Overpressure formation petrophysical modeling method and system considering multiple-porosity media

Abstract

The application discloses a method and system for overpressure formation rock physics modeling considering multiple pore media, and the method comprises the following steps: constructing a rock skeleton; adding a bound water pore to the rock skeleton; adding a bound water modulus to the rock skeleton containing the bound water pore; calculating a flexible pore ratio and a flexible porosity, and then adding a flexible pore to the rock skeleton containing the bound water modulus; adding a rigid pore to the rock skeleton containing the flexible pore; adding movable fluid to the double-pore rock skeleton; determining the volume modulus and shear modulus of each type of mineral in a saturated fluid equivalent model; and optimizing and adjusting the length-width ratio of the bound water pore and the length-width ratio of the rigid pore based on the volume modulus and shear modulus of each type of mineral in the saturated fluid equivalent model. The method adds the bound water pore and modulus to the rock skeleton on the basis of predicting formation pore pressure, adds fluid under consideration of different pore conditions, and thus improves the accuracy and reliability of the prediction result of the model velocity.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of geophysical technology, and particularly relates to a method and system for rock physics modeling of overpressure formation considering multiple pore media. BACKGROUND

[0002] Overpressure formation refers to the fluid pressure (i.e., pore pressure) in the pores of the formation being significantly higher than the normal hydrostatic pressure. Normally, the pore pressure of the formation is proportional to the depth of the formation and increases with the increase of the depth. However, in the overpressure formation, the pore pressure is much higher than the expected hydrostatic pressure due to some special factors. The overpressure formation often has a higher porosity and reservoir volume, because during the deposition of the formation, the fluid fails to be completely discharged, resulting in the pore space of the reservoir being filled with fluid. This "filling" enables the overpressure reservoir to store more oil and gas. At the same time, due to the overpressure effect, they have stronger sealing property in the formation and are not easy to leak, which helps to maintain the long-term stability of the oil and gas resources. Therefore, the study of overpressure reservoirs is of great significance to oil and gas exploration and development.

[0003] Rock physics modeling is a bridge connecting the physical parameters and elastic parameters of the connected reservoir, and can establish a mapping relationship with the seismic data. Through the rock physics model, the prediction of the P-wave and S-wave velocities can be realized, and the sensitive parameters of the reservoir can be better identified. At present, the traditional rock physics model has less discussion on the influence of pressure, and the research on the overpressure reservoir is also mainly focused on the overpressure formation mechanism and the prediction of pore pressure. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a method and system for rock physics modeling of overpressure formation considering multiple pore media.

[0005] The technical solution adopted by the present application to solve the technical problem is: a method for rock physics modeling of overpressure formation considering multiple pore media is constructed, comprising:

[0006] S1: constructing a rock skeleton;

[0007] S2: adding bound water pores to the rock skeleton to obtain a rock skeleton containing bound water pores;

[0008] S3: adding bound water modulus to the rock skeleton containing bound water pores to obtain a rock skeleton containing bound water modulus;

[0009] S4: calculating the proportion of flexible pores and calculating the flexible porosity first, and then adding flexible pores to the rock skeleton containing bound water modulus to obtain a rock skeleton containing flexible pores;

[0010] S5: adding rigid pores to the rock skeleton containing flexible pores to obtain a dual-pore rock skeleton.

[0011] S6: adding a movable fluid into the dual-porosity rock skeleton to obtain a saturated fluid equivalent model;

[0012] S7: Determine the bulk modulus (K i ) and shear modulus (μ i );

[0013] S8: Based on the bulk modulus of various minerals in the saturated fluid equivalent model (K i ) and shear modulus (μ i ), optimize and adjust the bound water pore aspect ratio and rigid pore aspect ratio, and then improve the prediction accuracy of P- and S-wave velocities.

[0014] In some embodiments, in step S1, the initial bulk modulus (K i0 ) and initial shear modulus (μ i0 ), the Voigt-Reuss-Hill model was used to determine the bulk modulus of the rock skeleton (K m0 ) and shear modulus (μ m0 ).

[0015] In some embodiments, in step S2, according to Kuster- The (KT) model adds bound water pores to the rock skeleton and sets the bound water pore aspect ratio (ɑ b0 ), calculate the bulk modulus of the rock skeleton after adding bound water (K sat-k ) and shear modulus (μ sat-k ).

[0016] In some embodiments, in step S3, the bulk modulus of irreducible water (K) is added to the rock skeleton containing irreducible water pores obtained in step S2 using the patch saturation Patchy model. b1 ) and shear modulus (μ b1 ) and sphere radius (b), frequency (f), permeability (p) and saturation (s), the bulk modulus of the rock skeleton containing the bound water modulus (K sat-p ) and shear modulus (μ sat-p ).

[0017] In some embodiments, in step S4, the flexible pore ratio is calculated according to formula (1):

[0018]

[0019] wherein in formula (1), S is the flexible pore ratio, A, B, C, D are constants related to the actual formation, Pn is the difference between the overburden pressure and the hydrostatic pressure, and Pe is the effective stress of the formation;

[0020] After obtaining the flexible pore ratio, the flexible porosity is calculated according to formula (2):

[0021] Pors=S* Pore (2)

[0022] In formula (2), Pors is the flexible porosity, and Pore is the effective porosity obtained by well logging interpretation.

[0023] The bulk modulus (K sat-s ) and shear modulus (μ sat-s ) of the rock skeleton containing flexible pores are calculated according to formula (3) and formula (4) respectively:

[0024]

[0025] wherein A, B, C in formula (3) and formula (4) are constants related to the actual formation.

[0026] In some embodiments, in step S5, a self-consistent (SCA) model is used to add rigid pores to the rock skeleton containing flexible pores to obtain a dual-porosity rock skeleton, the rigid pore aspect ratio (ɑ h1 ), the bulk modulus and shear modulus of the rigid pore are set, and the bulk modulus (K sat-h ) and shear modulus (μ sat-h ) of the dual-porosity rock skeleton are calculated.

[0027] In some embodiments, in step S6, the bulk modulus (K fl ) of the movable fluid is calculated using the Wood formula, the bulk modulus (K fl ) and shear modulus (μ fl ) of the movable fluid are added to the dual-porosity rock skeleton using the Gassmann model to obtain the saturated fluid equivalent model, the bulk modulus (K sat0 ) and shear modulus (μ sat0 ) of the saturated fluid equivalent model are calculated, and then the P-and S-wave velocities are obtained.

[0028] In some embodiments, in step S7, based on the initial irreducible water pore aspect ratio (α b1 ) and the rigid pore aspect ratio (α h1 ), the bulk modulus (K i0 ) and shear modulus (μ i0 ) of different minerals are adjusted so that the P-and S-wave velocity error is less than the initial prediction error threshold (Tv1 ), and finally determine the appropriate bulk modulus (K i ) and shear modulus (μ i ) of different minerals in the study area.

[0029] In some embodiments, in step S8, based on the bulk modulus (K i ) and shear modulus (μ i ) of each type of mineral in the saturated fluid equivalent model, an intelligent optimization algorithm is used, the maximum number of iterations (I) of the algorithm is set, the bound water pore aspect ratio (ɑ b ) in step S2 and the rigid pore aspect ratio (α h ) in step S5 are optimized, and the optimization range of the bound water pore aspect ratio (ɑ b ) is ɑ bmin —ɑ bmax , the optimization range of the rigid pore aspect ratio (α h ) is ɑ hmin —ɑ hmax , so that the error value of the calculated P and S wave velocities after the above steps S2 and S5 is less than the error threshold (T v2 ), if the error value of the P and S wave velocities is not less than the error threshold (T v2 ), return to optimization and iterate to the maximum number of times; if the error value of the P and S wave velocities is less than the error threshold (T v2 ), stop iteration and output the finally calculated bulk modulus (K sat ) and shear modulus (μ sat ) of the saturated fluid equivalent model, and then calculate the P and S wave velocities.

[0030] The application further provides a superpressure formation rock physics modeling system considering a multiple-pore medium, comprising a memory and a processor.

[0031] The memory is used to store a computer program.

[0032] The processor is used to realize the superpressure formation rock physics modeling method considering a multiple-pore medium of any one of the above embodiments when executing one or more programs stored on the memory.

[0033] The application has the following beneficial effects: the superpressure formation rock physics modeling method considering a multiple-pore medium of the application improves the accuracy and reliability of the model velocity prediction result by adding the bound water pores and modulus into the rock skeleton on the basis of predicting the formation pore pressure, and adding fluid under different pore conditions. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the present application, the present application will be further described below in conjunction with the accompanying drawings and embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. Other related drawings can also be obtained by those skilled in the art without creative labor. In the drawings:

[0035] Figure 1 is a flow chart of the overpressure formation petrophysical modeling method considering multiple-porosity media in some embodiments of the present application;

[0036] Figure 2 is a schematic diagram of the overpressure formation petrophysical modeling considering multiple-porosity media in some embodiments of the present application;

[0037] Figure 3 is a graph of the content of each component varying with depth in some embodiments of the present application;

[0038] Figure 4 is a flow chart of the pore pressure prediction in some embodiments of the present application;

[0039] Figure 5 is a graph of the flexible porosity and the rigid porosity varying with depth in some embodiments of the present application;

[0040] Figure 6 is a comparison graph of the calculated P and S wave velocities and the measured P and S wave velocities in some embodiments of the present application;

[0041] Figure 7 is a histogram of the P and S wave velocity error distribution in some embodiments of the present application. DETAILED DESCRIPTION

[0042] In order to have a more clear understanding of the technical features, objects and effects of the present application, the specific embodiments of the present application will be described in detail with reference to the accompanying drawings. In the following description, it should be understood that the orientation or positional relationship indicated by "front", "back", "upper", "lower", "left", "right", "vertical", "horizontal", "vertical", "horizontal", "top", "bottom", "inner", "outer", "head", "tail" and the like is based on the orientation or positional relationship shown in the drawings, and is constructed and operated in a particular orientation, only for the convenience of describing the present technical solution, and should not be understood as indicating that the device or element must have a particular orientation, therefore it should not be regarded as limiting the present application.

[0043] It should be noted that, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting", "fixing", "setting" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements or the interaction relationship between two elements. When an element is referred to as "on" or "below" another element, the element can be "directly" or "indirectly" above the other element, or there can be one or more intervening elements. The terms "first", "second", "third" and the like are only for the convenience of describing the technical solutions, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features with "first", "second", "third" and the like can be explicitly or implicitly included one or more of the features. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0044] In the following description, specific details are set forth such as specific system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it should be apparent to those skilled in the art that the present application can be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted in order not to obscure the description of the present application with unnecessary details.

[0045] Overpressure formation refers to the fluid pressure in the formation pores (i.e. pore pressure) being significantly higher than the normal hydrostatic pressure. Normally, the pore pressure of the formation is proportional to the depth of the formation and increases with the increase of the depth. However, in overpressure formation, the pore pressure is much higher than the expected hydrostatic pressure due to some special factors. Overpressure formation often has a higher porosity and reservoir volume, because during the deposition of the formation, the fluid fails to completely drain, resulting in the pore space of the reservoir being filled with fluid. This "filling" enables overpressure reservoirs to store more oil and gas. At the same time, due to the overpressure effect, they have stronger sealing properties in the formation and are not prone to leakage, which helps to maintain the long-term stability of oil and gas resources. Therefore, the study of overpressure reservoirs is of great significance to oil and gas exploration and development.

[0046] Rock physics modeling is a bridge between connected reservoir physical parameters and elastic parameters, which can establish a mapping relationship with seismic data. Through rock physics modeling, the prediction of P-wave and S-wave velocity can be realized, and the sensitive parameters of the reservoir can be better identified. At present, the traditional rock physics model has less discussion on the influence of pressure, and the research on overpressure reservoirs is also mainly focused on the overpressure formation mechanism and pore pressure prediction.

[0047] The research shows that there are few patents and more literatures about the rock physics modeling of overpressure reservoirs, and the effective medium theory is the theoretical basis for studying the rock physics model. Budiansky (1965) first proposed the self-consistent model (SCA), Kuster and Toksoz (1974) derived the two-phase equivalent medium model, namely the K-T model, from the first-order scattering theory, Cleary et al. (1980) established a two-phase equivalent medium model (DEM) suitable for the two-phase equivalent medium model, Xu and White (1995) established a theoretical model of mudstone, combined with the K-T model and the DEM model, and used the pore aspect ratio to divide the muddy pores and the sandy pores. The related research on the influence of pressure in the reservoir is mainly based on rock physics experiments. Mavko and Mukerji (1995) first proposed the pore space stiffness theory to describe the compressibility of the pore space, and Yunmei (2001) fitted the relationship between the dry rock modulus and the sandstone porosity, the mud content, the effective pressure, the temperature and the dry rock modulus. Russel (2013) combined the pore stiffness theory and the Gassmann equation to establish a rock physics model, and Liu Jun et al. (2019) obtained the relationship between the P-wave and S-wave velocities and the pressure of deep clastic rocks through experiments. In the current research, there are many studies on rock physics modeling. For the rock physics modeling process of overpressure formation, the influence of formation pressure is considered by using the pore space stiffness theory, and the mud content is used to estimate the mudstone pore content and then replace all the flexible pores. Different scholars have also proposed their own empirical theoretical models, but the flexible pores in different research areas are affected by the formation pressure, and need to be adjusted according to the actual situation of the research area. Therefore, how to reasonably represent the proportion of flexible pores and rigid pores, and establish a multiple-pore medium rock physics model considering the influence of pressure in overpressure formation is a problem to be solved at present.

[0048] In view of the above problems, the present application shows a kind of overpressure formation rock physics modeling method considering multiple-pore medium, on the basis of predicting formation pore pressure, bound water pore and bound water pore are added to rock skeleton, and the content of flexible pore and rigid pore is calculated, different pore case is added fluid, to improve the accuracy and reliability of model velocity prediction result.

[0049] Reference Figure 1 And Figure 2 The present application shows a kind of overpressure formation rock physics modeling method considering multiple-pore medium, wherein, Figure 1 It is the overpressure formation rock physics modeling flow chart considering multiple-pore medium, Figure 2 It is the overpressure formation rock physics modeling schematic diagram considering multiple-pore medium, can more directly show the overpressure formation rock physics modeling method considering multiple-pore medium of the present application.

[0050] In some embodiments, the method for rock physics modeling of overpressured formations considering multiple porous media includes:

[0051] S1: Construct rock skeleton; wherein, in step S1, set the initial bulk modulus (K i0 ) and initial shear modulus (μ i0 ), the Voigt-Reuss-Hill model was used to determine the bulk modulus of the rock skeleton (K m0 ) and shear modulus (μ m0 ). Furthermore, the initial modulus of each component of the rock can be estimated based on the logging data, and the rock skeleton can be constructed based on the VRH model. In this embodiment, the measured data of the research block (in this example, the mineral content changes with depth as shown in Figure 3 ), and obtain the mineral content (Vi) and density (ρ i ), porosity (ф0), permeability (p) and longitudinal and shear wave velocities (vp, vs) and other logging curves. According to the mineral composition of the rock skeleton, the initial quartz bulk modulus is given as 39GPa, shear modulus: 30GPa, clay bulk modulus: 46GPa, shear modulus: 19GPa, calcite bulk modulus: 30GPa, shear modulus: 22GPa. The bulk modulus of the rock skeleton (K) is calculated using the Voigt-Reuss-Hill model. m0 ) and shear modulus (μ m0 ), the rock skeleton and fluid densities are calculated by multiplying the volume fraction of each component by its density and then adding the two together. In this example, the rock skeleton minerals include quartz, clay, and calcite, with clay comprising the vast majority of the rock composition. The fluids filling the pores are divided into bound water and movable fluids, with the latter comprising water, oil, and gas.

[0052] S2: adding irreducible water pores to the rock skeleton to obtain a rock skeleton containing irreducible water pores; wherein, in step S2, according to Kuster- The (KT) model adds bound water pores to the rock skeleton and sets the bound water pore aspect ratio (ɑ b0 ), calculate the bulk modulus of the rock skeleton after adding bound water (K sat-k ) and shear modulus (μ sat-k ). Preferably, bound water pores are added to the rock skeleton, according to Kuster- (KT) Bulk modulus of the model to the rock skeleton (K m0 ) and shear modulus (μ m0 ) Add the bulk modulus of bound water pores (K b =0.01GPa), shear modulus (μ b =0 GPa) and the initial bound water pore aspect ratio (ɑb1 =0.2), the bulk modulus (K sat-k ) and shear modulus (μ sat-k ) of the rock skeleton containing the bound water pores are calculated.

[0053] S3: the bound water modulus is added to the rock skeleton containing the bound water pores to obtain a rock skeleton containing the bound water modulus. In step S3, the bulk modulus (K b1 ) and shear modulus (μ b1 ) of the bound water are added to the rock skeleton containing the bound water pores obtained in step S2 by using the Patchy model, and the bulk modulus (K sat-p ) and shear modulus (μ sat-p ) of the rock skeleton containing the bound water modulus are obtained by using the ball radius (b), frequency (f), permeability (p) and saturation (s). Preferably, the bulk modulus (K sat-k ) and shear modulus (μ sat-k ) of the rock skeleton containing the bound water pores are added to the bulk modulus (K b =2.65 GPa), shear modulus (μ b =0 GPa), ball radius (b=0.1), frequency (f=5000), permeability (p) and saturation (s) of the bound water by using the Patchy model, wherein the permeability and saturation of the present embodiment are obtained from the logging curve, and the frequency is the logging frequency, and the bulk modulus (K sat-p ) and shear modulus (μ sat-p ) of the rock skeleton containing the bound water modulus are calculated.

[0054] S4: the flexible pore ratio is calculated first, and then the flexible porosity is calculated, and the flexible pore is added to the rock skeleton containing the bound water modulus to obtain a rock skeleton containing the flexible pore (or defined as a soft pore dry rock skeleton), and the flexible pore ratio is calculated and the flexible porosity is calculated; wherein the Eaton method is used to predict the formation pressure, and then the effective stress and the pressure coefficient are obtained. In the normal pressure formation, the flexible pore ratio is directly estimated by the shale content, and with the gradual increase of the depth, the flexible pore ratio gradually decreases. But in the overpressure formation, due to the increase of the formation pore pressure, the trend of the decrease of the flexible pore ratio gradually slows down, and the present application proposes formula (1) to make the flexible pore ratio be adjusted by the overlying formation pressure, hydrostatic pressure and effective stress, which is more in line with the actual situation underground.

[0055] Herein, in step S4, the flexible pore ratio is calculated according to formula (1):

[0056]

[0057] Wherein, in formula (1), S is a flexible pore ratio, A, B, C, D are constants, related to the actual formation. Pn is the difference between the overburden pressure and hydrostatic pressure, Pe is the effective stress of the formation.

[0058] After obtaining the flexible pore ratio, the flexible porosity is calculated according to formula (2):

[0059] Pors=S* Pore (2)

[0060] In formula (2), Pors is the flexible porosity, Pore is the effective porosity, obtained by well logging interpretation.

[0061] Further, the pore space stiffness theory is to describe the compressibility of the pore space structure, k is the ratio of the pore space stiffness to the bulk modulus of the rock matrix, which is usually a function of the effective stress Pe. According to the actual formation of the specific research area, it is usually described as a natural logarithm or a linear relationship. The present application improves the pore space stiffness theory, and the improved bulk modulus and shear modulus are simultaneously adjusted by the pressure coefficient and the effective stress. The bulk modulus and shear modulus of the rock containing flexible pores are calculated respectively, and the improved pore space stiffness theory is used to calculate the bulk modulus (K sat-s ) and shear modulus (μ sat-s ) of the rock skeleton containing flexible pores as shown in formula (3) and formula (4).

[0062] The bulk modulus (K sat-s ) and shear modulus (μ sat-s ) of the rock skeleton containing flexible pores are calculated according to formula (3) and formula (4) respectively:

[0063]

[0064] Wherein, A, B, C in formula (3), formula (4) are constants, related to the actual formation.

[0065] Further, as shown in Figure 4 , Eaton method is used to predict the formation pressure, which is based on the normal compaction theory to construct the normal compaction trend line, and introduces the compaction correction coefficient to calculate the pore pressure, and then obtains the pressure coefficient Pc and the effective stress Pe.

[0066] P p =p o -(p o -p h )(Δt n / Δt)n (5)

[0067] P e =P o -P p (6)

[0068]

[0069] In formula (5), Pp is the predicted pore pressure, with units of MPa; Po is the overburden pressure, with units of MPa; Ph is the hydrostatic pressure, with units of MPa;△t n is the normal compaction acoustic travel time of the formation, with units of ps / m;△t is the measured acoustic travel time, with units of ps / m; Eaton parameter n is an empirical index, which is related to the actual region, and in the present example, n = 4.2. Pe in formula (6) is the effective stress, with units of MPa. Pc in formula (7) is the pressure coefficient.

[0070] After obtaining the overburden pressure, the hydrostatic pressure, the effective stress Pe and the pressure coefficient Pc, the flexible pore ratio Pors is obtained by using the proposed flexible pore ratio calculation formula for overpressure formation. In formula (1) of the present example, A = 30, B = 10, C = -1, and D = 1. The flexible pore ratio and the rigid pore ratio with depth are obtained as shown in Figure 5 Using the improved pore space stiffness theory, in formula (3) and (4) of the present example, A = 0.7, B = -0.05, and C = 0.95, the flexible pore is added to the rock skeleton obtained in the previous step to obtain the bulk modulus (K sat-s ) and the shear modulus (μ sat-s ) of the rock skeleton after adding the flexible pore.

[0071] S5: adding rigid pores to the rock skeleton containing flexible pores to obtain a dual-pore rock skeleton (or defined as a multi-pore dry rock skeleton); in step S5, the rigid pores are added to the rock skeleton containing flexible pores by using the self-consistent (SCA) model to obtain a dual-pore rock skeleton, and the aspect ratio (ɑ h1 ) of the rigid pore, the bulk modulus and the shear modulus of the rigid pore are set to calculate the bulk modulus (K sat-h ) and the shear modulus (μ sat-h ) of the dual-pore rock skeleton. Further, by using the self-consistent (SCA) model, the aspect ratio (ɑ h1 = 0.5) of the rigid pore, the bulk modulus (K h = 0.001 Gpa) and the shear modulus (μh= 0 Gpa) of the rigid pore, and the bulk modulus (K sat-s ) and the shear modulus (μ sat-s ) of the rock skeleton after adding the flexible pore are set. The bulk modulus (K sat-h ) and the shear modulus (μ sat-h ) of the dual-pore rock skeleton are calculated.

[0072] S6: adding movable fluid into the dual-porosity rock skeleton to obtain a saturated fluid equivalent model; in step S6, the bulk modulus (K fl ) of the movable fluid is calculated by using the Wood formula, the bulk modulus (K fl ) and the shear modulus (μ fl ) of the movable fluid are added into the dual-porosity rock skeleton by using the Gassmann model, the bulk modulus (K sat0 ) and the shear modulus (μ sat0 ) of the saturated fluid equivalent model are calculated, and then the P-wave velocity and the S-wave velocity are obtained.

[0073] The movable fluid is added into the rock skeleton containing the flexible pores and the rigid pores (dual-porosity rock skeleton). After the bound water, the flexible pores and the rigid pores are added, the bulk modulus (K fl ) and the shear modulus (μ fl = 0) of the movable fluid are added into the movable fluid pores in the rock by using the Gassmann model, wherein the bulk modulus (K fl ) of the movable fluid is calculated by using the Wood formula, and the bulk modulus (K sat0 ) and the shear modulus (μ sat0 ) of the rock after the movable fluid is added are calculated.

[0074] S7: determining the bulk modulus (K i ) and the shear modulus (μ i ) of each type of mineral in the saturated fluid equivalent model; in step S7, based on the initial aspect ratio (ɑ b1 ) of the bound water pores and the initial aspect ratio (ɑ h1 ) of the rigid pores, the bulk modulus (K i0 ) and the shear modulus (μ i0 ) of different minerals are adjusted so that the error of the P-wave velocity and the S-wave velocity is less than the initial prediction error threshold (T v1 ), and finally the appropriate bulk modulus (K i ) and the shear modulus (μ i ) of different minerals in the study area are determined.

[0075] Further, the bulk modulus (K i ) and the shear modulus (μ i ) of the minerals in the rock skeleton are determined. First, the initial aspect ratio (ɑ b1 ) of the bound water pores and the initial aspect ratio (ɑ h1 ) of the rigid pores are set, wherein the initial aspect ratio (ɑ b= 0.2, rigid pore aspect ratio a h = 0.5. Adjust different mineral bulk modulus (K i ), shear modulus (μ i ), calculate P-wave velocity and S-wave velocity according to bulk modulus (K sat ) and shear modulus (μ sat ), make P-wave and S-wave velocity error less than initial prediction error threshold T v1 , in this example, error threshold T v1 = 0.1, determine suitable bulk modulus and shear modulus of different minerals in the study area as shown in Table 1:

[0076] Table 1: Input parameters related to each mineral in the rock skeleton in the example

[0077]

[0078]

[0079] S8: Based on the bulk modulus (K i ) and shear modulus (μ i ) of each type of mineral in the saturated fluid equivalent model, the bound water pore aspect ratio and the rigid pore aspect ratio are optimized and adjusted, thereby improving the prediction accuracy of P-wave and S-wave velocity. In step S8, based on the bulk modulus (K i ) and shear modulus (μ i ) of each type of mineral in the saturated fluid equivalent model, an intelligent optimization algorithm is used to set the maximum number of iterations (I) of the algorithm, simultaneously optimize the bound water pore aspect ratio (a b ) in step S2 and the rigid pore aspect ratio (a h ) in step S5, and set the optimization range of the bound water pore aspect ratio (a b ) to a bmin — a bmax , and the optimization range of the rigid pore aspect ratio (a h ) to a hmin — a hmax , so that the error value of the P-wave and S-wave velocity calculated after the above steps S2 and S7 is brought in again is less than the error threshold (T v2 ). If the error value of the P-wave and S-wave velocity is not less than the error threshold (T v2 ), return to optimization and iterate to the maximum number of times; if the error value of the P-wave and S-wave velocity is less than the error threshold (T v2 ), stop iteration and output the final calculated bulk modulus (K sat ) and shear modulus (μ sat ) of the saturated fluid equivalent model, and then calculate the P-wave and S-wave velocity.

[0080] wherein the intelligent optimization algorithm is used to optimize and adjust the aspect ratio of bound water pores and rigid pores. Since the proportion of each type of pore changes greatly at different depths, the aspect ratio of the pores also changes with the formation. The optimization algorithm is used to find the optimal value of the aspect ratio of the pores. In this example, the intelligent optimization algorithm uses the particle swarm optimization algorithm, and of course the intelligent optimization algorithm can be selected according to actual needs. Further, in this example, the intelligent optimization algorithm uses the particle swarm optimization algorithm, sets the maximum number of iterations of the algorithm (I = 100), and optimizes the aspect ratio of the bound water pores (ɑ b ) in step S2 and the aspect ratio of the rigid pores (ɑ h ) in step S5, and determines that the optimization range of the aspect ratio of the bound water pores is ɑ bmin = 0.01—ɑ bmax = 0.4, and the optimization range of the aspect ratio of the rigid pores is ɑ hmin = 0.01—ɑ hmax = 0.9, and the above steps S2 to S7 are cycled, so that the error value between the predicted aspect ratio and the actual aspect ratio is less than the error threshold T v2 (T v2 = 0.01), if the error threshold T v2 cannot be reached, the optimization is continued and iterated to the maximum number; if the error threshold T v2 (T v2 = 0.01) is less than the error threshold, the iteration is stopped and the last calculated bulk modulus (K sat ) and shear modulus (μ sat ) are output, and then the parameters such as the aspect ratio, the aspect ratio ratio and the Poisson's ratio are calculated. The predicted aspect ratio is shown in Figure 6 , and the error distribution between the predicted aspect ratio and the actual aspect ratio is shown in Figure 7 .

[0081] The superpressure formation rock physics modeling method considering multiple-pore media of the present application includes pore pressure prediction, flexible pore content calculation method, improved pore space stiffness theory, and superpressure formation rock physics model construction process using intelligent optimization algorithm (such as particle swarm optimization algorithm) considering two types of pore aspect ratios. The former is the basis for developing superpressure formation rock physics modeling, and the latter can improve the accuracy of the predicted aspect ratio of the superpressure formation rock physics model.

[0082] Understandably, the superpressure formation rock physics modeling method considering multiple-pore media of the present application adds the pores and modulus of the bound water to the rock skeleton on the basis of predicting the pore pressure of the formation, and can calculate the content of the flexible pores and the rigid pores, considers adding fluid under different pore conditions, thereby improving the accuracy and reliability of the model velocity prediction results.

[0083] The application further discloses a superpressure formation petrophysical modeling system considering multiporosity medium, comprising a memory and a processor.

[0084] The memory is used for storing a computer program.

[0085] The processor is used for realizing the superpressure formation petrophysical modeling method considering multiporosity medium of the above embodiment when executing one or more programs stored on the memory.

[0086] The memory can be a computer readable signal medium or a computer readable memory or any combination of the above two. The memory may, for example, be but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the memory can include but are not limited to an electrical connection having one or more conductive wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. The processor includes but is not limited to a microprocessor, a microcontroller, a digital signal processor, a microcomputer, a central processing unit, a field programmable gate array, a programmable logic device, a state machine, a logic circuit, an analog circuit, a digital circuit, and / or any device based on operation of an operating signal (analog and / or digital) based on operating instructions.

[0087] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms is not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any suitable manner in any one or more embodiments or examples. In addition, different embodiments or examples described in the present specification and the features of different embodiments or examples can be combined and combined by those skilled in the art without contradiction.

[0088] It can be understood that the above embodiments only express the preferred implementation of the present application, which is described in a more specific and detailed manner, but cannot be understood as a limitation on the patent scope of the present application; it should be noted that the above technical features can be freely combined by those skilled in the art without departing from the concept of the present application, and a number of modifications and improvements can also be made, which are all within the protection scope of the present application; therefore, any equivalent transformation and modification made to the claims of the present application shall be within the scope of the claims of the present application.

Claims

1. A rock physics modeling method for overpressured formations considering multiple porous media, characterized in that: include: S1: building rock skeleton; In step S1, the initial bulk modulus K of different minerals is set i0 and initial shear modulus μ i0 , using the Voigt-Reuss-Hill model to determine the bulk modulus K of the rock skeleton m0 and shear modulus μ m0 ; S2: adding irreducible water pores to the rock skeleton to obtain a rock skeleton containing irreducible water pores; in step S2, according to The model adds bound water pores to the rock skeleton and sets the bound water pore aspect ratio ɑ b0 , calculate the bulk modulus K after adding bound water to the rock skeleton sat-k and shear modulus μ sat-k ; S3: Adding the bound water modulus to the rock skeleton containing the bound water pores to obtain the rock skeleton containing the bound water modulus; In step S3, the bulk modulus K of bound water is added to the rock skeleton containing the bound water pores obtained in step S2 using the patch saturation Patchy model. b1 and shear modulus μ b1 As well as the sphere radius b, frequency f, permeability p and saturation s, the bulk modulus K of the rock skeleton containing the bound water modulus is obtained sat-p and shear modulus μ sat-p ; S4: First calculate the flexible pore ratio and the flexible porosity, then add the flexible pores to the rock skeleton containing the bound water modulus to obtain the rock skeleton containing flexible pores; in step S4, calculate the flexible pore ratio according to formula (1): Wherein, in formula (1), S is the proportion of flexible pores, A1, B1, C1, and D1 are constants related to the actual formation, Pn is the difference between the overlying formation pressure and the hydrostatic pressure, e is a natural constant, Pe is the effective formation stress, and SH is the mud content of the formation rock; After obtaining the flexible pore ratio, the flexible porosity is calculated according to formula (2): Pors = S* Pore (2) In formula (2), Pors is the flexible porosity and Pore is the effective porosity, which is obtained from well logging interpretation; The bulk modulus K of the rock skeleton containing flexible pores is calculated according to formula (3) and formula (4) respectively: sat-s and shear modulus μ sat-s : Wherein, in formula (3), Pc is the pressure coefficient; in formula (3) and formula (4), A2, B2, and C2 are constants related to the actual formation; S5: adding rigid pores to the rock skeleton containing flexible pores to obtain a dual-porosity rock skeleton; S6: adding a movable fluid into the dual-porosity rock skeleton to obtain a saturated fluid equivalent model; S7: Determine the bulk modulus K of various minerals in the saturated fluid equivalent model i and shear modulus μ i ; S8: Based on the bulk modulus K of various minerals in the saturated fluid equivalent model i and shear modulus μ i , optimize and adjust the bound water pore aspect ratio and rigid pore aspect ratio, and then improve the prediction accuracy of P- and S-wave velocities.

2. The rock physics modeling method for overpressured formations considering multiple porous media according to claim 1, characterized in that: In step S5, the self-compatible model is used to add rigid pores to the rock skeleton containing flexible pores to obtain a dual-porosity rock skeleton, and the rigid pore aspect ratio ɑ is set to h1 , the bulk modulus and shear modulus of the rigid pores, and the bulk modulus K of the dual-porosity rock skeleton are calculated. sat-h and shear modulus μ sat-h .

3. The rock physics modeling method for overpressured formations considering multiple porous media according to claim 2, characterized in that: In step S6, the bulk modulus K of the movable fluid is calculated using the Wood formula fl , the bulk modulus K of the movable fluid is added to the dual-porosity rock skeleton using the Gassmann model fl , shear modulus μ fl , obtain the saturated fluid equivalent model, and calculate the bulk modulus K of the saturated fluid equivalent model sat0 and shear modulus μ sat0 , and then obtain the longitudinal and transverse wave velocities.

4. The rock physics modeling method for overpressured formations considering multiple porous media according to claim 3, characterized in that: In step S7, based on the initial bound water pore aspect ratio α b0 , rigid pore aspect ratio α h1 , adjust the bulk modulus K of different minerals i0 , shear modulus μ i0 , so that the P-wave and S-wave velocity errors are less than the initial prediction error threshold T v1 , and finally determine the appropriate bulk modulus K for different minerals in the study area i and shear modulus μ i .

5. The rock physics modeling method for overpressured formations considering multiple porous media according to claim 4, characterized in that: In step S8, based on the bulk modulus K of various minerals in the saturated fluid equivalent model, i , shear modulus μ i , using the intelligent optimization algorithm, set the maximum number of algorithm iterations I, and optimize the bound water pore aspect ratio ɑ in step S2 b0 and the rigid pore aspect ratio α in step S5 h1 , and set the bound water pore aspect ratio ɑ b0 The optimal range is ɑ bmin —ɑ bmax , rigid pore aspect ratio α h1 The optimal range is ɑ hmin —ɑ hmax , so that the error between the P-wave and S-wave velocities calculated after the above steps S2 and S5 and the actual P-wave velocities is less than the error threshold T v2 , if the error between the P-wave velocity and the actual P-wave velocity is not less than the error threshold T v2 , return to the optimal solution and iterate to the maximum number of times; If the error between the P-wave velocity and the actual P-wave velocity is less than the error threshold T v2 , then stop the iteration and output the final calculated bulk modulus K of the saturated fluid equivalent model sat and shear modulus μ sat , and then calculate the P- and S-wave velocities.

6. A rock physics modeling system for overpressured formations considering multiple porous media, characterized in that: include: Memory and processor; The memory is used to store computer programs; The processor is configured to implement the rock physics modeling method for overpressured formations considering multiple porous media as described in any one of claims 1 to 5 when executing one or more programs stored in the memory.

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