath submarine volcanoes. However, classical seismic wave propagation theory does not consider temperature effects, therefore it cannot directly invert the temperature parameters of the subsurface medium. To address this issue, the industry has developed velocity-temperature prediction methods based on empirical formulas and data conversion to indirectly convert velocity imaging results into temperature estimates. Although these indirect methods have achieved some success in certain research and production, they still have significant limitations when encountering situations where the velocity structure and temperature distribution are inconsistent.

[0005] Therefore, the present invention aims to provide a method, system, device and medium for constructing a velocity-temperature model of oil and gas reservoirs to solve the aforementioned problems. Summary of the Invention

[0006] The technical problem to be solved by this invention is that temperature parameters cannot be directly obtained in existing seismic exploration. The purpose is to provide a method, system, equipment and medium for constructing a velocity-temperature model for oil and gas reservoirs. By establishing a seismic wave propagation model of a thermo-acoustic coupled medium, the temperature factor of the subsurface medium is introduced into the seismic wave propagation theory, and a full waveform inversion (FWI) framework suitable for simultaneous velocity and temperature inversion is constructed. At the same time, the constructed objective function is used to measure the difference between simulated seismic data and observed data, and the gradient of the objective function with respect to P-wave velocity and temperature parameters is obtained by using the adjoint state method, thereby guiding the model update.

[0007] This invention is achieved through the following technical solution:

[0008] A method for constructing a velocity-temperature model for oil and gas reservoirs, the method comprising:

[0009] The environmental thermodynamic parameters of underground oil and gas reservoir media and the sound pressure components of seismic waves are obtained, and a seismic wave propagation model of thermo-acoustic coupled medium is constructed based on elastic theory and acoustic approximation theory.

[0010] Based on the seismic wave propagation model of the thermo-acoustic coupled medium, forward modeling was performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave.

[0011] The actual seismic sound pressure components are obtained, and the objective function is constructed by minimizing the error between the actual and simulated seismic sound pressure components. The gradient descent method is used to perform full waveform inversion, and the optimal model parameters are obtained by solving the objective function.

[0012] The optimal model parameters were used to update the parameters of the seismic wave propagation model in the thermo-acoustic coupled medium, resulting in an updated oil and gas reservoir velocity-temperature model.

[0013] Furthermore, the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure components of the seismic waves are obtained. Based on elastic theory and acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed, specifically as follows:

[0014] We obtained the environmental thermodynamic parameters of underground oil and gas reservoir media and constructed a generalized thermo-elastic coupled wave equation based on elasticity theory.

[0015] The sound pressure component of the seismic wave is obtained, and the stress component in the generalized thermo-elastic coupled wave equation is replaced with the sound pressure component of the seismic wave using the acoustic approximation theory to construct a seismic wave propagation model in the thermo-acoustic coupled medium.

[0016] Furthermore, based on the seismic wave propagation model of the thermo-acoustic coupled medium, forward modeling was performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave, specifically:

[0017] The simulated sample data is obtained, and the environmental thermodynamic parameters and seismic wave velocity components in the simulated sample data are input into the seismic wave propagation model of the thermo-acoustic coupled medium. The forward model of the seismic wave propagation model of the thermo-acoustic coupled medium is performed using the staggered grid finite difference method to obtain the simulated sound pressure component of the seismic wave.

[0018] Furthermore, the specific model for seismic wave propagation in the thermo-acoustic coupled medium is as follows: In the formula, The time first derivative of the sound pressure component; Indicates the bulk modulus of a fluid; Indicates fluid density; This indicates that the seismic wave velocity component in the i-direction is... First-order spatial partial derivative in the direction; This is the thermal stress coefficient; Indicates the seismic wave velocity component in The first time derivative in the direction; This represents the first-order spatial partial derivative of the sound pressure component in the direction i; The time derivative of the temperature increment; Indicates specific heat capacity; Indicates the thermal relaxation time; Indicates thermal conductivity; The second-order spatial partial derivative of the temperature increment; This indicates the initial temperature.

[0019] Furthermore, the objective function is specifically: In the formula, Indicates model parameters, ; and These represent the number of detectors and the number of seismic sources, respectively. This indicates the total duration of seismic wave propagation; This represents the actual earthquake sound pressure component; This represents the simulated sound pressure component.

[0020] The present invention also provides a system for constructing a velocity-temperature model of an oil and gas reservoir, the system being used in the method for constructing a velocity-temperature model of an oil and gas reservoir as described in any one of the above claims, the system comprising:

[0021] The initial model building module is used to obtain the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure component of the seismic wave. Based on the elastic theory and the acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed.

[0022] The forward modeling module is used to perform forward modeling based on the seismic wave propagation model of the thermo-acoustic coupled medium, using the staggered grid finite difference method to simulate the pressure components of the seismic wave.

[0023] The inversion optimization module is used to obtain the actual seismic pressure components and construct the objective function by minimizing the error between the actual and simulated seismic pressure components; the gradient descent method is used to perform full waveform inversion and solve the objective function to obtain the optimal model parameters;

[0024] The model parameter update module is used to update the parameters of the seismic wave propagation model of the thermo-acoustic coupled medium using the optimal model parameters, so as to obtain the updated oil and gas reservoir velocity-temperature model.

[0025] Furthermore, the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure components of the seismic waves are obtained. Based on elastic theory and acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed, specifically as follows:

[0026] We obtained the environmental thermodynamic parameters of underground oil and gas reservoir media and constructed a generalized thermo-elastic coupled wave equation based on elasticity theory.

[0027] The sound pressure component of the seismic wave is obtained, and the stress component of the generalized thermo-elastic coupled wave equation is replaced with the sound pressure component of the seismic wave using the acoustic approximation theory to construct a seismic wave propagation model for the thermo-acoustic coupled medium.

[0028] The present invention also provides a computer device, including a system memory and a processor, wherein the system memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0029] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described above.

[0030] The present invention also provides a computer program product containing instructions that, when executed by a cluster of computer devices, cause the cluster of computer devices to perform the method described in any of the preceding claims.

[0031] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0032] In this invention, a seismic wave propagation model for a thermo-acoustic coupled medium is established, incorporating the temperature factor of the subsurface medium into the seismic wave propagation theory, and constructing a full waveform inversion (FWI) framework suitable for simultaneous velocity and temperature inversion. Simultaneously, the constructed objective function is used to measure the difference between simulated seismic data and observed data, and the adjoint state method is employed to obtain the gradient of the objective function with respect to the P-wave velocity and temperature parameters, thereby guiding the model update. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0034] Figure 1 This is a schematic diagram of the method flow for constructing a velocity-temperature model of an oil and gas reservoir in this embodiment;

[0035] Figure 2 This is a schematic diagram of solving the difference using the staggered mesh difference scheme in this embodiment;

[0036] Figure 3 This is a schematic diagram of the inversion process in this embodiment;

[0037] Figure 4 This is a distribution map of the subsurface velocity-temperature model of the Marmousi2 model in this embodiment;

[0038] Figure 5 This is a schematic diagram of the acoustic pressure wave field generated at four different time steps under the 18th shot source in this embodiment.

[0039] Figure 6 This is a schematic diagram of the initial model required for the inversion modeling process in this embodiment;

[0040] Figure 7 This is a schematic diagram of the full-shot superimposed gradient of the velocity and temperature parameters during the first iteration update in this embodiment;

[0041] Figure 8 This is a schematic diagram of the inversion results after 20 iterations in this embodiment;

[0042] Figure 9 This is a schematic diagram of the module connections of a system for constructing a velocity-temperature model of an oil and gas reservoir in this embodiment;

[0043] Figure 10 This is a schematic diagram of the structure of a computer device in this embodiment. Detailed Implementation

[0044] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0045] In this disclosure, unless otherwise stated, the use of terms such as "first," "second," etc., to describe various elements is not intended to limit the positional, temporal, or importance relationships of these elements; such terms are merely used to distinguish one element from another. In some examples, the first element and the second element may refer to the same instance of that element, while in other cases, based on the context, they may refer to different instances.

[0046] The terminology used in the description of the various examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context explicitly indicates otherwise, an element may be one or more unless the number of elements is specifically limited. Furthermore, the term "and / or" as used in this disclosure covers any one of the listed items and all possible combinations thereof.

[0047] Example 1

[0048] See Figure 1 , Figure 1 A flowchart illustrating a method for constructing a velocity-temperature model for oil and gas reservoirs is shown, wherein the method includes:

[0049] S1: Obtain the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure component of the seismic wave, and construct a seismic wave propagation model of the thermo-acoustic coupled medium based on elastic theory and acoustic approximation theory;

[0050] It should be noted that, in this embodiment, the environmental thermodynamic parameters include thermal stress coefficient, temperature increment, specific heat capacity, and thermal relaxation time; other parameters may also be included in other embodiments, which are not limited here.

[0051] Specifically, in this embodiment, the environmental thermodynamic parameters of the underground oil and gas reservoir medium are first obtained, and a generalized thermo-elastic coupled wave equation is constructed based on elastic theory and acoustic approximation theory.

[0052] It should be noted that, in this embodiment, the wave in the thermoelastic medium is typically caused by the combined effects of thermal effects, mechanical stress, strain, and thermal diffusion. Considering the paradox of infinite heat propagation in classical thermoelastic theory, the generalized thermo-elastic coupled wave equation based on LS theory can be expressed as:

[0053] (1);

[0054] In the formula, Represents stress components; and Indicates the Lamé parameter; express Seismic wave velocity components in the direction First-order spatial partial derivative in the direction; express Seismic wave velocity components in the direction First-order spatial partial derivative in the direction; It represents the sum of the first-order spatial partial derivatives of the seismic wave velocity components in any direction; The symbol for Kronecker, ;

[0055] However, acoustic media are a special type of elastic medium. When only the propagation of the longitudinal wave-related waveform is considered, shear waves do not exist and can therefore be ignored. The absence of shear waves means that the system response mainly exhibits pure compressive fluctuations. Therefore, the Lamé parameters... Setting it to 0 and substituting it into formula (1), the system response is dominated only by volumetric strain, that is, only the behavior of the medium in the compression wave is considered. This simplifies the originally complex wave equation to a form similar to the acoustic wave equation, specifically expressed as:

[0056] (2);

[0057] Then, the sound pressure component of the seismic wave is obtained, and the sound pressure component of the seismic wave is used as the stress component in the generalized thermo-elastic coupled wave equation to construct a seismic wave propagation model of the thermo-acoustic coupled medium.

[0058] It should be noted that, in this embodiment, a new sound pressure component of the seismic wave is introduced. Replace the stress components in the generalized thermo-elastic coupled wave equation and make them satisfy... , The sum of principal stresses in all directions is used to obtain the seismic wave propagation model of the thermo-acoustic coupled medium, which is specifically expressed as follows:

[0059] (3);

[0060] In the formula, The time first derivative of the sound pressure component; Indicates the bulk modulus of a fluid; Indicates fluid density; express Seismic wave velocity components in the direction First-order spatial partial derivative in the direction; This is the thermal stress coefficient; The time derivative of the temperature increment represents the rate of temperature increase. Indicates the seismic wave velocity component in The first time derivative in the direction; Indicates the sound pressure component at First-order spatial partial derivative in the direction; express The time first derivative of the velocity component in the direction represents directional velocity acceleration; The time derivative of the temperature increment; The time-order first derivative representing the rate of temperature increase; Indicates specific heat capacity; Indicates thermal relaxation time. , This indicates the P-wave velocity of the seismic wave; Indicates thermal conductivity; Indicates the temperature increment at Second-order spatial partial derivative in the direction; Indicates the initial temperature; express In the direction of velocity acceleration The first-order spatial partial derivative in the direction.

[0061] S2: Based on the seismic wave propagation model of the thermo-acoustic coupled medium, forward modeling is performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave.

[0062] Specifically, in this embodiment, simulated sample data is obtained, and the environmental thermodynamic parameters and seismic wave velocity components in the simulated sample data are input into the seismic wave propagation model of the thermo-acoustic coupled medium. The forward modeling of the seismic wave propagation model of the thermo-acoustic coupled medium is performed using the staggered grid finite difference method to simulate the simulated sound pressure components of the seismic wave.

[0063] It should be noted that in this embodiment, the seismic wave propagation model of the thermo-acoustic coupled medium is first established using formula (3), and a forward modeling technique for the thermo-acoustic coupled equations that meets the requirements of industrial applications is formed based on the staggered grid finite difference method; the seismic wave propagation model of the thermo-acoustic coupled medium shown in formula (3) is expressed in the form of matrix multiplication, specifically as follows:

[0064] (4);

[0065] In the formula, Represents an unknown wave field vector. Indicates in Seismic wave velocity components in the direction, Indicates in Seismic wave velocity components in the direction; The propagation matrix is ​​represented by physical parameters and the spatial derivative operator; subscripts are used to denote the propagation matrix. This indicates that the matrix belongs to the seismic wave propagation model of the thermo-acoustic coupled medium; Represents the observation operator;

[0066] Among them, the propagation matrix (5);

[0067] In the formula, , , ; This represents taking the first-order partial derivative with respect to the x-direction; This represents taking the first-order partial derivative with respect to the z-direction; This represents taking the second partial derivative with respect to the x-direction; This indicates the second-order partial derivative with respect to the z-direction; Formula (5) is a rigid equation, which is split into a rigid part and a non-rigid part using a time splitting algorithm. The problem of too small a time step is solved by alternately calculating the solution of the rigid part as the initial value of the non-rigid part. Specifically, it is expressed as follows:

[0068] (6);

[0069] In the formula, Indicates the non-rigid part; Indicates the rigid part;

[0070] in,

[0071] (7);

[0072] Therefore, for the evolution operator of the seismic wave propagation model in the thermo-acoustic coupled medium, the following relationship can be obtained, expressed as:

[0073] (8);

[0074] Substitute equation (8) into equation (4), and discretize the time variable as follows: ,in For the time step, then regarding the rigid part The solution at the next moment is expressed as:

[0075] (9);

[0076] In the formula, Indicates the sound pressure component at the th The solution for the rigid part at time (the next time step). Indicates the sound pressure component at the th The value at time (current moment); Indicates the first The value of the rate of temperature increase at time (current moment); Indicates the rate of temperature increase in the first... Solution of the rigid part at time (next time);

[0077] Substitute formula (9) as the initial value into formula (4), and use... Figure 2 Solving the difference using the staggered grid difference scheme shown above yields the staggered grid difference scheme for the seismic wave propagation model in the thermo-acoustic coupled medium, specifically expressed as:

[0078] (10);

[0079] In the formula, Indicates the time step; and Represents grid points; as well as Represents the grid center; and They represent , First-order forward difference formula in the direction; and Let represent the first-order backward difference formula, and respectively. and They represent and Second-order central difference formula in the direction; express The simplified symbol replacement; express The simplified symbol replacement;

[0080] Then, simulated sample data of the sample area is obtained, and the environmental thermodynamic parameters and seismic wave velocity components in the simulated sample data are input into the seismic wave propagation model of the thermo-acoustic coupled medium. The forward modeling of the seismic wave propagation model of the thermo-acoustic coupled medium is performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave.

[0081] S3: Obtain the actual seismic sound pressure components, construct the objective function with the minimum error between the actual and simulated seismic sound pressure components, and use the gradient descent method to perform full waveform inversion to solve the objective function and obtain the optimal model parameters;

[0082] It should be noted that in this embodiment, a land-based vertical geophone will first be deployed in the sample area. This land-based vertical geophone can be one of the different types of sensors based on displacement, velocity, or acceleration, or other types of vertical geophones can be used. Then, the error between the actual seismic sound pressure component recorded by the land-based vertical geophone and the simulated sound pressure component obtained from the simulation is denoted as:

[0083] (11);

[0084] In the formula, This represents the actual earthquake sound pressure component; Represents the simulated sound pressure component;

[0085] To better characterize the error, the L2 norm (i.e., minimizing the sum of squared errors) is used to construct the objective function with the error minimized. The objective function is as follows:

[0086] (12);

[0087] In the formula, Indicates model parameters; and These represent the number of detectors and the number of seismic sources, respectively. This indicates the total duration of seismic wave propagation; This represents the actual earthquake sound pressure component; Represents the simulated sound pressure component;

[0088] Then, gradient descent is chosen to perform full waveform inversion. Compared to global optimization methods, this approach avoids searching across a wide model space and requires less computation. Model parameters are then updated iteratively. Gradually reduce the amount of observation data and simulation data The differences between them, and the steps for updating the model in each iteration are as follows:

[0089] (13);

[0090] In the formula, Represents the number of iterations. The step size (positive scalar) can be selected using a simple line search method, while This represents the gradient of the objective function;

[0091] The core of this gradient descent inversion method is determining the direction of the gradient. To calculate this gradient, equation (3) is expressed in matrix form:

[0092] (14);

[0093] In the formula, Represents the unknown wave field vector. Represents the source vector. The propagation matrix is ​​represented by physical parameters and spatial derivative operators;

[0094] According to the full waveform inversion theory, the following relationship can be obtained:

[0095] (15);

[0096] In the formula, Representing the propagation matrix For a specific model parameter m ( or Differentiate;

[0097] The gradient is calculated by taking the partial derivative of the objective function (mismatch function) shown in formula (12) with respect to the elasticity parameter. The calculation formula is as follows:

[0098] (16)

[0099] definition For the accompanying wave field;

[0100] (17);

[0101] Substituting formula (17) into formula (16) and referring to the chain rule, we can obtain the information about velocity. ,temperature gradient expression,

[0102] (18);

[0103] In the formula, Representing the propagation matrix Partial derivative with respect to the bulk modulus of the fluid; Representing the propagation matrix Partial derivative with respect to the thermal stress coefficient; Representing the propagation matrix Partial derivative with respect to thermal relaxation time; Representing the propagation matrix Partial derivative with respect to the initial temperature;

[0104] To simplify the process of full-waveform inversion of the thermo-acoustic equation, a fixed step size can be given. Furthermore, by combining formulas (13) and (18), the gradient method is applied to perform full waveform inversion of velocity and temperature until the iteration termination threshold is reached. To obtain the optimal model parameters, see [link / reference]. Figure 3The diagram illustrates the workflow of the inversion process.

[0105] It should be noted that in this embodiment, the objective function uses the sum of squares (L2 norm) of the differences between the observed records and the forward simulation records to measure the error; by iteratively minimizing this objective function, the model parameters are optimized and updated; the gradient calculation is derived using the adjoint state method, combining the forward field and the adjoint field of the seismic wave equation to obtain gradient expressions for velocity and temperature, and using this gradient information to update the respective parameters of velocity and temperature in the seismic wave propagation model of the thermo-acoustic coupled medium. S4: The parameters of the seismic wave propagation model of the thermo-acoustic coupled medium are updated using the optimal model parameters to obtain the corrected underground storage velocity-temperature model.

[0106] For example, in this embodiment, the well-known Marmousi2 complex subsurface model is selected to further verify the method; this model has complex geological structure and velocity distribution and is widely used as a standard for evaluating full waveform inversion methods.

[0107] In this embodiment, the original Marmousi2 model was appropriately modified, reducing its horizontal and vertical dimensions to 13.62 km and 5.64 km, respectively (grid sampling interval dx = dz = 20 m, grid size approximately 681 × 282). Density variations were ignored in the model, and the high-salinity salt layer in the original model was replaced with a high-temperature granite body. The model parameters for the high-temperature granite body are as follows: linear thermal expansion coefficient... It is 6.3×10 -6 K -1 Thermal conductivity It is 2.721 m·kg·s -3 ·K -1 Specific heat capacity 75 kg·m -1 ·s -2 ·K -1 .

[0108] Figure 4 The underground velocity of the Marmousi2 model designed in the embodiment is shown. Figure 4 (a) and temperature model ( Figure 4 The distribution map of (b) in the figure.

[0109] Referring to step S2 of this method, a forward modeling simulation under the real parameter model is first carried out on the embodiment to obtain real observed seismic data to simulate the recordings collected in the field under actual conditions. At the same time, in this two-dimensional model example, the seismic source and detector are arranged on the surface of the model for exciting and receiving data. A Ricker wavelet with a dominant frequency of 18 Hz is used as the seismic source, and it is excited sequentially along the surface at intervals of 20 m, for a total of 34 shots. The time sampling interval is dt=1 ms, so for the seismic recording time of t=2.7 s, 2700 time steps are required.

[0110] Figure 5 The image shows the acoustic pressure wave field generated by the 18th shot at four different time steps (t = 0.1 s, 0.9 s, 1.8 s, 2.7 s). The P-wave first penetrates the horizontal layer and is reflected at the horizontal interface ( Figure 5 (See Figure (a)). When entering complex media below the horizontal layer, the wave field becomes even more complex. Steep thrust fault systems generate numerous reflections and interlayer multiples (…). Figure 5 (See Figure (b)). At the acute angle of the thrust fault, strong scattered waves are generated between the disturbed high-velocity sediment mass within the thrust fault and the surrounding low-velocity sediment. The waves propagate for 1.8 seconds ( Figure 5 (Figure (c)) shows the appearance of reflected waves, refracted waves, scattered waves, interlayer multiples, and interface waves. 2.7 seconds later ( Figure 5 (d) In the diagram, the deepest reflections are close to the surface.

[0111] Figure 6 This demonstrates the initial model required for the inversion modeling process, in which Figure 6 Figure (a) shows the initial model of the P-wave velocity. Figure 6 Figure (b) shows the initial temperature model, where all small-scale structures have disappeared, and only large-scale structures remain.

[0112] Inversion is performed using the gradient proposed in step S3. Figure 7 Figures (a) and (b) show the full-shot superposition gradients of the velocity and temperature parameters obtained in the first iteration, indicating the magnitude and direction of the model update and guiding subsequent parameter updates. The gradient profiles show that both the P-wave velocity and temperature parameters can be updated well in all directions.

[0113] Figure 8 Figures (a) and (b) show the inversion results after 20 iterations. Figure 4 Compared with the actual model profile shown, the velocity and temperature parameters were well recovered from the initial model, proving the effectiveness of the inversion modeling method.

[0114] Specifically, in this embodiment, the present invention establishes a seismic wave propagation model for a thermo-acoustic coupled medium, introduces the temperature factor of the subsurface medium into the seismic wave propagation theory, and constructs a full waveform inversion (FWI) framework suitable for simultaneous velocity and temperature inversion. At the same time, the constructed objective function is used to measure the difference between simulated seismic data and observed data, and the adjoint state method is used to obtain the gradient of the objective function with respect to the P-wave velocity and temperature parameters, thereby guiding the model update.

[0115] Example 2

[0116] See Figure 9 The present invention also provides a system for constructing a velocity-temperature model of an oil and gas reservoir, which is used in the method for constructing a velocity-temperature model of an oil and gas reservoir as described in any one of the above claims, the system comprising:

[0117] The initial model construction module 100 is used to obtain the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure component of the seismic wave, and to construct a seismic wave propagation model of the thermo-acoustic coupled medium based on elastic theory and acoustic approximation theory.

[0118] The forward modeling module 200 is used to perform forward modeling based on the seismic wave propagation model of the thermo-acoustic coupled medium and the staggered grid finite difference method to obtain the simulated pressure component of the seismic wave.

[0119] The inversion optimization module 300 is used to obtain the actual seismic pressure components and construct the objective function by minimizing the error between the actual seismic pressure components and the simulated pressure components; the gradient descent method is used to perform full waveform inversion and solve the objective function to obtain the optimal model parameters;

[0120] The model parameter update module 400 is used to update the parameters of the seismic wave propagation model of the thermo-acoustic coupled medium using the optimal model parameters, so as to obtain the updated oil and gas reservoir velocity-temperature model.

[0121] Furthermore, the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure components of the seismic waves are obtained. Based on elastic theory and acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed, specifically as follows:

[0122] We obtained the environmental thermodynamic parameters of underground oil and gas reservoir media and constructed a generalized thermo-elastic coupled wave equation based on elasticity theory.

[0123] The sound pressure component of the seismic wave is obtained, and the stress component of the generalized thermo-elastic coupled wave equation is replaced with the sound pressure component of the seismic wave using the acoustic approximation theory to construct a seismic wave propagation model for the thermo-acoustic coupled medium.

[0124] It should be noted that the modules in the system of Embodiment 2 correspond to the steps in the method of Embodiment 1. The steps in the method of Embodiment 1 have been described in detail in Embodiment 1, and the module content in the system will not be described in detail in this Embodiment 2.

[0125] Example 3

[0126] See Figure 10 This embodiment also provides a computer device, including a system memory 1005 and a processor 1001. The system memory 1005 stores a computer program, and the processor 1001 executes the computer program to implement the steps of any of the methods described above.

[0127] It should be noted that the processor 1001 is used to execute the steps in the above method embodiments according to the instructions in the program code. Alternatively, when the processor 1001 executes the computer program, it implements the functions of each module / unit in the above system / device embodiments.

[0128] Specifically, in this embodiment, the computer program can be divided into one or more modules / units, which are stored in the system memory 1005 and executed by the processor 1001 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device.

[0129] The terminal device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor 1001 and a system memory 1005. Those skilled in the art will understand that this does not constitute a limitation on the terminal device; it may include more or fewer components than shown in the figures, or a combination of certain components, or different components. For example, the terminal device may also include an input / output device 1003, a network access device 1002, a bus 1006, etc.

[0130] The processor 1001 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0131] System memory 1005 can be an internal storage unit of the terminal device, such as a hard drive or RAM. System memory 1005 can also be a storage device 1004 of the terminal device, such as an external hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or FlashCard. Furthermore, system memory 1005 can include both internal storage units and storage device 1004. System memory 1005 is used to store computer programs and other programs and data required by the terminal device. System memory 1005 can also be used to temporarily store data that has been output or will be output.

[0132] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0133] Example 4

[0134] This embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0135] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), registers, hard disks, optical fibers, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof, or any other form of computer-readable storage medium in the art.

[0136] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside within an application-specific integrated circuit (ASIC). In embodiments of the invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device.

[0137] Example 5

[0138] This embodiment also provides a computer program product containing instructions that, when executed by a cluster of computer devices, cause the cluster of computer devices to perform the method described in Embodiment 1.

[0139] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for constructing a velocity-temperature model for oil and gas reservoirs, characterized in that, The methods include: The environmental thermodynamic parameters of underground oil and gas reservoir media and the sound pressure components of seismic waves are obtained, and a seismic wave propagation model of thermo-acoustic coupled medium is constructed based on elastic theory and acoustic approximation theory. Based on the seismic wave propagation model of the thermo-acoustic coupled medium, forward modeling was performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave. Obtain the actual earthquake sound pressure components, and construct the objective function by minimizing the error between the actual earthquake sound pressure components and the simulated sound pressure components; The gradient descent method is used to perform full waveform inversion, and the objective function is solved to obtain the optimal model parameters; The optimal model parameters were used to update the parameters of the seismic wave propagation model in the thermo-acoustic coupled medium, resulting in an updated oil and gas reservoir velocity-temperature model.

2. The method for constructing a velocity-temperature model of an oil and gas reservoir according to claim 1, characterized in that, The environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure components of seismic waves are obtained. Based on elastic theory and acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed, specifically as follows: We obtained the environmental thermodynamic parameters of underground oil and gas reservoir media and constructed a generalized thermo-elastic coupled wave equation based on elasticity theory. The sound pressure component of the seismic wave is obtained, and the stress component in the generalized thermo-elastic coupled wave equation is replaced with the sound pressure component of the seismic wave using the acoustic approximation theory to construct a seismic wave propagation model in the thermo-acoustic coupled medium.

3. The method for constructing a velocity-temperature model of an oil and gas reservoir according to claim 1, characterized in that, Based on the seismic wave propagation model of the thermo-acoustic coupled medium, forward modeling was performed using the staggered grid finite difference method to obtain the simulated sound pressure components of the seismic wave, specifically: The simulated sample data is obtained, and the environmental thermodynamic parameters and seismic wave velocity components in the simulated sample data are input into the seismic wave propagation model of the thermo-acoustic coupled medium. The forward model of the seismic wave propagation model of the thermo-acoustic coupled medium is performed using the staggered grid finite difference method to obtain the simulated sound pressure component of the seismic wave.

4. The method for constructing a velocity-temperature model of an oil and gas reservoir according to claim 1, characterized in that, The specific model for seismic wave propagation in thermo-acoustic coupled media is as follows: In the formula, The time first derivative of the sound pressure component; Indicates the bulk modulus of a fluid; Indicates fluid density; This indicates that the seismic wave velocity component in the i-direction is... First-order spatial partial derivative in the direction; This is the thermal stress coefficient; Indicates the seismic wave velocity component in The first time derivative in the direction; The first-order spatial partial derivative of the sound pressure component; The time derivative of the temperature increment; Indicates specific heat capacity; Indicates thermal relaxation time. , This indicates the P-wave velocity of the seismic wave; Indicates thermal conductivity; The second-order spatial partial derivative of the temperature increment; This indicates the initial temperature.

5. The method for constructing a velocity-temperature model of an oil and gas reservoir according to claim 1, characterized in that, The objective function is specifically: In the formula, Indicates model parameters, , This represents the P-wave velocity of a seismic wave. Indicates the initial temperature; and These represent the number of detectors and the number of seismic sources, respectively. This indicates the total duration of seismic wave propagation; This represents the actual earthquake sound pressure component; This represents the simulated sound pressure component.

6. A system for constructing a velocity-temperature model for oil and gas reservoirs, characterized in that, This system is used in the method for constructing a velocity-temperature model of an oil and gas reservoir as described in any one of claims 1-5, the system comprising: The initial model building module is used to obtain the environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure component of the seismic wave. Based on the elastic theory and the acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed. The forward modeling module is used to perform forward modeling based on the seismic wave propagation model of the thermo-acoustic coupled medium, using the staggered grid finite difference method to simulate the pressure components of the seismic wave. The inversion optimization module is used to obtain the actual seismic pressure components and construct the objective function by minimizing the error between the actual and simulated seismic pressure components; the gradient descent method is used to perform full waveform inversion and solve the objective function to obtain the optimal model parameters; The model parameter update module is used to update the parameters of the seismic wave propagation model of the thermo-acoustic coupled medium using the optimal model parameters, so as to obtain the updated oil and gas reservoir velocity-temperature model.

7. The system for constructing a velocity-temperature model of an oil and gas reservoir according to claim 6, characterized in that, The environmental thermodynamic parameters of the underground oil and gas reservoir medium and the sound pressure components of seismic waves are obtained. Based on elastic theory and acoustic approximation theory, a seismic wave propagation model of the thermo-acoustic coupled medium is constructed, specifically as follows: We obtained the environmental thermodynamic parameters of underground oil and gas reservoir media and constructed a generalized thermo-elastic coupled wave equation based on elasticity theory. The sound pressure component of the seismic wave is obtained, and the stress component of the generalized thermo-elastic coupled wave equation is replaced with the sound pressure component of the seismic wave using the acoustic approximation theory to construct a seismic wave propagation model for the thermo-acoustic coupled medium.

8. A computer device comprising a system memory and a processor, wherein the system memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method described in any one of claims 1 to 5.

10. A computer program product containing instructions, characterized in that, When the instructions are executed by a cluster of computer devices, the cluster of computer devices causes the cluster of computer devices to perform the method as described in any one of claims 1 to 5.

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