Tight sandstone rock physical modeling method and related equipment
A multi-scale rock physics modeling method combining VRH, SCA, and BISQ models has solved the problem of characterizing multi-scale coupling effects in tight sandstone reservoirs, improved the reliability of seismic wave velocity and attenuation prediction, and supported reservoir prediction and parameter inversion.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SOUTHERN MARINE SCIENCE & ENGINEERING GUANGDONG LABORATORY (ZHANJIANG)
- Filing Date
- 2025-12-26
- Publication Date
- 2026-05-08
AI Technical Summary
Existing rock physics models are unable to simultaneously characterize the multi-scale coupling effects between the framework, pores, fractures, and fluids in tight sandstone reservoirs, resulting in insufficient accuracy of seismic data in reservoir prediction, hydrocarbon detection, and carbon sequestration monitoring.
A multi-scale rock physics modeling method was constructed by combining the VRH model, SCA model, and BISQ model. By acquiring core data, well logging data, and reservoir conditions, the bulk modulus and shear modulus of the dry skeleton were calculated. Combined with Biot theory and jet flow, a layered patch saturation model was established to predict P-wave and S-wave velocities.
This improves the reliability of seismic wave velocity and attenuation prediction, provides theoretical basis and computational support for seismic response analysis and rock physical parameter inversion of unconventional reservoirs, and enhances the accuracy of reservoir prediction.
Smart Images
Figure CN121995463A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of exploration rock geophysics technology, and in particular to a method and related equipment for rock physics modeling of tight sandstone. Background Technology
[0002] With the exploration and development of unconventional oil and gas, the complex pore and fracture structures of tight rocks pose a challenge to rock physics modeling and seismic prediction. Constructing rock physics models is crucial for predicting reservoir elastic parameters. The wave propagation characteristics of these reservoirs exhibit significant multi-scale dispersion and attenuation effects: at the microscale, poor pore connectivity leads to fluid exchange being primarily controlled by jet flow, manifested as high-frequency velocity dispersion and energy loss; at the mesoscale, fluid transport within the fracture-pore system induces additional dispersion and attenuation, altering wavefield response characteristics. Existing rock physics models are mostly based on single-fluid or single-scale assumptions, making it difficult to simultaneously characterize the multi-scale coupling effects between the framework, pores, fractures, and fluids. This results in discrepancies between the model-predicted P-wave and S-wave velocities and actual logging and experimental data, particularly pronounced in the high-frequency band. This deficiency severely restricts the accuracy of seismic data applications in reservoir prediction, hydrocarbon detection, and carbon sequestration monitoring.
[0003] Therefore, constructing a multi-scale rock physics modeling method that can comprehensively consider both macroscopic Biot flow and microscopic jet flow mechanisms to simulate the multi-band wave velocity dispersion and attenuation characteristics of tight sandstone reservoirs is of great significance for predicting reservoir elastic parameters. This method can reflect the wave propagation law under the complex pore structure inside the rock and also provides a more reliable theoretical basis for seismic attribute inversion. Summary of the Invention
[0004] The main objective of this application is to propose a rock physics modeling method and related equipment for tight sandstone, which can improve the reliability of predicting seismic wave velocity and attenuation, and provide theoretical basis and computational support for seismic response analysis and rock physics parameter inversion of unconventional reservoirs.
[0005] To achieve the above objectives, one aspect of this application proposes a method for rock physics modeling of tight sandstone, the method comprising: Acquire core data, well logging data, rock physical parameters, and reservoir conditions; rock physical parameters include mineral composition, porosity, and permeability; reservoir conditions include formation temperature and formation pressure. The bulk modulus and shear modulus of the dry skeleton of dense sandstone were calculated based on rock physical parameters using the VRH model. The static modulus of saturated rock was obtained by mixing the mixed fluid with the dry skeleton using the SCA model. The P-wave and S-wave velocities were obtained by calculating the static modulus of saturated rock using the BISQ model.
[0006] In some embodiments, acquiring core data, well logging data, rock physical parameters, and reservoir conditions includes: Acquire core data, well logging data, and rock physical parameters; Determine the fluid type and fluid physical parameters; Determine reservoir conditions; The fluid physical parameters include: fluid density, fluid viscosity, and fluid bulk modulus.
[0007] In some embodiments, the bulk modulus and shear modulus of the dry framework of tight sandstone are calculated based on rock physical parameters using the VRH model. The static modulus of the saturated rock is obtained by mixing the mixed fluid with the dry framework using the SCA model, including: By adding mineral components using the VRH model, the mineral components are mixed to obtain the volume fraction of the mineral components. Based on the mineral composition and volume fraction, the bulk modulus and shear modulus of the dry framework of the dense sandstone were calculated. The static modulus of saturated rock was obtained by mixing the fluid with the dry skeleton using the SCA model.
[0008] In some embodiments, the mineral components include quartz, calcite, and clay, etc.
[0009] In some embodiments, the static modulus of saturated rock is obtained by mixing the mixed fluid with the dry skeleton using an SCA model, including: The saturated rock bulk modulus and saturated rock shear modulus were obtained by mixing the mixed fluid with the dry skeleton using the SCA model. The skeletal bulk modulus and skeletal shear modulus of saturated rock are obtained by calculating them using the Gassmann equation based on the bulk modulus and shear modulus of saturated rock.
[0010] In some embodiments, the P-wave and S-wave velocities are calculated using the BISQ model based on the static modulus of saturated rock, including: The frequency-dependent bulk modulus and shear modulus of the solid matrix under the combined action of macroscopic Biot flow and microscopic jet flow were obtained by calculating the static modulus of saturated rock using the BISQ model. The frequency-dependent bulk modulus and frequency-dependent shear modulus of rock were obtained by calculating the solid matrix bulk modulus and solid matrix shear modulus using the SCA model. The frequency-dependent bulk modulus and shear modulus of the rock were calculated using the Gassmann equation based on the frequency-dependent rock bulk modulus and shear modulus, and the frequency-dependent skeleton bulk modulus and shear modulus were obtained. A layered patch saturation model was established. The frequency-dependent skeleton bulk modulus and frequency-dependent skeleton shear modulus were input into the layered patch saturation model to calculate the dispersion changes caused by mesoscopic wave mass flow, and the P-wave and S-wave velocities were obtained.
[0011] To achieve the above objectives, another aspect of this application provides a physical modeling apparatus for tight sandstone, the apparatus comprising: The relevant parameter acquisition module is used to acquire core data, well logging data, rock physical parameters, and reservoir conditions. Rock physical parameters include mineral composition, porosity, and permeability. Reservoir conditions include formation temperature and formation pressure. The static modulus establishment module is used to calculate the dry skeleton bulk modulus and dry skeleton shear modulus of dense sandstone based on rock physical parameters using the VRH model. The SCA model is used to mix the mixed fluid with the dry skeleton to obtain the static modulus of saturated rock. The coupled model calculation module calculates the P-wave and S-wave velocities based on the static modulus of saturated rock using the BISQ model.
[0012] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the methods described above.
[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.
[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the methods described above.
[0015] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for rock physics modeling of tight sandstone. This scheme acquires core data, well logging data, rock physics parameters, and reservoir conditions. The rock physics parameters include mineral composition, porosity, and permeability; the reservoir conditions include formation temperature and formation pressure. The bulk modulus and shear modulus of the dry skeleton of tight sandstone are calculated based on the rock physics parameters using the VRH model. The static modulus of saturated rock is obtained by mixing the mixed fluid with the dry skeleton using the SCA model. The P-wave and S-wave velocities are calculated based on the static modulus of saturated rock using the BISQ model. Combining Biot theory, jet flow, and layered patch saturation model, a multi-scale dispersion and attenuation model of tight sandstone reservoir is constructed based on the equivalent solid matrix modulus. This improves the reliability of predicting seismic wave velocity and attenuation, and provides theoretical basis and computational support for seismic response analysis and rock physics parameter inversion of unconventional reservoirs. Attached Figure Description
[0016] Figure 1 This is a flowchart of the physical modeling method for tight sandstone provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of the physical modeling device for dense sandstone provided in the embodiments of this application; Figure 3 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application; Detailed Implementation To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.
[0017] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”
[0018] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.
[0020] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.
[0021] 1) VRH model.
[0022] In related technologies, the VRH model, or Voigt-Reuss-Hill average model, is the arithmetic mean of the upper Voigt limit and the lower Reuss limit.
[0023] 2) SCA model.
[0024] In related technologies, the SCA model, or Sequential Convex Approximation model, is a self-compatible approximation model. The SCA model adds cracks and pores to solid inclusions by applying mathematical solutions to the deformation of the inclusions. However, the elastic interaction between the inclusions is approximated by replacing the background medium with an equivalent medium that is not yet known.
[0025] 3) Gassmann equation.
[0026] Among related technologies, the Gassmann equation is an important theoretical tool for the study of rock elasticity physics.
[0027] 4) BISQ model.
[0028] In related technologies, the BISQ model, or Biot-Squirt model, considers the flow effects of pore fluids at both macroscopic and microscopic scales, calculates the dispersion and attenuation characteristics of rocks, and finally obtains the longitudinal and transverse wave velocities as a function of frequency.
[0029] 5) Macro Biot flow.
[0030] In related technologies, when elastic waves propagate in unsaturated porous media, the pore fluid will undergo macroscopic Biot flow, microscopic jet flow, and mesoscopic flow due to the different pore fluids.
[0031] 6) Layered patch saturation model.
[0032] In related technologies, the layered patch saturation model is an isotropic model of periodically distributed layered fluid saturation. Adjacent layers are saturated with different fluids, which compress the rock during wave propagation, creating pressure gradients between layers that lead to attenuation and dispersion. Figure 1 This is an optional flowchart of the rock physics modeling method for tight sandstone provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S103.
[0033] Step S101: Obtain core data, well logging data, rock physical parameters, and reservoir conditions; rock physical parameters include mineral composition, porosity, and permeability; reservoir conditions include formation temperature and formation pressure. In some embodiments, core data, well logging data, and rock physical parameters are acquired; fluid type and fluid physical parameters are determined; reservoir conditions are determined; wherein, fluid physical parameters include: fluid density, fluid viscosity, and fluid bulk modulus. Data is prepared and parameters are input; core data and well logging data of tight sandstone are collected to obtain mineral composition, porosity, permeability, and formation temperature and pressure. In the absence of well data, geological data and literature from analogous areas can be used as alternative inputs. The fluid type and its physical properties are determined, specifically the density, viscosity, and bulk modulus of the free fluid. This provides data support for subsequent model building and calculations.
[0034] Step S102: The bulk modulus and shear modulus of the dry skeleton of the dense sandstone are calculated based on the rock physical parameters using the VRH model. The static modulus of the saturated rock is obtained by mixing the mixed fluid with the dry skeleton using the SCA model.
[0035] In some embodiments, mineral components are added using a VRH model, and the mineral components are mixed to obtain their volume fractions. Based on the mineral components and volume fractions, the dry framework bulk modulus and dry framework shear modulus of the dense sandstone are calculated. The mixed fluid is then mixed with the dry framework using an SCA model to obtain the static modulus of the saturated rock. Using the VRH model, based on the mineral components (such as quartz, calcite, and clay) and their volume fractions of the dense sandstone, the equivalent elastic modulus of the rock can be estimated using VRH averaging, given the rock's composition and pore space. Here, minerals are added to the VRH model, mixing various minerals such as quartz, calcite, and clay to estimate the background matrix modulus of the rock. and .
[0036] The upper limit of the Voigt of the equivalent elastic modulus of N components yes:
[0037] Reuss lower bound of equivalent elastic modulus yes:
[0038] in, Let i be the volume component of the i-th medium. Let be the elastic modulus of the i-th medium.
[0039]
[0040]
[0041] In the formula, Let the bulk modulus of the i-th mineral be... Let be the skeletal shear modulus of the i-th mineral.
[0042] In some embodiments, the mineral components include quartz, calcite, and clay, etc.
[0043] In some embodiments, the mixed fluid is mixed with the dry rock skeleton using the SCA model to obtain the saturated rock bulk modulus and saturated rock shear modulus; the skeleton bulk modulus and skeleton shear modulus of the saturated rock are then calculated using the Gassmann equation based on the saturated rock bulk modulus and saturated rock shear modulus. The static elastic modulus of the saturated rock is obtained by mixing the pore fluid with the equivalent modulus with the dry rock skeleton using a self-compatible approximation model.
[0044] Here, Wu is used to estimate the self-compatibility modulus of the two-phase mixture:
[0045]
[0046] In the formula, i refers to the i-th material. and Let these be the bulk modulus and shear modulus of the I-th inclusion, respectively. It refers to its volume content, while P and Q are geometric factors, and the superscripts of P and Q are... Therefore, the geometric factor is for those with self-consistent equivalent moduli. and The inclusion material i in the background medium.
[0047] By incorporating pores and fractures containing different saturated fluids into the rock matrix using the SCA model, the bulk modulus of the saturated rock was obtained. and shear modulus .
[0048] Then, the Gassmann equation is used to remove the matrix, and the bulk modulus of the rock skeleton is calculated in reverse. and skeleton shear modulus .
[0049]
[0050]
[0051] In the formula, Expressed as total porosity; It is expressed as the bulk modulus of the fluid contained within.
[0052] Step S103: The P-wave and S-wave velocities are obtained by calculating the static modulus of saturated rock using the BISQ model.
[0053] In some embodiments, the frequency-dependent solid matrix bulk modulus and solid matrix shear modulus under the combined action of macroscopic Biot flow and microscopic jet flow are calculated using the BISQ model based on the static modulus of saturated rock. The frequency-dependent rock bulk modulus and frequency-dependent rock shear modulus are calculated using the SCA model based on the solid matrix bulk modulus and solid matrix shear modulus. The frequency-dependent skeleton bulk modulus and frequency-dependent skeleton shear modulus are calculated using the Gassmann equation based on the frequency-dependent rock bulk modulus and frequency-dependent rock shear modulus. A layered patch saturation model is established, and the frequency-dependent skeleton bulk modulus and frequency-dependent skeleton shear modulus are input into the layered patch saturation model to calculate the dispersion changes caused by mesoscopic wave mass flow, obtaining the P-wave and S-wave velocities. Using the results of the static model as input, a unified Biot-Squirt (BISQ) model is used to simultaneously consider the flow effects of pore fluid at both macroscopic and microscopic scales to calculate the dispersion and attenuation characteristics of the rock, ultimately obtaining the P-wave and S-wave velocities as a function of frequency.
[0054] The differences between the frequency-dependent modulus, dynamic solid modulus, and static solid modulus under the two theories were calculated using the corresponding effective medium models. The variables under the two theories relative to the low-frequency case were obtained. , , , They are calculated in similar ways.
[0055]
[0056]
[0057] Finally, the frequency-dependent bulk modulus of the solid matrix under the combined effects of Biot and the jet was calculated. and shear modulus .
[0058]
[0059]
[0060] The SCA model was used again to incorporate fractures and pores into the frequency-dependent equivalent solid matrix modulus, yielding the frequency-dependent bulk modulus of the rock. and shear modulus Then, the frequency-dependent bulk modulus of the skeleton was calculated using the Gassmann equation. and shear modulus .
[0061] Establish a layered patch saturation model and use frequency-dependent skeletal bulk modulus. and shear modulus Substituting the skeletal modulus as the model of the layered patch saturation, the dispersion variation caused by the mesoscopic wave mass flow is calculated.
[0062] The layered patch saturation model is an isotropic model of periodically distributed layered fluid saturation. Different fluids are saturated between adjacent layers, which compress the rock during wave propagation and generate pressure gradients between layers, leading to attenuation and dispersion.
[0063] Then the P-wave phase velocity The expression for the quality factor Q is:
[0064]
[0065] Among them, the complex P-wave modulus The summation velocity is:
[0066]
[0067] plural real numbers and parameters Defined as:
[0068]
[0069]
[0070] In the formula, and These represent the thickness of each layer, and .
[0071] Steps S101 to S103 of the embodiments of this application involve acquiring core data, well logging data, rock physical parameters, and reservoir conditions. Rock physical parameters include mineral composition, porosity, and permeability. Reservoir conditions include formation temperature and formation pressure. The bulk modulus and shear modulus of the dry framework of tight sandstone are calculated using the VRH model based on the rock physical parameters. The static modulus of the saturated rock is obtained by mixing the mixed fluid with the dry framework using the SCA model. The P-wave and S-wave velocities are calculated using the BISQ model based on the static modulus of the saturated rock. Combining Biot theory, jet flow, and the layered patch saturation model, a multi-scale dispersion and attenuation model of tight sandstone reservoirs is constructed based on the equivalent solid matrix modulus. This improves the reliability of predicting seismic wave velocity and attenuation, providing theoretical basis and computational support for seismic response analysis and rock physical parameter inversion of unconventional reservoirs.
[0072] Please see Figure 2 This application also provides a physical modeling device 200 for dense sandstone, which can implement the above-described method. The device includes: The relevant parameter acquisition module 201 is used to acquire core data, well logging data, rock physical parameters, and reservoir conditions; rock physical parameters include mineral composition, porosity, and permeability; reservoir conditions include formation temperature and formation pressure. The static modulus establishment module 202 is used to calculate the dry skeleton bulk modulus and dry skeleton shear modulus of dense sandstone based on rock physical parameters using the VRH model, and to mix the mixed fluid with the dry skeleton using the SCA model to obtain the static modulus of saturated rock. The coupled model calculation module 203 is used to calculate the P-wave and S-wave velocities based on the static modulus of saturated rock using the BISQ model.
[0073] In one embodiment, the relevant parameter acquisition module 201 is further used to acquire core data, well logging data, and rock physical parameters; determine the fluid type and fluid physical parameters; and determine reservoir conditions; wherein the fluid physical parameters include: fluid density, fluid viscosity, and fluid bulk modulus.
[0074] In one embodiment, the static modulus establishment module 201 further includes: The mineral mixing submodule is used to add mineral components through the VRH model, mix the mineral components, and obtain the volume fraction of the mineral components. The modulus calculation submodule is used to calculate the dry skeleton bulk modulus and dry skeleton shear modulus of dense sandstone based on mineral composition and volume fraction. The modulus establishment submodule is used to mix the mixed fluid with the dry skeleton using the SCA model to obtain the static modulus of saturated rock.
[0075] In one embodiment, the mineral components include quartz, calcite, and clay, etc.
[0076] In one embodiment, the modulus establishment submodule is also used to mix the mixed fluid with the dry skeleton using the SCA model to obtain the saturated rock bulk modulus and saturated rock shear modulus; and to calculate the saturated rock skeleton bulk modulus and skeleton shear modulus based on the saturated rock bulk modulus and saturated rock shear modulus using the Gassmann equation.
[0077] In one embodiment, the coupled model calculation module 203 is further configured to calculate, based on the static modulus of saturated rock using the BISQ model, the frequency-dependent solid matrix bulk modulus and solid matrix shear modulus under the combined action of macroscopic Biot flow and microscopic jet flow; calculate, based on the solid matrix bulk modulus and solid matrix shear modulus using the SCA model, the frequency-dependent rock bulk modulus and frequency-dependent rock shear modulus; calculate, based on the frequency-dependent rock bulk modulus and frequency-dependent rock shear modulus using the Gassmann equation, the frequency-dependent skeleton bulk modulus and frequency-dependent skeleton shear modulus; establish a layered patch saturation model, input the frequency-dependent skeleton bulk modulus and frequency-dependent skeleton shear modulus into the layered patch saturation model to calculate the dispersion changes caused by mesoscopic wave mass flow, and obtain the P-wave and S-wave velocities.
[0078] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0079] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.
[0080] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0081] Please see Figure 3 , Figure 3 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 301 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 302 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 302 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 302 and is called and executed by the processor 301 using the methods described above in the embodiments of this application. Input / output interface 303 is used to implement information input and output; The communication interface 304 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 305 transmits information between various components of the device (e.g., processor 301, memory 302, input / output interface 303, and communication interface 304); The processor 301, memory 302, input / output interface 303, and communication interface 304 are connected to each other within the device via bus 305.
[0082] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.
[0083] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.
[0084] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.
[0085] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0086] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
[0087] The tight sandstone rock physics modeling method, apparatus, electronic equipment, storage medium, and program product provided in this application acquire core data, well logging data, rock physics parameters, and reservoir conditions. Rock physics parameters include mineral composition, porosity, and permeability; reservoir conditions include formation temperature and formation pressure. The VRH model calculates the dry skeleton bulk modulus and dry skeleton shear modulus of the tight sandstone based on the rock physics parameters. The SCA model mixes the fluid with the dry skeleton to obtain the static modulus of the saturated rock. The BISQ model calculates the P-wave and S-wave velocities based on the static modulus of the saturated rock, improving the reliability of predicted seismic wave velocities and attenuation. This provides a theoretical basis and computational support for seismic response analysis and rock physics parameter inversion in unconventional reservoirs.
[0088] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.
[0089] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.
[0090] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.
[0091] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.
[0092] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0093] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.
[0094] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0095] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0096] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0097] If the integrated unit is implemented as 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 technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0098] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.
Claims
1. A method for physical modeling dense sandstone, characterized in that, The method includes the following steps: Acquire core data, well logging data, rock physical parameters, and reservoir conditions; the rock physical parameters include mineral composition, porosity, and permeability; the reservoir conditions include formation temperature and formation pressure. The bulk modulus and shear modulus of the dry skeleton of the dense sandstone were calculated using the VRH model based on the physical parameters of the rock. The static modulus of the saturated rock was obtained by mixing the mixed fluid with the dry skeleton using the SCA model. The P-wave and S-wave velocities were calculated using the BISQ model based on the static modulus of the saturated rock.
2. The method for physical modeling of dense sandstone according to claim 1, characterized in that, The acquisition of core data, well logging data, rock physical parameters, and reservoir conditions includes: Acquire the core data, the well logging data, and the rock physical parameters; Determine the fluid type and fluid physical parameters; Determine the reservoir conditions; The fluid physical parameters include: fluid density, fluid viscosity, and fluid bulk modulus.
3. The method for physical modeling of dense sandstone according to claim 1, characterized in that, The bulk modulus and shear modulus of the dry framework of the tight sandstone are calculated using the VRH model based on the rock physical parameters. The static modulus of the saturated rock is obtained by mixing the fluid with the dry framework using the SCA model, including: The mineral components are added using the VRH model, and the mineral components are mixed to obtain the volume fraction of the mineral components. The bulk modulus and shear modulus of the dry framework of the dense sandstone are calculated based on the mineral composition and the volume fraction. The static modulus of the saturated rock is obtained by mixing the fluid with the dry skeleton using the SCA model.
4. The method for physical modeling of dense sandstone according to claim 3, characterized in that, The mineral components include quartz, calcite, and clay, etc.
5. The method for physical modeling of dense sandstone according to claim 3, characterized in that, The step of mixing the mixed fluid with the dry skeleton using the SCA model to obtain the static modulus of the saturated rock includes: The saturated rock bulk modulus and saturated rock shear modulus were obtained by mixing the fluid with the dry skeleton using the SCA model. The skeletal bulk modulus and skeletal shear modulus of the saturated rock are obtained by calculating them using the Gassmann equation based on the bulk modulus and shear modulus of the saturated rock.
6. The method for physical modeling of tight sandstone according to claim 1, characterized in that, The calculation of P-wave and S-wave velocities based on the static modulus of the saturated rock using the BISQ model includes: The frequency-dependent solid matrix bulk modulus and solid matrix shear modulus under the combined action of macroscopic Biot flow and microscopic jet flow were obtained by calculating the static modulus of the saturated rock using the BISQ model. The frequency-dependent bulk modulus and frequency-dependent shear modulus of the rock are obtained by calculating the solid matrix bulk modulus and the solid matrix shear modulus using the SCA model. The frequency-related skeleton bulk modulus and frequency-related skeleton shear modulus are obtained by calculating based on the frequency-related rock bulk modulus and the frequency-related rock shear modulus using the Gassmann equation. A layered patch saturation model is established. The frequency-related skeleton bulk modulus and the frequency-related skeleton shear modulus are input into the layered patch saturation model to calculate the dispersion change caused by mesoscopic wave mass flow, and the P-wave and S-wave velocities are obtained.
7. A physical modeling device for dense sandstone, characterized in that, The device includes: The relevant parameter acquisition module is used to acquire core data, well logging data, rock physical parameters, and reservoir conditions; the rock physical parameters include mineral composition, porosity, and permeability; the reservoir conditions include formation temperature and formation pressure. The static modulus establishment module is used to calculate the dry skeleton bulk modulus and dry skeleton shear modulus of dense sandstone based on the rock physical parameters using the VRH model, and to obtain the static modulus of saturated rock by mixing the mixed fluid with the dry skeleton using the SCA model. The coupled model calculation module is used to calculate the P-wave and S-wave velocities based on the static modulus of the saturated rock using the BISQ model.
8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 6.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.