Carbonate reservoir pore type earthquake description method and system

Abstract

The invention discloses a carbonate reservoir pore type earthquake description method and system, and the method comprises the following steps: carrying out the pre-stack inversion, and obtaining the longitudinal wave impedance and transverse wave impedance of a reservoir; converting the longitudinal wave impedance and the transverse wave impedance into density according to the density indication factor to obtain a density three-dimensional data body, and further obtaining a longitudinal wave speed and a transverse wave speed through the density three-dimensional data body; calculating a porosity three-dimensional data volume by means of the density three-dimensional data volume; on the basis of the longitudinal wave velocity, the transverse wave velocity, the density three-dimensional data body and the porosity three-dimensional data body, the three-dimensional space change of the reservoir pore type is described through a pore structure rock physical model, quantitative characterization and earthquake description of the pore type are achieved, pore structure parameter description analysis is conducted on the target carbonate reservoir, and the pore structure parameter analysis accuracy is improved. According to the method, well-communicated pores, poor-communicated pores and crack distribution conditions can be quantitatively determined, the depicting accuracy is high, and the coincidence rate of the depicting result and the ground is high.

Description

Technical Field

[0001] The invention belongs to the technical field of reservoir seismic characterization, and relates to a carbonate reservoir pore type seismic characterization method and system. Background Art

[0002] The diversity of pore types and structures in carbonate reservoirs is the main factor causing the strong heterogeneity of reservoir physical properties, porosity and permeability, and the complex seismic elastic parameter response. However, there is currently a lack of seismic characterization techniques for studying the pore types of carbonate reservoirs.

[0003] Using rock physics models is an important aspect of using seismic data to characterize changes in pore structure. From the perspective of rock physics models, in the past few decades, many scholars have proposed different empirical formulas and models to characterize the types of pore structures. Such as the average time equation, secondary porosity indicator parameter curve (Schlumberger, 1974), fluid migration time indicator curve (Meese and Walther, 1976), circular pore model (Brite et al., 1985), Lucia model (Lucia, 1983), velocity migration curve (Anselmetti and Eberli, 1999), modified Wyllie average time formula (Saleh and Castagna, 2004), etc. These models and formulas have played a positive role in qualitatively analyzing and characterizing changes in different pore structure types. However, the above models are largely based on the knowledge obtained from experiments or logging data analysis, and the lack of mathematical foundations has limited their scope of application and effect. By extending the Biot theoretical model, Sun and Goldberg (1997a, 1997b, 2000, 2004) established a rock physics model based on the dynamic theory of fractured porous media. In this model, Sun (2000, 2004) defined a set of elastic parameters, named skeleton flexibility parameters. These skeleton flexibility parameters are elastic parameters independent of porosity, which are functions of P-wave velocity, S-wave velocity and density, and lay the foundation for the inversion of geophysical parameters. Theoretically speaking, the pore structure parameters in the pore structure rock physics model are the ratio of the major and minor axes of the pores and the response of the pore radius, providing a physical basis for its geological application. This poroelastic theoretical model has achieved the characterization of the complexity of the pore structure and the connectivity between pores in carbonate reservoirs to a certain extent, but it has only been verified to a certain extent on the core and logging scales (Sun, 2006; Dou, 2011).

[0004] There are few studies on how to use 3D seismic data to characterize the porosity, pore structure and permeability heterogeneity of carbonate reservoirs based on rock physics model research. In a few cases, Bracco Gartner et al. (2005) applied the rock physics model derived by Sun to the 3D post-stack seismic data of an oil field block in the Middle East to evaluate the pore type of carbonate reservoirs and further predict the permeability heterogeneity of the reservoir, and achieved certain results. However, due to the limitation of post-stack seismic information, this method made a lot of simplifications to the model, and it is difficult to achieve seismic characterization of complex pore types. In order to avoid the problem of massive calculations in pre-stack inversion, Dou proposed a method for simultaneous inversion of porosity and γ parameters using angle stacking data. The basic idea is to first use angle stacking data to invert longitudinal elastic impedance and shear elastic impedance, and then use the rock physics model to express these three inversion data bodies with carbonate reservoir porosity and γ parameters, and then use the above three data bodies to calculate porosity and γ parameters. Although the above technical methods have solved the purpose of seismic characterization of pore structure parameters to a certain extent, a major problem in their application is that some parameters in the inversion need to be set as constants, which limits their application in research and actual production. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that the seismic characterization method in the prior art cannot achieve quantitative characterization and seismic characterization of pore types, and to provide a carbonate reservoir pore type seismic characterization method and system. On the basis of achieving three-dimensional spatial characterization of pore types, a rock physics interpretation model of pore type classification, porosity, and permeability can be obtained, thereby improving the accuracy of carbonate reservoir physical property parameter prediction.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for seismic characterization of pore types in carbonate reservoirs comprises the following steps:

[0008] Perform pre-stack inversion to obtain the P-wave impedance and S-wave impedance of the reservoir;

[0009] Construct a density indicator factor, convert the longitudinal wave impedance and the transverse wave impedance into density, obtain a three-dimensional density data body, and further obtain the longitudinal wave velocity and the transverse wave velocity through the three-dimensional density data body;

[0010] Calculate the porosity three-dimensional data volume based on the density three-dimensional data volume;

[0011] The three-dimensional spatial variation of reservoir pore types is characterized by using three-dimensional data volumes of compressional wave velocity, shear wave velocity, density and porosity.

[0012] A further improvement of the present invention is:

[0013] The method of obtaining the longitudinal wave impedance and the transverse wave impedance of the reservoir comprises the following steps:

[0014] Perform reservoir optimization processing inversion and solve the L1 norm minimization problem through compressed sensing inversion:

[0015] y=Dm, m≥0 (1)

[0016] Where y is the observed value, m = R n×1 is the signal to be sampled, D is the measurement matrix;

[0017] According to the sparse representation of the signal, the seismic signal can be sparsely represented in a certain transform domain. Assuming that E represents the sparse basis, the signal representation is:

[0018] m=Ex (2)

[0019] Where E = R n×n represents a sparse matrix; substitute equation (2) into equation (1):

[0020] y=DEx, x≥0 (3)

[0021] Let B = R m×n is the perception matrix, then the signal can be rewritten as:

[0022]

[0023] During the reservoir inversion process, the input data include angle gathers, wavelets of each angle gather and low-frequency model, and the output is P-wave impedance and S-wave impedance.

[0024] Converting the longitudinal wave impedance and the shear wave impedance into density to obtain a density three-dimensional data volume includes the following steps:

[0025] The density-transverse wave impedance intersection volume is divided into multiple trend lines by using the density calculation indicator factor. The density three-dimensional data volume is obtained by using the density calculation indicator factor. The density indicator factor is expressed by formula (5):

[0026]

[0027] Where: is the ratio of longitudinal and transverse wave velocities; SI is the transverse wave impedance; AI is the longitudinal wave impedance; DCI is the density indicator factor.

[0028] The method of calculating the porosity three-dimensional data volume based on the density three-dimensional data volume specifically includes the following steps:

[0029] The porosity is calculated by formula (6):

[0030]

[0031] Where ρ is the seismic predicted density of the reservoir segment, ρ f is the fluid density, ρ b is the skeleton density.

[0032] Calculating the porosity three-dimensional data volume also includes the following steps:

[0033] Introduce the pore structure parameter γ, see formula (7):

[0034]

[0035] Where φ represents the porosity and f represents the integrated bulk modulus.

[0036] The calculation process of the pore structure parameter γ includes the following steps:

[0037]

[0038]

[0039]

[0040] In the formula, K f represents the skeleton bulk modulus, K s represents the bulk modulus of fluid, K represents the bulk modulus of rock, V p represents the longitudinal wave velocity, V s represents the shear wave velocity and ρ represents the density.

[0041] A carbonate reservoir pore type seismic characterization system, comprising a prestack inversion module, a density inversion module, a porosity inversion module and a pore structure parameter inversion module;

[0042] Prestack inversion module, used to perform prestack inversion and obtain the P-wave impedance and S-wave impedance of the reservoir;

[0043] The density inversion module is used to construct a density indicator factor, to convert the longitudinal wave impedance and the transverse wave impedance into density to obtain a three-dimensional density data body, and further obtain the longitudinal wave velocity and the transverse wave velocity through the three-dimensional density data body;

[0044] Porosity inversion module, used to calculate the porosity 3D data volume based on the density 3D data volume;

[0045] The pore structure parameter inversion module is used to characterize the three-dimensional spatial changes of reservoir pore types using the three-dimensional data volumes of P-wave velocity, S-wave velocity, density and porosity.

[0046] A terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any method described in the present invention when executing the computer program.

[0047] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of any method described in the present invention.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention discloses a method for seismic characterization of carbonate reservoir pore types. The method comprises the following steps: firstly, pre-stack inversion is performed to obtain the longitudinal wave impedance and the transverse wave impedance of the reservoir, and the longitudinal wave impedance and the transverse wave impedance are converted into density to obtain a three-dimensional density data body, so as to realize seismic prediction of density, and further, a three-dimensional data body of longitudinal wave velocity, transverse wave velocity and density and a porosity data body are obtained. Based on the obtained parameters, three-dimensional inversion of pore structure parameters is realized to characterize the three-dimensional spatial variation of the reservoir pore type, so as to realize quantitative characterization and seismic characterization of the pore type. By characterizing and analyzing the target carbonate rock layer through the present invention, the distribution of well-connected pores, poorly connected pores and fractures can be quantitatively determined, and the characterization result has a high consistency rate with the well. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 It is a flowchart of the present invention;

[0052] Figure 2 A diagram illustrating the pore types of the present invention;

[0053] Figure 3 A rock physics plate for density calculation of the present invention;

[0054] Figure 4 It is the inversion result diagram of porosity and pore structure parameters of the present invention (where a is the porosity plane diagram, and b is the pore structure parameter plane diagram). DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0056] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0058] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0059] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0060] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0062] See also Figure 1The embodiment of the present invention discloses a method for seismic characterization of pore types in carbonate reservoirs. First, a calculation method for parameters characterizing pore types is proposed at the logging scale, and the geological significance of the parameters is determined in combination with core analysis data. On the basis of pre-stack seismic inversion, density rock physics plates are used to achieve seismic prediction of density, and after obtaining the density, the longitudinal wave velocity and the transverse wave velocity are obtained. The three-dimensional spatial inversion of pore structure parameters is achieved by using the pore structure rock physics model and the density, longitudinal wave velocity and transverse wave velocity of the seismic inversion, and then the three-dimensional spatial changes of the reservoir pore type are characterized.

[0063] The specific steps include:

[0064] Step 1: Perform prestack inversion to obtain the P-wave impedance and S-wave impedance of the reservoir, see Figure 2 ;

[0065] Firstly, sparse pulse compressed sensing high-resolution seismic prestack inversion technology is used for prestack inversion. The input data include angle gathers, wavelets of each angle gather and low-frequency model, and the output data include longitudinal wave impedance and shear wave impedance.

[0066] See also Figure 2 , is the intersection diagram of P-wave impedance and porosity, and the color code is the pore structure parameter γ in the pore structure rock physics model. Using this color code, the porosity-P-wave impedance is divided into four trends, which are basically the changes in P-wave impedance of lithology when the porosity remains unchanged, that is, when the porosity remains unchanged, as the P-wave impedance decreases, the pore structure parameter γ continues to increase. According to the physical meaning of the pore structure parameter, when the porosity remains unchanged, the pore type changes from round pores to flat and linear pore types, that is, the pore structure parameter of intercrystalline solution pores is a low value (less than 4), the pore structure parameter of intercrystalline pores is a medium value (4-12), and the pore structure parameter greater than 12 is a fracture pore type.

[0067] Specifically, in response to the geological requirements for reservoir optimization processing and characterization, the embodiment of the present invention uses compressed sensing high-resolution inversion technology to perform reservoir optimization processing inversion. Compact Sensing Inversion is an inversion method developed to adapt to the basic properties of the inherent ill-posed problems in geophysical inversion.

[0068] The new idea of ​​compressed sensing inversion is to solve an L1 norm minimization problem:

[0069] y=Dm, m≥0 (1)

[0070] Where y is the observed value, m = R n×1 is the signal to be sampled, and D is the measurement matrix.

[0071] According to the sparse representation of the signal, most seismic signals can be sparsely represented in a certain transform domain. Assuming that E represents the sparse basis, the signal can be represented as:

[0072] m=Ex (2)

[0073] Where E = R n×n represents a sparse matrix. Substituting equation (2) into equation (1):

[0074] y=DEx, x≥0 (3)

[0075] Let B = R m×n is the perception matrix, then the signal can be rewritten as:

[0076]

[0077] In the actual inversion process, the input data is the angle gather data, each angle gather corresponds to the wavelet and the low-frequency model of P-wave impedance and S-wave impedance, and the output results include the seismic inversion absolute P-wave impedance, S-wave impedance and density three-dimensional data body, which are used for the subsequent P-wave velocity, S-wave velocity and porosity inversion.

[0078] Step 2: Density and porosity seismic inversion, see Figure 3 ;

[0079] The longitudinal wave impedance and the shear wave impedance are converted into density to obtain a three-dimensional density data body, and the longitudinal wave velocity and the shear wave velocity are further obtained through the three-dimensional density data body;

[0080] Figure 3 In the figure, the horizontal axis is the shear wave impedance and the vertical axis is the density, that is, the density is calculated by the shear wave impedance.

[0081] According to the Aki-Richard seismic wave equation analysis, when the seismic incident angle is less than 40-45 degrees, the pre-stack inversion density inversion error is very large, so for most data, the seismic pre-stack inversion density accuracy is relatively low and cannot be used for reservoir seismic characterization. P-wave impedance and S-wave impedance can be obtained through seismic pre-stack inversion, which is basically the embodiment of the near and mid-channel information of seismic data, which contains information on P-wave velocity, S-wave velocity and density, but these three information are coupled together, and there is no method in the prior art to distinguish these three.

[0082] In the embodiment of the present invention, the density calculation plate is used, see Figure 3 , converting the shear wave impedance into density. In the above conversion process, the density calculation indicator factor is used to divide the density-shear wave impedance intersection diagram into multiple trend lines, so as to improve the calculation accuracy of density and further obtain the longitudinal wave velocity and shear wave velocity

[0083] Specifically, the density calculation indicator (DCI) is a key parameter in the template, and the specific expression is:

[0084]

[0085] Where: is the ratio of longitudinal and transverse wave velocities, SI is the transverse wave impedance, AI is the longitudinal wave impedance, and DCI is the density indicator factor.

[0086] Step 3: Calculate using the density seismic inversion data volume, specifically, calculate the porosity three-dimensional data volume based on the density three-dimensional data volume;

[0087] After the density is obtained, the reservoir porosity is calculated using the porosity density calculation formula to obtain the reservoir porosity three-dimensional data body.

[0088] The porosity calculation formula is:

[0089]

[0090] Where: ρ is the seismic prediction density of the reservoir segment, ρ f is the fluid density, ρ b is the skeleton density. In actual oil and gas reservoirs, ρ f and ρ b It varies, but in order to simplify the calculation, it is usually set as a constant.

[0091] Step 4: Based on the three-dimensional data of P-wave velocity, S-wave velocity, density and porosity, pore structure parameter modeling is performed to describe the three-dimensional spatial variation of reservoir pore types;

[0092] The pore structure parameter γ introduced in the pore structure rock physics model is used to characterize the type of reservoir pores, and its calculation formula is as follows:

[0093]

[0094] Furthermore,

[0095]

[0096]

[0097]

[0098] Where φ is porosity; K f represents the skeleton bulk modulus; K s represents the bulk modulus of fluid; K represents the bulk modulus of rock; V p represents the longitudinal wave velocity; V s represents the shear wave velocity; ρ represents the density; and f represents the integrated bulk modulus.

[0099] From the above formula, it can be seen that the pore structure parameter γ is a function of the longitudinal wave velocity, the transverse wave velocity, the density and the porosity. In the second part, the density and porosity have been obtained, and the longitudinal wave velocity and the transverse wave velocity are obtained through the longitudinal wave impedance and the transverse wave impedance. After obtaining the three-dimensional data volume of these elastic parameters, the pore structure parameters are calculated using the above formula under the assumption that the fluid and skeleton bulk modulus are constant.

[0100] See also Figure 4 Furthermore, in this embodiment, the pore structure parameters seismic inversion based on the rock physics model

[0101] By constructing pore structure parameters and establishing a rock physics model, the required parameters are calculated based on prestack inversion, and substituted into the rock physics model to calculate the pore structure parameters and porosity, extract the pore structure parameters of the target layer, and then based on the core analysis data of the area, such as thin sections, lithology scanning, and X-diffraction analysis data, determine the geological significance of the parameters, and determine the numerical range of the pore structure parameters for well-connected pores, poorly connected pores, and fracture pores, to achieve quantitative characterization of pore types. The current characterization accuracy rate can reach 85% of the coincidence rate on the well.

[0102] Figure 4 is the plane diagram of porosity and pore structure parameters, Figure 4 a is the porosity plane diagram, from which we can see that the average porosity basically varies between 0-4.5%. Among them, the relatively high-quality reservoir areas with porosity greater than 1.5% are relatively continuous, especially in the central and western regions of the work area, where the porosity is basically above 3%, which is a high-quality relatively high-porosity area. The porosity in other eastern and southeastern regions is between 1.5-2.5%, which is a medium-low porosity area. Regional sedimentary phase analysis shows that the change in porosity is controlled by paleo-geomorphology, that is, the high-porosity area in the central and western regions is the highest paleo-geomorphology area, and the second highest paleo-geomorphology area corresponds to the medium-low porosity area. The paleo-geomorphology low-lying area is an area with a porosity of less than 1.5%.

[0103] Figure 4 b is the plane diagram of pore structure parameters, and the range of pore structure parameters is from 0 to 12. According to the previous analysis, within the reservoir range, that is, the porosity is greater than 1.5%, the change of pore structure parameters reflects the change of pore type, that is, pore structure parameters less than 4 are intercrystalline solution pores, between 4 and 8 are a mixture of intercrystalline solution pores and intercrystalline pores, and greater than 8 are intercrystalline pores. It can be seen from the plane diagram that for areas with porosity greater than 1.5%, the pore structure parameters are basically above 4, and are mainly greater than 8, that is, the pore type is mainly intercrystalline pores, and intercrystalline solution pores are weakly developed.

[0104] See also Figure 4, actual data testing shows that the new technology method of this patent has achieved the purpose of seismic calibration of pore type changes in carbonate reservoirs to a certain extent. For the rock physics model, the pore structure parameters of the logging scale inversion can characterize the reservoir pore type, that is, when the pore structure parameter is less than 4, the pore type is mainly intragranular dissolution pores, and when the pore structure parameter is between 4-8, the pore type is mainly dissolution-intergranular mixed pores. When the pore structure parameter is greater than, the pore type is mainly intercrystalline pores. Using the density inversion model, the shear wave impedance-density is divided into 7 different trends under the scale of the density calculation indicator parameter. Comparing the seismic inversion and the results based on the rock physics model, the method based on the rock physics model improves the density calculation accuracy by 30%. Using the pore structure parameters, the distribution of different pore types is characterized on the plane within the reservoir range.

[0105] This embodiment also discloses a carbonate reservoir pore type seismic characterization system, including a pre-stack inversion module, a density inversion module, a porosity inversion module and a pore structure parameter inversion module;

[0106] Prestack inversion module, used to perform prestack inversion and obtain the P-wave impedance and S-wave impedance of the reservoir;

[0107] The density inversion module is used to convert the longitudinal wave impedance and the shear wave impedance into density to obtain a three-dimensional density data body, and further obtain the longitudinal wave velocity and the shear wave velocity through the three-dimensional density data body;

[0108] Porosity inversion module, used to calculate the porosity 3D data volume based on the density 3D data volume;

[0109] The pore structure parameter inversion module is used to characterize the three-dimensional spatial variation of reservoir pore types based on the P-wave velocity, S-wave velocity, density 3D data volume and porosity data volume.

[0110] A schematic diagram of a terminal device provided in an embodiment of the present invention. The terminal device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0111] The computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to accomplish the present invention.

[0112] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0113] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0114] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0115] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0116] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for seismic characterization of pore types in carbonate reservoirs, characterized in that: The following steps are involved: Perform pre-stack inversion to obtain the P-wave impedance and S-wave impedance of the reservoir; Construct a density indicator factor, convert the longitudinal wave impedance and the transverse wave impedance into density, obtain a three-dimensional density data body, and further obtain the longitudinal wave velocity and the transverse wave velocity through the three-dimensional density data body; Calculate the porosity three-dimensional data volume based on the density three-dimensional data volume; The three-dimensional spatial variation of reservoir pore types is characterized by using three-dimensional data volumes of compressional wave velocity, shear wave velocity, density and porosity.

2. A carbonate reservoir pore type seismic characterization method according to claim 1, characterized in that: The method of obtaining the longitudinal wave impedance and the transverse wave impedance of the reservoir comprises the following steps: Perform reservoir optimization processing inversion and solve the L1 norm minimization problem through compressed sensing inversion: y=Dm,m≥0 (1) Where y is the observed value, m = R n×1 is the signal to be sampled, D is the measurement matrix; According to the sparse representation of the signal, the seismic signal can be sparsely represented in a certain transform domain. Assuming that E represents the sparse basis, the signal representation is: m=Ex (2) Where E = R n×n represents a sparse matrix; substitute equation (2) into equation (1): y=DEx,x≥0 (3) Let B = R m×n is the perception matrix, then the signal can be rewritten as:

3. A carbonate reservoir pore type seismic characterization method according to claim 2, characterized in that: During the reservoir inversion process, the input data include angle gathers, wavelets of each angle gather and low-frequency model, and the output is P-wave impedance and S-wave impedance.

4. A carbonate reservoir pore type seismic characterization method according to claim 1, characterized in that: Converting the longitudinal wave impedance and the shear wave impedance into density to obtain a density three-dimensional data volume includes the following steps: The density-transverse wave impedance intersection volume is divided into multiple trend lines by using the density calculation indicator factor. The density three-dimensional data volume is obtained by using the density calculation indicator factor. The density indicator factor is expressed by formula (5): Where: is the ratio of longitudinal and transverse wave velocities; SI is the transverse wave impedance; AI is the longitudinal wave impedance; DCI is the density indicator factor.

5. A carbonate reservoir pore type seismic characterization method according to claim 4, characterized in that: The method of calculating the porosity three-dimensional data volume based on the density three-dimensional data volume specifically includes the following steps: The porosity is calculated by formula (6): Where ρ is the seismic prediction density of the reservoir segment, ρ f is the fluid density, ρ b is the skeleton density.

6. A carbonate reservoir pore type seismic characterization method according to claim 1, characterized in that: Calculating the porosity three-dimensional data volume also includes the following steps: Introduce the pore structure parameter γ, see formula (7): Where φ represents the porosity and f represents the integrated bulk modulus.

7. A carbonate reservoir pore type seismic characterization method according to claim 6, characterized in that: The calculation process of the pore structure parameter γ includes the following steps: In the formula, K f represents the skeleton bulk modulus, K s represents the bulk modulus of fluid, K represents the bulk modulus of rock, V p represents the longitudinal wave velocity, V s represents the shear wave velocity and ρ represents the density.

8. A carbonate reservoir pore type seismic characterization system, characterized in that: It includes pre-stack inversion module, density inversion module, porosity inversion module and pore structure parameter inversion module; Prestack inversion module, used to perform prestack inversion and obtain the P-wave impedance and S-wave impedance of the reservoir; The density inversion module is used to construct a density indicator factor, to convert the longitudinal wave impedance and the transverse wave impedance into density to obtain a three-dimensional density data body, and further obtain the longitudinal wave velocity and the transverse wave velocity through the three-dimensional density data body; Porosity inversion module, used to calculate the porosity 3D data volume based on the density 3D data volume; The pore structure parameter inversion module is used to characterize the three-dimensional spatial changes of reservoir pore types using the three-dimensional data volumes of P-wave velocity, S-wave velocity, density and porosity.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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