Acoustic wave detection method, device, equipment, storage medium and program product

Abstract

Embodiments of the present application provide a sound wave detection method, device, equipment, storage medium and program product. The method comprises: performing acoustic logging on a target well to obtain four-component data; weighting the four-component data to generate four-component weighted data; substituting the four-component weighted data into a preset function to obtain a combined signal function; performing migration imaging to generate a reflection signal; determining a first candidate angle and a second candidate angle according to the reflection signal, and constructing a first formation model and a second formation model respectively; generating a first constructed signal and a second constructed signal of the first formation model, and generating a third constructed signal and a fourth constructed signal of the second formation model; determining a target angle based on a phase difference of the constructed signals; and generating a constructed imaging result according to the target angle and the four-component weighted data. By generating four-component weighted data carrying azimuth information and constructing a formation model, the 180° uncertainty problem of dipole shear wave logging is solved.

Description

Technical Field

[0001] This application relates to the field of geological exploration technology, and in particular to a method, apparatus, equipment, storage medium and program product for acoustic detection. Background Technology

[0002] In geological exploration, dipole shear wave logging technology identifies formation information by emitting elastic waves and analyzing the elastic waves reflected from the formation. Because the reflected elastic waves are easy to extract, highly sensitive, have strong azimuth identification capabilities, and can probe deep, dipole shear wave logging has unique advantages in geological exploration.

[0003] However, when identifying formation azimuth information using dipole shear wave logging, there is a 180° uncertainty problem due to the symmetry of the waveform. That is, the formation azimuth information of two azimuth angles that differ by 180° is the same, which makes it impossible to accurately identify the azimuth of geological structures, thus seriously limiting the application and development of this technology.

[0004] To address the 180° uncertainty problem in dipole shear wave logging, a method combining dipole and monopole sound sources has been developed. However, this method is difficult to obtain the reflected elastic waves due to high interference, requiring more complex logging equipment. Summary of the Invention

[0005] This application provides an acoustic wave detection method, apparatus, device, storage medium, and program product. By weighting and combining the reflected elastic waves, the generated data carries asymmetric azimuth information, thereby solving the 180° uncertainty problem of dipole shear wave logging without increasing the complexity of logging equipment and improving logging efficiency.

[0006] In a first aspect, embodiments of this application provide an acoustic detection method applied to a logging device. The logging device includes mutually orthogonal dipole acoustic sources and two pairs of receivers, comprising:

[0007] Four-component array acoustic logging was performed on the target well to obtain four-component data. The four-component data consists of reflected waves from the elastic waves transmitted by the dipole acoustic source and received by two pairs of receivers on the geological structure.

[0008] Based on a preset weighting formula, the four-component data are weighted to generate four-component weighted data;

[0009] The four-component weighted data is substituted into a preset function to obtain a combined signal function; then, the combined signal function is subjected to offset imaging to generate a reflected signal; the variable of the reflected signal is the angle variable.

[0010] Based on the reflected signals, determine the first and second candidate angles of the geological structure.

[0011] Construct a first stratigraphic model and a second stratigraphic model with the angles between the geological structure and the logging equipment as the first candidate angle and the second candidate angle, respectively.

[0012] Based on the four-component data of the first stratigraphic model, a first tectonic signal and a second tectonic signal are generated; and based on the four-component data of the second stratigraphic model, a third tectonic signal and a fourth tectonic signal are generated.

[0013] The target angle is determined from the first candidate angle and the second candidate angle based on the phase difference between the first and second constructed signals, and the phase difference between the third and fourth constructed signals.

[0014] Based on the target angle and the four-component weighted data, the structural imaging results of the target well are generated.

[0015] In one possible implementation, the method further includes:

[0016] For each receiver, the weights of the four-component data received by the receiver are determined based on the dipole sound source corresponding to the four-component data and the corresponding receiver.

[0017] Based on a preset weighting formula, the four-component data is weighted to generate four-component weighted data, including:

[0018] Based on the preset weighting formula, four-component weighted data is generated according to each four-component data and its weight.

[0019] In one possible implementation, the mutually orthogonal dipole sound sources include a first dipole sound source and a second dipole sound source; the four-component data includes the four-component data corresponding to the first dipole sound source and the four-component data corresponding to the second dipole sound source; the four-component weighted data includes the first component weighted data, the second component weighted data, the third component weighted data, and the fourth component weighted data; based on a preset weighting formula, four-component data is generated according to each four-component data and its weight, including:

[0020] Substitute the four-component data corresponding to the first dipole sound source into the first weighting relation to obtain the first component weighted data;

[0021] Substitute the four-component data corresponding to the first dipole sound source into the second weighting relation to obtain the second component weighted data;

[0022] Substituting the four-component data corresponding to the second dipole sound source into the third weighting relation, we obtain the third-component weighted data.

[0023] Substituting the four-component data corresponding to the second dipole sound source into the fourth weighting relation, we obtain the fourth-component weighted data.

[0024] In one possible implementation, the preset function is:

[0025] X(φ) = x·cos 2 φ-(xy+yx)·sinφcosφ+yy·sin 2 φ

[0026] Where X(φ) represents the combined signal function, xx represents the weighted data of the first component, xy represents the weighted data of the second component, yx represents the weighted data of the third component, yy represents the weighted data of the fourth component, and φ represents the angle variable;

[0027] Migration imaging is performed on the combined signal function to obtain the reflected signal, including:

[0028] Based on the offset algorithm, the combined signal function is imaged to obtain the reflected signal.

[0029] In one possible implementation, determining a first candidate angle and a second candidate angle of the geological structure based on the reflected signal includes:

[0030] Based on the reflected signal, determine the value of the angle variable corresponding to the maximum amplitude of the reflected signal;

[0031] Based on the value of the angle variable corresponding to the maximum amplitude of the reflected signal, the result of adding 90 degrees to the value is taken as the first candidate angle, and the result of subtracting 90 degrees from the value is taken as the second candidate angle.

[0032] In one possible implementation, a first structural signal and a second structural signal are generated based on the four-component data of the first stratigraphic model, and a third structural signal and a fourth structural signal are generated based on the four-component data of the second stratigraphic model, including:

[0033] Based on the second weighting relation and the four-component data of the first stratigraphic model, the second-component weighted data of the first stratigraphic model is obtained; based on the third weighting relation and the four-component data of the first stratigraphic model, the third-component weighted data of the first stratigraphic model is obtained.

[0034] The second component weighted data of the first stratigraphic model is used as the first structural signal; and the third component weighted data of the first stratigraphic model is used as the second structural signal.

[0035] Based on the second weighting relation and the four-component data of the second stratigraphic model, the second-component weighted data of the second stratigraphic model are obtained; based on the third weighting relation and the four-component data of the second stratigraphic model, the third-component weighted data of the second stratigraphic model are obtained.

[0036] The second component weighted data of the second stratigraphic model is used as the third structural signal; and the third component weighted data of the second stratigraphic model is used as the fourth structural signal.

[0037] In one possible implementation, a first structural signal and a second structural signal are generated based on the four-component data of the first stratigraphic model, and a third structural signal and a fourth structural signal are generated based on the four-component data of the second stratigraphic model, including:

[0038] Based on the preset weighting formula, the four-component data of the first stratigraphic model and the four-component data of the second stratigraphic model are weighted respectively to generate the four-component weighted data of the first stratigraphic model and the four-component weighted data of the second stratigraphic model.

[0039] The first angle and the second angle are obtained by adding or subtracting a preset value from the value of the angle variable when the reflected signal reaches its maximum value.

[0040] Substituting the four-component weighted data and the first angle from the first stratigraphic model into the reflection signal, we obtain the first tectonic signal.

[0041] Substituting the four-component weighted data and the second angle from the first stratigraphic model into the reflection signal, we obtain the second tectonic signal.

[0042] Substituting the four-component weighted data of the second stratigraphic model and the first angle into the combined signal function, we obtain the third tectonic signal;

[0043] Substituting the four-component weighted data and the second angle from the second stratigraphic model into the combined signal function yields the fourth tectonic signal.

[0044] In one possible implementation, determining the target angle from the first candidate angle and the second candidate angle based on the phase difference between the first and second constructed signals, and the phase difference between the third and fourth constructed signals, includes:

[0045] Based on the four-component weighted data, the phase difference between the first and second structural signals, and the phase difference between the third and fourth structural signals, the virtual model whose phase difference is consistent with that of the target well is determined from the first and second formation models as the target virtual model.

[0046] Based on the target virtual model, the candidate angles corresponding to the target virtual model are determined as the target angles.

[0047] Secondly, embodiments of this application provide an acoustic detection device applied to a logging equipment. The logging equipment includes mutually orthogonal dipole acoustic sources and two pairs of receivers. The device includes:

[0048] The four-component data acquisition module is used to perform four-component array acoustic logging on the target well and acquire four-component data. The four-component data consists of reflected waves from the elastic waves transmitted by the dipole acoustic source and received by two pairs of receivers on the geological structure.

[0049] The four-component weighted data generation module is used to weight four-component data based on a preset weighting formula to generate four-component weighted data.

[0050] The reflection signal determination module is used to substitute the four-component weighted data into a preset function to obtain a combined signal function; and to perform offset imaging on the combined signal function to generate a reflection signal; the variable of the reflection signal is the angle variable;

[0051] The candidate angle determination module is used to determine the first and second candidate angles of the geological structure based on the reflection signal.

[0052] The formation model construction module is used to construct a first formation model and a second formation model with the angles between the geological structure and the logging equipment as the first candidate angle and the second candidate angle, respectively.

[0053] The structural signal generation module is used to generate a first structural signal and a second structural signal based on the four-component data of the first stratigraphic model, and to generate a third structural signal and a fourth structural signal based on the four-component data of the second stratigraphic model.

[0054] The target angle determination module is used to determine the target angle from the first candidate angle and the second candidate angle based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal;

[0055] The structural imaging module is used to generate structural imaging results of the target well based on the target angle and four-component weighted data.

[0056] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0057] The memory stores the instructions that the computer executes;

[0058] The processor executes computer execution instructions stored in memory, causing the processor to perform the method provided in the first aspect above.

[0059] Fourthly, embodiments of this application provide a logging device, including: mutually orthogonal dipole sound sources, two pairs of receivers, and the electronic equipment provided in the third aspect above;

[0060] Mutually orthogonal dipole sound sources are used to excite elastic waves with orthogonal propagation directions;

[0061] Two pairs of receivers are located on multiple axes and azimuth angles of the logging equipment to receive reflected waves from multiple azimuths and multiple axial depths of the elastic wave.

[0062] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method provided in the first aspect above.

[0063] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method provided in the first aspect above.

[0064] The acoustic wave detection method, apparatus, equipment, storage medium, and program product provided in this application excite mutually orthogonal dipole acoustic sources to transmit elastic waves. These elastic waves propagate through the formation. After receiving the elastic waves from two pairs of receivers, the received four-component data are weighted and combined to generate four-component weighted data with asymmetric azimuth information. The four-component weighted data are then combined to obtain a combined signal function, and the reflected signal is determined. Based on the reflected signal, two possible azimuth angles of the geological structure are determined. Next, formation models are constructed based on these two angles. Using the four-component data simulated by the two formation models, two structural signals from the first formation model and two structural signals from the second formation model are generated. The phase difference between the two structural signals from the same model is used to finally determine the azimuth angle of the geological structure and image the target well structure. This solves the 180° uncertainty problem in dipole shear wave logging and achieves azimuth information identification of geological structures. By only theoretically analyzing two angles and establishing a virtual model, the complexity of theoretical calculations is greatly reduced, the timeliness of acoustic wave detection is improved, and it better meets the needs of actual logging. Meanwhile, this application achieves the filtering out of unipolar components without azimuth information in the four-component data by weighted combination, while also enhancing the dipole and quadrupole components with azimuth information, thereby improving data quality and the accuracy of acoustic wave detection. Attached Figure Description

[0065] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0066] Figure 1 An application scenario diagram provided for an embodiment of this application;

[0067] Figure 2 A schematic flowchart illustrating an acoustic detection method provided in an embodiment of this application;

[0068] Figure 3 This is a schematic diagram of the structure of a logging device provided in an embodiment of this application;

[0069] Figure 4a A graph of the first construction signal and the second construction signal provided for embodiments of this application;

[0070] Figure 4b A graph of the third and fourth construction signals provided in the embodiments of this application;

[0071] Figure 5 This is a schematic diagram of a hardware circuit for weighted combination of reflected signals provided in an embodiment of this application;

[0072] Figure 6 An overall framework diagram for generating four-component data via hardware circuitry is provided in this application embodiment;

[0073] Figure 7 A flowchart illustrating another acoustic detection method provided in this application embodiment;

[0074] Figure 8a A phase shift map of the cross-component obtained by the acoustic detection method is provided in an embodiment of this application;

[0075] Figure 8b A phase shift map of cross components obtained by prior art is provided for embodiments of this application;

[0076] Figure 9 This is a schematic diagram of the structure of an acoustic wave detection device provided in an embodiment of this application;

[0077] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0078] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0079] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0080] First, let me explain the terms used in this application:

[0081] Dipole shear wave logging, also known as dipole shear wave imaging logging, refers to the use of a dipole sound source to generate sound waves in the formation, and the use of the propagation characteristics of sound waves in the formation to obtain information on the elastic and mechanical properties of underground rock formations.

[0082] In geological exploration, dipole shear wave logging technology has promising applications in rock mechanics parameter calculation, identification of geological structures such as fractures and pores, and anisotropy analysis due to its advantages such as easy extraction of emitted elastic waves, high sensitivity, strong azimuth identification capability, and deep detection depth. However, because the dipole sound source is symmetrical, it suffers from a 180° uncertainty during detection, making it difficult to accurately distinguish the specific location of geological structures during azimuth detection.

[0083] Several solutions exist for addressing the 180° uncertainty issue. One solution involves using a combination of dipole and monopole sound sources, identifying the azimuth by analyzing the correlation between pressure polarity changes and azimuth changes within geological structures. However, this method requires information about the geological structures, which is difficult to obtain in actual well logging. Another solution is to use an eight-azimuth receiver. While this method can resolve the 180° uncertainty, it places high demands on the receiver performance of the logging equipment, and the signal-to-noise ratio of existing equipment does not meet logging requirements.

[0084] Therefore, existing technologies have not yet solved the problem of 180° uncertainty due to difficulties in data acquisition or inadequate logging equipment.

[0085] To address the aforementioned problems, this application provides an acoustic detection method that combines and processes four-component data to determine the accurate azimuth of geological structures, thus resolving the 180° uncertainty problem in dipole shear wave logging. Specifically, the method involves weighted combination of the four-component data returned from the geological structure by the elastic wave emitted by the dipole acoustic source and received by the receiver, retaining the azimuth-information component to generate weighted four-component data. Analyzing this weighted four-component data allows the accurate azimuth of the structure to be determined. First, this weighted four-component data is input into a preset function to obtain a combined signal function, which is then used for offset imaging to form a reflected signal. Based on the reflected signal, two possible azimuth angles of the geological structure can be determined. Based on these two possible angles, theoretical analysis is performed on the geological structure to generate two structural signals from a first stratigraphic model and two structural signals from a second stratigraphic model. Based on the phase difference between the two structural signals from the same model, the target angle is determined from the two possible angles, thereby determining the azimuth of the geological structure and constructing an image, thus resolving the 180° uncertainty problem. Furthermore, weighted combination of the four components can improve data quality and accuracy of sonic detection. At the same time, the accurate azimuth of the geological structure can be determined by comparing it with the theoretical results of only two possible angles, avoiding the construction of a large number of virtual models, simplifying the analysis and calculation process, improving the timeliness of sonic detection, and making it more suitable for actual well logging.

[0086] Figure 1This is an application scenario diagram provided for an embodiment of this application. For example... Figure 1 As shown, the acoustic detection method provided in this application can be applied to geological exploration processes. When working downhole, logging equipment can be used for geological exploration. This logging equipment includes a dipole acoustic source and a receiver. When the logging equipment reaches a designated location underground, the dipole acoustic source excites elastic waves in the formation in orthogonal directions. These elastic waves are reflected when they come into contact with geological structures within the formation. The receiver of the logging equipment receives the reflected signals and generates four-component data. This four-component data carries the azimuth information of the geological structures, allowing the location of the geological structures to be identified.

[0087] After receiving the four-component data, the receiver can send it to a computing unit for processing. This computing unit can be located within the logging equipment or in an electronic device connected to it. The computing unit can then process the reflected signals using this acoustic detection method to ultimately obtain the azimuth information of the geological structure.

[0088] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0089] Figure 2 This is a flowchart illustrating an acoustic detection method provided in an embodiment of this application. The execution entity of the method in this embodiment can be the aforementioned computing unit, which can be a module within a logging device or an independent electronic device communicatively connected to the logging device. Figure 2 As shown, the method includes:

[0090] Step S201: Perform four-component array acoustic logging on the target well to obtain four-component data.

[0091] Four-component array acoustic logging is a geological exploration logging technique that identifies geological structures and their locations by emitting and collecting acoustic waves in the formation. Four-component array acoustic logging can be performed using logging equipment.

[0092] In this embodiment, the logging equipment includes mutually orthogonal dipole sound sources and two pairs of receivers. The four-component data consists of reflected waves from the geological structures, received by the two pairs of receivers of the logging equipment, representing the elastic waves emitted by the dipole sound sources.

[0093] Figure 3 This is a structural schematic diagram of a well logging device provided in an embodiment of this application. Figure 3As shown, the logging equipment includes two mutually orthogonal dipole sound sources 310 and multiple receivers 330.

[0094] A dipole sound source 310 has two opposite excitation directions and can transmit elastic waves with the same amplitude along a specific axis. Two mutually orthogonal dipole sound sources 310 can be divided into a first dipole sound source X and a second dipole sound source Y according to their excitation directions.

[0095] A coordinate system is established based on the logging equipment. The axis of the logging equipment is taken as the z-axis of the coordinate system, the excitation direction of the first dipole sound source X is taken as the x-axis, and the excitation direction of the second dipole sound source Y is taken as the y-axis. When the first dipole sound source X is excited, the elastic wave propagates along the x-axis, and when the second dipole sound source Y is excited, the elastic wave propagates along the y-axis.

[0096] For example, each dipole sound source 310 can be composed of two triple-layer transducers distributed along 180°. By applying voltages of opposite polarity and the same amplitude to the two triple-layer transducers, electrical energy is converted into mechanical energy, thereby emitting elastic waves with opposite directions and the same amplitude.

[0097] Continue to refer to Figure 3 The receiver 330 consists of multiple receiver stations along the z-axis of the logging equipment. Each receiver station includes two pairs of receivers 330, which are arranged in a ring around the logging equipment to receive four-component data from different azimuths. Each pair of receivers 330 is arranged in a straight line along the x-axis or y-axis of the coordinate system, with the two pairs of receivers 330 perpendicular to each other, to receive reflected elastic waves from different azimuths, such as... Figure 3 The receiver 330 receives the reflected elastic waves in the Y1, Y2, X1, and X2 directions, respectively. The logging equipment has at least eight receiving stations to collect azimuth information of geological structures at different depths. The receiver 330 can be a receiving transducer to convert mechanical energy into electrical energy, i.e., to receive four-component data.

[0098] In some embodiments, the receiver 330 can be connected to the acquisition module, which directly acquires the four-component data received by the receiver 330. Active reception via a near-probe reduces electrical wiring and improves the signal-to-noise ratio of the acquired four-component data.

[0099] Since the receiver 330 is susceptible to electromagnetic interference, electromagnetic interference can be shielded by installing an electromagnetic shielding module, such as a bellows, outside the receiver 330, thereby further improving the robustness and signal-to-noise ratio of the four-component data.

[0100] The logging equipment also includes a sound insulation module 320. The sound insulation module 320 is located between the mutually orthogonal dipole sound source 310 and receiver 330. It is used to isolate the direct waves of elastic waves propagating along the logging equipment, thereby reducing noise interference caused by the direct waves.

[0101] The logging equipment may also include a central control module. This module, located within the logging equipment, is used to send control commands, store and transmit four-component data, and acquire parameters of the logging equipment. Sending control commands includes controlling the dipole acoustic source 310 to excite elastic waves, controlling the receiver 330 to receive the four-component data, and controlling the logging equipment's azimuth within the formation. The logging equipment's parameters refer to its operating parameters and azimuth information, including depth and azimuth angle. These parameters can be acquired through multiple sensors mounted on the central control module, such as attitude sensors and magnetometers.

[0102] The central control module connects to other parts of the logging equipment, such as the dipole sound source 310, receiver 330, and computing unit, to facilitate communication with these components. The central control module can communicate via serial communication, shift registers, etc., which can reduce system wiring and increase the anti-interference capability of the measuring equipment.

[0103] During geological exploration, after the logging equipment is powered on and self-tested by the central control module, the central control module controls the dipole sound source 310 to excite elastic waves. The elastic waves propagate in the formation and are reflected by the geological structure when they reach it. The receiver 330 receives the four-component data, and the central control module sends the four-component data to the computing unit for processing.

[0104] The specific method for controlling the dipole sound source 310 to excite elastic waves is to excite the dipole sound source 310 sequentially, such as first exciting the first dipole sound source X, and then exciting the second dipole sound source Y after the receiver 330 receives the four-component data.

[0105] The four-component data comprises four components of the signal reflected from the elastic waves excited by two dipole sound sources 310 and received by receivers 330 at different locations within a receiving station. Specifically, when the first dipole sound source X is excited, the four-component data received by receiver 330 in the X1 direction is denoted as XX1, the four-component data received by receiver 330 in the X2 direction is denoted as XX2, the four-component data received by receiver 330 in the Y1 direction is denoted as XY1, and the four-component data received by receiver 330 in the Y2 direction is denoted as XY2; when the second dipole sound source Y is excited, the four-component data received by receiver 330 in the X1 direction is denoted as YX1, the four-component data received by receiver 330 in the X2 direction is denoted as YX2, the four-component data received by receiver 330 in the Y1 direction is denoted as YY1, and the four-component data received by receiver 330 in the Y2 direction is denoted as YY2. According to this method, the four-component data includes eight components representing different locations.

[0106] Step S202: Based on the preset weighting formula, the four-component data is weighted to generate four-component weighted data.

[0107] Specifically, based on a preset weighting formula, the eight four-component data representing different directions are weighted and combined to generate four-component weighted data.

[0108] Because two mutually orthogonal dipole sound sources 310 are used, the acquired four-component data includes a monopole component without azimuth information, as well as a dipole component and a quadrupole component with azimuth information. By combining the four-component data, the monopole component without azimuth information in the reflected wave can be eliminated, while the dipole component and the quadrupole component with azimuth information can be retained.

[0109] The preset weighting relation can be determined based on the components of the four-component data that need to be retained, such as eliminating unipolar components and retaining dipole and quadrupole components; or it can be determined based on the phase of the four-component data and the correlation combination of the four-component data.

[0110] Four-component weighted data is data obtained by weighting and combining four-component data. The specific combination method can be determined according to actual usage requirements. For example, the four-component data corresponding to each dipole sound source can be combined, or the four-component data corresponding to each pair of receivers can be combined, etc.

[0111] In one example, by pre-setting a weighting formula, four-component weighted data can be obtained, including first-component weighted data xx, second-component weighted data xy, third-component weighted data yx, and fourth-component weighted data yy. By generating four-component weighted data, the eight four-component data carrying the azimuth information of geological structures are integrated into four four-component weighted data. While retaining the information of geological structures, this greatly reduces the amount of data, lowers the difficulty of subsequent data processing, and improves the logging speed.

[0112] In some embodiments, four-component weighted data can be obtained according to a preset weighting formula via hardware or software. This can be achieved through software programs in the logging equipment; alternatively, the four-component data can be transmitted to an electronic device connected to the logging equipment for processing.

[0113] After generating the four-component weighted data, it can be acquired and preprocessed to improve its quality and usability. Preprocessing of the four-component weighted data includes, but is not limited to, filtering, field-wave separation, screening, and removal of direct wave signals.

[0114] Step S203: Substitute the four-component weighted data into a preset function to obtain a combined signal function; and perform offset imaging on the combined signal function to generate a reflected signal.

[0115] A composite signal refers to a signal obtained by superimposing four-component weighted data in a certain direction. The composite signal function is a function obtained with that direction as the variable. The angle between that direction and the logging equipment is the variable of the function, i.e., the angle variable.

[0116] Migration imaging generates more accurate subsurface images by correcting for the migration caused by changes in the velocity of sound waves as they propagate through the strata and the complexity of the geological structure.

[0117] Specifically, in the coordinate system established by the logging equipment, the direction of superposition of the four-component weighted data is set as an azimuth rotated counterclockwise by a certain angle relative to the positive x-axis. Substituting the four-component weighted data into a preset function determines the combined signal function with angle as the variable, which is used to determine the intensity of the combined signal superimposed on the four-component weighted data at different azimuths. Then, offset imaging is performed on the combined signal function to obtain a more accurate reflection signal; the final reflection signal is also a function of the angle variable.

[0118] A preset function can be constructed based on the spatial geometric relationship between each dipole sound source and each receiver in the logging equipment. Specifically, the direction corresponding to the angle variable is determined, and the components of each four-component weighted data in the corresponding direction are superimposed.

[0119] In one example, the preset function can be:

[0120] X(φ) = x·cos 2 φ-(xy+yx)·sinφcosφ+yy·sin 2 φ

[0121] Where X(φ) is the combined signal function, and φ is the angle variable of counterclockwise rotation relative to the positive x-axis.

[0122] Step S204: Determine the first and second candidate angles of the geological structure based on the reflected signals.

[0123] The first and second candidate angles are the possible angles of the geological structure relative to the logging equipment.

[0124] The first and second candidate angles can be determined by analyzing the reflected signal. The amplitude of the reflected signal under various simulated variables can be determined. Theoretically, the amplitude of the reflected signal is maximized when the simulated superposition direction coincides with the actual reflected elastic wave direction. By obtaining the angle variable at which the amplitude of the emitted signal is maximized, the possible azimuth angles of the geological structure can be determined, and these possible azimuth angles can be identified as the first and second candidate angles.

[0125] The angle of the geological structure's strike and its angle relative to the logging equipment differ by 90°, thus presenting two solutions. The first candidate angle is φ0 + 90°, and the second candidate angle is φ0 - 90°. By changing the variable φ, the amplitude of the reflected signal in each direction, i.e., the reflected signal intensity, can be determined. The maximum value of the reflected signal intensity is determined by iterating through the variables, and the value of the variable when the reflected signal intensity reaches its maximum value is denoted as angle φ0. Angle φ0 represents the strike of the geological structure, and based on angle φ0, the possible angles of the geological structure relative to the logging equipment can be determined.

[0126] In one example, based on the reflected signal, the value of the angle variable corresponding to the maximum amplitude of the reflected signal is determined; based on the value of the angle variable corresponding to the maximum amplitude of the reflected signal, the value plus 90 degrees is taken as the first candidate angle, and the value minus 90 degrees is taken as the second candidate angle.

[0127] Step S205: Construct a first formation model and a second formation model with the angles between the geological structure and the logging equipment being the first candidate angle and the second candidate angle, respectively.

[0128] Specifically, the azimuth angle of the geological structure is set as the first candidate angle. That is, the geological structure is established at the azimuth angle of the first candidate angle based on the measuring equipment, thereby constructing the first formation model under the simulation environment of the fluid-filled well.

[0129] Assuming the second candidate angle is the angle of the geological structure relative to the measuring equipment, a second stratigraphic model is constructed based on this second candidate angle. The method for establishing the second stratigraphic model is the same as that for the first stratigraphic model, and will not be repeated here.

[0130] By simulating the reflection of elastic waves emitted by mutually orthogonal dipole sound sources 310 on geological structures in the first and second stratigraphic models, four-component data of the first and second stratigraphic models can be obtained.

[0131] Step S206: Based on the four-component data of the first stratigraphic model, generate the first tectonic signal and the second tectonic signal, and based on the four-component data of the second stratigraphic model, generate the third tectonic signal and the fourth tectonic signal.

[0132] By comparing the four-component data of the virtual model with the actual four-component data, the actual angle of the geological structure relative to the logging equipment can be determined.

[0133] The constructed signal specifically refers to a partial four-component data or a combination of partial four-component data carrying azimuth information, which facilitates subsequent comparison with the actual received four-component data.

[0134] Since the first and second tectonic signals need to retain the orientation information of the geological structures, the four-component weighted data of the first stratigraphic model can be generated based on the four-component data of the first stratigraphic model according to the method of generating four-component weighted data in step S202, and two signals can be selected from the four-component weighted data of the first stratigraphic model to be determined as the first and second tectonic signals; or the reflection signals at two angles can be determined as the first and second tectonic signals based on the four-component data of the first stratigraphic model according to the method of generating reflection signals in step S203.

[0135] The generation methods of the third and fourth tectonic signals in the second simulation model are the same as those of the first and second tectonic signals in the first stratigraphic model, and will not be repeated here.

[0136] Signals can be constructed in any combination of forms, and the above-mentioned generation methods do not cover all methods.

[0137] Step S207: Determine the target angle from the first candidate angle and the second candidate angle based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal.

[0138] Since the two possible angles of the geological structure relative to the logging equipment have been determined in step S204 based on the amplitude of the reflected signal, the unique solution can be determined from the two solutions based on the phase information of the four-component data.

[0139] Phase difference can be determined by the temporal relationship between signals, such as leading or lagging. It can also be determined through dynamic time warping and Fourier transform.

[0140] For example, Figure 4a A graph showing the first and second construction signals provided in the embodiments of this application. Figure 4a As shown, the first construction signal leads the second construction signal. Figure 4b A graph showing the third and fourth construction signals provided in the embodiments of this application. Figure 4b As shown, the fourth structural signal leads the third structural signal. Therefore, although the two candidate angles correspond to the same reflected signal amplitude, their phase differences are different. The candidate angle that matches the phase difference of the actual signal is the target angle of the actual geological structure phase relative to the logging equipment.

[0141] Specifically, the phase difference between the first and second structural signals, as well as the phase difference between the third and fourth structural signals, are determined. From the two phase differences, two structural signals that are consistent with the phase difference pattern of the actual signals are selected. The angle of the geological structure in the stratigraphic model corresponding to these two structural signals is the target angle of the geological structure.

[0142] The phase difference of the actual signal is generated based on the formation model's structural signal generation method and is determined according to the actual received four-component data. The target angle refers to the relative angle of the geological structure with respect to the logging equipment.

[0143] Step S208: Generate the structural imaging results of the target well based on the target angle and the four-component weighted data.

[0144] Based on the target angle, the orientation of the geological structure relative to the logging equipment can be determined. Since the logging equipment also moves during geological exploration, the azimuth angle of the geological structure can be determined based on the orientation of the logging equipment and the target angle.

[0145] The azimuth of a logging device specifically refers to the azimuth angle between the logging device and a certain geographical direction. For example, the azimuth angle between the y-axis of the logging device and the Earth's North Pole.

[0146] Based on the target angle of the geological structure relative to the logging equipment and the azimuth angle of the logging equipment relative to the geographical direction, the azimuth angle of the geological structure relative to the geographical direction can be determined according to spatial geometric relationships.

[0147] Specifically, based on the multiple receiving stations on the z-axis of the logging equipment, and the four-component data obtained by the two pairs of receivers 330 in each receiving station, the target angle can be obtained through the above method. The target angle of the geological structure at different locations of the logging equipment can be determined. Based on the azimuth of the logging equipment, a spatial geometric model can be constructed to determine the angle of the geological structure relative to the geographical direction, i.e., the azimuth.

[0148] After determining the azimuth of a geological structure, a high-resolution reflection image of the geological structure can be effectively generated based on the actual azimuth and four-component weighted data, providing important support for geological exploration.

[0149] Specifically, based on the azimuth of the geological structure, the four-component weighted data are combined and time-depth converted to draw a reflection image of the geological structure's location.

[0150] In reflectance imaging, the orientation of geological structures within the strata helps identify their morphology, boundaries, and internal features, thereby improving imaging resolution and accuracy. By determining the orientation of geological structures and using four-component weighted data, reflectance imaging maps of these structures can be created, providing crucial information for geological exploration and aiding in better analysis of subsurface structures and reservoir characteristics.

[0151] The acoustic detection method provided in this application excites mutually orthogonal dipole acoustic sources to send elastic waves. These elastic waves propagate through the formation. After two pairs of receivers receive four-component data, the received four-component data is weighted and combined to generate four-component weighted data with asymmetric azimuth information. The four-component weighted data is substituted into a preset function to obtain a combined signal function. The solution for the angle variable corresponding to the maximum amplitude of this function is obtained. Based on this solution, two possible solutions for the azimuth angle of the geological structure are obtained. Next, virtual models are constructed based on these two solutions. Using the four-component data from the two virtual models, two structural signals for the first formation model and two structural signals for the second formation model are generated. By using the phase difference between the two structural signals in the same model, the azimuth angle of the geological structure is finally determined, solving the 180° uncertainty problem and realizing the identification of the azimuth information of the geological structure. Theoretical analysis and virtual model building using only two solutions greatly reduce the complexity of theoretical calculations, improve the timeliness of acoustic detection, and better meet the needs of actual well logging.

[0152] Optionally, before generating four-component weighted data by weighting the four-component data received by the two pairs of receivers 330 based on a preset weighting formula, the acoustic wave detection method further includes: for each receiver 330, determining the weight of the four-component data received by the receiver 330 according to the dipole sound source corresponding to the four-component data received by the receiver 330 and the corresponding receiver 330.

[0153] Based on a preset weighting formula, the four-component data received by the two pairs of receivers 330 are weighted and combined to generate four-component weighted data, including: generating four-component weighted data based on the preset weighting formula, based on the four-component data received by the two pairs of receivers 330 and their weights.

[0154] During acoustic detection, the received four-component data is the result of superimposed multi-order waveforms. The unipolar component lacks azimuth characteristics, while the dipole and quadrupole components do. By processing the four-component data, filtering out useless unipolar components, retaining the dipole and quadrupole components, and enhancing the dipole and quadrupole components with azimuth information, the accuracy and efficiency of well logging can be improved.

[0155] After being excited by the same dipole sound source 310, each reflected waveform carries different components. Subtracting the four-component data received by two adjacent receivers 330 (such as XX1 and XY1) can eliminate the unipolar component and enhance the quadrupole component. Subtracting the four-component data received by two opposite receivers 330 (such as XX1 and XX2) can eliminate both the unipolar and quadrupole components and enhance the dipole component.

[0156] Based on the requirements for different components, the weights of the four-component data received by the receiver 330 are determined according to the dipole sound source 310 corresponding to the transmitted signal and the corresponding receiver 330.

[0157] For example, by assigning different weights to each of the four components, the proportion of dipole components to quadrupole components in the four-component weighted data can be adjusted to optimize the directionality and resolution of the four-component weighted data.

[0158] After determining the weights of the four-component data received by receiver 330, the four-component data is weighted and combined, that is, four-component weighted data is generated based on the two pairs of four-component data received by receiver 330 and their weights.

[0159] In one example, the mutually orthogonal dipole sound sources 310 include a first dipole sound source X and a second dipole sound source Y; the four-component data includes the four-component data corresponding to the first dipole sound source X and the four-component data corresponding to the second dipole sound source Y; the four-component weighted data includes the first component weighted data xx, the second component weighted data xy, the third component weighted data yx, and the fourth component weighted data yy; the specific generation method of the four-component weighted data can be:

[0160] Substituting the four-component data corresponding to the first dipole sound source X into the first weighting relation, we obtain the first component weighted data xx; substituting the four-component data corresponding to the first dipole sound source X into the second weighting relation, we obtain the second component weighted data xy; substituting the four-component data corresponding to the second dipole sound source Y into the third weighting relation, we obtain the third component weighted data yx; substituting the four-component data corresponding to the second dipole sound source Y into the fourth weighting relation, we obtain the fourth component weighted data yy.

[0161] The four-component data corresponding to the first dipole sound source X specifically refers to the four-component data received by each receiver 330 within the same receiving station after the first dipole sound source X is excited. The four-component data corresponding to the second dipole sound source Y specifically refers to the four-component data received by each receiver 330 after the second dipole sound source Y is excited.

[0162] Based on the receiver 330 corresponding to the four-component data, the four-component data corresponding to the first dipole sound source X can also be divided into four-component data XX1 corresponding to the receiver 330 in the positive x-axis direction, four-component data XX2 corresponding to the receiver 330 in the negative x-axis direction, four-component data XY1 corresponding to the receiver 330 in the positive y-axis direction, and four-component data XY2 corresponding to the receiver 330 in the negative y-axis direction.

[0163] The four-component data corresponding to the second dipole sound source Y can be divided into four-component data YX1 corresponding to the positive x-axis direction of the receiver 330, four-component data YX2 corresponding to the negative x-axis direction of the receiver 330, four-component data YY1 corresponding to the positive y-axis direction of the receiver 330, and four-component data YY2 corresponding to the negative y-axis direction of the receiver 330.

[0164] By substituting the four-component data into the preset weighting formula, the four-component weighted data can be determined, where:

[0165] The first weighted relation is: xx=(a+2b)×XX1-a×XX2-b×XY1-b×XY2;

[0166] The second weighted relation is: xy=(a+2b)×XY1-a×XY2-b×XX1-b×XX2;

[0167] The third weighted relation is: yx=(a+2b)×YX1-a×YX2-b×YY1-b×YY2;

[0168] The fourth weighted relation is: yy=(a+2b)×YY1-a×YY2-b×YX1-b×YX2.

[0169] a, b, and a+2b are the weights of each of the four components. The weights can be determined according to the above embodiment, for example, a is 0, b is 1; a is 1, b is 0; a is 0, b is 1; a is -1, b is 2, etc.

[0170] By adjusting the weights of each of the four components, in addition to filtering out the unipolar components that lack directional information, the dipole and quadrupole components can be enhanced. By reasonably enhancing the dipole and quadrupole components and controlling their proportions, the quality of the obtained four-component weighted data can be improved, thereby enhancing the detection capability and making the acoustic detection method more accurate.

[0171] Optionally, the weighted combination of the four components can be achieved by adding hardware circuitry to the central control module.

[0172] Specifically, four-component weighted data can be generated by designing a hardware circuit that combines multiple gain amplifiers and adders to weight the transmitted signal.

[0173] Figure 5 This is a schematic diagram of a four-component data weighted combination hardware circuit provided in an embodiment of this application. Figure 5 As shown, by connecting the four-component data received by different receivers 330 to the corresponding channels, the transmitted signal is weighted by an amplifier, and finally, multiple four-component data are superimposed by an adder to generate the corresponding four-component weighted data. According to Figure 5 When the input four-component data is the four-component data corresponding to the first dipole sound source X, the circuit can obtain the first component weighted data xx.

[0174] Based on the four-component weighted data, corresponding four-component data weighting combination hardware circuits can be designed. To reduce circuit complexity, if the time interval between the sequential excitation of the dipole sound source 310 is sufficient, only two weighting combination hardware circuits can be used to generate the four-component weighted data through multiplexing.

[0175] For example, Figure 6 This application provides an overall framework diagram for generating four-component data via hardware circuitry, as illustrated in an embodiment. Figure 6As shown, the signal input module provides an input interface for four-component data. When the input is the four-component data corresponding to the first dipole sound source X, the signal weighting module can weight the four-component data. Then, the signal combination module combines the weighted four-component data together to generate the first-component weighted data xx and the second-component weighted data xy. When the input is the four-component data corresponding to the second dipole sound source Y, it can generate the fourth-component weighted data yy and the third-component weighted data yx. Finally, the quantization acquisition module acquires the generated four-component weighted data. In this framework, the processor can also be used to control the amplifier, adder, and quantization acquisition module in the circuit, which can change the weights and combination methods of each four-component data. Generating four-component weighted data through hardware circuitry is more stable and reliable.

[0176] Optionally, based on the four-component data of the first stratigraphic model, a first structural signal and a second structural signal are generated, and based on the four-component data of the second stratigraphic model, a third structural signal and a fourth structural signal are generated, including:

[0177] Based on the second weighting relation and the four-component data of the first stratigraphic model, the second component weighted data of the first stratigraphic model is obtained; based on the third weighting relation and the four-component data of the first stratigraphic model, the third component weighted data of the first stratigraphic model is obtained; the second component weighted data of the first stratigraphic model is used as the first structural signal; and the third component weighted data of the first stratigraphic model is used as the second structural signal.

[0178] Based on the second weighting relation and the four-component data of the second stratigraphic model, the second component weighted data of the second stratigraphic model is obtained; based on the third weighting relation and the four-component data of the second stratigraphic model, the third component weighted data of the second stratigraphic model is obtained; the second component weighted data of the second stratigraphic model is used as the third structural signal; and the third component weighted data of the second stratigraphic model is used as the fourth structural signal.

[0179] Since the signal differences of the cross components are relatively large, the phase difference can be determined relatively clearly. Therefore, based on the four-component data of the first stratigraphic model and the four-component data of the second stratigraphic model, and using the method of generating four-component weighted data in the above embodiment, the cross components (i.e., the second component weighted data xy and the third component weighted data yx) in the four-component weighted data of the first stratigraphic model are determined as the first structural signal and the second structural signal of the first stratigraphic model; the cross components (i.e., the second component weighted data xy and the third component weighted data yx) in the four-component weighted data of the second stratigraphic model are determined as the third structural signal and the fourth structural signal of the second stratigraphic model.

[0180] For noise-free theoretical data, two candidate angles can be distinguished by weighting two components of the four-component weighted data from the virtual model, making it easier to compare with the actual signal and obtain the target angle. Furthermore, using two weighted components simplifies the combination of the four-component data.

[0181] Alternatively, in addition to the methods described above, the signal can be generated in the following ways.

[0182] Based on the four-component data of the first stratigraphic model, a first tectonic signal and a second tectonic signal are generated. Based on the four-component data of the second stratigraphic model, a third tectonic signal and a fourth tectonic signal are generated, including:

[0183] Based on a preset weighting formula, the four-component data of the first stratigraphic model and the four-component data of the second stratigraphic model are weighted and combined to generate four-component weighted data of the first stratigraphic model and four-component weighted data of the second stratigraphic model; the value of the angle variable when the combined signal function reaches its maximum value is added to or subtracted from the preset value to obtain the first angle and the second angle.

[0184] Substituting the four-component weighted data and the first angle from the first stratigraphic model into the combined signal function yields the first structural signal; substituting the four-component weighted data and the second angle from the first stratigraphic model into the combined signal function yields the second structural signal.

[0185] Substituting the four-component weighted data and the first angle from the second stratigraphic model into the combined signal function yields the third structural signal; substituting the four-component weighted data and the second angle from the second stratigraphic model into the combined signal function yields the fourth structural signal.

[0186] Based on the four-component data of the first stratigraphic model, the angle φ0 at which the combined signal function reaches its maximum value can be offset by a certain angle to obtain two structural signals, namely X(φ0+φ) of the first stratigraphic model. opt ) is the first constructed signal and X(φ0-φ opt ) is the second constructed signal, where φ opt As a preset value, adjusting this configurable angle can make the differences in the obtained first construct signal more obvious. φ opt This is a configurable parameter that can be adjusted based on the phase difference between the constructed signals.

[0187] Based on the four-component data of the second stratigraphic model, the angle φ0 at which the combined signal function reaches its maximum value can be offset by a certain angle to obtain two structural signals, namely X(φ0+φ) of the first stratigraphic model. opt ) is the third constructed signal and X(φ0-φ opt ) is the fourth constructed signal.

[0188] This approach, which identifies the constructed signal in a different way, provides multiple implementation methods for acoustic detection, making the analysis process more flexible.

[0189] Figure 7 This is a schematic flowchart illustrating another acoustic wave detection method provided in an embodiment of this application. Figure 7 As shown, in order to better understand the acoustic wave detection method provided in this embodiment, this embodiment further explains the scenarios in which the acoustic wave detection method is applied.

[0190] Step S701: Perform four-component array acoustic logging on the target well to obtain four-component data.

[0191] The logging equipment is placed in the designated location. First, the central control module performs a self-test on the logging equipment and acquires its location information, such as azimuth and depth. The logging equipment then operates, exciting the dipole sound source 310 and receiving four-component data.

[0192] Step S702: Based on the preset weighting formula, the four-component data received by the two pairs of receivers 330 are weighted to generate four-component weighted data.

[0193] After generating the four-component weighted data, the four-component weighted data is collected and preprocessed.

[0194] For example, Figure 8a This application provides an embodiment of a phase shift map of the cross-component obtained by the acoustic detection method. Figure 8b This application provides an embodiment of a prior art phase shift map of cross-components, where the cross-components correspond to the second-component weighted data and the third-component weighted data in the acoustic wave detection method. For example... Figure 8a As shown, the cross components (i.e., the weighted data of the second and third components) obtained by this acoustic detection method exhibit a significant phase shift. And as... Figure 8b As shown, the cross components obtained by the existing technology are symmetrical and cannot solve the 180° uncertainty problem.

[0195] Step S703: Substitute the four-component weighted data into a preset function to obtain a combined signal function; and perform offset imaging on the combined signal function based on the offset algorithm to obtain the reflected signal.

[0196] The default function is:

[0197] X(φ) = x·cos 2 φ-(xy+yx)·sinφcosφ+yy·sin 2 φ

[0198] Where xx represents the first component weighted data, xy represents the second component weighted data, yx represents the third component weighted data, yy represents the fourth component weighted data, and φ represents the angle between the geological structure and the logging equipment.

[0199] By substituting the weighted data of each component into a preset function, the combined signal function can be determined, and the variable of the combined signal function is the angle variable. Based on migration algorithms, such as wave equation migration and phase shift migration, the combined signal function is migrated for imaging to obtain the reflected signal.

[0200] Step S704: Based on the reflected signal, determine the value of the angle variable corresponding to the maximum value of the reflected signal amplitude; add 90 degrees to the value as the first candidate angle, and subtract 90 degrees from the value as the second candidate angle.

[0201] Step S705: Construct a first formation model and a second formation model with the angle between the geological structure and the logging equipment as the first candidate angle and the second candidate angle.

[0202] Step S706: Based on the four-component data of the first stratigraphic model, generate the first tectonic signal and the second tectonic signal, and based on the four-component data of the second stratigraphic model, generate the third tectonic signal and the fourth tectonic signal.

[0203] Step S707: Determine the target angle from the first candidate angle and the second candidate angle based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal.

[0204] Based on the four-component weighted data, the phase difference between the first and second structural signals, and the phase difference between the third and fourth structural signals, the virtual model whose phase difference is consistent with that of the target well is determined from the first and second stratigraphic models as the target virtual model; based on the target virtual model, the candidate angle corresponding to the target virtual model is determined as the target angle.

[0205] Step S708: Generate the structural imaging results of the target well based on the target angle and the four-component weighted data.

[0206] Figure 9 This is a schematic diagram of the structure of an acoustic wave detection device provided in an embodiment of this application, as shown below. Figure 9 As shown, the acoustic wave detection device provided in this application embodiment includes: a four-component data acquisition module 901, a four-component weighted data generation module 902, a reflection signal determination module 903, a candidate angle determination module 904, a stratigraphic model construction module 905, a tectonic signal generation module 906, a target angle determination module 907, and a tectonic imaging module 908.

[0207] The four-component data acquisition module 901 is used to perform four-component array acoustic logging on the target well to acquire four-component data; the four-component data consists of reflected waves from the elastic waves emitted by the dipole acoustic source received by two pairs of receivers and reflected on the geological structure; the four-component weighted data generation module 902 is used to weight the four-component data based on a preset weighting formula to generate four-component weighted data; the reflection signal determination module 903 is used to substitute the four-component weighted data into a preset function to obtain a combined signal function; and to perform offset imaging on the combined signal function to generate a reflection signal; the variable of the reflection signal is the angle variable; the candidate angle determination module 904 is used to determine the first candidate angle and the second candidate angle of the geological structure based on the reflection signal; the stratigraphic model construction module... 905 is used to construct a first formation model and a second formation model with the included angles of the geological structure relative to the logging equipment as the first candidate angle and the second candidate angle, respectively; the structural signal generation module 906 is used to generate a first structural signal and a second structural signal based on the four-component data of the first formation model, and to generate a third structural signal and a fourth structural signal based on the four-component data of the second formation model; the target angle determination module 907 is used to determine the target angle from the first candidate angle and the second candidate angle based on the phase difference between the first structural signal and the second structural signal, and the phase difference between the third structural signal and the fourth structural signal; the structural imaging module 908 is used to generate the structural imaging results of the target well based on the target angle and the four-component weighted data.

[0208] Optional, the four-component weighted data generation module 902 is specifically used for:

[0209] For each receiver, the weights of the four-component data received by the receiver are determined based on the dipole sound source corresponding to the four-component data received by the receiver and the corresponding receiver. Based on the preset weighting formula, four-component weighted data is generated based on the four-component data received by two pairs of receivers and their weights.

[0210] Optionally, the mutually orthogonal dipole sound sources include a first dipole sound source and a second dipole sound source; the four-component data includes the four-component data corresponding to the first dipole sound source and the four-component data corresponding to the second dipole sound source; the four-component weighted data includes the first component weighted data, the second component weighted data, the third component weighted data, and the fourth component weighted data; based on a preset weighting relation, the four-component weighted data generation module 902 is specifically used for:

[0211] Substituting the four-component data corresponding to the first dipole sound source into the first weighting relation yields the first component weighted data; substituting the four-component data corresponding to the first dipole sound source into the second weighting relation yields the second component weighted data; substituting the four-component data corresponding to the second dipole sound source into the third weighting relation yields the third component weighted data; substituting the four-component data corresponding to the second dipole sound source into the fourth weighting relation yields the fourth component weighted data.

[0212] Optionally, the reflected signal determination module 903 is specifically used for:

[0213] The four-component weighted data is substituted into a preset function to obtain a combined signal function; the combined signal function is then imaged based on an offset algorithm to obtain the reflected signal.

[0214] The default function is:

[0215] X(φ) = x·cos 2 φ-(xy+yx)·sinφcosφ+yy·sin 2 φ

[0216] Where xx represents the weighted data of the first component, xy represents the weighted data of the second component, yx represents the weighted data of the third component, yy represents the weighted data of the fourth component, and φ represents the angle variable.

[0217] Optionally, the candidate angle determination module 904 is specifically used for:

[0218] Based on the reflected signal, determine the value of the variable corresponding to the maximum amplitude of the reflected signal; based on the value of the variable corresponding to the maximum amplitude of the reflected signal, add 90 degrees to the value as the first candidate angle, and subtract 90 degrees from the value as the second candidate angle.

[0219] Optionally, a signal generation module 906 is constructed, specifically for:

[0220] Based on the second weighting relation and the four-component data of the first stratigraphic model, the second-component weighted data of the first stratigraphic model is obtained; based on the third weighting relation and the four-component data of the first stratigraphic model, the third-component weighted data of the first stratigraphic model is obtained; the second-component weighted data of the first stratigraphic model is used as the first structural signal; and the third-component weighted data of the first stratigraphic model is used as the second structural signal; based on the second weighting relation and the four-component data of the second stratigraphic model, the second-component weighted data of the second stratigraphic model is obtained; based on the third weighting relation and the four-component data of the second stratigraphic model, the third-component weighted data of the second stratigraphic model is obtained; the second-component weighted data of the second stratigraphic model is used as the third structural signal; and the third-component weighted data of the second stratigraphic model is used as the fourth structural signal.

[0221] Optionally, a signal generation module 906 is constructed, specifically for:

[0222] Based on a preset weighting formula, the four-component data of the first stratigraphic model and the four-component data of the second stratigraphic model are weighted and combined to generate four-component weighted data of the first stratigraphic model and four-component weighted data of the second stratigraphic model. The value of the angle variable when the reflected signal reaches its maximum value is added to or subtracted by a preset value to obtain the first angle and the second angle. The four-component weighted data of the first stratigraphic model and the first angle are substituted into the reflected signal to obtain the first structural signal. The four-component weighted data of the first stratigraphic model and the second angle are substituted into the reflected signal to obtain the second structural signal. The four-component weighted data of the second stratigraphic model and the first angle are substituted into the reflected signal to obtain the third structural signal. The four-component weighted data of the second stratigraphic model and the second angle are substituted into the reflected signal to obtain the fourth structural signal.

[0223] Optionally, the target angle determination module 907 is specifically used for:

[0224] Based on the four-component weighted data, the phase difference between the first and second structural signals, and the phase difference between the third and fourth structural signals, the virtual model whose phase difference is consistent with that of the target well is determined from the first and second stratigraphic models as the target virtual model; based on the target virtual model, the candidate angle corresponding to the target virtual model is determined as the target angle.

[0225] The acoustic wave detection device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0226] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 10 As shown, the electronic device 10 provided in this embodiment includes at least one processor 101 and a memory 102. The processor 101, memory 102, and communication components are connected via a bus.

[0227] In a specific implementation, at least one processor 101 executes computer execution instructions stored in memory 102, causing at least one processor 101 to perform the above-described method.

[0228] The specific implementation process of processor 101 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0229] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0230] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0231] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0232] This application also provides a well logging device, characterized in that it includes: mutually orthogonal dipole sound sources, two pairs of receivers, and the electronic equipment provided in the above embodiments;

[0233] Mutually orthogonal dipole sound sources are used to excite elastic waves with orthogonal propagation directions;

[0234] Two pairs of receivers are located on multiple axes and azimuth angles of the logging equipment to receive reflected waves from multiple azimuths and multiple axial depths of the elastic wave.

[0235] The logging equipment provided in this embodiment can be referred to as the logging equipment provided in the above method embodiment. The implementation principle and technical effect are similar, and will not be described in detail here.

[0236] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0237] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0238] The aforementioned readable storage medium 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. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0239] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0240] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0241] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0242] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0243] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0244] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0245] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for acoustic wave detection, characterized in that, The method is applied to well logging equipment, which includes mutually orthogonal dipole sound sources and two pairs of receivers, and includes: Four-component array acoustic logging is performed on the target well to obtain four-component data; the four-component data are the reflected waves of the elastic waves sent by the dipole acoustic source and received by the two pairs of receivers on the geological structure. Based on a preset weighting formula, the four-component data are weighted to generate four-component weighted data; The four-component weighted data are substituted into a preset function to obtain a combined signal function; and the combined signal function is then subjected to offset imaging to generate a reflected signal; the variable of the reflected signal is an angle variable; Based on the reflected signal, a first candidate angle and a second candidate angle of the geological structure are determined; Construct a first formation model and a second formation model, with the included angles of the geological structure relative to the logging equipment being the first candidate angle and the second candidate angle, respectively; Based on the four-component data of the first stratigraphic model, a first tectonic signal and a second tectonic signal are generated, and based on the four-component data of the second stratigraphic model, a third tectonic signal and a fourth tectonic signal are generated. Based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal, the target angle is determined from the first candidate angle and the second candidate angle; Based on the target angle and the four-component weighted data, the structural imaging results of the target well are generated.

2. The method according to claim 1, characterized in that, The method further includes: For each receiver, the weight of each of the four-component data received by the receiver is determined based on the dipole sound source corresponding to the four-component data and the corresponding receiver. Based on a preset weighting formula, the four-component data are weighted to generate four-component weighted data, including: Based on the preset weighting formula, the four-component weighted data is generated according to each of the four-component data and its weight.

3. The method according to claim 2, characterized in that, The mutually orthogonal dipole sound sources include a first dipole sound source and a second dipole sound source; the four-component data includes the four-component data corresponding to the first dipole sound source and the four-component data corresponding to the second dipole sound source; the four-component weighted data includes the first component weighted data, the second component weighted data, the third component weighted data, and the fourth component weighted data; Based on the preset weighting formula, the four-component weighted data is generated according to each of the four-component data and its weight, including: Substitute the four-component data corresponding to the first dipole sound source into the first weighting relation to obtain the first component weighted data; Substitute the four-component data corresponding to the first dipole sound source into the second weighting relation to obtain the second component weighted data; Substitute the four-component data corresponding to the second dipole sound source into the third weighting relation to obtain the third component weighted data; Substitute the four-component data corresponding to the second dipole sound source into the fourth weighting relation to obtain the fourth component weighted data.

4. The method according to claim 1, characterized in that, The preset function is: X(φ)=xx·cos 2 φ-(xy+yx)·sinφcosφ+yy·sin 2 f Where X(φ) represents the combined signal function, xx represents the weighted data of the first component, xy represents the weighted data of the second component, yx represents the weighted data of the third component, yy represents the weighted data of the fourth component, and φ represents the angle variable; The composite signal function is subjected to offset imaging to obtain the reflected signal, including: Based on the offset algorithm, the combined signal function is imaged to obtain the reflected signal.

5. The method according to claim 4, characterized in that, Based on the reflected signal, the first candidate angle and the second candidate angle of the geological structure are determined, including: Based on the reflected signal, determine the value of the angle variable corresponding to the maximum value of the reflected signal amplitude; Based on the value of the angle variable corresponding to the maximum amplitude of the reflected signal, the result of adding 90 degrees to the value is taken as the first candidate angle, and the result of subtracting 90 degrees from the value is taken as the second candidate angle.

6. The method according to claim 3, characterized in that, Based on the four-component data of the first stratigraphic model, a first structural signal and a second structural signal are generated; and based on the four-component data of the second stratigraphic model, a third structural signal and a fourth structural signal are generated, including: Based on the second weighting relation and the four-component data of the first stratigraphic model, the second-component weighted data of the first stratigraphic model is obtained; based on the third weighting relation and the four-component data of the first stratigraphic model, the third-component weighted data of the first stratigraphic model is obtained. The second component weighted data of the first stratigraphic model is used as the first structural signal; and the third component weighted data of the first stratigraphic model is used as the second structural signal. Based on the second weighting relation and the four-component data of the second stratigraphic model, the second component weighted data of the second stratigraphic model is obtained; based on the third weighting relation and the four-component data of the second stratigraphic model, the third component weighted data of the second stratigraphic model is obtained. The second component weighted data of the second stratigraphic model is used as the third structural signal; and the third component weighted data of the second stratigraphic model is used as the fourth structural signal.

7. The method according to any one of claims 1-6, characterized in that, Determining a target angle from the first candidate angle and the second candidate angle based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal, includes: Based on the four-component weighted data, the phase difference between the first and second structural signals, and the phase difference between the third and fourth structural signals, a virtual model whose phase difference is consistent with that of the target well is determined from the first and second formation models as the target virtual model. Based on the target virtual model, the candidate angle corresponding to the target virtual model is determined as the target angle.

8. A sound wave detection device, characterized in that, Applied to well logging equipment, the well logging equipment includes mutually orthogonal dipole sound sources and two pairs of receivers, the device comprising: The four-component data acquisition module is used to perform four-component array acoustic logging on the target well and acquire four-component data; the four-component data is the reflected wave of the elastic wave sent by the dipole acoustic source and received by the two pairs of receivers on the geological structure. The four-component weighted data generation module is used to weight the four-component data based on a preset weighting formula to generate four-component weighted data. The reflection signal determination module is used to substitute the four-component weighted data into a preset function to obtain a combined signal function; and to perform offset imaging on the combined signal function to generate a reflection signal; the variable of the reflection signal is an angle variable; The candidate angle determination module is used to determine the first candidate angle and the second candidate angle of the geological structure based on the reflected signal. The formation model construction module is used to construct a first formation model and a second formation model, with the geological structure relative to the logging equipment at the first candidate angle and the second candidate angle, respectively. The structural signal generation module is used to generate a first structural signal and a second structural signal based on the four-component data of the first stratigraphic model, and to generate a third structural signal and a fourth structural signal based on the four-component data of the second stratigraphic model. The target angle determination module is used to determine a target angle from the first candidate angle and the second candidate angle based on the phase difference between the first constructed signal and the second constructed signal, and the phase difference between the third constructed signal and the fourth constructed signal; The structural imaging module is used to generate structural imaging results of the target well based on the target angle and the four-component weighted data.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A well logging device, characterized in that, include: Mutually orthogonal dipole sound sources, two pairs of receivers, and the electronic device as described in claim 9; The mutually orthogonal dipole sound sources are used to excite elastic waves with orthogonal propagation directions; The two pairs of receivers are located at multiple axes and azimuth angles of the logging equipment, and are used to receive reflected waves of the elastic wave at multiple azimuths and multiple axial depths.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

Images