Acoustic wave logging soundproofing method and device based on phononic crystal

Abstract

The embodiment of the application discloses a kind of acoustic logging sound insulation methods based on phononic crystal.The method comprises: according to the instrument wave main frequency range of the instrument to be sound insulated, the band gap constraint condition of sound insulation body is set;Determine the material attribute and scattering body filling rate value range of sound insulation body, according to the reference size parameter and band gap constraint condition of the instrument to be sound insulated, the lattice constant value range of sound insulation body is determined;According to the lattice constant value range and scattering body filling rate value range, construct two-dimensional parameter space grid matrix;According to material attribute, establish finite element energy band solver;Characteristic solution is carried out using finite element energy band solver, and the band gap characteristics of each matrix element is obtained;According to reference size parameter and the matrix element that satisfies preset band gap screening condition and the band gap bandwidth of the largest band gap characteristics, sound insulation body is designed;Sound wave logging sound insulation processing is carried out to the instrument to be sound insulated using the sound insulation body after design, high-efficiency sound insulation is realized, and the data quality of sound wave logging is improved.

Description

Technical Field

[0001] This application relates to the field of oil and gas exploration and acoustic logging technology, specifically to an acoustic logging sound insulation method and device based on phonon crystals. Background Technology

[0002] In acoustic logging operations, the sound insulation body is a core component installed between the transmitting and receiving transducers to suppress interference from direct waves (instrument waves) propagating along the instrument housing, and directly determines the measurement accuracy of the formation acoustic signal.

[0003] Existing mainstream sound insulation solutions suffer from technical bottlenecks that cannot simultaneously meet both requirements: Grooved sound insulation (such as the structure disclosed in publication number CN118774760A): It achieves attenuation by extending the sound wave propagation path through periodic grooves, but geometric parameters such as groove depth and groove spacing are limited by mechanical strength, making it difficult to simultaneously meet sound insulation performance and downhole pressure resistance requirements in a wide frequency range, and structural failure is prone to occur in ultra-deep well conditions; Variable diameter sound insulation (such as the structure disclosed in publication number CN103352692B): It broadens the sound insulation bandwidth through abrupt changes in cross-section, but its suppression efficiency for low-frequency instrument waves below 10kHz is insufficient, and it cannot meet the needs of low-frequency array acoustic logging.

[0004] Therefore, there is an urgent need for a sonic logging sound insulation solution that can effectively solve the problems of narrow bandwidth, low efficiency and poor mechanical stability of traditional sound insulation materials. Summary of the Invention

[0005] In view of the above problems, this application is made in order to provide a phonon crystal-based acoustic logging sound insulation method, apparatus, computing device, computer storage medium and computer program product that overcomes or at least partially solves the above problems.

[0006] According to one aspect of the embodiments of this application, a sound insulation method for acoustic logging based on phonon crystals is provided, comprising: Obtain the dominant frequency range of the instrument wave corresponding to the logging instrument to be soundproofed; Based on the dominant frequency range of the instrument wave, set the bandgap constraint conditions for the target phononic crystal sound insulation body; Determine the material properties and scatterer filling rate range of the target phononic crystal sound insulator, and determine the lattice constant range of the target phononic crystal sound insulator based on the reference size parameters and bandgap constraint conditions of the logging instrument to be sounded. A two-dimensional parameter space grid matrix is ​​constructed based on the range of values ​​for the lattice constant and the scatterer filling rate. Each matrix element corresponds to a set of parameter combinations including the lattice constant and the scatterer filling rate. A finite element band structure solver is established based on material properties. The finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics. Each matrix element is input into the finite element bandgap solver to solve for the characteristic, and the bandgap characteristic corresponding to each matrix element is obtained. Based on the reference size parameters and the matrix element that meets the preset bandgap screening conditions and has the largest bandgap bandwidth in the bandgap features, the target phononic crystal sound insulation body is designed. During well logging operations, the designed target phononic crystal sound insulation body is used to perform acoustic logging sound insulation treatment on the sound-insulating well logging instrument.

[0007] Furthermore, the dominant frequency range of the instrument wave is... The bandgap constraint conditions include: the bandgap center frequency range is [value missing]. The bandgap bandwidth range is , , This represents the maximum value within the dominant frequency range of the instrument wave. This represents the minimum value within the dominant frequency range of the instrument wave. This represents the minimum bandgap bandwidth.

[0008] Furthermore, the preset bandgap screening conditions include: the bandgap existence flag is set to exist, the bandgap center frequency is within the range of the bandgap center frequency value, and the bandgap bandwidth is greater than or equal to the minimum bandgap bandwidth. Based on the reference size parameters and the matrix element that meets the preset bandgap screening conditions and has the largest bandgap bandwidth among the bandgap features, the design of the target phononic crystal sound insulation body further includes: The bandgap features that are marked as present, have a bandgap center frequency within the range of bandgap center frequency values, and have a bandgap bandwidth greater than or equal to the minimum bandgap bandwidth are selected. The target phononic crystal sound insulation body is designed based on the reference size parameters and the matrix elements corresponding to the bandgap characteristics of the maximum bandgap bandwidth.

[0009] Furthermore, the reference dimensional parameters include: the outer diameter of the soundproof logging instrument to be soundproofed and the inner diameter of the soundproof logging instrument to be soundproofed; The range of lattice constant values ​​for the target phononic crystal sound insulator, determined based on the reference size parameters of the logging instrument to be soundproofed and the bandgap constraint conditions, further includes: The maximum value of the lattice constant is determined based on the outer diameter and inner diameter of the logging instrument to be soundproofed, and the minimum value of the lattice constant is determined based on the maximum value of the matrix longitudinal wave velocity and the dominant frequency range of the instrument wave.

[0010] Furthermore, the construction of a two-dimensional parametric space grid matrix based on the range of lattice constant values ​​and the range of scatterer fill rate further includes: Based on a first preset step size, uniform discrete sampling is performed on the range of lattice constant values ​​to obtain a sequence of lattice constants containing a first preset number; Based on the second preset step size, the range of scatterer fill rate values ​​is uniformly discretely sampled to obtain a scatterer fill rate sequence containing the second preset number; The lattice constant sequence and the scatterer fill rate sequence are combined to generate a two-dimensional parameter space grid matrix with a first preset number of dimensions × a second preset number of dimensions.

[0011] Furthermore, each matrix element is input into the finite element bandgap solver for feature solving, and the bandgap features corresponding to each matrix element are further included: Divide the two-dimensional parametric space grid matrix into multiple subdomains; For each subdomain, the finite element band structure solver is invoked, and each matrix element in the subdomain is input into the finite element band structure solver to solve for the characteristics, thereby obtaining the band gap characteristics corresponding to each matrix element in the subdomain. Multiple subdomains are processed in parallel.

[0012] Furthermore, establishing a finite element band structure solver based on material properties further includes: Establish the equilibrium equations corresponding to the instrument waves based on material properties; Establish frequency domain elastic wave control equations based on the time-harmonic displacement and equilibrium equations of instrument waves; Based on Bloch's theorem, determine the Bloch displacement of the instrument wave propagating in the target phonon crystal with a periodic arrangement structure. The eigenvalue equations are determined based on the Bloch displacement and frequency domain elastic wave control equations. Finite element transformation is performed on the eigenvalue equations to obtain a finite element band structure solver.

[0013] According to another aspect of the embodiments of this application, a sound insulation device for acoustic logging based on phononic crystals is provided, comprising: The acquisition module is suitable for acquiring the dominant frequency range of the instrument wave corresponding to the soundproof logging instrument to be soundproofed; The bandgap constraint setting module is suitable for setting the bandgap constraint conditions of the target phononic crystal sound insulation body according to the dominant frequency range of the instrument wave. The determination module is suitable for determining the material properties and scatterer filling rate range of the target phononic crystal sound insulator, and for determining the lattice constant range of the target phononic crystal sound insulator based on the reference size parameters and bandgap constraint conditions of the logging instrument to be sounded. The spatial grid matrix construction module is suitable for constructing a two-dimensional parametric spatial grid matrix based on the range of lattice constant values ​​and the range of scatterer filling rate values. Each matrix element corresponds to a set of parameter combinations including lattice constant and scatterer filling rate. The finite element band structure solver creation module is suitable for creating finite element band structure solvers based on material properties. The finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics. The feature solving module is suitable for inputting each matrix element into the finite element bandgap solver to solve for the feature, and to obtain the bandgap feature corresponding to each matrix element. The design module is suitable for designing target phononic crystal sound insulation bodies based on reference size parameters and matrix elements that meet preset bandgap screening conditions and have the largest bandgap bandwidth in the bandgap features. The sound insulation module is suitable for performing acoustic sound insulation treatment on the logging instrument during well logging operations by using a designed target phononic crystal sound insulation body.

[0014] According to another aspect of the embodiments of this application, a computing device is provided, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-mentioned acoustic logging sound insulation method based on phononic crystal.

[0015] According to another aspect of the embodiments of this application, a computer storage medium is provided, wherein at least one executable instruction is stored in the storage medium, the executable instruction causing a processor to perform operations corresponding to the above-described acoustic logging sound insulation method based on phononic crystals.

[0016] According to another aspect of the embodiments of this application, a computer program product is provided, including at least one executable instruction that causes a processor to perform operations corresponding to the above-described acoustic logging sound insulation method based on phononic crystals.

[0017] The acoustic logging sound insulation method and apparatus based on phonon crystals provided in this application have high-efficiency sound insulation performance. Utilizing the bandgap characteristics of the material, it can accurately block sound wave propagation within the instrument's main operating frequency range, thereby significantly suppressing interference noise in formation signals and significantly improving the signal-to-noise ratio. Simultaneously, it exhibits strong broadband adaptability, maintaining stable sound insulation effects over a wide frequency range. Optimized processes ensure efficient suppression of low-frequency bands. The single-material design enhances pressure resistance, effectively reducing the risk of failure under high-temperature and high-pressure environments, and its outstanding mechanical stability ensures long-term reliable downhole operation. In the design and optimization phase, a parallel computing framework is employed, offering high computational efficiency and good scalability, significantly shortening the design cycle. Combined with a feasibility set strategy, it ensures the adaptability of the technical solution to actual well conditions, making it particularly suitable for complex exploration scenarios such as deep-sea and ultra-deep wells. Ultimately, this technology improves the overall data quality of acoustic logging and reduces equipment maintenance costs.

[0018] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of the embodiments of this application are described below. Attached Figure Description

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A schematic flowchart of a acoustic logging sound insulation method based on phononic crystals according to an embodiment of this application is shown; Figure 2 A schematic diagram showing the installation location of the target phononic crystal sound insulator; Figure 3 A schematic diagram of the first Brillouin zone and the irreducible Brillouin zone of a square lattice; Figure 4 This is a diagram of the band structure. Figure 5 A schematic diagram of a three-dimensional data cube; Figure 6 This is a schematic diagram of a sound insulation material based on a phononic crystal structure; Figure 7 This is a schematic diagram of sound attenuation per foot under a certain parameter; Figure 8 A structural block diagram of a acoustic logging sound insulation device based on a phononic crystal according to an embodiment of this application is shown; Figure 9 A schematic diagram of the structure of a computing device according to an embodiment of this application is shown. Detailed Implementation

[0020] 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.

[0021] Figure 1 A schematic flowchart of a acoustic logging sound insulation method based on phonon crystals according to an embodiment of this application is shown, as follows: Figure 1 As shown, the method includes the following steps: Step S101: Obtain the dominant frequency range of the instrument wave corresponding to the logging instrument to be soundproofed.

[0022] This section uses measured acoustic wave propagation data from a smooth, groove-free, diameter-free instrument housing to calibrate the dominant frequency range of the instrument wave propagating along the housing. The measured acoustic wave propagation data refers to the time-domain and frequency-domain propagation data of the elastic wave (i.e., the instrument wave) propagating along the instrument housing under simulated downhole conditions or in actual well site environments. It contains two key types of information: the time-domain amplitude signal of the instrument wave and the frequency distribution signal of the instrument wave. These are used to accurately locate the main energy concentration frequency band (dominant frequency range) of the instrument wave, providing a measured basis for setting bandgap constraints and avoiding a disconnect between the bandgap design and the actual instrument wave frequency band.

[0023] The following details the methods for obtaining measured sound wave propagation data: Based on actual acoustic logging conditions, the following steps were taken using a combination of simulation and field measurements: (1) Test preparation: Select a logging instrument housing (without grooves or diameter changes, and the material is consistent with the actual instrument, such as TC4 titanium alloy) that is compatible with the target phononic crystal sound insulation body. Cut a housing section that matches the design length of the sound insulation body. Simulate the downhole high temperature (200℃) and high pressure (140MPa) environment. Place the housing section in the simulated drilling fluid medium (restore the downhole sound wave propagation environment). The axial design total length d of the target phononic crystal sound insulation body is less than the axial source distance TR between the transmitting transducer and the receiving transducer of the logging instrument to be sound-insulated. (2) Signal transmission and acquisition: A transmitting transducer identical to the actual well logging is installed at one end of the shell section, and a receiving transducer is installed at the other end. The transmitting transducer outputs an excitation signal with the same frequency range as the actual well logging, and the receiving transducer synchronously acquires the elastic wave signal propagating along the shell. The time domain signal (amplitude-time curve) is recorded through the data acquisition system. (3) Data preprocessing: The acquired time-domain signal is denoised (to eliminate drilling fluid interference and environmental noise), and Fourier transform (FFT) is used to convert the time-domain signal into a frequency-domain signal (amplitude-frequency curve) to obtain the frequency distribution characteristics of the instrument wave; (4) Data verification: Select the same model of logging instrument without sound insulation structure at the actual well site, conduct on-site measurement, repeat the above signal acquisition and preprocessing steps, compare the measured data of the simulated environment and the actual well site, correct the deviation, and ensure the authenticity and representativeness of the measured data.

[0024] Based on the above measured sound wave propagation data, the dominant frequency range of the instrument wave is determined as follows: using the preprocessed frequency domain signal (amplitude-frequency curve) as the core basis, the dominant frequency range of the instrument wave is calibrated through the following steps: (1) Identify the peak frequency: In the frequency domain curve, find the frequency point with the highest instrument wave amplitude, which is the dominant frequency of the instrument wave. (Core frequency, the frequency at which the instrument wave energy is most concentrated); (2) Determine the main frequency range: based on the main frequency Centered on the frequency range, a frequency interval with an amplitude not less than 70% of the peak amplitude is selected as the dominant frequency range of the instrument wave. For example, if the actual measured clock frequency The frequency range corresponding to 70% amplitude is 8~12kHz, then the calibration... , ,in, This represents the maximum value within the dominant frequency range of the instrument wave. This represents the minimum range of the dominant frequency of the instrument wave. (3) Range verification: In combination with actual logging requirements, if there are multiple frequency peaks with high amplitude (multiple main frequencies) in the instrument wave, the 70% amplitude range corresponding to all peaks will be merged to form a complete main frequency range, ensuring that the subsequent bandgap design can cover all major instrument wave frequency bands.

[0025] Step S102: Set the bandgap constraint conditions for the target phononic crystal sound insulation body according to the dominant frequency range of the instrument wave.

[0026] The bandgap constraint conditions must fully cover the dominant frequency range of the instrument wave and meet the sound insulation performance requirements. Therefore, it is necessary to determine them in conjunction with the measured dominant frequency range of the instrument wave. The setting of the bandgap constraint conditions mainly includes: setting the range of values ​​for the bandgap center frequency and setting the range of values ​​for the bandgap bandwidth.

[0027] Specifically: (1) In order to ensure that the instrument wave can be effectively blocked and the sound insulation is effective, the bandgap center frequency of the designed target phononic crystal sound insulation body must fall within the dominant frequency range of the instrument wave to ensure that the bandgap can accurately cover the core propagation frequency band of the instrument wave; if the bandgap center frequency deviates from this range, the instrument wave will not be effectively blocked and the sound insulation will fail; therefore, the bandgap center frequency value range can be set as follows: .

[0028] (2) In order to achieve better sound insulation, a minimum bandgap bandwidth is required. The width is not less than the dominant frequency range of the instrument wave (i.e. This ensures that the bandgap can completely cover the dominant frequency range of the instrument wave; generally, the larger the bandgap bandwidth, the better the sound insulation effect. Therefore, the upper limit of the bandgap bandwidth is set to... This encourages the design of wider bandgap bands; considering the width of the instrument's dominant frequency range, the minimum bandgap bandwidth is set to [value missing]. Therefore, the range of values ​​for the bandgap bandwidth is set as follows: This clarifies the quantitative design requirements for sound insulation performance. For example, if the main frequency range is 8~12kHz (width 4kHz), then set... This ensures that the band gap width is not less than 4kHz, achieving full-band blocking of instrument waves.

[0029] Step S103: Determine the material properties and scatterer filling rate range of the target phononic crystal sound insulator, and determine the lattice constant range of the target phononic crystal sound insulator based on the reference size parameters and bandgap constraint conditions of the logging instrument to be sounded.

[0030] The material properties of the target phonon crystal sound insulator are typically divided into matrix material and scattering material. Based on the material properties of the housing of the logging instrument to be soundproofed, the physical parameters of the matrix of the target phonon crystal sound insulator, including matrix density, are determined. Elastic modulus Poisson's ratio (Conventional logging instruments use TC4 titanium alloy or 304 stainless steel, and the parameters are fixed engineering values.) The scatterer employs a cavity design (air-filled) to mitigate the risk of interface failure in composite structures. Its fixed physical parameters are: density. elastic modulus Poisson's ratio .

[0031] The scatterer fill factor is the ratio of the scatterer area to the total area of ​​the unit cell. A minimum scatterer fill factor is typically required. To ensure that the scattering intensity is sufficient to form a band gap, the maximum fill rate of the scatterer is achieved. To ensure that the minimum wall thickness of the sound insulation body is ≥2mm and meets the downhole compressive strength requirement of 140MPa, the range of values ​​for the scattering body filling rate can be obtained. .

[0032] Define a two-dimensional square unit cell as the smallest repeating unit of the target phononic crystal sound insulation body, with the cell side length being the lattice constant. A circular cavity scatterer is set at the center of the unit cell; The reference dimensional parameters of the soundproof logging instrument include: the outer diameter of the soundproof logging instrument. The inner diameter of the soundproof logging instrument Typically, the lattice constant must not exceed the instrument wall thickness to ensure structural manufacturability. Therefore, the constraint boundary can be determined based on the instrument wall thickness, i.e., the maximum value of the lattice constant range can be determined based on the outer diameter and inner diameter of the instrument. The maximum value satisfies The minimum value of the lattice constant is determined based on the maximum value of the longitudinal wave velocity in the matrix and the dominant frequency range of the instrument wave. The minimum value satisfies To match the Bragg scattering condition for the highest target sound insulation frequency, where, The longitudinal wave velocity of the matrix is ​​given, and the final lattice constant ranges from 1 to 2. .

[0033] Step S104: Construct a two-dimensional parameter space grid matrix based on the range of values ​​for the lattice constant and the scatterer filling rate. Each matrix element corresponds to a set of parameter combinations including the lattice constant and the scatterer filling rate.

[0034] After determining the range of values ​​for the lattice constant and the scatterer fill rate, a two-dimensional parametric space grid matrix can be constructed based on these ranges. Specifically, the first preset step size, also known as the lattice constant scanning step size, is determined using the following method: ,in, The number of calculation points for the lattice constant, satisfying Then, the range of lattice constant values ​​is uniformly discretely sampled based on a first preset step size. For example, the first discrete sample value is... Then, based on the previous discrete sample value, the first preset step size is increased to obtain the next discrete sample value, until the last discrete sample value is... , to obtain a quantity containing the first preset number The lattice constant sequence; the second preset step size, also known as the scatterer fill rate scan step size, is determined by the following method: ,in, The number of calculation points for the scatterer fill rate, satisfying... Then, based on the second preset step size, the range of scatterer fill rate values ​​is uniformly discretely sampled. For example, the first discrete sample value is... Then, based on the previous discrete sample value, the first preset step size is increased to obtain the next discrete sample value, until the last discrete sample value is... , to obtain a quantity containing the second preset number The scatterer filling rate sequence is obtained; the lattice constant sequence and the scatterer filling rate sequence are combined by parameters to generate a two-dimensional parameter space grid matrix with a first preset number of dimensions × a second preset number of dimensions, wherein each matrix element of the two-dimensional parameter space grid matrix uniquely corresponds to a set of discretized lattice constants. With scatterer fill rate The parameters are combined to form a standardized parameter set, which serves as the input unit for the subsequent bandgap solver. The two-dimensional parameter space grid matrix is ​​as follows: .

[0035] Step S105: Establish a finite element band structure solver based on material properties. The finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics.

[0036] The finite element bandgap solver is a numerical calculation tool based on the finite element method and periodic boundary conditions, used to solve for the bandgap characteristics of phononic crystal sound insulators. These bandgap characteristics include: bandgap presence indicators. (Boolean value), bandgap center frequency Bandgap bandwidth

[0037] For example, a finite element band structure solver can be built using the following method: Establish the equilibrium equations corresponding to the instrument waves based on material properties; Establish frequency domain elastic wave control equations based on the time-harmonic displacement and equilibrium equations of instrument waves; Based on Bloch's theorem, determine the Bloch displacement of the instrument wave propagating in the target phonon crystal with a periodic arrangement structure. The eigenvalue equations are determined based on the Bloch displacement and frequency domain elastic wave control equations. Finite element transformation is performed on the eigenvalue equations to obtain a finite element band structure solver.

[0038] Specifically, (1) the three core equations are established: The propagation of elastic waves (instrument waves) in solids is governed by three core equations, which form the basis for the derivation of the frequency domain elastic wave control equations: 1. Equilibrium Equation (Momentum Conservation): Neglecting volume forces, the momentum conservation equation in a linear elastic medium is:

[0039] in, It is a second-order stress tensor. For the density of the medium, It is a displacement vector. For time, It is the Hamiltonian differential operator.

[0040] 2. Geometric equation (strain-displacement relationship): Strain tensor under small deformation conditions With displacement vector The relationship is:

[0041] Among them, superscript This is a matrix transpose operator used to eliminate rigid body rotation components in displacement gradients and extract pure deformation strain.

[0042] 3. Constitutive Equation (Hooke's Law for Isotropic Materials): For metallic matrix materials, the stress-strain relationship of isotropic media is as follows:

[0043] in, , Let Lamé constant be . The trace of the strain tensor For a unit second tensor; the conversion relationship between the Lamé constant and material properties is:

[0044] (2) Derivation of the frequency domain elastic wave control equation For instrument waves with a fixed dominant frequency range, the assumption of time harmonic field (simple harmonic vibration) is adopted. By combining geometric equations and constitutive equations to eliminate time variables and time-domain variables, the control equation of elastic waves in the frequency domain is derived, which provides a basis for solving the theory of periodic structures.

[0045] The expression for the harmonic field of the displacement vector is:

[0046] in, For position vectors, Angular frequency, For sound wave frequency, It is the imaginary unit.

[0047] Substitute the time harmonic displacement of the instrument wave into the equilibrium equation in (1) to establish the frequency domain elastic wave control equation;

[0048] This equation is the core governing equation for the propagation of elastic waves in solids, and it is also the fundamental equation for solving the energy band structure in the finite element method.

[0049] (3) Introduction of Bloch's Theorem and Establishment of Generalized Eigenvalue Equations To mathematically transform the complex wave problem of an infinitely long periodic sound insulation material into a generalized eigenvalue problem of a single unit cell, and to provide a standard mathematical prototype for the subsequent finite element solver, Bloch's theorem is introduced here, and a generalized eigenvalue equation is established. Phononic crystals have a periodic arrangement structure, and the elastic parameters of the medium satisfy translational symmetry:

[0050] in, For a square unit cell, the basis vectors are lattice vectors. , , , It is an integer.

[0051] According to Bloch's theorem, when an elastic wave propagates in a periodic structure, the vibration modes of all unit cells are completely identical, with only a fixed phase difference between adjacent unit cells. Therefore, it is unnecessary to model the entire periodic structure; analyzing only a single unit cell is sufficient to characterize the overall wave properties. The displacement field of the periodic structure satisfies the standard Bloch solution form:

[0052] in, It is the Blochbo vector (located in the first Brillouin zone). A periodic function with the same period as the crystal lattice, i.e. .

[0053] Substituting the Bloch displacement solution into the frequency domain elastic wave control equation obtained in (2), and combining the differential characteristics of periodic functions, the complex partial differential equation is transformed into a theoretical generalized eigenvalue equation with wave vector k as parameter and angular frequency ω as eigenvalue:

[0054] in, : with Bloch wave The relevant stiffness matrix is ​​determined by the geometry of the unit cell, material parameters, and periodic boundary conditions; The mass matrix is ​​determined by the material density distribution within the unit cell. : Displacement vector of nodes within the unit cell; : The eigenvalue to be solved, corresponding to the propagation frequency of the elastic wave. , It is a theoretical operator symbol that only defines the mathematical forms of the stiffness and mass terms without specific values. The equations are still continuous problems with infinite degrees of freedom and cannot be solved directly by a computer. It only clarifies the mathematical essence that the periodic elastic wave problem can be transformed into eigenvalue solutions, and provides a theoretical prototype for the finite element band structure solver.

[0055] (4) Establishment of finite element band structure solver This step follows the theoretical generalized eigenvalue equation derived in (3). (3) only completed the theoretical operator modeling of the periodic elastic wave problem. The resulting partial differential strong form equation is an infinite-degree-of-freedom continuous mathematical model, which has the problem of strict requirements for displacement continuity and cannot be directly solved numerically by computer. Therefore, this step transforms the theoretical continuous partial differential equation into a finite-degree-of-freedom integral numerical equation that can be recognized and solved by computer through finite element mathematical transformation, thus completing the theoretical implementation of the bandgap solver. The specific weak form derivation process is as follows: 1. Derivation of weak form equations (equation fitting and order reduction) The frequency domain elastic wave control equations and theoretical generalized eigenvalue equations constructed in (2) and (3) are differential strong-form equations. These equations require that the displacement field in the solution domain be second-order continuous and differentiable everywhere. However, the finite element method uses piecewise element interpolation of the displacement field, which cannot meet the stringent condition of high-order continuity throughout the domain. Direct solution will result in calculation divergence and accuracy failure. In order to adapt to the characteristics of finite element numerical calculation, this application adopts the Galerkin weighted residual method to reduce the order of the strong-form equations: a virtual displacement test function is introduced to construct a residual integral, and the high-order differential operators of the equations are eliminated by integration by parts, transforming the high-order partial differential equations into low-order integral weak-form equations, which greatly reduces the requirement for continuity of the displacement field and makes it suitable for the piecewise solution logic of the finite element method.

[0056] Combining the Bloch periodic reset boundary shifting characteristics of (3), the elastic wave weak form governing equations for the adapted periodic phonon crystal structure are finally derived:

[0057] in, For Bloch periodic displacement field, This is the Galerkin virtual displacement test function. For complex conjugate operators, adapted to the complex phase boundary characteristics of periodic structures; first term integral The change in the elastic strain potential energy of the structure represents the source of the subsequent integral of the stiffness matrix; the second integral term... The change in structural kinetic energy corresponds to the source of the subsequent mass matrix integral. This weak form equation completely abandons higher-order differential operations and is the core foundation equation for subsequent element integration, matrix assembly, and numerical solution. It follows the theoretical model in (3) and realizes the key transformation from theoretical equation to finite element computable equation.

[0058] 2. Spatial Discretization and Matrix Assembly (Discretization Modeling) (3) The derived theoretical generalized eigenvalue equation is a continuous partial differential equation with infinite degrees of freedom, which cannot be directly solved numerically by computer. Therefore, it is necessary to discretize the computational domain of a single unit cell using a finite element mesh. This application uses quadratic quadrilateral isoparametric elements to divide the unit cell mesh and utilizes element shape functions. Interpolation characterizes the displacement field at any location within an element, achieving a discretized expression of continuous displacement. The element displacement interpolation formula is:

[0059] in, For discrete displacement at any point within the element, It is a quadratic shape function matrix. The element node displacement vector. These are the local coordinates of the element.

[0060] Based on the discrete displacement field, the stiffness matrix of a single finite element is obtained by element integration of the weak form equations. With the mass matrix The core integral formula is as follows:

[0061] in, The strain-displacement matrix, The material's elastic constitutive matrix, It is a single-unit integration domain.

[0062] Finally, based on the global numbering correspondence of the mesh nodes, the small stiffness matrices and small mass matrices of all elements are superimposed and assembled one by one to obtain the overall initial stiffness matrix of the unit cell. With the overall initial mass matrix This completely transforms the problem of continuous fluctuation with infinite degrees of freedom into a discrete matrix problem with finite degrees of freedom, laying the foundation for subsequent boundary constraints and numerical solutions.

[0063] To address the inability to numerically solve continuous wave problems, a finite element mesh is used to discretize the computational domain of a single unit cell. The mesh is divided using isoparametric quadrilateral elements, and the displacement field at any position within the element is characterized by shape function interpolation. Integral calculations are performed on each element to obtain the element stiffness matrix and element mass matrix. Then, based on the node number correspondence, all element matrices are assembled as a whole to obtain the initial global stiffness matrix and global mass matrix of the unit cell, thus realizing the transformation of an infinite-degree-of-freedom continuous problem into a finite-node-degree-of-freedom discretized problem.

[0064] 3. Introduction of periodic boundary conditions and matrix reduction Based on the phase constraint characteristics of Bloch's theorem in (3), the Floquet-Bloch periodic boundary conditions are applied using the master-slave degree-of-freedom method to correlate the displacements of opposite nodes in the unit cell and quantify the phase difference effect of the periodic structure. The left and lower boundaries of the unit cell are defined as master boundaries (degrees of freedom independent), and the right and upper boundaries as slave boundaries (degrees of freedom dependent on master boundaries). The master-slave boundary displacement correlation formula for a square unit cell is as follows:

[0065] in, respectively wave vector The horizontal and vertical components, is the lattice constant. is the Bloch complex phase factor.

[0066] Through the aforementioned phase correlation relationship, all redundant degrees of freedom from the boundary can be linearly represented by the independent degrees of freedom of the main boundary, thus constructing a degree-of-freedom transformation matrix. The overall matrix is ​​transformed by coordinate transformation and redundant variables are eliminated, ultimately reducing the matrix to obtain the result with respect to the wave vector. The relevant numerically solvable matrix is ​​transformed using the following formula:

[0067] in, The transformation matrix for wave vector correlation degrees of freedom is... This is the complex conjugate transpose operator. After this step, the final reduced stiffness matrix is ​​obtained. Reduce the quality matrix As a standard numerical matrix, it follows the theoretical generalized eigenvalue equation (3) to complete the final implementation of the theoretical model into an engineering computable numerical model.

[0068] Based on the phase constraint characteristics of Bloch's theorem, the Floquet-Bloch periodic boundary is applied using the master-slave degree-of-freedom method: the left and lower boundaries of the unit cell are set as master boundaries (degrees of freedom independent), and the right and upper boundaries are set as slave boundaries (degrees of freedom dependent on master boundaries); the master-slave boundary displacement correlation is established according to the wave vector phase relationship, and the redundant degrees of freedom of the slave boundaries are represented by the degrees of freedom of the master boundaries. After substituting them into the global matrix, redundant variables are eliminated, and finally, the result is obtained. Numericalized and directly solvable wave vector-dependent reduced stiffness and reduced mass matrices complete the final implementation of theoretical equations into engineering numerical models.

[0069] 4. Solution and Output Logic Based on the reduced numerical matrix, a standard generalized eigenvalue equation that can be directly solved by a computer is constructed, fully implementing the theoretical solution form of (3). The solution formula is as follows:

[0070] in, The nodal displacement eigenvectors This corresponds to the characteristic angular frequency.

[0071] To fully characterize the wave properties of periodic structures, along a square lattice, such as Figure 3 The irreducible Brillouin zone high symmetric path shown By uniformly discretizing the points, a series of scanning wave vectors are generated. Substitute these values ​​into the eigenvalue equations one by one to solve for the characteristic frequencies corresponding to each wave vector. Through frequency conversion formula After obtaining the sound wave frequency, a complete band dispersion curve is plotted, such as... Figure 4 As shown.

[0072] By iterating through all the solutions for discrete wave vectors, we can identify the complete bandgap region without characteristic frequencies and extract the core parameter: the bandgap existence indicator. , Bandgap center frequency , Bandgap bandwidth , Finally, a standardized parametric finite element energy band solver for input crystal cell geometric parameters and output bandgap performance parameters is constructed , realizing automated and batch solving of energy band characteristics.

[0073] Step S106: Input each matrix element into the finite element energy band solver for eigenvalue solving to obtain the bandgap characteristics corresponding to each matrix element.

[0074] After the establishment of the finite element energy band solver, each matrix element can be input into the finite element energy band solver for eigenvalue solving. The finite element energy band solver can output the bandgap characteristics corresponding to each matrix element through calculation.

[0075] In an optional implementation manner of this application, in order to improve the calculation efficiency, a parallel computing framework can be adopted for eigenvalue solving. According to the number of available computer CPU cores The two-dimensional parameter space grid matrix is divided into subdomains, and each core independently calls the finite element energy band solver to solve the bandgap characteristics corresponding to each matrix element within the corresponding subdomain. The bandgap characteristics are the standardized triple results: bandgap existence flag (Boolean value), bandgap center frequency , bandgap bandwidth . All calculation results are stored as a three-dimensional data cube , as Figure 5 shown, realizing batch solving of the full parameter space.

[0076] Among them, the eigenvalue solving for the matrix elements within multiple subdomains is processed in parallel. That is to say, K cores can parallelly call the finite element energy band solver to solve the bandgap characteristics corresponding to each matrix element within the corresponding subdomain.

[0077] Step S107: Design a target phononic crystal sound insulation body according to the reference size parameters and the matrix element with the largest bandgap bandwidth that meets the preset bandgap screening conditions.

[0078] The reference size parameters of the logging tool to be sound-insulated also include: the axial source distance TR between the transmitting transducer and the receiving transducer.

[0079] In order to prevent the target phononic crystal sound insulation body from covering the transducer working area of the logging tool to be sound-insulated, it is usually required that the total axial design length d of the target sound insulation body is less than the axial source distance TR between the transmitting transducer and the receiving transducer of the logging tool to be sound-insulated. That is, the constraint d < TR is satisfied, as Figure 2 shown.

[0080] Bandgap screening conditions are used to select effective bandgap features from all bandgap features that initially meet the sound insulation performance requirements. Since using preset bandgap screening conditions may select at least one effective bandgap feature, the matrix element (containing lattice constant and scatterer filling rate) corresponding to the bandgap feature with the largest bandwidth among all effective bandgap features that meet the preset screening conditions is used as the final design parameter. This parameter can be combined with the aforementioned requirement for the total axial design length d of the target sound insulation body, and the core design of the target phononic crystal sound insulation body can be performed based on the matrix element corresponding to the bandgap feature with the largest bandwidth. Figure 6 As shown, sound attenuation can be calculated by measuring the sound pressure difference between points A and B.

[0081] In one optional embodiment of this application, the preset bandgap screening conditions include: a bandgap existence flag indicating its existence, a bandgap center frequency within the range of bandgap center frequency values, and a bandgap bandwidth greater than or equal to the minimum bandgap bandwidth. Therefore, bandgap features that simultaneously satisfy the following constraints can be screened from the stored three-dimensional data cube: a bandgap existence flag indicating its existence, a bandgap center frequency within the range of bandgap center frequency values, and a bandgap bandwidth greater than or equal to the minimum bandgap bandwidth. , , ; The selected bandgap features are sorted in descending order of bandgap bandwidth. The matrix element corresponding to the bandgap feature with the largest bandgap bandwidth, namely the lattice constant and the scatterer filling rate, is selected. Based on the reference size parameters and the matrix element corresponding to the bandgap feature with the largest bandgap bandwidth, the target phononic crystal sound insulation body is designed.

[0082] By designing unit cells using a single material or by optimizing material properties, the interfacial adhesion problem of traditional metal-rubber composite structures can be avoided, thereby improving reliability and pressure resistance under high temperature and high pressure environments.

[0083] Step S108: During well logging operations, the designed target phononic crystal sound insulation body is used to perform acoustic logging sound insulation treatment on the sound-insulating well logging instrument.

[0084] After designing the target phonon crystal sound insulator according to step S107, the logging operation is officially started. During the operation, the designed target phonon crystal sound insulator is assembled on the outside of the logging instrument to be soundproofed. With the help of the bandgap sound insulation characteristics of the target phonon crystal sound insulator, external interference sound waves such as downhole fluid disturbance, tubing vibration and formation clutter are blocked, while the instrument's own sound wave leakage is suppressed. This completes the sound insulation protection of the logging instrument and creates good conditions for stable acquisition of acoustic logging data.

[0085] Figure 7This is a schematic diagram of sound attenuation per foot under certain parameters. It can be clearly seen from the diagram that the attenuation reaches its extreme value in certain frequency ranges.

[0086] This application solves the core problem of traditional sound insulation materials in acoustic logging by introducing the phononic crystal bandgap theory, and has the following advantages: High-efficiency sound insulation performance: This application utilizes the elastic wave bandgap characteristics of periodic lattice units to achieve highly efficient sound wave attenuation within a specific frequency band (such as the dominant frequency range of instrument waves). Compared to traditional grooved or composite structures (which only achieve partial attenuation through path extension or impedance difference), this application can directly block sound wave propagation within the bandgap frequency band, improving the signal-to-noise ratio of formation signals. This overcomes the bottlenecks of narrow bandwidth and low efficiency in existing technologies, and is particularly suitable for low-frequency instrument wave suppression.

[0087] Wideband adaptability: Through parametric modeling and optimization processes (grid scanning and bandgap constraints), stable sound insulation performance can be maintained over a wide frequency range. While traditional variable-diameter structures improve bandwidth, they are insufficient in suppressing low frequencies, whereas this method, based on band structure solutions, can cover a wider frequency band.

[0088] Excellent mechanical stability and reliability: The periodic cell design avoids the interfacial adhesion problems of traditional composite materials (such as metal-rubber combinations). The phonon crystal structure of this application utilizes a single material or optimizes material properties (density) ρ and elastic modulus E This technology can be implemented without complex processes, thereby improving pressure resistance and long-term stability. This reduces maintenance costs and is suitable for deep-sea or ultra-deep-well exploration.

[0089] Computational efficiency and scalability: Parallel computing frameworks significantly improve optimization speed. This is achieved through gridded parameter space (lattice constants). a and fill rate fr The K process calls the finite element band structure solver in parallel and ensures that the design meets the actual constraints through the feasible solution set, which can select the optimal solution in a short time.

[0090] Environmental adaptability: The method takes into account well condition limitations (such as the length of the sound insulation body). d Less than source distance TR And the design is made in accordance with actual constraints by using a FeasibleSet.

[0091] In summary, this application proposes a fully parameterized phononic crystal sound insulation design scheme based on the bandgap theory of phononic crystal elastic waves. Based on the designed phononic crystal sound insulation, acoustic logging sound insulation is performed. The coherent scattering effect of the periodic cell structure blocks the propagation of elastic waves in the target frequency band, breaking through the bottlenecks of traditional sound insulation materials such as narrow bandwidth, low efficiency, and poor mechanical stability, and providing a more reliable solution for acoustic logging under complex well conditions.

[0092] The acoustic logging sound insulation method based on phonon crystals provided in this application has high-efficiency sound insulation performance. It can utilize the bandgap characteristics of materials to accurately block sound wave propagation within the instrument's main operating frequency range, thereby significantly suppressing interference noise in formation signals and significantly improving the signal-to-noise ratio. Simultaneously, it has strong broadband adaptability, maintaining stable sound insulation effects over a wide frequency range. Optimized processes ensure efficient suppression of low-frequency bands. The single-material design enhances pressure resistance, effectively reducing the risk of failure under high-temperature and high-pressure environments, and exhibits outstanding mechanical stability, ensuring long-term reliable downhole operation. In the design and optimization stages, a parallel computing framework is adopted, offering high computational efficiency and good scalability, significantly shortening the design cycle. Combined with a feasibility set strategy, the technical solution's adaptability to actual well conditions is guaranteed, making it particularly suitable for complex exploration scenarios such as deep-sea and ultra-deep wells. Ultimately, this technology improves the overall data quality of acoustic logging and reduces equipment maintenance costs.

[0093] Figure 8 A structural block diagram of a acoustic logging sound insulation device based on a phonon crystal according to an embodiment of this application is shown, as follows: Figure 8 As shown, the device includes: The acquisition module 801 is adapted to acquire the dominant frequency range of the instrument wave corresponding to the soundproof logging instrument to be isolated. The bandgap constraint setting module 802 is adapted to set the bandgap constraint conditions of the target phononic crystal sound insulation body according to the dominant frequency range of the instrument wave. The determination module 803 is suitable for determining the material properties and scatterer filling rate range of the target phononic crystal sound insulation body, and for determining the lattice constant range of the target phononic crystal sound insulation body based on the reference size parameters and bandgap constraint conditions of the logging instrument to be sound-insulated. The spatial grid matrix construction module 804 is suitable for constructing a two-dimensional parametric spatial grid matrix based on the range of lattice constant values ​​and the range of scatterer filling rate values, wherein each matrix element corresponds to a set of parameter combinations including lattice constant and scatterer filling rate; The finite element band structure solver creation module 805 is suitable for creating a finite element band structure solver based on material properties. The finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics. The feature solving module 806 is adapted to input each matrix element into the finite element bandgap solver to solve for the feature, and obtain the bandgap feature corresponding to each matrix element. Design module 807 is suitable for designing target phononic crystal sound insulation body based on reference size parameters and matrix elements that meet preset bandgap screening conditions and have the largest bandgap bandwidth in the bandgap features. The sound insulation processing module 808 is suitable for performing acoustic logging sound insulation processing on the sound-insulating logging instrument by using the designed target phononic crystal sound insulation body during well logging operations.

[0094] Optionally, the dominant frequency range of the instrument wave is: The bandgap constraint conditions include: the bandgap center frequency range is [value missing]. The bandgap bandwidth range is , , This represents the maximum value within the dominant frequency range of the instrument wave. This represents the minimum value within the dominant frequency range of the instrument wave. This represents the minimum bandgap bandwidth.

[0095] Optionally, the preset bandgap screening conditions include: the bandgap existence flag is present, the bandgap center frequency is within the range of the bandgap center frequency value, and the bandgap bandwidth is greater than or equal to the minimum bandgap bandwidth. The design module is further adapted to: filter out bandgap features that are marked as having a bandgap presence, have a bandgap center frequency within the range of bandgap center frequency values, and have a bandgap bandwidth greater than or equal to the minimum bandgap bandwidth; The target phononic crystal sound insulation body is designed based on the reference size parameters and the matrix elements corresponding to the bandgap characteristics of the maximum bandgap bandwidth.

[0096] Optionally, the reference size parameters include: the outer diameter of the soundproof logging instrument to be soundproofed and the inner diameter of the soundproof logging instrument to be soundproofed; The determination module is further adapted to: determine the maximum value of the lattice constant range based on the outer diameter and inner diameter of the logging instrument to be soundproofed, and determine the minimum value of the lattice constant range based on the maximum value of the matrix longitudinal wave velocity and the dominant frequency range of the instrument wave.

[0097] Optionally, the spatial grid matrix construction module is further adapted to: uniformly discretely sample the range of lattice constant values ​​based on a first preset step size to obtain a sequence of lattice constants containing a first preset number; Based on the second preset step size, the range of scatterer fill rate values ​​is uniformly discretely sampled to obtain a scatterer fill rate sequence containing the second preset number; The lattice constant sequence and the scatterer fill rate sequence are combined to generate a two-dimensional parameter space grid matrix with a first preset number of dimensions × a second preset number of dimensions.

[0098] Optionally, the feature solving module is further adapted to: divide the two-dimensional parameter space grid matrix into multiple subdomains; For each subdomain, the finite element band structure solver is invoked, and each matrix element in the subdomain is input into the finite element band structure solver to solve for the characteristics, thereby obtaining the band gap characteristics corresponding to each matrix element in the subdomain. Multiple subdomains are processed in parallel.

[0099] Optionally, the finite element band structure solver module is further adapted to: establish the equilibrium equations corresponding to the instrument wave based on the material properties; Establish frequency domain elastic wave control equations based on the time-harmonic displacement and equilibrium equations of instrument waves; Based on Bloch's theorem, determine the Bloch displacement of the instrument wave propagating in the target phonon crystal with a periodic arrangement structure. The eigenvalue equations are determined based on the Bloch displacement and frequency domain elastic wave control equations. Finite element transformation is performed on the eigenvalue equations to obtain a finite element band structure solver.

[0100] The descriptions of the above modules refer to the corresponding descriptions in the method embodiments, and will not be repeated here.

[0101] The acoustic logging sound insulation device based on phonon crystals provided in this application has high-efficiency sound insulation performance. It can utilize the bandgap characteristics of the material to accurately block sound wave propagation within the instrument's main operating frequency range, thereby significantly suppressing interference noise in formation signals and significantly improving the signal-to-noise ratio. Simultaneously, it has strong broadband adaptability, maintaining stable sound insulation effects over a wide frequency range. Optimized processes ensure efficient suppression of low-frequency bands. The single-material design enhances pressure resistance, effectively reducing the risk of failure under high-temperature and high-pressure environments, and its outstanding mechanical stability ensures long-term reliable downhole operation. In the design and optimization phase, a parallel computing framework is adopted, offering high computational efficiency and good scalability, significantly shortening the design cycle. Combined with a feasibility set strategy, the technical solution's adaptability to actual well conditions is guaranteed, making it particularly suitable for complex exploration scenarios such as deep-sea and ultra-deep wells. Ultimately, this technology improves the overall data quality of acoustic logging and reduces equipment maintenance costs.

[0102] This application provides a non-volatile computer storage medium storing at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the acoustic logging sound insulation method based on phononic crystal in any of the above method embodiments.

[0103] This application provides a computer program product, which includes at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the acoustic logging sound insulation method based on phononic crystal in any of the above method embodiments.

[0104] Figure 9 The diagram shows a structural schematic of an embodiment of the computing device of this application. The specific embodiments of this application do not limit the specific implementation of the computing device.

[0105] like Figure 9 As shown, the computing device may include: a processor 902, a communications interface 904, a memory 906, and a communications bus 908.

[0106] The processor 902, communication interface 904, and memory 906 communicate with each other via communication bus 908. Communication interface 904 is used to communicate with other network elements such as clients or other servers. Processor 902 executes program 910, specifically performing the relevant steps in the embodiment of the acoustic logging sound insulation method based on phononic crystals for computing devices described above.

[0107] Specifically, program 910 may include program code that includes computer operation instructions.

[0108] The processor 902 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computing device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0109] Memory 906 is used to store program 910. Memory 906 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0110] Specifically, program 910 can be used to cause processor 902 to execute the acoustic logging sound insulation method based on phononic crystals in any of the above method embodiments. The specific implementation of each step in program 910 can be found in the corresponding descriptions of the steps and units in the above embodiments of acoustic logging sound insulation based on phononic crystals, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0111] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, the embodiments of this application are not directed to any particular programming language. It should be understood that the contents of the embodiments of this application described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best implementation of the embodiments of this application.

[0112] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0113] Similarly, it should be understood that, in order to simplify this disclosure and aid in understanding one or more of the various inventive aspects, in the foregoing description of exemplary embodiments of the present application, various features of the present application embodiments are sometimes grouped together into a single embodiment, figure, or description thereof. However, this approach to disclosure should not be construed as reflecting an intention that the claimed embodiments of the present application require more features than expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the present application.

[0114] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0115] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are meant to be within the scope of the embodiments of this application and form different embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

[0116] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of this application. The embodiments of this application can also be implemented as device or apparatus programs (e.g., computer programs and computer program products) for performing part or all of the methods described herein. Such programs implementing the embodiments of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0117] It should be noted that the above embodiments are illustrative of the embodiments of this application and not limiting of the embodiments of this application, and those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Embodiments of this application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

Claims

1. A sound insulation method for acoustic logging based on phonon crystals, comprising: Obtain the dominant frequency range of the instrument wave corresponding to the logging instrument to be soundproofed; Based on the dominant frequency range of the instrument wave, the bandgap constraint conditions of the target phononic crystal sound insulation body are set; Determine the material properties and scatterer filling rate range of the target phononic crystal sound insulator, and determine the lattice constant range of the target phononic crystal sound insulator based on the reference size parameters of the logging instrument to be sounded and the bandgap constraint conditions. A two-dimensional parameter space grid matrix is ​​constructed based on the range of values ​​for the lattice constant and the range of values ​​for the scatterer filling rate, wherein each matrix element corresponds to a set of parameter combinations including the lattice constant and the scatterer filling rate; A finite element band structure solver is established based on the material properties, wherein the finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics; Each matrix element is input into the finite element bandgap solver for feature solving, and the bandgap feature corresponding to each matrix element is obtained. Based on the aforementioned reference size parameters and the matrix element that satisfies the preset bandgap screening conditions and has the largest bandgap bandwidth among the bandgap features, a target phononic crystal sound insulation body is designed. During well logging operations, the sound-insulating treatment of the well logging instrument to be sound-insulated is performed using a designed target phononic crystal sound insulation body.

2. The method according to claim 1, wherein, The instrument's dominant frequency range is: The bandgap constraint conditions are set as follows: the bandgap center frequency range is [value missing]. The bandgap bandwidth range is , , This represents the maximum value within the dominant frequency range of the instrument wave. This represents the minimum value within the dominant frequency range of the instrument wave. This represents the minimum bandgap bandwidth.

3. The method according to claim 2, wherein, The preset bandgap screening conditions include: the bandgap existence flag is present, the bandgap center frequency is within the range of the bandgap center frequency value, and the bandgap bandwidth is greater than or equal to the minimum bandgap bandwidth. The step of designing the target phononic crystal sound insulation body based on the reference size parameters and the matrix element that satisfies the preset bandgap screening conditions and has the largest bandgap bandwidth in the bandgap features further includes: The bandgap features that are marked as present, have a bandgap center frequency within the range of bandgap center frequency values, and have a bandgap bandwidth greater than or equal to the minimum bandgap bandwidth are selected. Based on the reference size parameters and the matrix elements corresponding to the bandgap characteristics of the maximum bandgap bandwidth, the target phononic crystal sound insulation body is designed.

4. The method according to claim 2 or 3, wherein, The reference size parameters include: the outer diameter of the soundproof logging instrument to be soundproofed and the inner diameter of the soundproof logging instrument to be soundproofed; The step of determining the range of lattice constant values ​​corresponding to the target phononic crystal sound insulation body based on the reference size parameters of the logging instrument to be soundproofed and the bandgap constraint condition further includes: The maximum value of the lattice constant is determined based on the outer diameter and inner diameter of the logging instrument to be soundproofed, and the minimum value of the lattice constant is determined based on the maximum value of the matrix longitudinal wave velocity and the dominant frequency range of the instrument wave.

5. The method according to any one of claims 1-3, wherein, The step of constructing a two-dimensional parametric space grid matrix based on the range of lattice constant values ​​and the range of scatterer fill rate further includes: Based on a first preset step size, the range of lattice constant values ​​is uniformly discretely sampled to obtain a sequence of lattice constants containing a first preset number; Based on the second preset step size, the range of scatterer fill rate values ​​is uniformly discretely sampled to obtain a scatterer fill rate sequence containing the second preset number; The lattice constant sequence and the scatterer fill rate sequence are combined to generate a two-dimensional parameter space grid matrix with a first preset number of dimensions × a second preset number of dimensions.

6. The method according to any one of claims 1-3, wherein, The step of inputting each matrix element into the finite element bandgap solver for feature solving to obtain the bandgap feature corresponding to each matrix element further includes: Divide the two-dimensional parametric space grid matrix into multiple subdomains; For each subdomain, the finite element band structure solver is invoked, and each matrix element in the subdomain is input into the finite element band structure solver for feature solving, so as to obtain the band gap feature corresponding to each matrix element in the subdomain. Multiple subdomains are processed in parallel.

7. The method according to any one of claims 1-3, wherein, The step of establishing a finite element band structure solver based on the material properties further includes: Establish the equilibrium equations corresponding to the instrument waves based on the material properties described; The frequency domain elastic wave control equation is established based on the time-harmonic displacement of the instrument wave and the aforementioned equilibrium equation. Based on Bloch's theorem, determine the Bloch displacement of the instrument wave propagating in the target phonon crystal with a periodic arrangement structure. The eigenvalue equation is determined based on the Bloch displacement and the frequency domain elastic wave control equation. The eigenvalue equations are subjected to finite element transformation to obtain a finite element band structure solver.

8. A acoustic logging sound insulation device based on phonon crystal, comprising: The acquisition module is suitable for acquiring the dominant frequency range of the instrument wave corresponding to the soundproof logging instrument to be soundproofed; The bandgap constraint setting module is adapted to set the bandgap constraint conditions of the target phononic crystal sound insulation body according to the dominant frequency range of the instrument wave; The determination module is suitable for determining the material properties and scatterer filling rate range of the target phononic crystal sound insulator, and for determining the lattice constant range of the target phononic crystal sound insulator based on the reference size parameters of the logging instrument to be sounded and the bandgap constraint conditions. A spatial grid matrix construction module is adapted to construct a two-dimensional parametric spatial grid matrix based on the range of values ​​of the lattice constant and the range of values ​​of the scatterer filling rate, wherein each matrix element corresponds to a set of parameter combinations including the lattice constant and the scatterer filling rate; A finite element band structure solver establishment module is adapted to establish a finite element band structure solver based on the material properties, wherein the finite element band structure solver is a solver whose input is matrix elements and whose output is band gap characteristics; The feature solving module is adapted to input each matrix element into the finite element bandgap solver to solve for the feature, thereby obtaining the bandgap feature corresponding to each matrix element. The design module is adapted to design a target phononic crystal sound insulation body based on the reference size parameters and the matrix element that meets the preset bandgap screening conditions and has the largest bandgap bandwidth in the bandgap features. The sound insulation module is suitable for using a designed target phononic crystal sound insulation body to perform acoustic logging sound insulation treatment on the logging instrument to be sound-insulated during well logging operations.

9. A computing device, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the acoustic logging sound insulation method based on phononic crystal as described in any one of claims 1-7.

10. A computer storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the acoustic logging sound insulation method based on phononic crystals as described in any one of claims 1-7.

11. A computer program product comprising at least one executable instruction that causes a processor to perform an operation corresponding to the acoustic logging sound insulation method based on phononic crystals as described in any one of claims 1-7.

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