A method and apparatus for fracture parameter prediction

Abstract

The application discloses a kind of crack parameter prediction method and device.The method includes, the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the rock of purpose layer are determined;Given the initial crack density, azimuth and filling fluid factor of the rock of purpose layer;According to the current crack density, azimuth and filling fluid factor, the predicted wave velocity of P wave, SV wave and SH wave is obtained by rock physics model, the error between measured wave velocity and predicted wave velocity is determined;If the error is greater than error threshold, new crack density, azimuth and filling fluid factor are generated according to the set rule, the wave velocity is predicted again, and the error is determined;If the error is not greater than threshold, the current crack density and azimuth are determined as the crack density and azimuth of the rock of purpose layer.The method obtains the simplified quantitative rock physics model between crack parameter and seismic wave (or acoustic wave) velocity, the required parameters are less and easy to obtain, realizes the rapid and efficient inversion of crack parameter, and is suitable for multi-scale crack prediction.

Description

Technical Field

[0001] This invention relates to the field of applied geophysics, and in particular to a method and apparatus for predicting fracture parameters. Background Technology

[0002] Fractures are widely distributed in the Earth's crust and have a significant impact on the elastic properties of rocks and the flow of underground fluids. Therefore, detecting and characterizing fractures is an important aspect of many engineering fields, including oil and gas exploration and development, tunnel engineering, mining engineering, and carbon dioxide storage. Currently, seismic and sonic logging technologies are among the main techniques for detecting and characterizing underground fractures. These technologies can be further divided into the following two categories based on their principles:

[0003] (1) Identifying fractures using image processing or signal analysis techniques. This type of technique directly extracts fracture information from seismic or well logging data using image processing or signal analysis methods such as edge detection, curvature, and coherence. This method is suitable for large-scale fractures, but for small-scale fractures (i.e., fractures much smaller than the wavelength of seismic or acoustic waves), it is usually difficult to identify them directly from the seismic or well logging data profile. Therefore, this type of technique cannot be used to detect and describe small-scale fractures.

[0004] (2) Establish a quantitative relationship between fracture parameters and seismic wave (or acoustic wave) properties using a rock physics model, and then use this quantitative relationship to invert fracture properties. Subsurface fractures can cause seismic waves or acoustic waves to exhibit significant dispersion, attenuation, and frequency-varying anisotropy, thus a quantitative relationship between these properties and fracture properties (i.e., a rock physics model) can be established, and fracture parameters can then be directly inverted from seismic or acoustic wave properties. This type of method has a clear physical basis and therefore has strong applicability, applicable not only to large-scale fractures but also to small-scale fractures. Summary of the Invention

[0005] The inventors discovered that, of the two types of technologies mentioned above, the first type has a narrower scope of application, only suitable for detecting large-scale cracks; while the second type, starting from the propagation laws of seismic waves (or sound waves) in fractured rocks, establishes a quantitative relationship between their properties and crack characteristics, thereby enabling crack detection and description. Therefore, the second type of technology has stronger applicability, but its effectiveness depends on the establishment of an accurate and efficient rock physics model. Current rock physics models mainly suffer from problems such as too many parameters and difficulty in obtaining these parameters, leading to significant uncertainties in the inversion of crack properties. Therefore, establishing a rock physics model with fewer and more readily available parameters is of great significance for the accurate inversion of crack properties.

[0006] In order to at least partially solve the technical problems existing in the prior art, the inventors made this invention, which provides a crack prediction method and device through specific implementation, realizing rapid and efficient inversion of crack parameters.

[0007] In a first aspect, embodiments of the present invention provide a method for predicting crack parameters, including:

[0008] The steps for determining matrix rock parameters include determining the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the target layer rock, wherein the matrix rock and the target layer rock have the same matrix and do not have fractures.

[0009] The initialization step for fracture parameters of the target layer rock is to give the initial fracture density, azimuth angle and filling fluid factor of the target layer rock.

[0010] The target layer rock wave velocity prediction steps are as follows: based on the current fracture density, azimuth angle and filling fluid factor, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through a rock physics model, and the error between the measured wave velocities and the predicted wave velocities of P-wave, SV-wave and SH-wave is determined.

[0011] If the current error is greater than the set error threshold, generate new crack density, azimuth and filling fluid factor according to the set rules, and return to execute the target layer rock wave velocity prediction step;

[0012] If the current error is not greater than the error threshold, the current crack density and azimuth are determined as the crack density and azimuth of the target layer rock.

[0013] In a second aspect, embodiments of the present invention provide a crack parameter prediction device, comprising:

[0014] The matrix rock parameter determination module is used to determine the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the target layer rock. The matrix rock and the target layer rock have the same matrix and do not have cracks.

[0015] The target layer rock fracture parameter setting module is used to specify the initial fracture density, azimuth angle, and filling fluid factor of the target layer rock.

[0016] The target layer rock wave velocity prediction module is used to obtain the predicted wave velocities of P-waves, SV-waves and SH-waves through a rock physics model based on the current fracture density, azimuth angle and filling fluid factor, and to determine the error between the measured wave velocities and the predicted wave velocities of P-waves, SV-waves and SH-waves.

[0017] The judgment module is used to determine whether the current error is greater than the set error threshold;

[0018] If the judgment module determines that it is true, the target layer rock fracture parameter setting module is further used to generate new fracture density, azimuth angle and filling fluid factor according to the set rules; the target layer rock wave velocity prediction module redetermines the error between the measured wave velocity and the predicted wave velocity of P wave, SV wave and SH wave according to the new fracture density, azimuth angle and filling fluid factor.

[0019] The fracture parameter determination module is used to determine the current fracture density and azimuth as the fracture density and azimuth of the target layer rock if the judgment module determines that it is not true.

[0020] Thirdly, embodiments of the present invention provide a computer program product, including a computer program / instruction, wherein the computer program / instruction, when executed by a processor, implements the above-described crack parameter prediction method.

[0021] Fourthly, embodiments of this disclosure provide a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described crack parameter prediction method.

[0022] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0023] (1) The fracture parameter prediction method provided in this embodiment of the invention obtains a simplified and quantitative rock physics model between fracture parameters and seismic wave (or acoustic wave) velocity. This model has the advantages of having few parameters and being easy to obtain. First, the P-wave velocity and S-wave velocity of the matrix rock corresponding to the target layer are determined. Given the initial fracture density, azimuth, and filling fluid factor of the target layer rock, the model is used to iteratively optimize the fracture density, azimuth, and filling fluid factor by referring to the measured values ​​of P-wave, SV-wave, and SH-wave until the error between the predicted wave velocity and the measured value meets the requirements, thus obtaining the final fracture parameters. The parameters required in this embodiment of the invention are only the P-wave velocity and S-wave velocity of the matrix rock and the measured values ​​of P-wave, SV-wave, and SH-wave velocities of the target layer rock. A convenient and efficient fracture parameter inversion process is constructed, realizing efficient and accurate inversion interpretation of fracture parameters.

[0024] (2) The crack parameter prediction method provided in the embodiments of the present invention has a wide range of applications and can predict crack parameters at multiple scales.

[0025] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0026] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0027] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0028] Figure 1 This is a flowchart of the crack parameter prediction method in Embodiment 1 of the present invention;

[0029] Figure 2 This refers to the well logging data and fracture density prediction results in Embodiment 2 of the present invention;

[0030] Figure 3 This is a schematic diagram of the crack parameter prediction device in an embodiment of the present invention. Detailed Implementation

[0031] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0032] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Every smaller range between any stated value or intermediate value within a stated range, and any other stated value or intermediate value within said range, is also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0033] Unless otherwise stated, 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 invention pertains. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention. All references to this specification are incorporated by way of citation to disclose and describe methods and / or materials associated with those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

[0034] Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," just as "including," when used as a conjunction in the claims, is understood. Additionally, the use of any term "or" in the specification or claims is intended to indicate "non-exclusive or." Terms such as "first" and "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0035] To address the issues of narrow applicability of crack property prediction in existing technologies or high uncertainty in prediction results due to numerous related parameters, this invention provides a crack parameter prediction method and apparatus that achieves rapid and efficient inversion of crack parameters and is applicable to multi-scale crack prediction.

[0036] Example 1

[0037] Embodiment 1 of the present invention provides a method for predicting crack parameters, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0038] Step S11: Determine the P-wave velocity and S-wave velocity of the matrix rock corresponding to the target layer rock.

[0039] The matrix rock and the target layer rock have the same matrix and are free of fractures. The goal is to obtain the P-wave velocity and S-wave velocity of the target layer rock under fracture-free conditions.

[0040] The P-wave velocity and S-wave velocity here can be the P-wave velocity and S-wave velocity of seismic waves, or the P-wave velocity and S-wave velocity of sound waves. Correspondingly, the P-wave, SV-wave, and SH-wave that follow can be the P-wave, SV-wave, and SH-wave of seismic waves, or the P-wave, SV-wave, and SH-wave of sound waves.

[0041] The P-wave and S-wave velocities of the matrix rock can be determined using data from field well logging, seismic data, or laboratory measurements.

[0042] Step S12: Given the initial fracture density, azimuth, and filling fluid factor of the target rock layer.

[0043] The initial values ​​of fracture density, azimuth angle, and filling fluid factor can be set by first obtaining possible values ​​of fracture density, azimuth angle, and filling fluid factor based on existing data and conventional research results. Then, depending on the optimization algorithm used in subsequent iterations, a larger possible value can be selected and its value gradually decreased in subsequent iterations to finally obtain the optimized value; or a smaller possible value can be selected and its value gradually increased in subsequent iterations to finally obtain the optimized value.

[0044] Step S13: Based on the current fracture density, azimuth angle, and filling fluid factor, obtain the predicted wave velocities of P-wave, SV-wave, and SH-wave using a rock physics model, and determine the error between the measured wave velocities and the predicted wave velocities of P-wave, SV-wave, and SH-wave.

[0045] In some embodiments, the rock physics model characterizing the P-wave and S-wave velocities of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, as well as the relationship between P-wave, SV-wave, and SH-wave velocities, can be pre-established in the following manner:

[0046] The criteria for classifying dense and non-dense rocks are determined; based on the Hudson model, a first rock physics model applicable to dense rocks and a second rock physics model applicable to non-dense rocks are established, thus forming a rock physics model.

[0047] Furthermore, the criteria for classifying dense and non-dense rocks can be determined based on porosity and / or permeability parameters. For example, rocks with a porosity of 10% or less and a permeability of 0.01 md or less are classified as dense rocks, while rocks with a porosity greater than 10% and a permeability greater than 0.01 md are classified as non-dense rocks. Typically, the classification can also be determined solely based on permeability.

[0048] This embodiment does not limit the specific criteria for classifying dense rocks and non-dense rocks.

[0049] I. Establishment of the first rock physics model.

[0050] For dense rocks, a first relationship is established between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted; a second relationship is established between the S-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the SV-wave velocity of the rock to be predicted; and a third relationship is established between the S-wave velocity of the matrix rock, the fracture density, and azimuth of the rock to be predicted, and the SH-wave velocity of the rock to be predicted. The first, second, and third relationships constitute a first rock physics model applicable to dense rocks.

[0051] If the rock matrix is ​​relatively dense with low porosity and permeability, it can be assumed that there is no fluid exchange between the rock matrix and the fractures. In this case, the wave velocity can be calculated using the following simplified formula:

[0052] 1. The first relationship between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted is established as follows:

[0053] (1)

[0054] In formula (1), The predicted P-wave velocity value for the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. It is also the incident angle of the seismic wave (or sound wave), that is, the azimuth angle of the crack relative to the direction of propagation of the seismic wave (or sound wave); The longitudinal wave velocity is the velocity of the matrix rock.

[0055] The filling fluid factor A characterizes the effect of the filling fluid in the fracture on the sound velocity. The expression for the filling fluid factor A in dense rock is as follows:

[0056] (2)

[0057] In formula (2), The bulk modulus of the filling fluid; The aspect ratio of the crack; The density of the matrix rock is given. Therefore, after determining the optimal value of the filling fluid factor A through iterative optimization, if the bulk modulus of the filling fluid can be obtained, the longitudinal and transverse aspect ratio of the fracture can also be obtained through formula (2).

[0058] 2. The second relationship between the shear wave velocity of the matrix rock, the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted, and the SV wave velocity of the rock to be predicted is established as follows:

[0059] (3)

[0060] In formula (3), The predicted SV wave velocity of the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. The transverse wave velocity is the velocity of the matrix rock.

[0061] 3. The third relationship between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted is established as follows:

[0062] (4)

[0063] In formula (4), The predicted SH wave velocity of the rock to be predicted is... and The values ​​represent the crack density and azimuth of the rock to be predicted. The transverse wave velocity of the matrix rock. and This is determined through the above step S11.

[0064] II. Establishment of the Second Rock Physics Model.

[0065] For non-dense rocks, a fourth relationship is established between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted and the P-wave velocity of the rock to be predicted; a fifth relationship is established between the S-wave velocity of the matrix rock, the fracture density of the rock to be predicted and the SV-wave velocity of the rock to be predicted; and a sixth relationship is established between the S-wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted and the SH-wave velocity of the rock to be predicted. The fourth, fifth, and sixth relationships constitute a second rock physics model applicable to non-dense rocks.

[0066] If the rock matrix has well-developed pores, with high porosity and permeability, fluid exchange can occur between the rock matrix and the fluid in the fractures, leading to fluid pressure equilibrium throughout the rock. In this case, the wave velocity can be calculated using the following simplified formula:

[0067] 1. The fourth relationship is established between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted, as follows:

[0068] (5)

[0069] In formula (5), The predicted P-wave velocity value for the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. The longitudinal wave velocity is the velocity of the matrix rock.

[0070] 2. The fifth relationship between the transverse wave velocity of the matrix rock and the fracture density of the rock to be predicted and the SV wave velocity of the rock to be predicted is established as follows:

[0071] (6)

[0072] In formula (6), The predicted SV wave velocity of the rock to be predicted. For the crack density of the rock to be predicted, The transverse wave velocity is the velocity of the matrix rock.

[0073] 3. The sixth relationship between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted is established as follows:

[0074] (7)

[0075] In formula (7), The predicted SH wave velocity of the rock to be predicted is... and The values ​​represent the crack density and azimuth of the rock to be predicted. The transverse wave velocity is the velocity of the matrix rock.

[0076] When rock porosity is relatively developed, i.e., in non-dense rocks, the filling fluid factor is expressed as follows:

[0077] (8)

[0078] In formula (8), For the porosity of the matrix rock, This represents the bulk modulus of the rock particle skeleton.

[0079] If the porosity and density of the matrix rock are obtained in step S11, and the optimal value of the filling fluid factor A is determined through iterative optimization, the bulk modulus of the filling fluid can be obtained through formula (8).

[0080] If the target layer rock is dense rock, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through the first rock physics model; if the target layer rock is non-dense rock, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through the second rock physics model.

[0081] The error E between the measured wave velocity and the predicted wave velocity of P-wave, SV-wave, and SH-wave can be obtained according to the following formula (9):

[0082] (9)

[0083] In formula (9), and The predicted and measured wave velocities are i=1,1,3, representing P-wave, SV-wave, and SH-wave, respectively.

[0084] Step S14: Determine whether the current error is not greater than the error threshold.

[0085] If not, proceed to step S15; if yes, proceed to step S16.

[0086] Step S15: Generate new crack density, azimuth angle and filling fluid factor according to the set rules.

[0087] A new set of crack parameters can be generated using optimization algorithms (such as gradient descent).

[0088] After step S15, return to step S13.

[0089] Step S16: Determine the current fracture density and azimuth as the fracture density and azimuth of the target layer rock.

[0090] If the current error is determined to be no greater than the error threshold, it indicates that the measured wave velocity matches the theoretically predicted wave velocity, and the corresponding crack density, azimuth angle, and fluid factor are output.

[0091] Specific application scenarios can include using data from well logging, seismic data, etc., to obtain the velocities of P-waves, SV-waves, and SH-waves at different locations and depths in the target layer region, i.e., obtaining the measured wave velocities of P-waves, SV-waves, and SH-waves at each detection point in the target layer; for each detection point in the target layer, through the above steps S13-S16, using the measured wave velocities of P-waves, SV-waves, and SH-waves at the corresponding detection point, the rock physics model is used to iteratively optimize the fracture density, azimuth angle, and filling fluid factor of the detection point until the optimal values ​​are obtained.

[0092] The fracture parameter prediction method provided in Embodiment 1 of this invention obtains a simplified and quantitative rock physics model relating fracture parameters to seismic wave (or acoustic wave) velocities. This model has advantages such as fewer parameters and ease of obtaining them. First, the P-wave and S-wave velocities of the matrix rock corresponding to the target layer are determined. Given the initial fracture density, azimuth, and filling fluid factor of the target layer rock, the model is used to iteratively optimize the fracture density, azimuth, and filling fluid factor by referring to P-wave, SV-wave, and SH-wave measurements until the error between the predicted and measured wave velocities meets the requirements, thus obtaining the final fracture parameters. This embodiment of the invention requires only the P-wave and S-wave velocities of the matrix rock and the measured wave velocity values ​​of the target layer rock, constructing a convenient and efficient fracture parameter inversion process, achieving efficient and accurate inversion interpretation of fracture parameters. Furthermore, this method has a wide range of applications and can predict fracture parameters at multiple scales.

[0093] Example 2

[0094] This invention provides an application example of a fracture parameter prediction method for predicting fracture parameters in a target layer of an oilfield in Xinjiang. Since the adjacent layers of the target layer have almost no fracture development and their lithology is similar to that of the target layer, the P-wave and S-wave velocities of the adjacent layers are selected as the P-wave and S-wave velocities of the matrix rock of the target layer. Then, given the initial fracture density, azimuth angle, and filling fluid factor parameters, and since the target layer rock is relatively dense, the P-wave, SH-wave, and SV-wave velocities are calculated using formulas (1), (3), and (4) from Example 1. Simultaneously, the P-wave and S-wave velocities of the target layer varying with depth can be obtained using well logging data. The calculated and measured P-wave and S-wave velocities are compared until the target function value falls within the error range, at which point the final fracture parameters are output. Figure 2 In the image, the left side shows the longitudinal wave velocity measurement curve, the middle side shows the transverse wave (including SV and SH waves) velocity measurement curve, and the right side shows the crack density curve predicted in Example 2.

[0095] The results show that the fracture density is distributed between 0 and 0.06, the fractures are distributed at high angles (dip angle of about 70 degrees), and the fluid contained in the fractures is gas. These results are consistent with other well logging results and geological understanding. This invention requires significantly fewer parameters than conventional fracture detection methods based on rock physics models, and the parameters are easier to obtain; therefore, this invention has significant technical advantages over traditional methods.

[0096] Based on the inventive concept of this invention, embodiments of this invention also provide a crack parameter prediction device, the structure of which is as follows: Figure 3 As shown, it includes:

[0097] The matrix rock parameter determination module 31 is used to determine the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the target layer rock, wherein the matrix rock and the target layer rock have the same matrix and do not have cracks.

[0098] The target layer rock fracture parameter setting module 32 is used to specify the initial fracture density, azimuth angle and filling fluid factor of the target layer rock.

[0099] The target layer rock wave velocity prediction module 33 is used to obtain the predicted wave velocities of P-wave, SV-wave and SH-wave through a rock physics model based on the current fracture density, azimuth angle and filling fluid factor, and to determine the error between the measured wave velocities and the predicted wave velocities of P-wave, SV-wave and SH-wave.

[0100] The judgment module 34 is used to determine whether the current error is greater than the set error threshold.

[0101] If the judgment module 34 determines that it is true, the target layer rock fracture parameter setting module 32 is further used to generate new fracture density, azimuth angle and filling fluid factor according to the set rules; the target layer rock wave velocity prediction module 33 redetermines the error between the measured wave velocity and the predicted wave velocity of P wave, SV wave and SH wave according to the new fracture density, azimuth angle and filling fluid factor.

[0102] The crack parameter determination module 35 is used to determine the current crack density and azimuth as the crack density and azimuth of the target layer rock if the judgment module 34 determines that it is not true.

[0103] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0104] Based on the inventive concept of the present invention, embodiments of the present invention also provide a computer program product, including a computer program / instruction, wherein the computer program / instruction, when executed by a processor, implements the above-mentioned crack parameter prediction method.

[0105] Based on the inventive concept of the present invention, embodiments of the present invention also provide a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described crack parameter prediction method.

[0106] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0107] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0108] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0109] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0110] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0111] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0112] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments; however, those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims.

Claims

1. A method for predicting crack parameters, characterized in that, include: The steps for determining matrix rock parameters include determining the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the target layer rock, wherein the matrix rock and the target layer rock have the same matrix and do not have fractures. The initialization step for fracture parameters of the target layer rock is to give the initial fracture density, azimuth angle and filling fluid factor of the target layer rock. The target layer rock wave velocity prediction steps are as follows: based on the current fracture density, azimuth angle and filling fluid factor, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through a rock physics model, and the error between the measured wave velocities and the predicted wave velocities of P-wave, SV-wave and SH-wave is determined. If the current error is greater than the set error threshold, generate new crack density, azimuth and filling fluid factor according to the set rules, and return to execute the target layer rock wave velocity prediction step; If the current error is not greater than the error threshold, the current crack density and azimuth are determined as the crack density and azimuth of the target layer rock. The rock physics model is established in advance by: determining the criteria for classifying dense rocks and non-dense rocks; establishing a first rock physics model applicable to dense rocks and a second rock physics model applicable to non-dense rocks based on the Hudson model, thus forming a rock physics model. The rock physics model is used to characterize the P-wave and S-wave velocities of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, as well as the relationship between P-wave, SV-wave, and SH-wave velocities. Establish a first rock physics model applicable to dense rocks, specifically including: for dense rocks, establishing a first relationship between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted and the P-wave velocity of the rock to be predicted; a second relationship between the S-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted and the SV-wave velocity of the rock to be predicted; and a third relationship between the S-wave velocity of the matrix rock, the fracture density, and azimuth of the rock to be predicted and the SH-wave velocity of the rock to be predicted; the first rock physics model applicable to dense rocks is constituted by the first, second, and third relationships.

2. The method as described in claim 1, characterized in that, The establishment of the first relationship between the P-wave velocity of the matrix rock, the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted, specifically includes: The first relationship between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted is established as follows: （1）； In formula (1), The predicted P-wave velocity value for the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. The longitudinal wave velocity is the velocity of the matrix rock.

3. The method as described in claim 1, characterized in that, A second relationship is established between the shear wave velocity of the matrix rock, the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted, and the SV wave velocity of the rock to be predicted. Specifically, this includes: The second relationship between the shear wave velocity of the matrix rock, the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted, and the SV wave velocity of the rock to be predicted is established as follows: （2）； In formula (2), The predicted SV wave velocity of the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. The transverse wave velocity is the velocity of the matrix rock.

4. The method as described in claim 1, characterized in that, A third relationship is established between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted. Specifically, this includes: The third relationship between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted is established as follows: （3）； In formula (3), The predicted SH wave velocity of the rock to be predicted is... and The values ​​represent the crack density and azimuth of the rock to be predicted. The transverse wave velocity is the velocity of the matrix rock.

5. The method as described in claim 1, characterized in that, Establishing a second rock physics model applicable to non-dense rocks, specifically including: For non-dense rocks, a fourth relationship is established between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted and the P-wave velocity of the rock to be predicted; a fifth relationship is established between the S-wave velocity of the matrix rock, the fracture density of the rock to be predicted and the SV-wave velocity of the rock to be predicted; and a sixth relationship is established between the S-wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted and the SH-wave velocity of the rock to be predicted. The fourth, fifth, and sixth relations constitute a second rock physics model applicable to non-dense rocks.

6. The method as described in claim 5, characterized in that, The establishment of a fourth relationship between the P-wave velocity of the matrix rock, the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted, specifically includes: The fourth relationship is established between the P-wave velocity of the matrix rock, the fracture density, azimuth, and filling fluid factor of the rock to be predicted, and the P-wave velocity of the rock to be predicted, as follows: （4）； In formula (4), The predicted P-wave velocity value for the rock to be predicted. , and These represent the fracture density, azimuth angle, and filling fluid factor of the rock to be predicted. The longitudinal wave velocity is the velocity of the matrix rock.

7. The method as described in claim 5, characterized in that, A fifth relationship is established between the transverse wave velocity of the matrix rock and the fracture density and SV wave velocity of the rock to be predicted, specifically including: The fifth relationship between the transverse wave velocity of the matrix rock and the fracture density of the rock to be predicted and the SV wave velocity of the rock to be predicted is established as follows: （5）； In formula (5), The predicted SV wave velocity of the rock to be predicted. For the crack density of the rock to be predicted, The transverse wave velocity is the velocity of the matrix rock.

8. The method as described in claim 5, characterized in that, A sixth relationship is established between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted. Specifically, this includes: The sixth relationship between the shear wave velocity of the matrix rock, the fracture density and azimuth of the rock to be predicted, and the SH wave velocity of the rock to be predicted is established as follows: （6）； In formula (6), The predicted SH wave velocity of the rock to be predicted is... and The values ​​represent the crack density and azimuth of the rock to be predicted. The transverse wave velocity is the velocity of the matrix rock.

9. The method as described in claim 1, characterized in that, Before performing the target layer rock parameter prediction step for the first time, the method further includes: The target layer of rock is determined to be either dense or non-dense rock according to the aforementioned classification criteria; correspondingly... The method of obtaining the predicted wave velocities of P-waves, SV-waves, and SH-waves through a rock physics model specifically includes: If the target layer rock is dense rock, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through the first rock physics model; If the target layer rock is non-dense rock, the predicted wave velocities of P-wave, SV-wave and SH-wave are obtained through the second rock physics model.

10. A crack parameter prediction device, characterized in that, The apparatus is used to perform the crack parameter prediction method according to claim 1, and the apparatus includes: The matrix rock parameter determination module is used to determine the longitudinal wave velocity and transverse wave velocity of the matrix rock corresponding to the target layer rock. The matrix rock and the target layer rock have the same matrix and do not have cracks. The target layer rock fracture parameter setting module is used to specify the initial fracture density, azimuth angle, and filling fluid factor of the target layer rock. The target layer rock wave velocity prediction module is used to obtain the predicted wave velocities of P-waves, SV-waves and SH-waves through a rock physics model based on the current fracture density, azimuth angle and filling fluid factor, and to determine the error between the measured wave velocities and the predicted wave velocities of P-waves, SV-waves and SH-waves. The judgment module is used to determine whether the current error is greater than the set error threshold; If the judgment module determines that it is true, the target layer rock fracture parameter setting module is further used to generate new fracture density, azimuth angle and filling fluid factor according to the set rules; the target layer rock wave velocity prediction module redetermines the error between the measured wave velocity and the predicted wave velocity of P wave, SV wave and SH wave according to the new fracture density, azimuth angle and filling fluid factor. The fracture parameter determination module is used to determine the current fracture density and azimuth as the fracture density and azimuth of the target layer rock if the judgment module determines that it is not true.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the crack parameter prediction method according to any one of claims 1 to 9.

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