Dipole shear wave remote sensing method, system and electronic equipment for azimuth localization of geological bodies

Abstract

This application provides a method, system, and electronic device for azimuth localization of geological bodies using dipole shear waves. The method includes: alternately exciting two sets of orthogonally polarized shear waves using a dual-dipole acoustic source in each borehole to form an azimuth-sensitive wavefield; acquiring four-component data generated after reflection of the azimuth-sensitive wavefield by the downhole geological body using an orthogonal dipole array; performing well-circumferential scanning imaging on the four-component data to obtain a reflected acoustic imaging profile; extracting the target geological body from the dominant azimuth of energy focusing in the reflected acoustic imaging profile and calculating the corresponding geological body parameters; integrating the geological body parameters corresponding to each borehole to form a multi-well geological body parameter set; and performing multi-well coverage statistics based on the multi-well geological body parameter set to obtain the true azimuth of the target geological body in the target exploration area. This application solves the problem of azimuth ambiguity in shear wave long-range geological body detection caused by wavefield symmetry in existing technologies, and achieves high-precision three-dimensional inversion and unique localization of geological bodies.

Description

Technical Field

[0001] This application belongs to the field of engineering geophysical exploration technology, and relates to a method, system and electronic equipment for azimuth positioning of geological bodies using dipole shear waves. Background Technology

[0002] In dipole shear wave long-range detection technology, because the shear waves generated by the dipole acoustic source have strict polarization characteristics, their reflected wave field exhibits a centrally symmetric spatial response characteristic under single-well observation conditions. Specifically, when the normal direction of the geological reflection interface forms a certain azimuth angle with the well axis... At that time, its mirror image orientation The resulting reflected waves are completely consistent in travel time, amplitude polarity, and four-component received data. In traditional single-well dipole shear wave imaging processing, after conventional azimuth corrections such as Alford rotation, the imaging results are... and The energy is symmetrically distributed in two directions, making it impossible to distinguish the true inclination of the geological body; only its direction can be identified.

[0003] To overcome these existing limitations, various technical approaches have been designed in this field. For example, a circumferential multi-azimuth sensor array can be added to the receiver to determine azimuth based on the amplitude differences of signals received from different azimuths; or an instrument eccentricity measurement scheme can be introduced to jointly determine the true azimuth using the maximum amplitude angle and phase difference of the synthesized signal. However, the above methods have extremely high requirements for hardware consistency, wellbore regularity, and environmental stability, and even small system errors or noise interference can easily lead to azimuth misjudgment. Other studies have attempted to combine P-waves, Stoneley waves, or multi-wave joint inversion, but because shear waves are significantly more sensitive to azimuth changes than other wave types, and the time difference between fast and slow shear waves can only constrain the azimuth range from 0° to 180°, it is still impossible to overcome the mathematical limitations of wavefield symmetry. Summary of the Invention

[0004] This application provides a method, system, and electronic device for azimuth localization of geological bodies using dipole shear waves, which solves the problem of ambiguity in the azimuth of geological bodies in shear wave long-range detection caused by wave field symmetry in existing technologies.

[0005] In a first aspect, this application provides a method for azimuth positioning of geological bodies using dipole shear waves, applied to a multipole array acoustic logging tool. The multipole array acoustic logging tool performs logging operations in multiple boreholes arranged in a grid within a target exploration area. The multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual-dipole acoustic source, and the acoustic wave receiving device is equipped with an orthogonal dipole array. The method includes:

[0006] In each of the aforementioned boreholes, two sets of orthogonally polarized transverse waves are alternately excited by the dual dipole sound source at a preset misalignment angle, forming an azimuth-sensitive wave field with azimuth and phase difference characteristics.

[0007] The orthogonal dipole array is used to acquire four-component data of the azimuth-sensitive wavefield after reflection by the downhole geological body.

[0008] Based on a dynamic weighted stacking algorithm, well-circumferential scanning imaging is performed on the four-component data to obtain a reflected acoustic imaging profile. Based on a multi-parameter fusion azimuth and range joint inversion algorithm, the target geological body is extracted from the dominant azimuth of energy focusing in the reflected acoustic imaging profile, and the corresponding geological body parameters are calculated. The geological body parameters include distance from the well, true dip angle, depth range, true apparent azimuth angle and its mirror azimuth angle.

[0009] The geological parameters obtained from the inversion of each borehole are integrated to form a multi-well geological parameter set;

[0010] Based on the multi-well geological body parameter set, multi-well coverage statistics based on spatial gridding and Bayesian inference are performed to obtain the true location of the target geological body in the target exploration area.

[0011] In one implementation of the first aspect, the method further includes: performing time-domain waveform feature enhancement and dispersion characteristic compensation preprocessing on the four-component data before performing well-circumferential scanning imaging on the four-component data; wherein the time-domain waveform feature enhancement of the four-component data includes:

[0012] Based on the spatial correlation of the four-component data, an orientation-sensitive operator matrix is ​​constructed. :

[0013] ;

[0014] In the formula The preset azimuth scanning angle, and ;

[0015] Based on the four-component data, calculate the cross-correlation matrix of the four-component data within the time window. The cross-correlation matrix is ​​used to reflect the phase and amplitude relationship between different receiving channels.

[0016] Based on the orientation-sensitive operator matrix and the cross-correlation matrix And by combining the time window function W, the polarization components of different orientation scanning angles are extracted. :

[0017] ;

[0018] In the formula, W is the time window function. Let be the cross-correlation matrix. To scan at the azimuth angle The polarization components extracted below; It is at the preset azimuth scanning angle Energy measurement of the signal after polarization filtering;

[0019] The dispersion compensation for the four-component data includes:

[0020] Based on the unique dispersion effect of long-range detection, a dispersion correction model related to the sound source frequency and depth is established:

[0021] ;

[0022] In the formula For reference phase velocity, Here, z is the dispersion intensity coefficient, and z is the depth. For the frequency of the sound source, For reference frequency, This indicates that at a depth of z and a sound source frequency of z Wave propagation phase velocity at time;

[0023] Based on the aforementioned dispersion correction model, an inverse dispersion operator is constructed for phase correction of signals in the frequency domain;

[0024] Based on the aforementioned inverse frequency dispersion operator, phase compensation and reconstruction are performed on the four-component data channel by channel.

[0025] In one implementation of the first aspect, based on a dynamic weighted superposition algorithm, well-circumferential scanning imaging is performed on the four-component data to obtain a reflected acoustic imaging profile, including:

[0026] Establish a mapping model between the azimuth scan angle and the four-component data. :

[0027] ,

[0028] In the formula For orientation-dependent adaptive weighting functions; The four-component data are defined as follows: m=1 represents the XX component data, m=2 represents the XY component data, m=3 represents the YX component data, and m=4 represents the YY component data. This is the azimuth-range-time domain imaging result;

[0029] Scanning angles around the well in all directions Based on the mapping model Calculate the scanning angle in each direction The energy response under the condition is used to obtain the reflected acoustic wave imaging profile; in the reflected acoustic wave imaging profile, the energy at the true azimuth is focused to form the main lobe, while the energy at the false azimuth is suppressed to form the side lobes.

[0030] One implementation of the first aspect also includes:

[0031] The advantageous azimuth for energy focusing of the reflected acoustic imaging profile is determined using an objective function that enhances azimuth resolution; the expression for the objective function is:

[0032] ,

[0033] In the formula, N represents the total number of resolvable geological bodies around the well; w k For the adaptive weight of the k-th geological body, , Let be the signal-to-noise ratio of the k-th reflected signal; λ is the polarity-time joint coefficient. This is the polarity response term, reflecting the degree of matching between the polarization direction of the reflected wave and the transmitting / receiving device; τ is the difference between the actual and theoretical travel time of the k-th geological body; τ is the normalized time window calibration parameter used to control the main lobe width of the sinc function.

[0034] In one implementation of the first aspect, a joint azimuth and range inversion algorithm based on multi-parameter fusion is used to extract the target geological body from the advantageous azimuth of the reflected acoustic imaging profile energy focusing, and to calculate the corresponding geological body parameters, including:

[0035] Based on the preset azimuth-distance constraint formula, the polarization angle of the reflected wave is calculated. The orientation-distance constraint relationship is as follows:

[0036] ,

[0037] In the formula S ij Let be the energy integral of the component data ij, where {i,j∈{X,Y};

[0038] Based on instrument orientation correction angle Calculate the true viewing azimuth angle θ; wherein the formula for calculating the true viewing azimuth angle θ is:

[0039] ,

[0040] In the formula S ij Let i be the energy integral of the component data ij, where {i,j∈{X,Y}. This is the azimuth correction angle for the instrument;

[0041] The true tilt angle α is calculated based on the amplitude ratio of the component data; wherein the amplitude ratio of the component data is defined as:

[0042] ,

[0043] In the formula A ij Let be the amplitude of the component data ij, {i,j∈{X,Y};

[0044] The formula for calculating the true inclination angle α is:

[0045] ,

[0046] In the formula It is an anisotropic compensation factor;

[0047] Distance from well The calculation formula is:

[0048] ,

[0049] In the formula v s Let ΔT be the transverse wave velocity, ΔT be the arrival time difference between the XY and YX components, and θ be the true apparent azimuth angle. The polarization angle of the reflected wave;

[0050] The formula for calculating the depth range Z is:

[0051] ,

[0052] In the formula, Z0 is the initial depth of the reflector as determined by drilling data, D is the distance from the well, and α is the true dip angle. θ is the wellbore inclination angle, γ is the actual apparent azimuth angle, and γ is the wellbore azimuth angle.

[0053] One implementation of the first aspect also includes:

[0054] Based on the principle of acoustic interference, the target reflector is simultaneously mapped to the true viewing azimuth θ and its mirror azimuth θ+180°, and the confidence of the two mapping directions is quantified to obtain the confidence scores of the true viewing azimuth θ and the mirror azimuth θ+180°.

[0055] In one implementation of the first aspect, the dual-dipole sound source includes a first dipole sound source and a second dipole sound source, wherein the first dipole sound source is arranged along the X-axis of the downhole coordinate system, and the second dipole sound source is offset from the X-axis by a preset angle. Non-orthogonal arrangement, among which Furthermore, the axial center distance between the first dipole sound source and the second dipole sound source is less than one-quarter of the preset transverse wave wavelength c, and the emission phase difference is... .

[0056] In one implementation of the first aspect, performing multi-well coverage statistics based on spatial gridding and Bayesian inference, based on the multi-well geological body parameter set, includes:

[0057] Construct the reflector identifier vector R k :

[0058] ,

[0059] In the formula Let k be the distance from the well to the kth geological body. Let be the true dip angle of the k-th geological body. Let k be the depth of the k-th geological body. This represents the true apparent azimuth of the k-th geological body;

[0060] The target exploration area is divided into several grid cells according to a preset grid resolution: the grid cell is represented as follows:

[0061] ,

[0062] ,

[0063] ,

[0064] ;

[0065] In the formula This represents the initial boundary of the mesh element in the X-axis direction. For the termination boundary, Δx i The width of the grid cell; Let be the upper boundary of the mesh cell in the Y-axis direction. Let Δy be the lower boundary. j The height of the grid cell; Let be the upper boundary of the mesh cell in the Z-axis direction. Let Δz be the lower boundary. k The depth of the mesh cell;

[0066] The grid resolution is:

[0067] ,

[0068] In the formula, c is the wavelength of the transverse wave, and v s f is the transverse wave velocity. max The highest sound source frequency;

[0069] A geological body-grid mapping function Γ is established to project each geological body onto its corresponding grid cell; wherein the expression of the geological body-grid mapping function Γ is:

[0070] ,

[0071] Based on the Bayesian posterior probability model, the grid cell G ijk Total number of times the geological bodies in each borehole were covered:

[0072] ,

[0073] In the formula, M is the total number of boreholes in the target exploration area, and N is... m Let m be the number of geological bodies in the m-th borehole, where m ∈ M. This is an indicator function used to establish the association between geological bodies and grid cells;

[0074] Based on the total number of coverage counts, the probability of the existence of a real reflector is calculated; the formula for calculating the probability of the existence of a real reflector is:

[0075] .

[0076] Secondly, this application provides a dipole shear wave remote sensing geological body azimuth positioning system, comprising:

[0077] A multipole array acoustic logging tool is used to perform logging operations in multiple boreholes arranged in a grid within a target exploration area. The multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual dipole sound source and the acoustic wave receiving device is equipped with an orthogonal dipole array.

[0078] A geological body orientation positioning device is communicatively connected to the multipole array acoustic logging tool and is used to perform the method described in any of the above descriptions.

[0079] Thirdly, this application provides an electronic device, comprising:

[0080] The memory is used to store computer programs;

[0081] A processor, the processor being configured to execute a computer program stored in the memory, so as to cause the electronic device to perform the method described in any of the preceding descriptions.

[0082] As described above, the dipole shear wave remote sensing geological body azimuth positioning method, system, and electronic equipment described in this application have the following beneficial effects:

[0083] (1) By adopting a double dipole sound source misalignment layout, and combining a compact layout with an axial center spacing less than one-quarter of the transverse wave wavelength with a time-controlled alternating excitation mechanism, an asymmetric wave field excitation architecture was constructed, breaking the symmetry of the wave field in traditional acoustic logging and realizing precise control of the synthetic beam direction.

[0084] (2) By using adaptive weighted well perimeter scanning and polarization-to-time difference dual feature fusion, the bimodal symmetrical response mode commonly found in traditional imaging is improved to the main lobe-side lobe separation mode, which greatly enhances the energy focusing of the true orientation and effectively suppresses mirror or reverse false responses.

[0085] (3) By transforming the reflector from the local downhole coordinate system to the global geographic coordinate system, precise depth positioning of the spatial location of the distant detection target was achieved;

[0086] (4) By using bidirectional azimuth mapping confidence quantification and Bayesian multi-well coverage statistics, the full-space uniqueness determination of the true azimuth of geological bodies is realized, effectively eliminating the 180° azimuth ambiguity in dipole shear wave remote detection. Attached Figure Description

[0087] Figure 1 The diagram shown is a schematic representation of the grid arrangement of boreholes within the target exploration area according to an embodiment of this application.

[0088] Figure 2 The flowchart shown is a method for azimuth positioning of geological bodies using dipole shear waves according to an embodiment of this application.

[0089] Figure 3 The image shown is a schematic diagram of a three-dimensional geological body according to an embodiment of this application.

[0090] Figure 4 The diagram shown illustrates the principle of real and dummy reflectors covering each other under multi-aperture intersection conditions according to an embodiment of this application.

[0091] Figure 5 The diagram shows the orientation interpretation results of the reflectors of four boreholes according to an embodiment of this application.

[0092] Figure 6 The diagram shown is a structural schematic of a dipole transverse wave remote detection geological body orientation positioning system according to an embodiment of this application.

[0093] Figure 7 The diagram shown is a structural schematic of an electronic device according to an embodiment of this application. Detailed Implementation

[0094] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0095] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0096] The following embodiments of this application provide a method, system, and electronic device for azimuth localization of geological bodies using dipole shear waves. This application solves the problem of ambiguity in the azimuth of geological bodies caused by wave field symmetry in existing technologies by designing a three-in-one technical architecture of "dual-source excitation – multi-pore convergence – statistical inference". It achieves high-precision three-dimensional inversion and unique localization of the true azimuth, distance from the well, true dip angle, and depth of the geological body.

[0097] The dipole shear wave remote detection geological body positioning method described in this application is applied to a multipole array acoustic logging tool, which performs logging operations in multiple boreholes arranged in a grid within the target exploration area.

[0098] Please see Figure 1 The image shows a schematic diagram of the grid arrangement of boreholes within the target exploration area according to an embodiment of this application.

[0099] like Figure 1 As shown, the target exploration area has four symmetrically distributed boreholes (i.e., wells), located at the four vertices of a square grid. The spacing between each borehole is reasonably designed according to the detection depth and shear wave wavelength to ensure effective cross-coverage of the same underground geological body.

[0100] Specifically, the multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual dipole acoustic source, and the acoustic wave receiving device is equipped with an orthogonal dipole array.

[0101] The following will describe in detail the principle and implementation of a dipole shear wave remote detection method, system and electronic equipment for azimuth positioning of geological bodies according to this embodiment, so that those skilled in the art can understand the dipole shear wave remote detection method, system and electronic equipment for azimuth positioning of geological bodies according to this embodiment without creative labor.

[0102] Please see Figure 2 The above is a flowchart of a method for azimuth positioning of geological bodies using dipole transverse wave remote sensing according to an embodiment of this application.

[0103] like Figure 2 As shown, this embodiment provides a method for azimuth positioning of geological bodies using dipole shear waves, including the following steps S100 to S600.

[0104] In step S100, in each of the boreholes, two sets of orthogonally polarized transverse waves are alternately excited by the double dipole sound source at a preset misalignment angle to form an azimuth-sensitive wave field with azimuth and phase difference characteristics.

[0105] In one embodiment of this application, the dual dipole sound source includes a first dipole sound source (T1) and a second dipole sound source (T2), wherein the first dipole sound source is arranged along the X-axis of the downhole coordinate system, and the second dipole sound source is offset from the X-axis by a preset misalignment angle. Non-orthogonal arrangement, among which Furthermore, the axial center distance d between the first dipole sound source and the second dipole sound source is less than one-quarter of the preset transverse wave wavelength c, i.e. , f is the transverse wave velocity. c The center frequency is given, and the emission phase difference between the first dipole sound source and the second dipole sound source is given. .

[0106] In this embodiment, the double dipole sound source is positioned at a preset misalignment angle. The arrangement is non-orthogonal, where T1 excites a linearly polarized shear wave along the X-axis of the downhole coordinate system, while T2 excites a linearly polarized shear wave along an angle with the X-axis. The direction of the excitation generates a secondary transverse wave with a rotational polarization component. Through this asymmetric arrangement, the dual-dipole sound source actively breaks the system symmetry, thereby achieving azimuth decoupling.

[0107] In one embodiment of this application, the dual-dipole sound source employs a time-controlled alternating emission mechanism to construct a directional wave field with orientation sensitivity.

[0108] Specifically, the time-domain excitation signal of the double-dipole sound source can be expressed as:

[0109] ,

[0110] in,

[0111] ,

[0112] ,

[0113] In the formula The amplitude of the reflected wave emitted by the first dipole sound source is given. The amplitude of the reflected wave emitted by the second dipole sound source. Let f be the envelope function. c The center frequency is Δθ, and the preset offset angle is Δθ. For launch delay.

[0114] During the time-controlled alternating transmission process, T1 and T2 are... The phase difference operates alternately, with a transmission delay Δt ∈ [0.1 ms, 1 ms], causing the linear polarization component in the X-axis direction to coherently superimpose with the rotational polarization component in the Δθ direction, thereby forming a composite beam with enhanced amplitude in a specific orientation. By fine-tuning Δθ (e.g., adjusting within ±5°), the pointing of the main lobe of the wavefield can be precisely controlled, achieving directional scanning within a ±10° range, while maintaining good orthogonal polarization characteristics and effectively suppressing multipath interference.

[0115] In this implementation, an asymmetric wavefield excitation architecture is constructed by adopting a staggered layout of dual dipole sound sources, combined with a compact layout where the axial center spacing is less than one-quarter of the shear wave wavelength and a time-controlled alternating excitation mechanism. This breaks the symmetry of the wavefield in traditional acoustic logging and enables precise control of the synthetic beam direction.

[0116] In step S200, the four-component data of the azimuth-sensitive wavefield after reflection by the downhole geological body are acquired by the orthogonal dipole array.

[0117] Specifically, the orthogonal dipole array used is an asymmetric triaxial receiver, with a preset tilt angle ∈ [13°, 17°] between its Z-axis and the normal to the XY plane. The sensitivity deviation of each channel is strictly controlled within: , This is to ensure the consistency and fidelity of multi-component data.

[0118] The collected four-component data is represented as (XX, XY, YX, YY), where XX represents the same polarization component transmitted and received in the X direction; YY represents the same polarization component transmitted and received in the Y direction; XY represents the cross-polarization component transmitted and received in the X direction; and YX represents the cross-polarization component transmitted and received in the Y direction.

[0119] In this embodiment, the acquired four-component data is a time-domain signal. To prevent the weak far-field reflection signal from being suppressed in subsequent processing, this application further includes applying dynamic gain compensation to the time-domain signal in one embodiment.

[0120] Specifically, the following exponential gain function is adopted:

[0121] G(t) = G0 × e at ,

[0122] in,

[0123] ,

[0124] In the formula, G0 is the initial gain coefficient, v s For transverse wave velocity, t represents the maximum distance from the well (i.e., the maximum detection distance), and t is a time variable. The typical value is 30m.

[0125] This dynamic gain mechanism can adaptively enhance far-field signals according to propagation distance, effectively improving the signal-to-noise ratio of deep or weakly reflective events, while avoiding near-field signal oversaturation, providing a high-quality data foundation for subsequent orientation-sensitive imaging and inversion.

[0126] In step S300, based on the dynamic weighted superposition algorithm, well perimeter scanning imaging is performed on the four-component data to obtain a reflected acoustic imaging profile.

[0127] In one embodiment of this application, the method further includes: performing time-domain waveform feature enhancement and dispersion characteristic compensation preprocessing on the four-component data before performing well-circumferential scanning imaging on the four-component data.

[0128] The time-domain waveform feature enhancement is achieved through polarization filtering, which can effectively separate and accurately extract spatial signal components related to the azimuth response of geological bodies. The dispersion characteristic compensation is used to correct waveform distortion caused by dispersion effects when shear waves propagate in non-uniform media.

[0129] In one embodiment of this application, time-domain waveform feature enhancement of the four-component data includes the following steps S301 to S303.

[0130] In step S301, based on the spatial correlation of the four-component data, an orientation-sensitive operator matrix is ​​constructed. :

[0131] ;

[0132] In the formula The preset azimuth scanning angle, and .

[0133] In step S302, based on the four-component data, the cross-correlation matrix of the four-component data within the time window is calculated. .

[0134] The cross-correlation matrix is ​​used to reflect the phase and amplitude relationship between different receiving channels.

[0135] In step S303, based on the orientation-sensitive operator matrix and the cross-correlation matrix And by combining the time window function W, the polarization components of different orientation scanning angles are extracted. :

[0136] ;

[0137] In the formula, W is the time window function, used to suppress noise and retain the effective signal. Let be the cross-correlation matrix. To scan at the azimuth angle The polarization components extracted below; It is at the preset azimuth scanning angle The energy measure of the signal after polarization filtering.

[0138] In one embodiment of this application, the dispersion characteristic compensation of the four-component data includes the following steps S304 to S306.

[0139] In step S304, based on the dispersion effect unique to far-field detection, a dispersion correction model related to the sound source frequency and depth is established:

[0140] ;

[0141] In the formula For reference phase velocity, Here, z is the dispersion intensity coefficient, and z is the depth. For the frequency of the sound source, For reference frequency, This indicates that at a depth of z and a sound source frequency of z The wave propagation phase velocity at time.

[0142] In step S305, based on the dispersion correction model, an inverse dispersion operator is constructed for phase correction of the signal in the frequency domain.

[0143] In step S306, based on the inverse frequency dispersion operator, phase compensation and reconstruction are performed on the four-component data channel by channel.

[0144] In this implementation, the signal-to-noise ratio of the weak reflection signal is significantly improved by the dispersion characteristic compensation, and the time-frequency structure of the original waveform is restored, thereby providing high-fidelity and high-resolution time-frequency feature input for subsequent azimuth estimation, anisotropy analysis or target recognition.

[0145] In one embodiment of this application, the well perimeter scanning imaging of the four-component data is performed based on a dynamic weighted superposition algorithm to obtain a reflected acoustic imaging profile, including the following steps S307 and S308.

[0146] In step S307, a mapping model between the azimuth scan angle and the four-component data is established. :

[0147] ,

[0148] In the formula For orientation-dependent adaptive weighting functions; The four-component data are defined as follows: m=1 represents the XX component data, m=2 represents the XY component data, m=3 represents the YX component data, and m=4 represents the YY component data. This is the azimuth-range-time domain imaging result.

[0149] In step S308, traverse all azimuth scanning angles around the well. Based on the mapping model Calculate the scanning angle in each direction The energy response under the condition is used to obtain the reflected acoustic wave imaging profile.

[0150] In the reflected acoustic imaging profile, the energy from the true orientation is focused to form the main lobe, while the energy from the false orientation is suppressed to form side lobes.

[0151] In one embodiment of this application, the method for azimuth localization of geological bodies using dipole shear waves further includes: using an objective function that enhances azimuth resolution to determine the advantageous azimuth for energy focusing of the reflected acoustic imaging profile.

[0152] Specifically, the expression for the objective function is:

[0153] ,

[0154] In the formula, N represents the total number of resolvable geological bodies around the well; w k For the adaptive weight of the k-th geological body, , Let be the signal-to-noise ratio of the k-th reflected signal; λ is the polarity-time joint coefficient. This is the polarity response term, reflecting the degree of matching between the polarization direction of the reflected wave and the transmitting / receiving device; τ is the difference between the actual and theoretical travel time of the k-th geological body; τ is the normalized time window calibration parameter used to control the main lobe width of the sinc function.

[0155] In this embodiment, a polarity-time joint processing strategy is adopted: when When (i.e., in the reverse false orientation region), the weight w k Introducing a polarity correction factor This weakens the reverse response. Verified by actual measurement data, this mechanism can neutralize false azimuth (such as...) The energy of the main lobe is suppressed to less than 15% of the main lobe energy.

[0156] Furthermore, by iteratively optimizing the objective function E(θ), and with the preferred configuration of λ=0.7, the azimuth resolution of this application is significantly improved compared to traditional methods that rely solely on travel time or solely on energy.

[0157] In this implementation, by using adaptive weighted well-circumferential scanning and polarization-to-time difference dual feature fusion, the bimodal symmetrical response mode commonly found in traditional imaging is improved into a main lobe-side lobe separation mode, which greatly enhances the energy focusing of the true orientation and effectively suppresses mirror or reverse false responses.

[0158] In step S400, based on the multi-parameter fusion azimuth and distance joint inversion algorithm, the target geological body is extracted from the advantageous azimuth of the reflected acoustic imaging profile energy focusing, and the corresponding geological body parameters are calculated.

[0159] Specifically, the geological body parameters include distance from the well, true dip angle, depth range, true apparent azimuth angle and its mirror azimuth angle.

[0160] In one embodiment of this application, the target geological body is extracted from the advantageous azimuth of the reflected acoustic imaging profile based on a multi-parameter fusion azimuth and range joint inversion algorithm, and the corresponding geological body parameters are calculated, including the following steps S401 to S400:

[0161] In step S401, the polarization angle of the reflected wave is calculated based on the preset azimuth-distance constraint relationship. .

[0162] Specifically, the orientation-distance constraint relationship is as follows:

[0163] ,

[0164] In the formula S ij Let be the energy integral of the component data ij, where {i,j∈{X,Y}.

[0165] In step S402, based on the instrument azimuth correction angle Calculate the true viewing azimuth angle θ.

[0166] Specifically, the formula for calculating the true viewing azimuth angle θ is as follows:

[0167] ,

[0168] In the formula S ij Let i be the energy integral of the component data ij, where {i,j∈{X,Y}. The azimuth correction angle for the instrument.

[0169] In step S403, the true tilt angle α is calculated based on the amplitude ratio of the component data.

[0170] Specifically, the amplitude ratio of the component data is defined as:

[0171] ,

[0172] In the formula Aij Let be the amplitude of the component data ij, {i,j∈{X,Y};

[0173] The formula for calculating the true inclination angle α is:

[0174] ,

[0175] In the formula It is an anisotropy compensation factor used to correct amplitude distortion caused by formation shear wave anisotropy.

[0176] In one embodiment of this application, the method further includes employing an anisotropic real-time compensation mechanism to dynamically update the anisotropic compensation factor k by analyzing the propagation speed of fast and slow shear waves in real time.

[0177] Specifically, the compensation item is determined by the following formula:

[0178] ,

[0179] In the formula For anisotropic perturbation terms, they can be estimated in real time based on the measured waveform splitting time difference or inversion model; For the difference in speed between fast and slow shear waves, ; The average shear wave velocity; This is the true azimuth scanning angle.

[0180] In this implementation, the true dip angle α of the geological body can be inverted by establishing a quantitative relationship between the amplitude ratio R and the anisotropy compensation factor k. Through the effective correction of the shear wave splitting effect by the real-time anisotropy compensation mechanism, the dip angle inversion error can be controlled within 5°, thereby significantly improving the accuracy and reliability of tectonic interpretation.

[0181] In step S404, the distance from the well is calculated. .

[0182] Specifically, distance from the well The calculation formula is:

[0183] ,

[0184] In the formula v s ΔT is the transverse wave velocity, ΔT is the arrival time difference between the XY and YX components, θ is the true apparent azimuth angle, and φ is the polarization angle of the reflected wave.

[0185] In step S405, the depth range Z is calculated.

[0186] In one embodiment of this application, the formula for calculating the depth range Z is:

[0187] ,

[0188] In the formula, Z0 is the initial depth of the reflector as determined by drilling data, D is the distance from the well, α is the true dip angle, σ is the well inclination angle, θ is the actual apparent azimuth angle, and γ is the wellbore azimuth angle.

[0189] In this embodiment, the calculation formula for the depth range Z integrates multiple parameters such as the distance from the well D, the true inclination angle α, the well inclination angle σ, and the wellbore azimuth angle γ, to construct a strict three-dimensional spatial geometric constraint relationship.

[0190] Specifically, the true dip angle can be obtained by inversion in step S403; the well inclination angle represents the angle between the wellbore axis and the vertical direction, and the wellbore azimuth angle represents the direction of the well inclination projection on the horizontal plane, usually with true north as the reference.

[0191] In this implementation, by transforming the reflector from the local downhole coordinate system to the global geographic coordinate system, precise depth positioning of the spatial location of the distant detection target is achieved.

[0192] In one embodiment of this application, the phase difference between the polarization direction of the reflected wave and the normal to the incident plane satisfies the following condition:

[0193] ,

[0194] In the formula, D is the distance from the well. θ is the preset misalignment angle of the double dipole sound source, c is the transverse wave wavelength, and θ is the wavelength of the transverse wave. r Let be the true apparent azimuth of the r-th geological body.

[0195] In this embodiment, when At that time, phase difference In θ r With θ r The value varies at +180°, causing a time difference (Δt) in the arrival of the reflected wave at the sound receiving device. XY ,Δt YX ) and amplitude polarity (P XX ,P YY It exhibits asymmetry.

[0196] In one embodiment of this application, the method further includes: based on the principle of acoustic interference, simultaneously mapping the target reflector to the true viewing azimuth angle θ and its mirror azimuth angle θ+180°, and quantifying the confidence of the two mapping directions to obtain the confidence scores of the true viewing azimuth angle θ and the mirror azimuth angle θ+180°.

[0197] Specifically, the normalized amplitude A of the reflected wave is extracted at the k-th borehole azimuth θ position. k And, combined with the measured transmit-receive azimuth deviation angle Δψ, the theoretical correction amplitude is calculated. :

[0198] .

[0199] In one embodiment of this application, a positional weighting function can be used. Evaluate the reliability of the mapping. The positional weighting function... Only and Two candidate orientations are assigned weights, while the weights of the remaining orientations are reset to zero, in order to focus on the physically possible solution space.

[0200] Measured data show that when the reflection-receiver azimuth deviation angle Δψ < 15°, the reflection amplitude attenuation at the mirror azimuth θ+180° is ≤ 30%. However, due to the asymmetry of polarization response and phase interference, the confidence scores between θ and θ+180° show a significant difference. At this point, the confidence difference in bidirectional mapping is significant.

[0201] In this implementation, a precise spatial transformation relationship between the geological coordinate system and the wellbore coordinate system is established, enabling high-precision calibration of the three-dimensional position of the reflector. The calibration results include: distance from the wellbore D, the true apparent azimuth angle θ and its symmetric solution θ+180°, the true dip angle α, and the corresponding well depth range Z.

[0202] Please see Figure 3 The image shown is a schematic diagram of a three-dimensional image of a geological body according to an embodiment of this application.

[0203] The three-dimensional image of the geological body includes a true image at the actual azimuth angle θ and a false image at the mirror azimuth angle θ+180°. For example... Figure 3 As shown, the real and false images of the geological body are centrally symmetrically distributed around the borehole, reflecting the inherent 180° azimuth ambiguity characteristic of dipole shear wave remote sensing under single-well conditions.

[0204] In step S500, the geological parameters obtained from each borehole through inversion are integrated to form a multi-well geological parameter set.

[0205] In one embodiment of this application, the construction steps of the multi-well geological body parameter set include the following steps S501 to S503.

[0206] In step S501, geological body parameters after inversion processing are collected from each borehole, including but not limited to key information such as distance from the well D, true dip angle α, true apparent azimuth angle θ and its mirror azimuth θ+180°, and depth range Z. All data are ensured to undergo consistency correction to eliminate deviations caused by measurement errors or formation heterogeneity.

[0207] In step S502, the data from each borehole is converted into a unified coordinate system (such as a global geographic coordinate system) to facilitate cross-well comparison and fusion analysis. This step typically involves the correction of well inclination angle, wellbore azimuth angle, and formation reference surface.

[0208] In step S503, a multi-well geological body parameter set is constructed based on the standardized data.

[0209] In step S600, based on the multi-well geological body parameter set, multi-well coverage statistics based on spatial gridding and Bayesian inference are performed to obtain the true location of the target geological body in the target exploration area.

[0210] Please see Figure 4 The image shows a schematic diagram illustrating the coverage principle of a real reflector and a dummy reflector under multi-aperture intersection conditions according to an embodiment of this application.

[0211] like Figure 4 As shown, when multiple boreholes observe the same subsurface geological body, each borehole generates two candidate reflectors simultaneously due to 180° azimuth ambiguity: one located at the true azimuth θ, and the other at its mirror azimuth θ+180°. Because the spatial locations of each borehole differ, the true reflector exhibits spatial consistency across multi-well data, with its inverted positions converging in the same area in three-dimensional space. In contrast, the false reflector's spatial location diverges due to azimuth reversal, preventing effective convergence.

[0212] In one embodiment of this application, the multi-well coverage statistics based on the multi-well geological body parameter set include the following steps S601 to S605.

[0213] In step S601, construct the reflector identifier vector R. k :

[0214] ,

[0215] In the formula Let α be the distance from the well to the k-th geological body. k Let be the true dip angle of the k-th geological body. Let k be the depth of the k-th geological body. is the true apparent azimuth of the k-th geological body.

[0216] In step S602, the target exploration area is divided into several grid units according to a preset grid resolution.

[0217] Specifically, the grid cell is represented as:

[0218] ,

[0219] ,

[0220] ,

[0221] ;

[0222] In the formula This represents the initial boundary of the mesh element in the X-axis direction. For the termination boundary, Δx i The width of the grid cell; Let be the upper boundary of the mesh cell in the Y-axis direction. Let Δy be the lower boundary. j The height of the grid cell; Let be the upper boundary of the mesh cell in the Z-axis direction. Let Δz be the lower boundary. k The depth of the grid cell.

[0223] The grid resolution is:

[0224] ,

[0225] In the formula, c is the wavelength of the transverse wave, and v s f is the transverse wave velocity. max This is the highest sound source frequency.

[0226] In step S603, a geological body-grid mapping function Γ is established, and each geological body is projected to the corresponding grid cell through the mapping function.

[0227] Specifically, the expression for the geological body-grid mapping function Γ is:

[0228] ,

[0229] In step S604, based on the Bayesian posterior probability model, the statistics of the grid cell G are calculated. ijk Total number of times the geological bodies in each borehole were covered:

[0230] ,

[0231] In the formula, M is the total number of boreholes in the target exploration area, and N is... m Let m be the number of geological bodies in the m-th borehole, where m ∈ M. This is an indicator function used to establish the association between geological bodies and grid cells.

[0232] In step S605, the probability of the existence of a real reflector is calculated based on the total number of coverage counts.

[0233] Specifically, the formula for calculating the probability of the existence of the real reflector is as follows:

[0234] .

[0235] Please see Figure 5 The diagram shows the orientation interpretation results of the reflectors of four boreholes according to an embodiment of this application.

[0236] Because the four boreholes are distributed in a grid pattern in space, the real reflectors have spatial consistency in the interpretation results of each well, and their intersection area is concentrated and focused; while the false reflectors are scattered due to azimuth reversal, and cannot form an effective overlap between multiple wells. Figure 5 This intuitively demonstrates the technical effectiveness of multi-well coverage statistics in eliminating 180° ambiguity.

[0237] In one embodiment of this application, the application uses a positional information weighting function. To quantify the confidence level of multiple wells, and to classify the confidence level of the multiple wells into a three-level confidence system.

[0238] Specifically, the positional weight function The expression:

[0239] ,

[0240] in,

[0241] Ak′= ·cos(2Δψ),

[0242] In the formula, ϕ is the current scanning azimuth angle. Let be the normalized amplitude of the reflected wave extracted from the k-th borehole at the θ azimuth position, Ak′ be the theoretical amplitude at the corresponding θ+180° azimuth position, Δψ be the transmit-receive azimuth deviation angle, and δ be the Dirac function.

[0243] This three-level confidence system provides a quantifiable decision basis for azimuth unambiguity resolution, significantly improving the interpretation robustness and automation level of dipole shear wave long-range detection in complex tectonic environments.

[0244] Specifically, the three-level confidence system includes:

[0245] (1) High reliability: when When the time is right, it indicates that the orientation has a strong physical response and high consistency, and can be used as a reliable criterion for the true orientation;

[0246] (2) credible: when When this occurs, it indicates that there is a valid signal in that direction, but it is affected by noise or multiple solutions, and it is necessary to combine multi-well data or geological prior information to assist in the judgment.

[0247] (3) To be verified: when At that time, it was considered that there was insufficient evidence to support the location, and it may be a false response or interference product, which needs to be excluded or verified through subsequent multi-well coverage statistics or Bayesian inference.

[0248] In this implementation, the full-space uniqueness determination of the true orientation of the geological body is achieved through bidirectional orientation mapping confidence quantification and Bayesian multi-well coverage statistics, effectively eliminating the inherent 180° orientation ambiguity in dipole shear wave long-range detection.

[0249] It should be noted that the scope of protection of the dipole shear wave remote detection geological body azimuth positioning method described in this application embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principle of this application is included within the scope of protection of this application.

[0250] Please see Figure 6 The image shown is a schematic diagram of the structure of a dipole transverse wave remote detection geological body orientation positioning system according to an embodiment of this application.

[0251] like Figure 6 As shown, this embodiment provides a dipole shear wave remote detection geological body azimuth positioning system, the system including a multipole array acoustic logging instrument and a geological body azimuth positioning device.

[0252] In one embodiment of this application, the multipole array acoustic logging tool performs logging operations in multiple boreholes arranged in a grid within the target exploration area; the multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual dipole sound source, and the acoustic wave receiving device is equipped with an orthogonal dipole array.

[0253] In one embodiment of this application, the geological body orientation positioning device is communicatively connected to the multipole array acoustic logging tool and is used to execute the method described in any of the above-mentioned embodiments.

[0254] In other embodiments, the geological body orientation device can be integrated into the multipole array acoustic logging tool to form an integrated logging system, thereby achieving a compact equipment structure and improved on-site processing capabilities.

[0255] It should be noted that the structure and principle of the geological body orientation positioning device described in this application embodiment correspond one-to-one with the steps in the above-mentioned dipole transverse wave remote detection geological body orientation positioning method, so they will not be repeated here.

[0256] The geological body orientation positioning device provided in this application embodiment can realize the geological body orientation positioning method of dipole shear wave remote detection described in this application. However, the implementation device of the geological body orientation positioning method of dipole shear wave remote detection described in this application includes, but is not limited to, the structure of the geological body orientation positioning device listed in this embodiment. All structural modifications and substitutions of the prior art made according to the principle of this application are included within the protection scope of this application.

[0257] Please see Figure 7 The image shown is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0258] like Figure 7 As shown, this embodiment provides an electronic device, including a memory and a processor.

[0259] The memory is used to store computer programs.

[0260] The processor is configured to execute a computer program stored in the memory to cause the electronic device to perform any of the methods described above.

[0261] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0262] This embodiment also includes one or more of the following: a multimedia component, an input / output (I / O) interface, and a communication component.

[0263] The multimedia component may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory or transmitted via a communication component. The audio component also includes at least one speaker for outputting audio signals. The I / O interface provides an interface between the processor and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. The communication component is used for wired or wireless communication between the timer and other devices. Wireless communication includes, for example, Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of these. Therefore, the corresponding communication component may include a Wi-Fi module, a Bluetooth module, or an NFC module.

[0264] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or modules or units may be electrical, mechanical, or other forms.

[0265] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of this application, depending on actual needs. For example, the functional modules / units in the various embodiments of this application may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0266] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0267] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0268] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for azimuth positioning of geological bodies using dipole shear waves, characterized in that, An application is made to a multipole array acoustic logging tool, which performs logging operations in multiple boreholes arranged in a grid within a target exploration area. The multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual-dipole acoustic source, and the acoustic wave receiving device is equipped with an orthogonal dipole array. The method includes: In each of the aforementioned boreholes, two sets of orthogonally polarized transverse waves are alternately excited by the dual dipole sound source at a preset misalignment angle, forming an azimuth-sensitive wave field with azimuth and phase difference characteristics. The orthogonal dipole array is used to acquire four-component data of the azimuth-sensitive wavefield after reflection by the downhole geological body. Based on the dynamic weighted superposition algorithm, well perimeter scanning imaging is performed on the four-component data to obtain the reflected acoustic imaging profile. Based on a multi-parameter fusion-based azimuth and distance joint inversion algorithm, the target geological body is extracted from the advantageous azimuth of the reflected acoustic imaging profile energy focusing, and the corresponding geological body parameters are calculated. The geological body parameters include distance from the well, true dip angle, depth range, true apparent azimuth angle and its mirror azimuth angle. The geological parameters obtained from the inversion of each borehole are integrated to form a multi-well geological parameter set; Based on the multi-well geological body parameter set, multi-well coverage statistics based on spatial gridding and Bayesian inference are performed to obtain the true location of the target geological body in the target exploration area.

2. The method according to claim 1, characterized in that, Also includes: Before performing well-circumferential scanning imaging on the four-component data, the four-component data is preprocessed with time-domain waveform feature enhancement and dispersion characteristic compensation. in Time-domain waveform feature enhancement of the four-component data includes: Based on the spatial correlation of the four-component data, an orientation-sensitive operator matrix is ​​constructed. : ； In the formula The preset azimuth scanning angle, and 0°≤ <180°; Based on the four-component data, calculate the cross-correlation matrix of the four-component data within the time window. The cross-correlation matrix is ​​used to reflect the phase and amplitude relationship between different receiving channels. Based on the orientation-sensitive operator matrix and the cross-correlation matrix And by combining the time window function W, the polarization components of different orientation scanning angles are extracted. : ； In the formula, W is the time window function. Let be the cross-correlation matrix. To scan at the azimuth angle The polarization components extracted below; It is a preset azimuth scanning angle Energy measurement of the signal after polarization filtering; The dispersion compensation for the four-component data includes: Based on the unique dispersion effect of long-range detection, a dispersion correction model related to the sound source frequency and depth is established: ； In the formula For reference phase velocity, Here, z is the dispersion intensity coefficient, and z is the depth. For the frequency of the sound source, For reference frequency, This indicates that at a depth of z and a sound source frequency of z Wave propagation phase velocity at time; Based on the aforementioned dispersion correction model, an inverse dispersion operator is constructed for phase correction of signals in the frequency domain; Based on the aforementioned inverse frequency dispersion operator, phase compensation and reconstruction are performed on the four-component data channel by channel.

3. The method according to claim 1, characterized in that, Based on a dynamic weighted superposition algorithm, well-circumferential scanning imaging is performed on the four-component data to obtain a reflected acoustic imaging profile, including: Establish a mapping model between the azimuth scan angle and the four-component data. : ， In the formula For orientation-dependent adaptive weighting functions; The four-component data are defined as follows: m=1 represents the XX component data, m=2 represents the XY component data, m=3 represents the YX component data, and m=4 represents the YY component data. This is the azimuth-range-time domain imaging result; Scanning angles around the well in all directions Based on the mapping model Calculate the scanning angle in each direction The energy response under the condition is used to obtain the reflected acoustic wave imaging profile; in the reflected acoustic wave imaging profile, the energy at the true azimuth is focused to form the main lobe, while the energy at the false azimuth is suppressed to form the side lobes.

4. The method according to claim 1, characterized in that, Also includes: The advantageous azimuth for energy focusing of the reflected acoustic imaging profile is determined using an objective function that enhances azimuth resolution; the expression for the objective function is: ， In the formula, N represents the total number of resolvable geological bodies around the well; w k The adaptive weights for the k-th geological body are... , Let be the signal-to-noise ratio of the k-th reflected signal; λ is the polarity-time joint coefficient. This is the polarity response term, reflecting the degree of matching between the polarization direction of the reflected wave and the transmitting / receiving device; τ is the difference between the actual and theoretical travel time of the k-th geological body; τ is the normalized time window calibration parameter used to control the main lobe width of the sinc function.

5. The method according to claim 1, characterized in that, Based on a multi-parameter fusion-based joint azimuth and range inversion algorithm, the target geological body is extracted from the advantageous azimuth of energy focusing in the reflected acoustic imaging profile, and the corresponding geological body parameters are calculated, including: Based on the preset azimuth-distance constraint formula, the polarization angle of the reflected wave is calculated. The orientation-distance constraint relationship is as follows: ， In the formula S ij Let be the energy integral of the component data ij, where {i,j∈{X,Y}; Based on instrument orientation correction angle Calculate the true viewing azimuth angle θ; wherein the formula for calculating the true viewing azimuth angle θ is: ， In the formula S ij Let i be the energy integral of the component data ij, where {i,j∈{X,Y}. This is the azimuth correction angle for the instrument; The true tilt angle α is calculated based on the amplitude ratio of the component data; wherein the amplitude ratio of the component data is defined as: ， In the formula A ij Let be the amplitude of the component data ij, {i,j∈{X,Y}; The formula for calculating the true tilt angle α is: ， In the formula It is an anisotropic compensation factor; Distance from well The calculation formula is: ， In the formula v s Let ΔT be the transverse wave velocity, ΔT be the arrival time difference between the XY and YX components, and θ be the true apparent azimuth angle. The polarization angle of the reflected wave; The formula for calculating the depth range Z is: ， In the formula, Z0 is the initial depth of the reflector as determined by drilling data, D is the distance from the well, and α is the true dip angle. θ is the wellbore inclination angle, γ is the actual apparent azimuth angle, and γ is the wellbore azimuth angle.

6. The method according to claim 5, characterized in that, Also includes: Based on the principle of acoustic interference, the target reflector is simultaneously mapped to the true viewing azimuth angle θ and its mirror azimuth angle θ+180°, and the confidence of the two mapping directions is quantified to obtain the confidence scores of the true viewing azimuth angle θ and the mirror azimuth angle θ+180°.

7. The method according to claim 1, characterized in that, The dual-dipole sound source includes a first dipole sound source and a second dipole sound source, wherein the first dipole sound source is arranged along the X-axis of the downhole coordinate system, and the second dipole sound source is offset from the X-axis by a preset angle. Non-orthogonal arrangement, among which Furthermore, the axial center distance between the first dipole sound source and the second dipole sound source is less than one-quarter of the preset transverse wave wavelength c, and the emission phase difference is... .

8. The method according to claim 1, characterized in that, Based on the aforementioned multi-well geological body parameter set, multi-well coverage statistics based on spatial gridding and Bayesian inference are performed, including: Construct the reflector identifier vector R k : ， In the formula Let k be the distance from the well to the kth geological body. Let be the true dip angle of the k-th geological body. Let k be the depth of the k-th geological body. This represents the true apparent azimuth of the k-th geological body; The target exploration area is divided into several grid cells according to a preset grid resolution: the grid cell is represented as follows: ， ， ， ； In the formula This represents the initial boundary of the mesh element in the X-axis direction. For the termination boundary, Δx i The width of the grid cell; Let be the upper boundary of the mesh cell in the Y-axis direction. Let Δy be the lower boundary. j The height of the grid cell; Let be the upper boundary of the mesh cell in the Z-axis direction. Let Δz be the lower boundary. k The depth of the grid cell; The grid resolution is: ， In the formula, c is the wavelength of the transverse wave, and v s f is the transverse wave velocity. max The highest sound source frequency; A geological body-grid mapping function Γ is established to project each geological body onto its corresponding grid cell; wherein the expression of the geological body-grid mapping function Γ is: ， Based on the Bayesian posterior probability model, the statistical analysis of the grid cell G ijk Total number of times the geological bodies in each borehole were covered: ， In the formula, M is the total number of boreholes in the target exploration area, and N is... m Let m be the number of geological bodies in the m-th borehole, where m ∈ M. This is an indicator function used to establish the association between geological bodies and grid cells; Based on the total number of coverage counts, the probability of the existence of a real reflector is calculated; the formula for calculating the probability of the existence of a real reflector is: 。 9. A dipole transverse wave long-range geological body positioning system, characterized in that, include: A multipole array acoustic logging tool is used to perform logging operations in multiple boreholes arranged in a grid within a target exploration area. The multipole array acoustic logging tool includes an acoustic wave transmitting device and an acoustic wave receiving device, wherein the acoustic wave transmitting device is equipped with a dual dipole sound source and the acoustic wave receiving device is equipped with an orthogonal dipole array. A geological body orientation positioning device is communicatively connected to the multipole array acoustic logging tool and is used to perform the method as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: The memory is used to store computer programs; A processor for executing a computer program stored in the memory to cause the electronic device to perform the method of any one of claims 1 to 8.

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