Elastic parameter prediction method and device considering low-frequency experiment boundary condition

Abstract

The application relates to an elastic parameter prediction method and device considering low-frequency experiment boundary conditions, wherein the method comprises the following steps: acquiring pipeline fluid volume information of a low-frequency device; obtaining corresponding elastic parameters through the pipeline fluid volume information based on a preset elastic parameter model, wherein the preset elastic parameter model is constructed based on low-frequency experiment boundary conditions; thus, in the low-frequency experiment, by inputting the pipeline fluid volume information into the preset elastic parameter model constructed based on the boundary conditions, the boundary conditions can be fully considered, and the elastic parameters under the influence of the boundary conditions can be effectively predicted, thereby providing more accurate and powerful support for subsequent lithology differentiation and oil and gas exploration using seismic information.

Description

Technical Field

[0001] This invention belongs to the field of applied geophysical seismic exploration, and particularly relates to a method and apparatus for predicting elastic parameters considering low-frequency experimental boundary conditions. Background Technology

[0002] Low-frequency experimental methods offer numerous advantages in measuring the mechanical properties of rocks (Mikhaltsevitch et al., 2014). These methods are primarily based on forced vibration, and low-frequency equipment has been widely used in laboratories in recent years (Subramaniyan et al., 2014). Under confining pressure oscillation, this method measures the stress-strain relationship of the sample and calculates elastic parameters based on their correlation. One of the key techniques in low-frequency experiments is the accurate interpretation of data, where the boundary conditions of the saturated sample have a crucial impact on the measurement results. Dunn (1986) and White (1986) demonstrated that using forced vibration on rock samples with open boundary conditions leads to radial fluid motion, causing dispersion and attenuation of the elastic modulus. Pimienta et al. (2016) showed that the connection between the fluid conduit and the sample has a significant impact on obtaining modulus parameters for saturated fluid samples. This is because the location of the conduit section, which cannot be separated from the sample by the nearest valve, forms a fluid reservoir space, also known as the "dead volume," directly connected to the pore space of the sample. Considering that Gassmann theory (Gassmann, 1951) is primarily used to verify the validity of experimental data measured from saturated fluid samples, the aforementioned studies, while identifying the influence of boundary conditions in low-frequency experiments, failed to quantify it accurately using mathematical formulas. Therefore, to address the impact of "residual fluid volume" on the elastic parameters obtained from saturated fluid samples, a direct and effective quantitative analysis of the relationship between "residual fluid volume" and the elastic parameters of saturated fluid samples is needed. Summary of the Invention

[0003] Based on this, it is necessary to provide a method and apparatus for predicting elastic parameters that takes into account low-frequency experimental boundary conditions to address the above-mentioned technical problems. This method can fully consider the boundary conditions and effectively and quantitatively analyze the relationship between the "remaining fluid capacity volume" and the elastic parameters of the saturated fluid sample. In other words, it can effectively predict the elastic parameters affected by boundary conditions, providing more accurate and powerful support for the subsequent use of seismic information to distinguish lithology and detect oil and gas.

[0004] The first aspect of this invention provides a method for predicting elastic parameters considering low-frequency experimental boundary conditions, the method comprising:

[0005] Obtain fluid volume information in pipelines used by low-frequency equipment;

[0006] Based on a preset elastic parameter model, the corresponding elastic parameters are obtained through the fluid volume information in the pipeline. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions.

[0007] Optionally, the construction of the preset elasticity parameter model includes:

[0008] The relative change in sample volume under boundary conditions is obtained, wherein the boundary conditions include: the sample being in a sealed boundary and the sample being in an open boundary, and the relative change in sample volume is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0009] Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

[0010] Optionally, when the sample is in a sealed state, the relative change in sample volume under boundary conditions is obtained, including:

[0011] The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

[0012] Optionally, the volume change of the fluid is the sum of the pore fluid volume change and the pipe fluid volume change. Specifically, the volume change of the fluid is characterized as follows:

[0013]

[0014] Changes in the volume of the experimental rock sample skeleton:

[0015] ΔV s =ΔV s1 +ΔV s2

[0016] in,

[0017]

[0018]

[0019] ΔV s2 =-VΔP s / K s

[0020] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV sIt is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0021] Optionally, the relative change in sample volume when the sample is in a sealed state is characterized as follows:

[0022]

[0023] Optionally, the boundary condition is: when the sample is in an open state, the relative change in sample volume includes:

[0024]

[0025] Among them, K d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0026] Optionally, the preset elastic parameter model is characterized as follows:

[0027]

[0028] A second aspect of the present invention provides an elastic parameter prediction device considering low-frequency experimental boundary conditions, the device comprising:

[0029] The fluid pipeline volume acquisition module is used to acquire fluid volume information for pipelines used in low-frequency equipment.

[0030] The elastic parameter module is used to obtain the corresponding elastic parameters based on the fluid volume information in the pipeline, according to a preset elastic parameter model. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions.

[0031] Optionally, the construction of the preset elasticity parameter model includes:

[0032] The sample volume relative change module is used to obtain the sample volume relative change under boundary conditions, wherein the boundary conditions include: the sample is in a sealed boundary and the sample is in an open boundary, and the sample volume relative change is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0033] The construction module is used to construct the preset elastic parameter model based on the total pressure experienced by the sample and the volume change modulus of the saturated fluid, through the relative change of the sample volume.

[0034] Optionally, when the sample is in a sealed state, the module for monitoring the relative change in sample volume is specifically used for:

[0035] The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

[0036] Optionally, the volume change of the fluid is the sum of the pore fluid volume change and the pipe fluid volume change. Specifically, the volume change of the fluid is characterized as follows:

[0037]

[0038] Changes in the volume of the experimental rock sample skeleton:

[0039] ΔV s =ΔV s1 +ΔV s2

[0040] in,

[0041]

[0042]

[0043] ΔV s2 =-VΔP s / K s

[0044] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0045] Optionally, the relative change in sample volume when the sample is in a sealed state is characterized as follows:

[0046]

[0047] Optionally, when the sample is in an open state, the relative change in sample volume includes:

[0048]

[0049] Among them, K dIt is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0050] Optionally, the preset elastic parameter model is characterized as follows:

[0051]

[0052] A third aspect of the present invention provides a terminal device, including a processor and a memory; the memory is used to store computer instructions, and the processor is used to execute the computer instructions stored in the memory to implement the above-described method for predicting elastic parameters considering low-frequency experimental boundary conditions.

[0053] A fourth aspect of the present invention provides a computer-readable storage medium storing one or more programs that can be executed by one or more processors to implement the above-described method for predicting elastic parameters considering low-frequency experimental boundary conditions.

[0054] The beneficial effects of this invention are as follows: In low-frequency experiments, by inputting the fluid volume information of the pipeline into the preset elastic parameter model based on boundary conditions, the boundary conditions can be fully considered, the elastic parameters affected by the boundary conditions can be effectively predicted, and the relationship between the "remaining fluid capacity volume" and the elastic parameters of the saturated fluid sample can be effectively and quantitatively analyzed, providing more accurate and powerful support for the subsequent use of seismic information to distinguish lithology and detect oil and gas. Attached Figure Description

[0055] Figure 1 This is a flowchart (I) of an elastic parameter prediction method considering low-frequency experimental boundary conditions in one embodiment;

[0056] Figure 2 This is a schematic diagram (II) of an elastic parameter prediction method considering low-frequency experimental boundary conditions in one embodiment;

[0057] Figure 3 This is a low-frequency device using the forced oscillation method applied in another embodiment;

[0058] Figure 4 This is a comparison diagram of elastic parameters before and after the experiment in another embodiment;

[0059] Figure 5 This is a structural block diagram of an elastic parameter prediction device that considers low-frequency experimental boundary conditions in another embodiment.

[0060] Figure 6 This is an internal structural diagram of the terminal device in another embodiment. Detailed Implementation

[0061] 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 and not intended to limit the scope of this application.

[0062] Figure 1 This is a flowchart (I) of an elastic parameter prediction method considering low-frequency experimental boundary conditions in one embodiment; Figure 2 This is a schematic diagram (II) of an elastic parameter prediction method considering low-frequency experimental boundary conditions in one embodiment; Figure 3 This is a low-frequency device using the forced oscillation method applied in another embodiment; Figure 4 This is a comparison diagram of elastic parameters before and after the experiment in another embodiment; Figure 5 This is a structural block diagram of an elastic parameter prediction device that considers low-frequency experimental boundary conditions in another embodiment. Figure 6 This is an internal structural diagram of the terminal device in another embodiment.

[0063] Example 1:

[0064] according to Figures 1 to 4 As can be seen, the elastic parameter prediction method considering low-frequency experimental boundary conditions provided in this embodiment is mainly used to address the problem of the influence of boundary effects on the measurement results of elastic parameters of saturated samples in low-frequency experimental measurements. In order to obtain more accurate data in experimental measurements, it is necessary to consider the influence of some factors in the experimental measurement process. Among them, boundary conditions have a significant impact on experimental data, which will affect the comparison and analysis with actual seismic data.

[0065] Specifically, the method includes:

[0066] S101: Obtain fluid volume information for pipelines used in low-frequency equipment;

[0067] Specifically, the low-frequency device is the equipment used for conducting low-frequency experiments, including but not limited to, such as Figure 3 The equipment shown includes, for example, pressure gantry, hydraulically driven pressure unit, piezoelectric actuator, and core holder.

[0068] Furthermore, the dimensional information of the fluid pipe involved in step S101 is not limited in this embodiment, and it includes, but is not limited to, one or more of the following: the dimensional information of the fluid pipe or the volume of saturated fluid in the fluid pipe; in addition, the dimensional information involved is not limited here, as long as the dimensional information can be used to calculate the volume of saturated fluid in the fluid pipe. For example: the length of the fluid pipe, the length of the flow channel in the fluid pipe, the cross-sectional area of ​​the flow channel in the fluid pipe, or the volume of fluid flowing through the fluid pipe per unit time.

[0069] In addition, Figure 3 The "remaining fluid capacity volume" refers to the "volume of saturated fluid in the fluid pipe". Furthermore, in this embodiment, the number and layout of the fluid pipes are not limited.

[0070] In another embodiment, Figure 3 In this process, the fluid conduit connects the sample and the pore space of the sample.

[0071] S102: Based on a preset elastic parameter model, obtain the corresponding elastic parameters through the fluid volume information in the pipeline;

[0072] The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions.

[0073] It is worth noting that this embodiment does not limit the preset elastic parameter model, as long as it can fully consider the boundary conditions based on the pipeline fluid volume information and effectively predict the elastic parameters affected by the boundary conditions, so as to provide more accurate and powerful support for the subsequent use of seismic information to distinguish lithology and detect oil and gas.

[0074] For example: the preset elasticity parameter model is an improved Gassmann model, such as:

[0075]

[0076] Among them, K sat K represents the bulk modulus of a fluid-saturated sample. d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of solid skeleton volume caused by fluid pressure. It is the porosity of the rock, K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0077] Therefore, in this embodiment, in the low-frequency experiment, by inputting the pipeline fluid volume information into the preset elastic parameter model based on boundary conditions, the boundary conditions can be fully considered, and the elastic parameters affected by the boundary conditions can be effectively predicted, providing more accurate and powerful support for the subsequent use of seismic information to distinguish lithology and detect oil and gas.

[0078] Example 2:

[0079] Based on the study of the influence of residual fluid volume on elastic parameters during the experimental measurement process, it was found that the experimental sample could not be completely sealed because the fluid pipes connected to the pore space of the sample; and these fluid pipes formed fluid storage space, which affected the results of the elastic parameters of the saturated fluid sample.

[0080] Therefore, in this embodiment, the Gassmann model is improved based on the influence of the fluid pipeline on the elastic parameters of the saturated fluid sample, so as to effectively predict the elastic parameters under the influence of boundary conditions based on the improved Gassmann model (preset elastic parameter model).

[0081] Specifically, according to Figures 1 to 4 As can be seen, for the preset elastic parameter model, this embodiment provides a method for constructing the preset elastic parameters, which includes:

[0082] S201: Obtain the relative change in sample volume under boundary conditions;

[0083] The boundary conditions include: the sample being in a sealed boundary (i.e., undrained boundary conditions) and the sample being in an open boundary (drained boundary conditions). Moreover, the relative change in sample volume is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0084] Specifically, one implementation of step S201 includes:

[0085] Step S2011: Obtain the volume change of the fluid and the volume change of the experimental rock sample skeleton when the sample is sealed at the boundary during the low-frequency experiment, and obtain the relative volume change of the sample when the sample is sealed at the boundary based on the two.

[0086] It is worth noting that when the sample is under boundary-sealed conditions (without drainage), changes in fluid pressure alter the volumes of the solid skeleton and the fluid, while changes in skeleton stress change the solid volume. However, during experimental measurements, the saturated fluid sample cannot be completely sealed; fluid channels exist at both ends of the sample, connecting the pore spaces. The space formed by these fluid channels is called the fluid channel volume ("residual fluid capacity volume") (see...). Figure 3 and 4This paper, based on the original Gassmann model, takes into account the influence of fluid pipe volume.

[0087] Specifically, the volume change of the fluid is the sum of the volume changes of the pore fluid and the volume changes of the pipe fluid, and the volume change of the fluid is characterized as follows:

[0088]

[0089] Changes in the volume of the experimental rock sample skeleton:

[0090] ΔV s =ΔV s1 +ΔV s2 (2)

[0091] in,

[0092]

[0093]

[0094] ΔV s2 =-VΔP s / K s (5)

[0095] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0096] Based on (1)-(5) above, the relative change in sample volume when the sample is under boundary sealing can be characterized as follows:

[0097]

[0098] Step S2012: When the sample is in an open state (drainage boundary condition), the change in fluid pressure alters the solid skeleton, and the fluid itself is discharged under stress, without any change in fluid volume. The change in skeleton stress alters the change in solid volume. Therefore, the relative change in sample volume can be expressed as:

[0099]

[0100] Among them, Kd It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0101] S202: Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

[0102] The total pressure ΔP experienced by the experimental sample is expressed as:

[0103] ΔP=ΔP s +ΔP f (8)

[0104] Where, ΔP s It is the stress on the sample skeleton (skeleton stress), ΔP f It is the fluid pressure, that is, the total pressure is equal to the sum of the skeleton stress and the fluid pressure.

[0105] The bulk modulus of a fluid-saturated sample is expressed as:

[0106] K sat = -VΔP / ΔV (9)

[0107] Among them, K sat This represents the bulk modulus of the fluid-saturated sample.

[0108] Therefore, in step S202, according to the above (6)-(9), the preset elastic parameter model can be characterized as follows:

[0109]

[0110] Equation (10) is an improved Gassmann model based on the Gassmann equation (Gassmann, 1951), taking into account the influence of fluid pipe volume. When V D →0, equation (10) can degenerate into the standard Gassmann equation, i.e., the saturated sample is under undrained boundary conditions; when V D →∞, the saturated sample is under the boundary condition of drainage.

[0111] This embodiment shows good consistency with the elastic parameters measured in the low-frequency experiment of saturated samples affected by boundary effects, which greatly improves the accuracy of elastic parameter measurement. It can directly and effectively analyze the relationship between the remaining fluid volume and the elastic parameters of saturated fluid samples, providing more accurate and powerful support for subsequent use of seismic information to distinguish lithology and detect oil and gas.

[0112] Example 3:

[0113] according to Figure 2 - Figure 4 As can be seen, the purpose of this invention is to provide a method for constructing a preset elastic parameter model. This method involves studying the influence of the remaining fluid volume on the elastic parameters during experimental measurements. Because the fluid pipes connect to the pore space of the sample, the experimental sample cannot be completely sealed. These fluid pipes form fluid storage spaces, affecting the elastic parameter results of the saturated fluid sample.

[0114] Based on the influence of fluid conduits on the elastic parameters of saturated fluid samples, the Gassmann model is improved to effectively predict the elastic parameters under the influence of boundary conditions.

[0115] The method for predicting elastic parameters considering sample boundary effects in low-frequency measurements is characterized in that the total pressure ΔP experienced by the experimental sample is expressed as...

[0116] ΔP=ΔP s +ΔP f (1)

[0117] Where, ΔP s It is the stress on the sample skeleton (skeleton stress), ΔP f It is fluid pressure, that is, the total pressure is equal to the sum of the skeleton stress and the fluid pressure;

[0118] When the sample is under boundary-sealed conditions (without drainage), changes in fluid pressure alter the volumes of the solid skeleton and the fluid, while changes in skeleton stress change the solid volume. During experimental measurements, the saturated fluid sample cannot be completely sealed; fluid conduits connect the pore spaces of the sample at both ends. The space formed by these fluid conduits is called the fluid conduit volume ("residual fluid capacity volume") (see...). Figure 2 and 3 Based on the original Gassmann model, the fluid pipe volume V is considered. D The effect of this means that the volume change of the fluid becomes the sum of the volume changes of the pore fluid and the volume changes of the pipe fluid:

[0119]

[0120] ΔV s =ΔV s1 +ΔV s2 (3)

[0121] in,

[0122]

[0123]

[0124] ΔV s2 =-VΔP s / K s (6)

[0125] In equations (3)-(6), ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s This is the bulk modulus of the solid framework. Therefore, the relative change in sample volume can be expressed as:

[0126]

[0127] When the sample is in an open state (drainage boundary condition), changes in fluid pressure alter the solid skeleton, and the fluid itself, under stress, is expelled without changing its volume. Changes in skeleton stress alter the solid volume. Therefore, the relative change in sample volume can be expressed as:

[0128]

[0129] Among them, K d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0130] The bulk modulus of a fluid-saturated sample is expressed as:

[0131] K sat = -VΔP / ΔV, (9)

[0132] Combining equations (1), (7), and (8), we get:

[0133]

[0134] Equation (10) is an improved version of the Gassmann equation (Gassmann, 1951) that takes into account the influence of fluid pipe volume. When V D →0, equation (10) can degenerate into the standard Gassmann equation, i.e., the saturated sample is under undrained boundary conditions; when V D →∞, the saturated sample is under the boundary condition of drainage.

[0135] A comparison between specific core measurement data and prediction results illustrates the following:

[0136] In the low-frequency experiment, the Savonnieres limestone sample was subjected to forced oscillation. The sample had a density of 1920 kg / m³, a porosity of 29%, a permeability of 450 mD, and n-decane as the pore fluid. The confining pressure was set to 10 MPa, and the pore pressure was 3 MPa. In the experiment, the residual fluid volume varied from 2 ml to 260 ml. The corresponding elastic parameters were obtained using the modified Gassmann formula.

[0137] Figure 4 This is a comparison chart of the improved Gassmann model and experimental data. Solid framework modulus K. s = 76.8 GPa (Simmons and Wang, 1971) and fluid volume K f =0.86 GPa (White, 1986). Figure 4 The measured bulk modulus is in good agreement with the results predicted by the improved Gassmann model.

[0138] The above specific embodiments are specific support for the technical idea of ​​the prediction method of elastic parameters considering sample boundary effects in low-frequency experimental measurement proposed by the present invention. They should not be used to limit the scope of protection of the present invention. Any equivalent changes or modifications made on the basis of the technical solution according to the technical idea proposed by the present invention shall still fall within the scope of protection of the technical solution of the present invention.

[0139] In Example 2, the influence of residual fluid volume on elastic parameters was studied during experimental measurements. The fluid conduits in the sample connected to pore spaces, preventing the sample from being completely sealed. These conduits formed fluid storage spaces, affecting the elastic parameters of the fluid-saturated sample. Example 2 improved the Gassmann model by considering the influence of residual fluid volume, predicting elastic parameters under boundary conditions. Compared to existing Gassmann models, this method fully considers boundary conditions and effectively predicts elastic parameters under their influence, providing more accurate and robust support for subsequent seismic information-based lithology differentiation and oil and gas exploration.

[0140] Example 4:

[0141] In another embodiment, such as Figure 5 As shown, an elastic parameter prediction device considering low-frequency experimental boundary conditions is provided. The device includes:

[0142] A fluid pipeline volume acquisition module is used to acquire fluid volume information of a pipeline used in low-frequency equipment, wherein the fluid pipeline connects the sample and the pore space of the sample;

[0143] The elastic parameter module is used to obtain the corresponding elastic parameters based on the fluid volume information in the pipeline, using a preset elastic parameter model.

[0144] Optionally, the construction of the preset elasticity parameter model includes:

[0145] The sample volume relative change module is used to obtain the sample volume relative change under boundary conditions, wherein the boundary conditions include: the sample is in a sealed boundary and the sample is in an open boundary, and the sample volume relative change is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0146] The construction module is used to construct the preset elastic parameter model based on the total pressure experienced by the sample and the volume change modulus of the saturated fluid, through the relative change of the sample volume.

[0147] Optionally, when the sample is in a sealed state, the module for monitoring the relative change in sample volume is specifically used for:

[0148] The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

[0149] Optionally, the volume change of the fluid is the sum of the pore fluid volume change and the pipe fluid volume change. Specifically, the volume change of the fluid is characterized as follows:

[0150]

[0151] Changes in the volume of the experimental rock sample skeleton:

[0152] ΔV s =ΔV s1 +ΔV s2

[0153] in,

[0154]

[0155]

[0156] ΔV s2 =-VΔP s / K s

[0157] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0158] Optionally, the relative change in sample volume when the sample is in a sealed state is characterized as follows:

[0159]

[0160] Optionally, when the sample is in an open state, the relative change in sample volume includes:

[0161]

[0162] Among them, K d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0163] Optionally, the preset elastic parameter model is characterized as follows:

[0164]

[0165] This device improves the Gassmann model by considering the influence of residual fluid volume, predicting elastic parameters under boundary conditions. Compared to existing Gassmann models, this method fully considers boundary conditions and effectively predicts elastic parameters influenced by them, providing more accurate and robust support for subsequent seismic information-based lithology differentiation and hydrocarbon exploration.

[0166] Example 5:

[0167] A terminal device is provided, which may be a server or a computer device, and its internal structure diagram may be as follows: Figure 6As shown. The terminal device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores relevant data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for predicting elastic parameters considering low-frequency experimental boundary conditions, wherein the method includes:

[0168] Obtain fluid volume information in pipelines used by low-frequency equipment;

[0169] Based on a preset elastic parameter model, the corresponding elastic parameters are obtained through the fluid volume information in the pipeline. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions.

[0170] Optionally, the construction of the preset elasticity parameter model includes:

[0171] The relative change in sample volume under boundary conditions is obtained, wherein the boundary conditions include: the sample being in a sealed boundary and the sample being in an open boundary, and the relative change in sample volume is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0172] Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

[0173] Optionally, when the sample is in a sealed state, the relative change in sample volume under boundary conditions is obtained, including:

[0174] The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

[0175] Optionally, the volume change of the fluid is the sum of the pore fluid volume change and the pipe fluid volume change. Specifically, the volume change of the fluid is characterized as follows:

[0176]

[0177] Changes in the volume of the experimental rock sample skeleton:

[0178] ΔV s =ΔV s1 +ΔV s2

[0179] in,

[0180]

[0181]

[0182] ΔV s2 =-VΔP s / K s

[0183] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0184] Optionally, the relative change in sample volume when the sample is in a sealed state is characterized as follows:

[0185]

[0186] Optionally, the boundary condition is: when the sample is in an open state, the relative change in sample volume includes:

[0187]

[0188] Among them, K d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0189] Optionally, the preset elastic parameter model is characterized as follows:

[0190]

[0191] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the terminal device to which the solution of this application is applied. A specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0192] Example 6: This example provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the above-described method for predicting elastic parameters considering low-frequency experimental boundary conditions. The method includes:

[0193] Obtain fluid volume information in pipelines used by low-frequency equipment;

[0194] Based on a preset elastic parameter model, the corresponding elastic parameters are obtained through the fluid volume information in the pipeline. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions.

[0195] Optionally, the construction of the preset elasticity parameter model includes:

[0196] The relative change in sample volume under boundary conditions is obtained, wherein the boundary conditions include: the sample being in a sealed boundary and the sample being in an open boundary, and the relative change in sample volume is characterized as the ratio between the volume change of the fluid and the volume change of the experimental rock sample skeleton during the low-frequency experiment.

[0197] Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

[0198] Optionally, when the sample is in a sealed state, the relative change in sample volume under boundary conditions is obtained, including:

[0199] The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

[0200] Optionally, the volume change of the fluid is the sum of the pore fluid volume change and the pipe fluid volume change. Specifically, the volume change of the fluid is characterized as follows:

[0201]

[0202] Changes in the volume of the experimental rock sample skeleton:

[0203] ΔV s =ΔV s1 +ΔV s2

[0204] in,

[0205]

[0206]

[0207] ΔV s2 =-VΔP s / Ks

[0208] Moreover, ΔV f It represents the change in total fluid volume, where V is the sample volume. It is the porosity of the rock, V D V is the volume of the fluid pipe. p It is the pore volume of the sample, ΔV s It is the change in the volume of the solid skeleton, which is equal to the fluid pressure (ΔV). s1 ) and skeleton stress (ΔV s2 The volume change caused by ) K f It is the bulk modulus of the fluid, K s It is the bulk modulus of the solid skeleton.

[0209] Optionally, the relative change in sample volume when the sample is in a sealed state is characterized as follows:

[0210]

[0211] Optionally, the boundary condition is: when the sample is in an open state, the relative change in sample volume includes:

[0212]

[0213] Among them, K d It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

[0214] Optionally, the preset elastic parameter model is characterized as follows:

[0215]

[0216] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0217] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0218] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for predicting elastic parameters considering low-frequency experimental boundary conditions, characterized in that, The method includes: Obtain fluid volume information in pipelines used by low-frequency equipment; Based on a preset elastic parameter model, the corresponding elastic parameters are obtained through the fluid volume information in the pipeline. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions. The construction of the preset elastic parameter model includes: The relative change in sample volume under low-frequency experimental boundary conditions is obtained, wherein the boundary conditions include: the sample being in a sealed boundary and the sample being in an open boundary, and the relative change in sample volume is characterized as: the ratio of the change in fluid volume to the change in volume of the experimental rock sample skeleton during the low-frequency experiment. Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

2. The method according to claim 1, characterized in that, When the sample is under boundary sealing, the relative change in sample volume under boundary conditions is obtained, including: The volume changes of the fluid and the volume changes of the experimental rock sample skeleton during the low-frequency experiment were obtained, and the relative volume changes of the sample when the sample was sealed at the boundary were obtained based on the two.

3. The method according to claim 2, characterized in that, The volume change of the fluid is the sum of the volume changes of the pore fluid and the volume changes of the pipe fluid. Specifically, the volume change of the fluid is characterized as follows: Changes in the volume of the experimental rock sample skeleton: in, and, It is the change in the total fluid volume. It is the sample volume. It refers to rock porosity. It is the volume of the fluid pipe. It is the pore volume of the sample. It is the change in the volume of the solid skeleton, which is equal to the fluid pressure. and skeleton stress The resulting volume change, It is the bulk modulus of the fluid. It is the bulk modulus of the solid framework. It is the stress on the sample skeleton. It is fluid pressure.

4. The method according to claim 3, characterized in that, The relative change in sample volume when the sample is under boundary sealing is characterized as follows: 。 5. The method according to claim 4, characterized in that, When the sample is in an open state, the relative change in sample volume includes: in, It is the bulk modulus of the sample's water displacement. It is the rate of change of sample volume caused by skeletal stress. It is the rate of change of volume of the solid skeleton caused by fluid pressure.

6. The method according to claim 5, characterized in that, The preset elastic parameter model is characterized as follows: 。 7. An elastic parameter prediction device considering low-frequency experimental boundary conditions, characterized in that, The device includes: The fluid pipeline volume acquisition module is used to acquire fluid volume information for pipelines used in low-frequency equipment. The elastic parameter module is used to obtain the corresponding elastic parameters based on the fluid volume information in the pipeline, according to a preset elastic parameter model. The preset elastic parameter model is constructed based on low-frequency experimental boundary conditions. The construction of the preset elastic parameter model includes: The relative change in sample volume under low-frequency experimental boundary conditions is obtained, wherein the boundary conditions include: the sample being in a sealed boundary and the sample being in an open boundary, and the relative change in sample volume is characterized as: the ratio of the change in fluid volume to the change in volume of the experimental rock sample skeleton during the low-frequency experiment. Based on the total pressure experienced by the sample and the volumetric modulus of the saturated fluid, the preset elastic parameter model is constructed by the relative change in the sample volume.

8. A terminal device, characterized in that, Including processor and memory; The memory is used to store computer instructions, and the processor is used to run the computer instructions stored in the memory to implement the method for predicting elastic parameters considering low-frequency experimental boundary conditions as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the method for predicting elastic parameters considering low-frequency experimental boundary conditions as described in any one of claims 1 to 6.

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