Overpressure stratum rock physical modeling method and system considering multiple pore media

Abstract

The invention discloses an overpressure stratum rock physical modeling method and system considering multiple pore media. The method comprises the following steps: constructing a rock skeleton; adding bound water pores into the rock skeleton; adding bound water modulus into the rock skeleton containing bound water pores; the proportion of flexible pores and the flexible porosity are calculated firstly, and then the flexible pores are added into the rock skeleton containing the bound water modulus; adding the rigid pores into the rock skeleton containing the flexible pores; adding a movable fluid to the dual-pore rock skeleton; determining bulk moduli and shear moduli of various minerals of the saturated fluid equivalent model; based on the volume modulus and the shear modulus of various minerals of the saturated fluid equivalent model, optimizing and adjusting the irreducible water pore aspect ratio and the rigid pore aspect ratio. According to the method, on the basis of predicting the formation pore pressure, bound water pores and moduli are added into a rock skeleton, and fluid is added by considering different pore conditions, so that the accuracy and reliability of a model speed prediction result are improved.

Description

Technical Field

[0001] The present invention relates to the field of geophysical technology, and in particular to a method and system for rock physics modeling of overpressure formations taking into account multiple porous media. Background Art

[0002] Overpressured formations refer to formations in which the fluid pressure (i.e., pore pressure) in the pores of the formation is significantly higher than the normal hydrostatic pressure. Under normal circumstances, the pore pressure of a formation is proportional to the depth of the formation and increases with increasing depth. However, in overpressured formations, the pore pressure is much higher than the expected hydrostatic pressure due to certain special factors. Overpressured formations often have higher porosity and reservoir volume because the fluid was not completely discharged during the formation deposition process, resulting in the pore space of the reservoir being filled with fluid. This "filling" allows overpressured reservoirs to store more oil and gas. At the same time, due to the overpressure effect, they are more tightly sealed in the formation and are less likely to leak, which helps maintain the long-term stability of oil and gas resources. Therefore, studying overpressured reservoirs is of great significance for oil and gas exploration and development.

[0003] Rock physics modeling is a bridge connecting reservoir physical parameters and elastic parameters, and can establish a mapping relationship with seismic data. Rock physics models can be used to predict P- and S-wave velocities and better identify sensitive parameters of reservoirs. Currently, there is little discussion on the impact of pressure on traditional rock physics models, and research on overpressure reservoirs is mostly focused on the overpressure genesis mechanism and pore pressure prediction. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and system for rock physics modeling of overpressure formations taking into account multiple porous media.

[0005] The technical solution adopted by the present invention to solve the technical problem is to construct a rock physics modeling method for overpressure formations considering multiple porous media, including:

[0006] S1: Building rock skeleton;

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

[0008] 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;

[0009] S4: first calculating the proportion of flexible pores and the flexible porosity, and then adding the flexible pores to the rock skeleton containing the 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-porosity rock skeleton;

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

[0012] S7: Determine the bulk modulus (K) of various minerals in the saturated fluid equivalent model i ) and shear modulus (μ i );

[0013] S8: Based on the bulk modulus (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 ), and calculate the bulk modulus (K sat-k ) and shear modulus (μ sat-k ).

[0016] In some embodiments, in step S3, the bulk modulus (K) of irreducible water is added to the rock skeleton containing irreducible water pores obtained in step S2 using the patchy saturation 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 proportion of flexible pores, A, B, C, and D are constants related to the actual formation, Pn is the difference between the overlying formation pressure and the hydrostatic pressure, and Pe is the effective formation stress;

[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, which is obtained from well logging interpretation;

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

[0024]

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

[0026] In some embodiments, in step S5, a self-compatible (SCA) 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. h1 ), the bulk modulus and shear modulus of the rigid pores, and the bulk modulus (K sat-h ) and shear modulus (μ sat-h ).

[0027] In some embodiments, in step S6, the bulk modulus (K fl ), the bulk modulus (K fl ), shear modulus (μ fl ), obtain the saturated fluid equivalent model, and calculate the bulk modulus (K sat0 ) and shear modulus (μ sat0 ) and then obtain the longitudinal and transverse wave velocities.

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

[0029] In some embodiments, in step S8, based on the bulk modulus (K i ), shear modulus (μ i ), using the intelligent optimization algorithm, set the maximum number of iterations (I) of the algorithm, and optimize the bound water pore aspect ratio (ɑ) in step S2 b ) and the rigid pore aspect ratio (α h ), and set the bound water pore aspect ratio (ɑ b ) The optimal range is ɑ bmin —ɑ bmax , rigid pore aspect ratio (α h ) The optimal range is ɑ hmin —ɑ hmax , so that the error between the P-wave velocity and the actual P-wave velocity calculated after the above steps S2 and S5 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 search 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 ), the iteration is stopped and the final calculated bulk modulus (K sat ) and shear modulus (μ sat ), and then calculate the P- and S-wave velocities.

[0030] The present invention also provides a rock physics modeling system for overpressure formations considering multiple porous media, comprising: a memory and a processor;

[0031] The memory is used to store computer programs;

[0032] The processor is used to implement the rock physics modeling method of overpressure formation considering multiple porous media in any of the above embodiments when executing one or more programs stored in the memory.

[0033] The implementation of the present invention has the following beneficial effects: the rock physics modeling method of overpressure formations considering multiple porous media of the present application, on the basis of predicting the formation pore pressure, adds the pore and modulus of bound water into the rock skeleton, and adds fluid considering different pore conditions, thereby improving the accuracy and reliability of the model velocity prediction results. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solution of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be understood that the following drawings only show certain embodiments of the present invention and 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. In the drawings:

[0035] Figure 1 is a flow chart of a method for rock physics modeling of overpressured formations considering multi-porosity media in some embodiments of the present invention;

[0036] Figure 2 is a schematic diagram of rock physics modeling of overpressured formations considering multi-porosity media in some embodiments of the present invention;

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

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

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

[0040] Figure 6 is a comparison diagram of the calculated longitudinal and transverse wave velocities and the measured longitudinal and transverse wave velocities in some embodiments of the present invention;

[0041] Figure 7 It is a histogram of the distribution of longitudinal and shear wave velocity errors in some embodiments of the present invention. DETAILED DESCRIPTION

[0042] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific embodiments of the present invention are now described in detail with reference to the accompanying drawings. In the following description, it should be understood that the directions or positional relationships indicated by "front", "back", "up", "down", "left", "right", "longitudinal", "horizontal", "vertical", "horizontal", "top", "bottom", "inside", "outside", "head", "tail", etc. are based on the directions or positional relationships shown in the accompanying drawings, are constructed and operated in a specific direction, and are only for the convenience of describing the present technical solution, rather than indicating that the device or element referred to must have a specific direction, and therefore cannot be understood as a limitation to the present invention.

[0043] It should also be noted that, unless otherwise clearly specified and limited, the terms such as "installed", "connected", "connected", "fixed", "set" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. When an element is referred to as being "on" or "under" another element, the element can be "directly" or "indirectly" located on the other element, or there may be one or more intermediate elements. The terms "first", "second", "third", etc. are only for the convenience of describing the present technical solution, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first", "second", "third", etc. can explicitly or implicitly include one or more of the features. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0044] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0045] Overpressured formations refer to formations in which the fluid pressure (i.e., pore pressure) in the pores of the formation is significantly higher than the normal hydrostatic pressure. Under normal circumstances, the pore pressure of a formation is proportional to the depth of the formation and increases with increasing depth. However, in overpressured formations, the pore pressure is much higher than the expected hydrostatic pressure due to certain special factors. Overpressured formations often have higher porosity and reservoir volume because the fluid was not completely discharged during the formation deposition process, resulting in the pore space of the reservoir being filled with fluid. This "filling" allows overpressured reservoirs to store more oil and gas. At the same time, due to the overpressure effect, they are more tightly sealed in the formation and are less likely to leak, which helps maintain the long-term stability of oil and gas resources. Therefore, studying overpressured reservoirs is of great significance for oil and gas exploration and development.

[0046] Rock physics modeling is a bridge connecting reservoir physical parameters and elastic parameters, and can establish a mapping relationship with seismic data. Rock physics models can be used to predict P- and S-wave velocities and better identify sensitive parameters of reservoirs. Currently, there is little discussion on the impact of pressure on traditional rock physics models, and research on overpressure reservoirs is mostly focused on the overpressure genesis mechanism and pore pressure prediction.

[0047] The survey found that there are few patents and many literatures on rock physics modeling of overpressure reservoirs, among which the effective medium theory is the theoretical basis for studying rock physics models. Budiansky (1965) first proposed the self-consistent model (SCA), Kuster and Toksoz (1974) derived the two-phase equivalent medium model, namely the KT model, based on the first-order scattering theory, Cleary et al. (1980) established a two-phase equivalent medium model (DEM), and Xu and White (1995) established a theoretical model for muddy sandstone, combining the KT model and the DEM model, and using the pore aspect ratio to realize the division of muddy pores and sandy pores. The relevant research on the influence of pressure in the reservoir is mostly 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 Yun Meihou (2001) fitted the relationship between sandstone porosity, mud content, effective pressure, temperature and dry rock modulus and dry rock modulus. Russel (2013) combined the pore stiffness theory and the Gassmann equation to establish a rock physics quantitative version. Liu Jun et al. (2019) obtained the relationship between the P- and S-wave velocities and pressure of deep clastic rocks through experiments. In the current research, there have been many studies on rock physics modeling. For the rock physics modeling process of overpressured formations, the pore space stiffness theory is mainly used to consider the influence of formation pressure, and the mud content is used to estimate the mudstone pore content and then replace all flexible pores. Different scholars have also proposed their own empirical theoretical models for this, but the flexible pores in different study areas are affected by formation pressure differently, which needs to be adjusted according to the actual situation of the study area. Therefore, how to reasonably characterize the proportion of flexible pores and rigid pores and establish a multi-porous medium rock physics model considering the influence of pressure for overpressured formations is a problem that needs to be solved at present.

[0048] In response to the above problems, the present invention shows a method for rock physics modeling of overpressure formations taking into account multiple porous media. On the basis of predicting the formation pore pressure, irreducible water pores and bound water pores are added to the rock skeleton, and the contents of flexible pores and rigid pores are calculated. Fluids are added considering different porosity conditions, thereby improving the accuracy and reliability of the model velocity prediction results.

[0049] See also Figure 1 and Figure 2 The present invention shows a method for rock physics modeling of overpressured formations considering multi-porosity media, wherein: Figure 1 This is a flow chart of rock physics modeling of overpressured formations considering multiple porous media. Figure 2 It is a schematic diagram of rock physics modeling of overpressured formations considering multiple porous media, which can more intuitively demonstrate the rock physics modeling method of overpressured formations considering multiple porous media of the present invention.

[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, 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 ). Further, the initial modulus of each component can be estimated based on the logging data of the given rock, and the rock skeleton can be constructed based on the VRH model. In this embodiment, the measured data of the study block (in this example, the mineral content changes with depth, see Figure 3 ), and obtain the mineral content (Vi) and density (ρ i ), porosity (ф0), permeability (p) and longitudinal and transverse 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. Using the Voigt-Reuss-Hill model, the bulk modulus of the rock skeleton (K m0 ) and shear modulus (μ m0 ), rock skeleton and fluid density are calculated by multiplying the volume content of each component by the density of each component and then adding them together. In this example, the rock skeleton minerals include quartz, clay and calcite, among which the clay content accounts for the vast majority of the rock components, and the fluids filled in the pores are divided into bound water and movable fluids, among which the movable fluids include 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 ), and calculate the bulk modulus (K sat-k ) and shear modulus (μ sat-k ). Preferably, bound water pores are added to the rock skeleton, according to Kuster- (KT) The 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), and the bulk modulus of the rock skeleton containing bound water pores (K sat-k ) and shear modulus (μ sat-k ).

[0053] S3: Add 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 ) 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 ). Preferably, the bulk modulus (K sat-k ) and shear modulus (μ sat-k ) Bulk modulus of bound water (K b =2.65GPa), shear modulus (μ b =0 GPa), sphere radius (b=0.1), frequency (f=5000), permeability (p) and saturation (s), wherein the permeability and saturation of this embodiment are obtained from the well logging curve, the frequency is the well logging frequency, and the bulk modulus (K sat-p ) and shear modulus (μ sat-p ).

[0054] 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 (or defined as a soft pore dry rock skeleton), calculate the flexible pore ratio and the flexible porosity; wherein, the Eaton method is used to predict the formation pressure, and then the effective stress and pressure coefficient are obtained. In normal pressure formations, the flexible pore ratio is directly estimated by the mud content, and the flexible pore ratio gradually decreases with increasing depth. However, in overpressure formations, due to the increase in formation pore pressure, the trend of the flexible pore ratio decreasing gradually slows down. The present invention proposes formula (1), which makes the flexible pore ratio regulated by the overlying formation pressure, hydrostatic pressure, and effective stress at the same time, which is more in line with the actual underground situation.

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

[0056]

[0057] In formula (1), S is the proportion of flexible pores, A, B, C, and D are constants related to the actual formation. Pn is the difference between the overlying formation pressure and the hydrostatic pressure, and Pe is the effective formation stress.

[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 and Pore is the effective porosity, which are obtained from well logging interpretation.

[0061] Furthermore, the pore space stiffness theory is used to describe the compression resistance 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. Depending on the actual strata in the specific study area, it is usually described as a natural logarithm or a linear relationship. The present invention improves the pore space stiffness theory, and the improved bulk modulus and shear modulus are simultaneously regulated by the pressure coefficient and the effective stress. The bulk modulus and shear modulus of the rock after adding flexible pores are calculated respectively. The improved pore space stiffness theory calculates the bulk modulus (K) of the rock skeleton containing flexible pores. sat-s ) and shear modulus (μ sat-s ) as shown in formula (3) and formula (4).

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

[0063]

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

[0065] Furthermore, if Figure 4 As shown, the Eaton method is used to predict the formation pressure. The Eaton method constructs a normal compaction trend line based on the normal compaction theory, introduces a 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, in MPa; Po is the overburden pressure, in MPa; Ph is the hydrostatic pressure, in MPa; △t n is the acoustic time difference of normal compaction of the formation, in μs / m; △t is the measured acoustic time difference, in μs / m; Eaton parameter n is an empirical index related to the actual area, in this example n = 4.2. In formula (6), Pe is the effective stress, in MPa. In formula (7), Pc is the pressure coefficient.

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

[0071] S5: Add rigid pores to the rock skeleton containing flexible pores to obtain a dual-porosity rock skeleton (or define it as a porous dry rock skeleton); In step S5, the self-compatible (SCA) 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 h1 ), the bulk modulus and shear modulus of the rigid pores, and the bulk modulus (K sat-h ) and shear modulus (μ sat-h ). Furthermore, using the self-consistent (SCA) model, the rigid hole aspect ratio (ɑ h1 =0.5), rigid pore volume modulus (K h =0.001Gpa) and shear modulus (μh = 0Gpa), as well as the bulk modulus of the rock skeleton with flexible pores added (K sat-s ) and shear modulus (μ sat-s ). The bulk modulus (K) of the dual-porosity rock skeleton is calculated. sat-h ) and shear modulus (μ sat-h ).

[0072] S6: Add movable fluid to the dual-porosity rock skeleton to obtain a saturated fluid equivalent model; In step S6, the bulk modulus (K fl ), the bulk modulus (K fl ), shear modulus (μ fl ), obtain the equivalent model of the saturated fluid, and calculate the bulk modulus (K sat0 ) and shear modulus (μ sat0 ), and then obtain the longitudinal and transverse wave velocities, where the longitudinal and transverse wave velocities include the longitudinal wave velocity and the transverse wave velocity.

[0073] Add movable fluid to the rock skeleton containing flexible pores and rigid pores (double-porosity rock skeleton). After adding bound water, flexible pores and rigid pores, the bulk modulus (K fl ), shear modulus (μ fl = 0), where the bulk modulus of the movable fluid (K fl ) is the bulk modulus and saturation of the fluid filling the movable fluid pores. The bulk modulus of the rock after adding the movable fluid is calculated by Wood's formula (K sat0 ) and shear modulus (μ sat0 ).

[0074] S7: Determine the bulk modulus (K) of various minerals in the saturated fluid equivalent model. i ) and shear modulus (μ i ); In step S7, based on the initial bound water pore aspect ratio (α b1 ), rigid pore aspect ratio (α h1 ), adjusting the bulk modulus of different minerals (K 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 i ) and shear modulus (μ i ).

[0075] Furthermore, the bulk modulus of rock skeleton minerals (K i ) and shear modulus (μ i ). First, set the initial bound water pore aspect ratio (ɑ b1 ), rigid pore pore aspect ratio (ɑ h1 ), where the initial bound water pore aspect ratio ɑ is set according to the properties of the filler and pores. b=0.2, rigid pore aspect ratio ɑ h =0.5. Adjust the bulk modulus of different minerals (K i ), shear modulus (μ i ), according to the bulk modulus (K sat ) and shear modulus (μ sat ) Calculate the P-wave velocity and S-wave velocity so that the P-wave and S-wave velocity errors are less than the initial prediction error threshold T v1 In this example, the error threshold T v1 =0.1, and the appropriate bulk modulus and shear modulus of different minerals in the study area are determined as shown in Table 1:

[0076] Table 1 Input parameters related to minerals in the rock skeleton in the example

[0077]

[0078]

[0079] 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. In step S8, based on the bulk modulus (K i ), shear modulus (μ i ), using the intelligent optimization algorithm, set the maximum number of iterations (I) of the algorithm, and optimize the bound water pore aspect ratio (ɑ) in step S2 b ) and the rigid pore aspect ratio (α h ), and set the bound water pore aspect ratio (ɑ b ) The optimal range is ɑ bmin —ɑ bmax , rigid pore aspect ratio (α h ) The optimal range is ɑ hmin —ɑ hmax , so that the error between the P-wave velocity and the actual P-wave velocity calculated after the above steps S2 and S7 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 search 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 ), the iteration is stopped and the final calculated bulk modulus (K sat ) and shear modulus (μ sat ), and then calculate the P- and S-wave velocities.

[0080] Among them, the intelligent optimization algorithm is used to optimize and adjust the bound water pore aspect ratio and the rigid pore aspect ratio. Since the proportion of each type of pore varies greatly at different depths, the pore aspect ratio also changes with the change of the formation. The optimization algorithm is used to find the optimal value of the pore aspect ratio. The intelligent optimization algorithm of this example uses the particle swarm algorithm. Of course, the intelligent optimization algorithm can be selected according to actual needs. Furthermore, the intelligent optimization algorithm of this example uses the particle swarm algorithm, sets the maximum number of iterations of the algorithm (I=100), and optimizes the bound water pore aspect ratio (ɑ) in step S2. b ) and step S5 rigid pore aspect ratio (ɑ h ), and determine that the optimal range of bound water pore aspect ratio is ɑ bmin =0.01—ɑ bmax =0.4, the optimal range of rigid pore aspect ratio is ɑ hmin =0.01—ɑ hmax =0.9, and the above steps S2 to S7 are repeated to make the error between the predicted P-wave velocity and the actual P-wave velocity less than the error threshold T v2 (T v2 =0.01), if the error threshold T is not reached v2 , return to continue the optimization and iterate to the maximum number of times; if it is less than the error threshold T v2 (T v2 =0.01), the iteration stops and the final calculated bulk modulus (K sat ) and shear modulus (μ sat ), and then calculate the P-wave velocity, P-wave velocity ratio and Poisson's ratio. Figure 6 As shown in the figure, the error distribution between the P-wave velocity and the actual P-wave velocity is as follows: Figure 7 shown.

[0081] The rock physics modeling method for overpressured formations considering multiple porous media in the present application includes pore pressure prediction, flexible pore ratio calculation method, improved pore space stiffness theory, and a process for constructing a rock physics model for overpressured formations that simultaneously considers two pore aspect ratios using an intelligent optimization algorithm (such as a particle swarm optimization algorithm). The former is the basis for carrying out rock physics modeling for overpressured formations, and the latter can improve the accuracy of predicting P- and S-wave velocities using the rock physics model for overpressured formations.

[0082] It can be understood that the rock physics modeling method of overpressured formations considering multiple porous media of the present application, on the basis of predicting the formation pore pressure, adds the pores and modulus of bound water to the rock skeleton, and can calculate the content of flexible pores and rigid pores, and add fluids considering different pore conditions, thereby improving the accuracy and reliability of the model velocity prediction results.

[0083] The present invention also discloses a rock physics modeling system for overpressure formations taking into account multiple porous media, comprising: a memory and a processor;

[0084] The memory is used to store computer programs;

[0085] The processor is used to implement the rock physics modeling method of overpressure formation considering multiple porous media of the above embodiment when executing one or more programs stored in the memory.

[0086] The memory may be a computer readable signal medium or a computer readable memory or any combination of the two. The memory may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of memory may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 that operates signals (analog and / or digital) based on operating instructions.

[0087] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0088] It can be understood that the above embodiments only express the preferred implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the patent scope of the present invention. It should be pointed out that, for ordinary technicians in this field, without departing from the concept of the present invention, the above technical features can be freely combined, and several deformations and improvements can be made, which all belong to the protection scope of the present invention. Therefore, all equivalent changes and modifications made to the scope of the claims of the present invention should belong to the scope covered by the claims of the present invention.

Claims

1. A rock physics modeling method for overpressured formations considering multiple porous media, characterized in that: include: S1: Building rock skeleton; S2: adding irreducible water pores to the rock skeleton to obtain a rock skeleton containing irreducible water pores; 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; S4: first calculating the proportion of flexible pores and the flexible porosity, and then adding the flexible pores to the rock skeleton containing the bound water modulus to obtain a rock skeleton containing flexible pores; S5: adding rigid pores to the rock skeleton containing flexible pores to obtain a dual-porosity rock skeleton; S6: adding movable fluid to 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 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 method for rock physics modeling of overpressured formations considering multiple porous media according to claim 1, characterized in that: 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 ).

3. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 2, characterized in that: In step S2, according to The (KT) model adds bound water pores to the rock skeleton and sets the bound water pore aspect ratio (ɑ b0 ), and calculate the bulk modulus (K sat-k ) and shear modulus (μ sat-k ).

4. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 3, characterized in that: In step S3, the bulk modulus (K) of irreducible water is added to the rock skeleton containing irreducible water pores obtained in step S2 using the patchy 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 ).

5. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 4, characterized in that: In step S4, the flexible pore ratio is calculated according to formula (1): Wherein, in formula (1), S is the proportion of flexible pores, A, B, C, and D are constants related to the actual formation, Pn is the difference between the overlying formation pressure and the hydrostatic pressure, and Pe is the effective formation stress; 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). sat-s ) and shear modulus (μ sat-s ): Among them, A, B, and C in formula (3) and formula (4) are constants and are related to the actual formation.

6. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 5, characterized in that: In step S5, the self-compatible (SCA) 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 h1 ), the bulk modulus and shear modulus of the rigid pores, and the bulk modulus (K sat-h ) and shear modulus (μ sat-h ).

7. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 6, characterized in that: In step S6, the bulk modulus (K fl ), the bulk modulus (K fl ), shear modulus (μ fl ), obtain the saturated fluid equivalent model, and calculate the bulk modulus (K sat0 ) and shear modulus (μ sat0 ) and then obtain the longitudinal and transverse wave velocities.

8. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 7, characterized in that: In step S7, based on the initial bound water pore aspect ratio (α b1 ), rigid pore aspect ratio (α h1 ), adjusting the bulk modulus of different minerals (K 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 i ) and shear modulus (μ i ).

9. The method for rock physics modeling of overpressured formations considering multiple porous media according to claim 8, characterized in that: In step S8, based on the bulk modulus (K i ), shear modulus (μ i ), using the intelligent optimization algorithm, set the maximum number of iterations (I) of the algorithm, and optimize the bound water pore aspect ratio (ɑ) in step S2 b ) and the rigid pore aspect ratio (α h ), and set the bound water pore aspect ratio (ɑ b ) The optimal range is ɑ bmin —ɑ bmax , rigid pore aspect ratio (α h ) The optimal range is ɑ hmin —ɑ hmax , so that the error between the P-wave velocity and the actual P-wave velocity calculated after the above steps S2 and S5 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 ), the iteration is stopped and the final calculated bulk modulus (K sat ) and shear modulus (μ sat ), and then calculate the P- and S-wave velocities.

10. 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 used to implement the rock physics modeling method for overpressure formations considering multiple porous media as described in any one of claims 1 to 9 when executing one or more programs stored in the memory.

Images