Multi-parameter seismic imaging method and system

Abstract

The invention discloses a multi-parameter seismic imaging method and system, and relates to the technical field of oil and gas geophysical prospecting engineering, and the method comprises the following steps: inputting migration speed, migration porosity, and initialized speed disturbance and porosity disturbance imaging results into a demigration operator, and obtaining predicted seismic data; inputting the residual error of the predicted seismic data and the observed seismic data into an adjoint operator to obtain a gradient direction for updating speed disturbance and porosity disturbance; speed disturbance and porosity disturbance imaging results are updated based on the gradient direction; iterating the updating process of the speed disturbance and porosity disturbance imaging result, and when the number of iterations is reached, outputting the final speed disturbance and porosity disturbance imaging result. Compared with a sound wave least square reverse time migration method, the method provided by the invention has higher resolution and amplitude fidelity, and effectively solves the problem that high-precision imaging cannot be carried out on elastic parameter and physical property parameter disturbance at the same time in the existing seismic imaging technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas geophysical engineering, in particular to a multi-parameter seismic imaging method and system. BACKGROUND

[0002] Among the remaining oil and gas resources in China, tight sandstone oil and gas reservoirs occupy an important position. However, due to the small difference in wave impedance between the tight reservoir and the surrounding rock, it is difficult to accurately identify the reservoir only by using elastic parameters such as velocity and wave impedance. When seismic waves propagate in the tight reservoir, their response is not only affected by elastic parameters, but also by physical parameters sensitive to the reservoir (such as porosity and absorption attenuation). These reservoir parameters are closely related to the physical properties of the reservoir. Therefore, for tight reservoirs with small differences in wave impedance from surrounding rocks, fully utilizing elastic parameters and physical parameters of the reservoir for identification is the key to accurate evaluation of high-quality reservoirs.

[0003] Seismic imaging is a key technology for imaging the perturbation of underground medium parameters based on pre-stack seismic data, and its imaging results can be used for oil and gas reservoir identification and evaluation. However, the conventional migration imaging methods such as Kirchhoff migration and reverse-time migration are easily affected by incomplete observation systems and limited seismic frequency bands, and their imaging results are often disturbed by migration noise, and have problems such as uneven imaging amplitude and low resolution. Least squares reverse-time migration is a seismic imaging method based on an inversion framework, which uses a linearized wave equation as a forward operator to build an inversion model to iteratively solve the imaging problem, which can effectively suppress migration noise, compensate for imaging amplitude, and improve imaging resolution. In theory, this method can achieve high-resolution imaging of any medium parameter sensitive to seismic waves. Therefore, studying the least squares reverse-time migration method that can simultaneously image the elastic parameters and physical parameters of tight oil and gas reservoirs is of great significance for the exploration of tight oil and gas reservoirs.

[0004] However, there are two challenges when using conventional least squares reverse-time migration methods for elastic parameter and physical parameter imaging. First, traditional reverse migration operators are mostly based on elastic parameters such as acoustic waves, elastic waves, and viscoelastic waves, and cannot image physical parameter perturbations. Second, these equations do not fully consider the seismic wave attenuation caused by the dispersion effect of the fluid in the reservoir, resulting in a decrease in imaging amplitude fidelity and resolution. SUMMARY

[0005] Based on the defects of the prior art, the present application provides a multi-parameter seismic imaging method and system, which solves the problem that the existing seismic imaging technology cannot simultaneously image the elastic and physical parameter perturbations with high resolution, and cannot compensate for the decrease in imaging amplitude fidelity and resolution caused by the dispersion effect of the fluid in the reservoir.

[0006] The present application adopts the following technical solutions: In a first aspect, the present application provides a multi-parameter seismic imaging method, comprising the following steps: Obtaining observed seismic data, a migration velocity field and a migration porosity field of a target tight oil and gas reservoir working area, and initializing velocity perturbation and porosity perturbation imaging results; wherein the migration velocity field is used to describe the distribution of the seismic wave velocity of the underground background medium, and the migration porosity field is used to describe the distribution of the porosity of the underground background medium; Inputting the migration velocity field, the migration porosity field, the initialized velocity perturbation and porosity perturbation imaging results into a reverse migration operator to obtain predicted seismic data; inputting the residual of the predicted seismic data and the observed seismic data into an adjoint operator to obtain a gradient direction for updating the velocity perturbation and the porosity perturbation; updating the velocity perturbation and the porosity perturbation imaging results based on the gradient direction; wherein the reverse migration operator is obtained by linearizing and approximating a tight oil and gas medium seismic wave equation, and the adjoint operator is obtained by deriving the reverse migration operator through an adjoint state method; Iterating the updating process of the velocity perturbation and the porosity perturbation imaging results, and outputting the final velocity perturbation and porosity perturbation imaging results when the number of iterations is reached.

[0007] Preferably, the reverse migration operator is specifically as follows: ; In the formula, f is a seismic wavelet, p s is a scattered wave field generated by parameter perturbation, v 0 and m v is a migration velocity and a velocity perturbation, and is a porosity and a porosity perturbation, b f is a viscous attenuation parameter, is a physical parameter related to permeability, t is time, is a Laplace operator; wherein, p 0 is a background wave field, which is calculated by solving the following tight oil and gas medium seismic wave equation: .

[0008] Preferably, the adjoint operator is specifically as follows: ; ; In the formula, g v and ggradients of the update velocity perturbation and the porosity perturbation respectively, r a residual wavefield, which is obtained by reverse-time propagating the residual based on a seismic wave equation of a dense oil and gas medium.

[0009] Preferably, the velocity perturbation and the porosity perturbation imaging results are updated based on the gradient direction, and the updating is specifically shown as follows: ; wherein, ; in the formula, k is the iteration number, is the update step length, is the weighting coefficient, x is the spatial sampling interval, t is the time sampling interval.

[0010] Preferably, the migration velocity is obtained by a conventional travel time tomography inversion method, and the migration porosity is obtained by a conventional porosity inversion method.

[0011] In a second aspect, the present application further provides a multi-parameter seismic imaging system, comprising: an acquisition module, configured to acquire observed seismic data, a migration velocity field and a migration porosity field of a target dense oil and gas reservoir working area, and initialize velocity perturbation and porosity perturbation imaging results; wherein the migration velocity field is used to describe the distribution of the seismic wave velocity of the underground background medium, and the migration porosity field is used to describe the distribution of the porosity of the underground background medium; a calculation module, configured to input the migration velocity field, the migration porosity field, the initialized velocity perturbation and porosity perturbation imaging results into a reverse migration operator to obtain predicted seismic data; input the residual of the predicted seismic data and the observed seismic data into an adjoint operator to obtain a gradient direction for updating the velocity perturbation and the porosity perturbation; update the velocity perturbation and the porosity perturbation imaging results based on the gradient direction; wherein the reverse migration operator is obtained by linear approximation of a seismic wave equation of a dense oil and gas medium, and the adjoint operator is obtained by deducing the reverse migration operator by an adjoint state method; an iteration module, configured to iterate the updating process of the velocity perturbation and the porosity perturbation imaging results, and output the final velocity perturbation and porosity perturbation imaging results when the iteration number is reached.

[0012] Compared with the prior art, the above at least one technical solution of the present application can achieve the following beneficial effects: The application firstly acquires observed seismic data, migration velocity and migration porosity of a target tight oil and gas reservoir working area, and initializes velocity perturbation and porosity perturbation imaging results. Then, by linearizing approximation on a tight oil and gas medium wave equation, an inverse migration operator containing physical property parameter perturbation is constructed, and on this basis, a companion operator which can be used to jointly update velocity perturbation and porosity perturbation imaging results is derived, and then by using an iterative optimization algorithm, high-resolution joint imaging of velocity perturbation and porosity perturbation is realized. Specifically, the migration velocity and migration porosity are input into the inverse migration operator to obtain predicted seismic data; the residual of the predicted seismic data and the observed seismic data is input into the companion operator to obtain a gradient direction for updating the velocity perturbation and the porosity perturbation; and the velocity perturbation and the porosity perturbation imaging results are updated based on the gradient direction. The application can simultaneously calculate high-resolution imaging results of the velocity perturbation and the porosity perturbation, and effectively solve the problem that in the existing seismic imaging technology, elastic parameters and physical property parameter perturbations cannot be simultaneously imaged with high precision.

[0013] In addition, the seismic wave equation of the tight oil and gas medium can describe the dispersion effect of the fluid in the reservoir, so the method of the application can compensate for the seismic wave attenuation caused by the dispersion effect of the fluid in the reservoir, has higher resolution and amplitude fidelity than the acoustic least squares reverse time migration method, and solves the problem that the existing technology cannot compensate for the reduction of imaging amplitude fidelity and resolution caused by the dispersion effect of the reservoir fluid. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0015] Figure 1 A flowchart of a multi-parameter seismic imaging method of the application; Figure 2 A migration velocity field map of an embodiment of the application; Figure 3 A migration porosity field map of an embodiment of the application; Figure 4 A velocity perturbation imaging result map of an embodiment of the application; Figure 5 A porosity perturbation imaging result map of an embodiment of the application; Figure 6 A velocity perturbation imaging result map of a conventional acoustic least squares reverse time migration of the application. DETAILED DESCRIPTION

[0016] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present application.

[0017] The tight oil and gas medium seismic wave equation considers the dispersion of fluid in the reservoir, and clearly shows the relationship between seismic data and physical parameters such as porosity, thereby providing a model basis with few parameters and feasible calculation for reservoir parameter inversion and imaging. Therefore, the purpose of the present application is to provide a multi-parameter least square reverse time migration method based on the tight oil and gas medium seismic wave equation, aiming at solving the technical problem that the existing seismic imaging technology cannot simultaneously realize high-resolution imaging of elastic and physical parameter perturbation. Figure 1 The present application comprises the following steps:

[0018] S1: setting an observation system and migration parameters, and initializing the velocity perturbation and porosity perturbation imaging results to 0.

[0019] The migration parameters include the spatial sampling point number and sampling interval of the migration parameter field (migration velocity field and migration porosity field), the observation time and time sampling interval of the seismic data, the seismic wavelet, and the maximum iteration number.

[0020] Obtaining observed seismic data (seismic shot gather data), obtaining a migration velocity field (input parameter v 0) by a conventional travel time tomography inversion method, and obtaining a migration porosity field (input parameter ) by a conventional porosity inversion method.

[0021] The migration velocity field is used to describe the distribution of the seismic wave velocity of the underground background medium. Further, the migration velocity field is the background component of the seismic wave velocity of the underground medium, which is the medium-low wave number information, and is used to calculate the background wave field in the inverse migration operator.

[0022] The migration porosity field is used to describe the distribution of the porosity of the underground background medium. Further, the migration porosity field is the background component of the porosity of the underground medium, which is the medium-low wave number information, and is used to calculate the background wave field in the inverse migration operator.

[0023] S2: inputting the migration velocity field, the migration porosity field, the initialized velocity perturbation and porosity perturbation imaging results into the inverse migration operator to obtain predicted seismic data.

[0024] The predicted seismic data by the inverse migration operator based on the tight oil and gas medium seismic wave equation has the following calculation formula: (1) (2); wherein, p 0 is a background wavefield, f is a seismic wavelet, p s is a scattered wavefield generated by parameter perturbation (i.e. predicted seismic data), v 0 and m v is a migration velocity and a velocity perturbation, and is a porosity and a porosity perturbation, and the viscous damping parameter b f is set as a constant of the order of 10 -4 , and the physical parameter related to permeability is set as a constant of the order of 10 2 . The reverse migration operator is a forward equation for calculating seismic data from the velocity perturbation imaging result and the porosity perturbation imaging result.

[0025] S3: inputting the residual of the predicted seismic data and the observed seismic data to the adjoint operator to obtain a gradient direction for updating the velocity perturbation and the porosity perturbation.

[0026] The data residual is calculated from the predicted seismic data in step S2 and the observed seismic data: (3); wherein, r is the data residual, p obs is the observed seismic data.

[0027] The gradient is calculated by the adjoint operator of the reverse migration operator: (4); (5); wherein, g v and g are the gradients for updating the velocity perturbation and the porosity perturbation respectively, r * is an adjoint wavefield of the data residual, which is obtained by inverse-time reverse propagation of the data residual based on the seismic wave equation of the tight oil and gas medium.

[0028] Further, in order to ensure that the updated amount of the porosity perturbation is of the same dimension as the porosity perturbation, a weighting coefficient of the porosity perturbation imaging result is calculated: (6); wherein, x is a spatial sampling interval, t is a time sampling interval.

[0029] updating the velocity perturbation and the porosity perturbation imaging results by the steepest descent method: (7); wherein, the upper side represents the iteration number.

[0030] S4: repeatedly performing S2 and S3 until the iteration number is greater than the maximum iteration number set in S1, and outputting the velocity perturbation imaging result and the porosity perturbation imaging result.

[0031] Based on the same concept, the present application further provides a multi-parameter seismic imaging system, comprising an acquisition module, a calculation module and an iteration module.

[0032] The acquisition module is used to acquire observed seismic data, a migration velocity field and a migration porosity field of a target tight oil and gas reservoir working area, and initialize velocity perturbation and porosity perturbation imaging results; wherein, the migration velocity field is used to describe the distribution of the seismic wave velocity of the underground background medium, and the migration porosity field is used to describe the distribution of the porosity of the underground background medium.

[0033] The calculation module is used to input the migration velocity field, the migration porosity field, the initialized velocity perturbation and porosity perturbation imaging results into a reverse migration operator to obtain predicted seismic data; input the residual of the predicted seismic data and the observed seismic data into an adjoint operator to obtain a gradient direction for updating the velocity perturbation and the porosity perturbation; and update the velocity perturbation and the porosity perturbation imaging results based on the gradient direction; wherein, the reverse migration operator is obtained by linear approximation of the seismic wave equation of the tight oil and gas medium, and the adjoint operator is obtained by the adjoint state method.

[0034] The iteration module iterates the updating process of the velocity perturbation and the porosity perturbation imaging results, and outputs the final velocity perturbation and porosity perturbation imaging results when the iteration number is reached.

[0035] Embodiment In order to make the technical scheme of the present application more simple and clear, a specific application example is given below for illustration: The method of the present application is applied to two-dimensional seismic data, and the input observed data, a migration velocity field (such as shown in FIG. 1) and a porosity field (such as shown in FIG. 2) are inputted; Figure 2 Figure 3 ​​The observation system and migration parameters were set up. The observation system distribution was as follows: 90 shot points were evenly distributed at 60-meter intervals on the surface, received by 552 surface receivers with a receiver interval of 10 meters. The migration parameters were as follows: 219 transverse sampling points and 101 longitudinal sampling points for the migration velocity field, a spatial sampling interval of 10 meters, a temporal sampling interval of 0.5 milliseconds, a sampling time of 1 second, a 40-Hz Ricker wavelet as the main frequency of the seismic wavelet, a viscous attenuation parameter of 0.0001, and physical property parameters related to permeability were 100.

[0036] Initialize the velocity perturbation and porosity perturbation imaging results to 0, and set the maximum number of iterations to 10.

[0037] Based on the migrated velocity field, migrated porosity field, velocity perturbation imaging results, and porosity perturbation imaging results, the seismic data are predicted using a démigration operator based on the seismic wave equation for tight oil and gas media. The data residuals are calculated, and the gradient is calculated using the adjoint operator of the démigration operator. The velocity perturbation imaging results and porosity perturbation imaging results are then updated.

[0038] When the number of iterations reaches 10, the velocity perturbation imaging result of the 10th iteration is output (such as Figure 4 ) and porosity perturbation imaging results (as shown in Figure 5 shown).

[0039] In order to compare the method of the present invention with the data-driven seismic imaging method, the same migration velocity model and migration parameters are used to image the observed seismic data through acoustic least squares reverse time migration, and the imaging results of velocity disturbance are obtained (such as Figure 6 shown).

[0040] The imaging method of the present invention can compensate for the attenuation of seismic waves caused by the diffusion effect of fluid in the reservoir. The imaging results are different from the velocity perturbation imaging results of conventional acoustic least square reverse time migration (such as Figure 6 As shown in Figure 2, the imaging resolution of underground structures is improved, especially the deep structures are clearer. In addition, the imaging method of the present invention can not only calculate the velocity disturbance imaging results (such as Figure 4 As shown in ), the attenuation parameter (porosity) perturbation imaging results can also be obtained (as shown in Figure 5 ), while the conventional least squares reverse time migration method can only calculate the imaging results of velocity disturbances (such as Figure 6 shown).

[0041] The method of the present application constructs an inverse migration operator which explicitly contains the property parameter disturbance and can depict the dispersion effect of reservoir fluid by linearizing and approximating the wave equation of the tight oil and gas medium. On this basis, the gradient operator which can be used to jointly update the velocity disturbance and porosity disturbance imaging results is derived, and then the high-resolution joint imaging of the velocity disturbance and porosity disturbance is realized by using the iterative optimization algorithm. The method effectively solves the problem that the existing seismic imaging technology cannot simultaneously perform high-precision imaging on the elastic parameter and property parameter disturbance, and provides technical support for fine characterization of the tight oil and gas reservoir.

[0042] Therefore, compared with the prior art method, the method of the present application can improve the imaging resolution of the velocity disturbance, The imaging result of the porosity disturbance can also be calculated, which is of great significance for the exploration of the tight oil and gas reservoir.

[0043] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to the embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be interpreted as including all the preferred embodiments and all the changes and modifications falling within the scope of the present application.

[0044] Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and changes.

Claims

1. A multi-parameter seismic imaging method, characterized in that: The following steps are involved: Obtain observed seismic data, migrated velocity fields, and migrated porosity fields of the target tight oil and gas reservoir area, and initialize velocity perturbation and porosity perturbation imaging results. The migrated velocity field is used to describe the distribution of seismic wave velocity in the underground background medium, and the migrated porosity field is used to describe the distribution of porosity in the underground background medium. The migrated velocity field, migrated porosity field, and the initialized velocity perturbation and porosity perturbation imaging results are input into the demigration operator to obtain predicted seismic data. The residual between the predicted seismic data and the observed seismic data is input into the adjoint operator to obtain the gradient direction for updating the velocity perturbation and porosity perturbation. The velocity perturbation and porosity perturbation imaging results are updated based on the gradient direction. The demigration operator is obtained by linearizing and approximating the seismic wave equation for tight oil and gas media, and the adjoint operator is derived from the demigration operator using the adjoint state method. The updating process of the velocity perturbation and porosity perturbation imaging results is iterated, and when the number of iterations is reached, the final velocity perturbation and porosity perturbation imaging results are output.

2. A multi-parameter seismic imaging method according to claim 1, characterized in that: The de-migration operator is specifically as follows: ; Where, f is the seismic wavelet, p s is the scattered wave field generated by parameter perturbation, v 0 and m v are the offset velocity and velocity disturbance, and are porosity and porosity perturbation, b f is the viscous attenuation parameter, is a physical property parameter related to permeability, t For time, is the Laplace operator; in, p 0 is the background wave field, which is calculated by solving the following tight oil and gas medium seismic wave equation: 。 3. A multi-parameter seismic imaging method according to claim 2, characterized in that: The adjoint operator is specifically as follows: ; ; Where, g v and g are the gradients of the updated velocity perturbation and porosity perturbation, r * is the accompanying wave field of the residual, which is obtained by performing reverse time propagation on the residual based on the seismic wave equation of tight oil and gas media.

4. A multi-parameter seismic imaging method according to claim 3, characterized in that: The velocity disturbance and porosity disturbance imaging results are updated based on the gradient direction, as shown below: ; in, ; Where, k is the number of iterations, is the update step size, is the weighting coefficient, x is the spatial sampling interval, t is the time sampling interval.

5. The multi-parameter seismic imaging method according to claim 1, wherein: The migrated velocity is obtained by conventional traveltime tomography inversion method, and the migrated porosity is obtained by conventional porosity inversion method.

6. A multi-parameter seismic imaging system, characterized in that: include: The acquisition module is used to obtain the observed seismic data, the migrated velocity field, and the migrated porosity field of the target tight oil and gas reservoir area, and initialize the velocity perturbation and porosity perturbation imaging results. The migrated velocity field is used to describe the distribution of seismic wave velocity in the underground background medium, and the migrated porosity field is used to describe the distribution of porosity in the underground background medium. A calculation module is used to input the migrated velocity field, migrated porosity field, and initialized velocity perturbation and porosity perturbation imaging results into a démigration operator to obtain predicted seismic data; input the residual between the predicted seismic data and the observed seismic data into an adjoint operator to obtain the gradient direction for updating the velocity perturbation and porosity perturbation; and update the velocity perturbation and porosity perturbation imaging results based on the gradient direction. The démigration operator is obtained by linearizing and approximating the seismic wave equation for tight oil and gas media, and the adjoint operator is derived from the démigration operator using the adjoint state method. The iteration module iterates the updating process of the velocity disturbance and porosity disturbance imaging results, and outputs the final velocity disturbance and porosity disturbance imaging results when the number of iterations is reached.

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