Dipole acoustic sleeve behind casing logging correction apparatus and method

Abstract

This invention relates to the field of well logging signal correction, specifically to a dipole acoustic logging correction device and method. The method first segments the original dispersion curve of the acoustic signal from the casing well, obtaining multiple dispersion segment curves. Corresponding matching dispersion segment curves are then bound to known media. Based on the phase and amplitude differences between frequencies of the matching dispersion segment curves of any two known media, and the acoustic impedance of the known media, a first signal distortion coefficient between the two known media is obtained. Based on the difference between the energy of the matching dispersion segment curve of the known media and the energy of the original dispersion curve, a second signal distortion coefficient for the unknown media is obtained. The clustering process of each data point on the original dispersion curve is then adjusted to obtain an adjusted dispersion curve. This invention effectively removes interference components from the dispersion curve of the original acoustic signal, improving the accuracy of signal correction during well logging.

Description

Technical Field

[0001] This invention relates to the field of well logging signal correction, and specifically to a dipole acoustic logging correction device and method. Background Technology

[0002] Dipole acoustic logging behind casing is a core method for assessing the characteristics of oil and gas reservoirs. It generates flexural wave signals at the interface between the casing and the formation by exciting a dipole acoustic source. The shear wave velocity and mechanical parameters of the formation are inverted by combining the acoustic wave dispersion characteristics. In casing wells, the propagation path of acoustic waves is affected by the coupling effect of multiple media such as casing steel, cement sheath, well fluid and formation, resulting in the received signal being mixed with interference components such as casing resonant waves and well fluid guided waves.

[0003] Existing technologies typically rely on open-hole well theoretical models for acoustic dispersion correction to eliminate the influence of interference signals. However, due to the presence of various media around the wellbore, and when different media are in complex states, such as localized corrosion of the casing due to long-term use leading to uneven thickness changes, or cracks in the cement sheath, the intensity of acoustic dispersion fluctuates significantly. Consequently, existing methods cannot effectively remove interference components from the dispersion curve of the original acoustic signal, reducing the accuracy of signal correction during the logging process. Summary of the Invention

[0004] To address the technical problem that existing methods cannot effectively remove interference components from the dispersion curve of the original acoustic signal, thus reducing the accuracy of signal correction during well logging, the present invention aims to provide a dipole acoustic logging correction device and method. The specific technical solution adopted is as follows:

[0005] This invention proposes a method for correcting dipole acoustic logging after casing, the method comprising:

[0006] The acoustic signal of the casing well is transformed in the frequency domain to obtain the phase and amplitude of each frequency, and the original dispersion curve of the acoustic signal is constructed. The horizontal axis of the original dispersion curve is the frequency and the vertical axis is the phase velocity. The thickness, acoustic propagation speed and acoustic impedance of each known medium in the casing well are also obtained.

[0007] Based on the fluctuations of the original dispersion curve, the original dispersion curve is segmented to obtain multiple dispersion segment curves. Based on the acoustic wave propagation speed and thickness of each known medium, and the frequency range occupied by each dispersion segment curve, the matching dispersion segment curve for each known medium is selected from the dispersion segment curves. Based on the phase difference and amplitude difference of each frequency between the frequency ranges of the matching dispersion segment curves of any two known media, and combined with the acoustic impedance of any two known media, the first signal distortion coefficient between any two known media is obtained.

[0008] Based on the differences between the phase velocity and the theoretical phase velocity, the differences between the amplitude and the theoretical amplitude at each frequency within the frequency range of the matched dispersion piecewise curve for each known medium, and the acoustic impedance of each known medium, the medium interpretation degree of the original dispersion curve is obtained; based on the differences between the energy of the matched dispersion piecewise curves of all known media and the energy of the original dispersion curve, and the medium interpretation degree, the second signal distortion coefficient of the unknown medium is obtained.

[0009] Based on the first signal distortion coefficient and the second signal distortion coefficient, the clustering process of each data point on the original dispersion curve is adjusted to obtain an adjusted dispersion curve.

[0010] Furthermore, obtaining multiple dispersion piecewise curves includes:

[0011] The second derivative of the original dispersion curve is calculated to obtain the second derivative value of each data point on the original dispersion curve;

[0012] Data points whose second derivative values ​​are greater than a preset mutation threshold are taken as mutation data points of the original dispersion curve.

[0013] By using each mutation data point, the original dispersion curve is segmented to obtain multiple dispersion segmented curves.

[0014] Furthermore, the step of selecting the matching dispersion piecewise curve for each known medium from the various dispersion piecewise curves includes:

[0015] Take any known medium as the target known medium, use the sound wave propagation speed of the target known medium as the numerator, use twice the thickness of the target known medium as the denominator, and use the ratio as the resonant sound wave frequency of the target known medium.

[0016] The range of all frequencies between the original frequency of the acoustic signal from the casing well and the resonant acoustic frequency of the target known medium is defined as the finite acoustic frequency range of the target known medium.

[0017] The numerator is the number of frequencies contained in the intersection between the finite acoustic frequency range of the target known medium and the frequency range occupied by each dispersion segment curve, and the denominator is the number of frequencies contained in the frequency range occupied by each dispersion segment curve. The ratio is used as the degree of matching between each dispersion segment curve and the target known medium.

[0018] The dispersion segment curve corresponding to the maximum value of the matching degree is used as the matching dispersion segment curve of the target known medium.

[0019] Furthermore, obtaining the first signal distortion coefficient between any two known media includes:

[0020] The average value of the phase of all frequencies within the frequency range occupied by the matched dispersion piecewise curve of each known medium is taken as the overall phase value of each known medium.

[0021] The average amplitude of the amplitude of all frequencies within the frequency range occupied by the matched dispersion piecewise curve of each known medium is taken as the overall amplitude value of each known medium.

[0022] The absolute value of the difference between the acoustic impedances of any two known media is used as the numerator, the sum of the acoustic impedances of any two known media is used as the denominator, and the ratio is used as the reflection coefficient between any two known media.

[0023] Based on the reflection coefficient between any two known media, the difference between the overall phase value and the difference between the overall amplitude value between any two known media are weighted to obtain the first signal distortion coefficient between any two known media.

[0024] Further, the step of weighting the difference in the overall phase value and the difference in the overall amplitude value between any two known media based on the reflection coefficient between any two known media to obtain the first signal distortion coefficient between any two known media includes:

[0025] Based on the calculation formula for the first signal distortion coefficient, the first signal distortion coefficient between any two known media is obtained. The calculation formula for the first signal distortion coefficient is as follows:

[0026]

[0027] in, Indicates the first species and first The first signal distortion coefficient between known media; Indicates the first species and first Reflection coefficients between known media; Indicates the first The overall phase value of a known medium; Indicates the first The overall phase value of a known medium; Indicates the first The overall amplitude value of a known medium; Indicates the first The overall amplitude value of a known medium.

[0028] Furthermore, the medium interpretation of obtaining the original dispersion curve includes:

[0029] The average absolute value of the difference between the phase velocity and the theoretical phase velocity at all frequencies within the frequency range of the matched dispersion piecewise curve for each known medium is normalized by negative correlation to obtain the phase velocity accuracy for each known medium.

[0030] The amplitude accuracy of each known medium is obtained by performing negative correlation normalization on the average of the absolute values ​​of the differences between the amplitudes of all frequencies and the theoretical amplitudes in the frequency range of the matched dispersion piecewise curve for each known medium.

[0031] The average value of the phase velocity accuracy and the amplitude accuracy is taken as the overall accuracy for each known medium.

[0032] By utilizing the overall realism of each known medium, the acoustic impedance of each known medium is weighted, summed, and normalized to obtain the medium interpretation of the original dispersion curve.

[0033] Furthermore, the second signal distortion coefficient obtained from the unknown medium includes:

[0034] The total energy value of the original dispersion curve is obtained by integral calculation of the original dispersion curve.

[0035] The energy value of the matching dispersion piecewise curve for each known medium is obtained by integral calculation. The sum of the energy values ​​of the matching dispersion piecewise curves for all known media is used as the reference energy value of the original dispersion curve.

[0036] Based on the formula for calculating residual energy, the residual energy value of the unknown medium is obtained. The formula for calculating residual energy is as follows:

[0037]

[0038] in, Represents the residual energy value of the unknown medium; This indicates the media interpretation degree of the original dispersion curve; This represents the total energy value of the original dispersion curve; The reference energy value representing the original dispersion curve;

[0039] The residual energy value of the unknown medium is used as the numerator, the reference energy value of the original dispersion curve is used as the denominator, and the ratio is used as the second signal distortion coefficient of the unknown medium.

[0040] Furthermore, obtaining the adjusted dispersion curve includes:

[0041] Use the Euclidean distance between any two data points on the original dispersion curve as the distance metric between any two data points;

[0042] Based on the first signal distortion coefficient between any two known media and the second signal distortion coefficient of the unknown medium, the distance metric between any two data points on the original dispersion curve is adjusted to obtain the adjusted distance metric between any two data points.

[0043] Based on the adjusted distance metric between any two data points, all data points on the original dispersion curve are clustered to obtain multiple clusters.

[0044] Clusters containing fewer than a preset threshold of data points are removed, and the data points in all remaining clusters are subjected to curve fitting. The fitted curve is then used as the dispersion adjustment curve.

[0045] Furthermore, obtaining the adjusted distance metric between any two data points includes:

[0046] For any two data points on the original dispersion curve, if the two data points belong to different matched dispersion piecewise curves, the first signal distortion coefficient between the known mediums corresponding to the matched dispersion piecewise curves where the two data points are located is used as the distance adjustment weight between the two data points.

[0047] If one data point belongs to a matched dispersion piecewise curve and the other data point belongs to a non-matched dispersion piecewise curve, then the average of the first signal distortion coefficient and the second signal distortion coefficient of the unknown medium between the known medium corresponding to the matched dispersion piecewise curve where one data point is located and the known medium corresponding to the nearest matched dispersion piecewise curve is used as the distance adjustment weight between the two data points.

[0048] If two data points belong to the same matched dispersion piecewise curve or two data points belong to a non-matched dispersion piecewise curve, then the distance adjustment weight between the two data points is set to a value of 0.

[0049] The product of the distance adjustment weight and the distance metric between any two data points on the original dispersion curve is used as the distance adjustment amount between any two data points.

[0050] The sum of the distance metric and the distance adjustment amount between any two data points is used as the adjusted distance metric between any two data points.

[0051] The present invention also proposes a dipole acoustic logging correction device, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the steps of a dipole acoustic logging correction method.

[0052] The present invention has the following beneficial effects:

[0053] This invention addresses the limitation of existing methods in effectively removing interference components from the dispersion curve of the original acoustic signal, thus reducing the accuracy of signal correction during well logging. Therefore, it first segments the original dispersion curve to obtain multiple segmented dispersion curves. The fluctuation characteristics of each segmented dispersion curve can be considered to be caused by a specific medium. Then, matching segmented dispersion curves for each known medium are selected from these segmented dispersion curves, achieving the binding of known media with the segmented dispersion curves. The obtained first signal distortion coefficient reflects the degree of distortion in the amplitude and phase of the acoustic signal due to reflection and transmission phenomena during propagation in different known media. Considering that, in addition to... In addition to interference from known media, there is also interference from unknown media such as casing corrosion, scale layers, thin interbedded reservoir layers, and drilling fluid invasion zones. Therefore, this invention first uses the obtained media interpretation degree to reflect the original dispersion curve's interpretation degree of the known media and the possibility of unknown media existing around the casing well. Then, it uses the second signal distortion coefficient to reflect the degree of influence on the propagation process of the acoustic signal in the unknown media. Subsequently, the clustering process of each data point on the original dispersion curve is adjusted to obtain an adjusted dispersion curve, which effectively removes the interference components in the dispersion curve of the original acoustic signal, solves the signal mixing problem caused by multi-media interference, and improves the accuracy of signal correction in the logging process. Attached Figure Description

[0054] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart of a dipole acoustic logging correction method provided in one embodiment of the present invention. Detailed Implementation

[0056] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a dipole acoustic logging correction device and method according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0058] The following description, in conjunction with the accompanying drawings, details the specific scheme of the dipole acoustic logging correction device and method provided by the present invention.

[0059] Please see Figure 1 The diagram illustrates a flowchart of a dipole acoustic logging correction method according to an embodiment of the present invention, the method comprising:

[0060] Step S1: Perform frequency domain transformation on the acoustic signal of the casing well to obtain the phase and amplitude of each frequency, and construct the original dispersion curve of the acoustic signal. The horizontal axis of the original dispersion curve is the frequency, and the vertical axis is the phase velocity. Also, obtain the thickness, acoustic propagation velocity and acoustic impedance of each known medium in the casing well.

[0061] The cross-sectional structure of a casing well can be roughly divided from the outside to the inside into: formation → cement sheath → guide pipe → surface casing → technical casing → oil layer casing → wellbore center. The dipole acoustic logging device mainly consists of a sound source transmitting module, a receiving module, sensors, and a processing and control module.

[0062] The sound source transmitting module employs a switchable monopole / dipole / quadrupole sound source. The excitation circuit utilizes a gated sine wave pulse design, combined with broadband impedance matching technology, to improve the excitation efficiency of monopole / dipole / quadrupole waves. The receiving module is equipped with a multi-directional, multi-station transducer to achieve full-wavelength acquisition, including longitudinal waves, transverse waves, and cross dipole waves. The transmitting module is activated and switches the dipole sound source mode as needed, transmitting flexural waves towards the casing, cement sheath, and formation. A segmented linear frequency modulated (LFM) signal is used to excite the dipole sound source. This signal consists of multiple continuous LFM sub-signals, each with a frequency range covering the target detection frequency band, and adjacent sub-signals have a preset overlap in frequency range. By controlling the gating timing of the excitation circuit, the dipole sound source alternately transmits this segmented LFM signal in different directions, ensuring that the sound wave energy is evenly distributed within the target frequency band corresponding to each sound wave component. Then, the multi-directional, multi-station transducer of the receiving module starts working, acquiring the full-wavelength signal containing information about the casing, cement sheath, and formation to obtain the original sound wave signal.

[0063] Then, the received acoustic signal from the casing well is subjected to frequency domain transformation to obtain the phase and amplitude of each frequency. In one embodiment of the present invention, Fourier transform can be used to achieve frequency domain transformation, which is not limited here. The original dispersion curve of the acoustic signal is then constructed. The general process of constructing the dispersion curve is as follows: for each frequency point in the frequency domain, the phase value of the frequency at different receivers is extracted. The phase velocity corresponding to the frequency is calculated by the ratio of the phase difference between adjacent receivers to the distance between the receivers. Then, the correspondence between frequency and phase velocity is established to generate the original dispersion curve. The curve uses frequency as the abscissa and phase velocity as the ordinate to fully present the propagation speed characteristics of the acoustic wave at different frequencies at the target depth point. The construction of the dispersion curve is a well-known technical means in the art and will not be described in detail here.

[0064] Simultaneously, the thickness, acoustic propagation velocity, and acoustic impedance of each known medium in the casing well are recorded. The known medium refers to various different media around the casing well, such as formations, cement sheaths, and casing. In addition to these known media that can interfere with the acoustic signal, there may also be unknown media such as casing corrosion and cement sheath cracks that may interfere with the acoustic signal.

[0065] Step S2: Based on the fluctuations of the original dispersion curve, segment the original dispersion curve to obtain multiple dispersion segment curves; based on the acoustic wave propagation speed and thickness of each known medium, and the frequency range occupied by each dispersion segment curve, select the matching dispersion segment curve for each known medium from the dispersion segment curves; based on the phase difference and amplitude difference of each frequency between the frequency ranges of the matching dispersion segment curves of any two known media, and combined with the acoustic impedance of any two known media, obtain the first signal distortion coefficient between any two known media.

[0066] In actual production, reservoirs may have complex lithological structures such as thin interbedded layers. Therefore, when using theoretical medium impedance to correct acoustic wave errors, there is a problem of insufficient accuracy. Since acoustic waves propagate in different media, there are obvious characteristic abrupt change points. The propagation characteristics of acoustic waves change significantly before and after the abrupt change points, forming obvious inflection points. These inflection points can serve as boundaries to distinguish different media. Therefore, the original dispersion curve can be segmented based on the fluctuation of the original dispersion curve to obtain multiple dispersion segment curves. The fluctuation characteristics of each dispersion segment curve can be considered as caused by the acoustic wave in a certain specific medium. Subsequently, the corresponding dispersion segment curve can be bound to each known medium to facilitate accurate analysis of the influence of acoustic wave propagation in different known media.

[0067] Preferably, in one embodiment of the present invention, the method for obtaining multiple dispersion piecewise curves specifically includes:

[0068] The second derivative of the original dispersion curve is calculated to obtain the second derivative value of each data point on the original dispersion curve. The larger the absolute value of the second derivative value of a data point, the more obvious the abrupt change of the original dispersion curve at that data point. Therefore, data points whose absolute value of the second derivative value is greater than a preset abrupt change threshold can be regarded as abrupt change data points of the original dispersion curve. The original dispersion curve is segmented using each abrupt change data point to obtain multiple dispersion segmented curves. The preset abrupt change threshold ranges from 40 to 60. In one embodiment of the present invention, the preset abrupt change threshold is set to 50. The preset abrupt change threshold can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0069] When sound waves propagate in a medium layer of finite thickness, they will be reflected at the upper and lower interfaces of the medium, forming standing wave resonance. Therefore, based on the sound wave propagation speed and thickness of each known medium, as well as the frequency range occupied by each dispersion segment curve, the matching dispersion segment curve for each known medium can be selected from the dispersion segment curves, thereby realizing the binding of the known medium with the corresponding dispersion segment curve. Among them, a certain known medium corresponds to a dispersion segment curve, that is, the matching dispersion segment curve of that known medium.

[0070] Preferably, in one embodiment of the present invention, the method for obtaining multiple dispersion piecewise curves specifically includes:

[0071] Because of the standing wave resonance phenomenon in the casing well structure, the wavelength of the sound wave propagating in the medium is approximately twice the thickness of the medium. Therefore, any known medium can be taken as the target known medium, the sound wave propagation speed of the target known medium can be used as the numerator, twice the thickness of the target known medium can be used as the denominator, and the ratio can be used as the resonant sound wave frequency of the target known medium.

[0072] The range of all frequencies between the original frequency of the acoustic signal from the casing well and the resonant acoustic frequency of the target known medium is defined as the finite acoustic frequency range of the target known medium.

[0073] The numerator is the number of frequencies contained in the intersection between the finite acoustic frequency range of the target known medium and the frequency range occupied by each dispersion segment curve, and the denominator is the number of frequencies contained in the frequency range occupied by each dispersion segment curve. The ratio is used as the degree of matching between each dispersion segment curve and the target known medium.

[0074] The greater the degree of matching between a certain dispersion segment curve and the target known medium, the more likely the dispersion segment curve is to be caused by the propagation of sound waves in the target known medium. Therefore, the dispersion segment curve corresponding to the maximum value of the matching degree can be used as the matching dispersion segment curve of the target known medium.

[0075] The matching dispersion piecewise curves for each known medium can be obtained using the same method described above. For the unselected dispersion piecewise curves, i.e., the non-matching dispersion piecewise curves, they can be considered to be caused by the unknown medium.

[0076] When a sound wave propagates from one known medium to another, its signal characteristics are interfered with. For example, during the propagation of a sound wave from a sleeve to a cement ring, reflection and refraction occur simultaneously at the interface between the two, causing changes in the phase and amplitude of the sound wave in different known media, resulting in signal distortion. Therefore, the first signal distortion coefficient between any two known media can be obtained by considering the phase and amplitude differences between the frequencies of the matched dispersion piecewise curves of any two known media, combined with the acoustic impedance of any two known media. The first signal distortion coefficient reflects the degree of distortion in the amplitude and phase of the original sound wave signal due to reflection and transmission during its propagation in different known media. Subsequently, the original dispersion curve can be adjusted based on the first signal distortion coefficient to eliminate the influence of interference components.

[0077] Preferably, in one embodiment of the present invention, the method for obtaining the first signal distortion coefficient between any two known media specifically includes:

[0078] The average phase value of all frequencies within the frequency range occupied by the matching dispersion piecewise curve of each known medium is taken as the overall phase value of each known medium, and the average amplitude value of all frequencies within the frequency range occupied by the matching dispersion piecewise curve of each known medium is taken as the overall amplitude value of each known medium.

[0079] The absolute value of the difference in acoustic impedance between any two known media is used as the numerator, and the sum of the acoustic impedances of any two known media is used as the denominator. The ratio is used as the reflection coefficient between any two known media. The larger the reflection coefficient, the more obvious the reflection phenomenon of sound waves at the interface between the two known media is.

[0080] Furthermore, based on the reflection coefficient between any two known media, the differences in the overall phase value and the overall amplitude value between any two known media can be weighted to obtain the first signal distortion coefficient between any two known media.

[0081] Preferably, in one embodiment of the present invention, the method for obtaining the first signal distortion coefficient between any two known media further includes:

[0082] Based on the calculation formula for the first signal distortion coefficient, the first signal distortion coefficient between any two known media is obtained. The calculation formula for the first signal distortion coefficient is as follows:

[0083]

[0084] in, Indicates the first species and first The first signal distortion coefficient between known media; Indicates the first species and first Reflection coefficients between known media; Indicates the first The overall phase value of a known medium; Indicates the first The overall phase value of a known medium; Indicates the first The overall amplitude value of a known medium; Indicates the first The overall amplitude value of a known medium.

[0085] When a sound wave undergoes significant reflection between two known media, the reflection coefficient between the two known media is... If the reflection coefficient is relatively large, the reflection characteristics of the sound wave will directly affect the amplitude change of the sound wave. And when the reflection coefficient between two known media is relatively large... When the volume is small, the sound wave undergoes a relatively obvious refraction phenomenon between the two known media, and the refraction characteristics of the sound wave will directly affect the phase change of the sound wave.

[0086] Step S3: Based on the difference between the phase velocity and the theoretical phase velocity, the difference between the amplitude and the theoretical amplitude at each frequency in the frequency range of the matched dispersion piecewise curve of each known medium, and the acoustic impedance of each known medium, obtain the medium interpretation degree of the original dispersion curve; based on the difference between the energy of the matched dispersion piecewise curve of all known media and the energy of the original dispersion curve, and the medium interpretation degree, obtain the second signal distortion coefficient of the unknown medium.

[0087] Considering that in addition to known media, there may be unknown media such as casing corrosion, scale layers, mud cake thickening layers in the wellbore enlargement zone, cement annulus void filling material, loose joint layers, thin interlayers in the reservoir, and drilling fluid invasion zones, etc., the thickness, acoustic wave propagation velocity, and acoustic impedance of the unknown media are unknown. Therefore, it is impossible to analyze the influence of the unknown media on acoustic wave propagation using these parameters. The presence of unknown media will cause residual energy in the original dispersion curve. Therefore, this embodiment of the invention first obtains the original dispersion based on the difference between the phase velocity and the theoretical phase velocity, the difference between the amplitude and the theoretical amplitude at each frequency in the frequency range of the matched dispersion piecewise curve of each known medium, as well as the acoustic impedance of each known medium. The medium interpretation degree of the curve reflects how well the original dispersion curve interprets the known medium and the probability of the existence of an unknown medium around the casing well. The higher the medium interpretation degree, the better the original dispersion curve interprets the known medium, and the higher the probability that there is a known medium around the casing well and no unknown medium. Subsequently, the energy of the unknown medium represented by the original dispersion curve can be accurately calculated based on the medium interpretation degree, and the influence of the unknown medium on the propagation of sound waves can be accurately analyzed. Among them, the theoretical phase velocity and theoretical amplitude of sound waves in a specific known medium are known fixed values, and the theoretical phase velocity and theoretical amplitude are different for different known media.

[0088] Preferably, in one embodiment of the present invention, the method for obtaining the medium interpretation degree of the original dispersion curve specifically includes:

[0089] For each known medium, the average absolute value of the difference between the phase velocity and the theoretical phase velocity at all frequencies within the frequency range of the matched dispersion piecewise curve is negatively correlated and normalized to limit the calculation results to a certain range. Within a certain range, the phase velocity accuracy of each known medium is obtained. The higher the phase velocity accuracy, the higher the probability that a known medium exists around the casing well.

[0090] In embodiments of the present invention, the natural constant can be used. negative exponential function with base or The function form is used to perform negative correlation normalization, which is not limited here, and the same method can be used in subsequent steps to perform negative correlation normalization. The function represents the normalization function used for normalization processing. In one embodiment of the present invention, the normalization processing can specifically be, for example, maximum and minimum value normalization processing. Furthermore, the normalization in subsequent steps can all adopt maximum and minimum value normalization processing. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of values, or activation functions and hyperbolic tangent functions can be used to implement normalization processing. These will not be elaborated or limited further.

[0091] For each known medium, the average absolute value of the difference between the amplitude and the theoretical amplitude at all frequencies within the frequency range of the matched dispersion piecewise curve is negatively correlated and normalized to limit the calculation results to a certain range. Within this range, the amplitude accuracy of each known medium is obtained. Similarly, the greater the amplitude accuracy, the higher the probability that a known medium exists around the casing well.

[0092] Furthermore, the average value of the phase velocity accuracy and amplitude accuracy is used as the comprehensive accuracy for each known medium. Then, using the comprehensive accuracy of each known medium, the acoustic impedance of each known medium is weighted, summed, and normalized to limit the calculation results to a range of... Within this range, the medium interpretation of the original dispersion curve is obtained.

[0093] As an example, in one embodiment of the present invention, the expression for the medium interpretation degree of the original dispersion curve can be specifically as follows:

[0094]

[0095] in, This indicates the media interpretation degree of the original dispersion curve; Indicates the first The overall realism of a known medium; Indicates the first Acoustic impedance of a known medium; Indicates the number of known types of media; This represents the hyperbolic tangent function, used for normalization.

[0096] The unknown medium surrounding the casing well will exhibit residual energy on the original dispersion curve. Therefore, based on the difference between the energy of the dispersion segment curves corresponding to all known media and the energy of the original dispersion curve, and combined with the media interpretation degree of the original dispersion curve, the second signal distortion coefficient of the unknown medium can be obtained. The second signal distortion coefficient reflects the degree of influence on the propagation process of the acoustic signal in the unknown medium. Subsequently, the original dispersion curve can be effectively adjusted by combining the first signal distortion coefficient between known media and the second signal distortion coefficient of the unknown medium to remove the interference components in the original dispersion curve.

[0097] Preferably, in one embodiment of the present invention, the method for obtaining the second signal distortion coefficient of the unknown medium specifically includes:

[0098] The original dispersion curve is integrated to obtain the total energy value of the original dispersion curve. Then, the matching dispersion piecewise curves of each known medium are integrated to obtain the energy value of the matching dispersion piecewise curves of each known medium. The sum of the energy values ​​of the matching dispersion piecewise curves of all known media is used as the reference energy value of the original dispersion curve. The reference energy value can be considered as the energy magnitude exhibited by the known medium on the original dispersion curve.

[0099] Then, based on the formula for calculating the residual energy value, the residual energy value of the unknown medium is obtained. The formula for calculating the residual energy value is as follows:

[0100]

[0101] in, Represents the residual energy value of the unknown medium; This indicates the media interpretation degree of the original dispersion curve; This represents the total energy value of the original dispersion curve; This represents the reference energy value of the original dispersion curve.

[0102] The residual energy value of the unknown medium is used as the numerator, the reference energy value of the original dispersion curve is used as the denominator, and the ratio is used as the second signal distortion coefficient of the unknown medium.

[0103] As an example, in one embodiment of the present invention, the expression for the second signal distortion coefficient of the unknown medium can be specifically as follows:

[0104]

[0105] in, This represents the second signal distortion coefficient in an unknown medium; Represents the residual energy value of the unknown medium; This represents the reference energy value of the original dispersion curve.

[0106] Thus, the influence of the unknown medium on the acoustic signal has been accurately analyzed.

[0107] Step S4: Based on the first signal distortion coefficient and the second signal distortion coefficient, adjust the clustering process of each data point on the original dispersion curve to obtain the adjusted dispersion curve.

[0108] Because acoustic signals can be interfered with when propagating in different known and unknown media, the original dispersion curve of the acoustic signal contains a lot of interference components and undergoes certain distortions. As a result, the original dispersion curve cannot accurately reflect the reservoir characteristics of the casing well. Therefore, the clustering process of each data point on the original dispersion curve can be adjusted according to the first signal distortion coefficient and the second signal distortion coefficient to obtain an adjusted dispersion curve.

[0109] Preferably, in one embodiment of the present invention, the method for obtaining the dispersion curve specifically includes:

[0110] First, the Euclidean distance between any two data points on the original dispersion curve is used as the distance metric between any two data points.

[0111] Based on the first signal distortion coefficient between any two known media and the second signal distortion coefficient of the unknown medium, the distance metric between any two data points on the original dispersion curve is adjusted to obtain the adjusted distance metric between any two data points.

[0112] Preferably, in one embodiment of the present invention, the method for obtaining the adjusted distance metric between any two data points specifically includes:

[0113] For any two data points on the original dispersion curve, if the two data points belong to different matched dispersion piecewise curves, it means that the two data points are formed by sound waves in two different known media. Therefore, the first signal distortion coefficient between the known media corresponding to the matched dispersion piecewise curves where the two data points are located can be used as the distance adjustment weight between the two data points. The larger the distance adjustment weight, the greater the degree of adjustment of the distance measurement between the two data points is required.

[0114] If one data point belongs to a matched dispersion piecewise curve and the other data point belongs to an unmatched dispersion piecewise curve, it means that the two data points are formed by sound waves in a known medium and an unknown medium, respectively. Then, the average of the first signal distortion coefficient between the known medium corresponding to the matched dispersion piecewise curve where one of the data points is located and the known medium corresponding to the nearest matched dispersion piecewise curve, and the second signal distortion coefficient of the unknown medium, is used as the distance adjustment weight between the two data points.

[0115] If two data points belong to the same matched dispersion piecewise curve or two data points belong to the same unmatched dispersion piecewise curve, it means that the two data points are formed by sound waves in the same known or unknown medium. At this time, the sound waves are not disturbed. Therefore, the distance adjustment weight between the two data points can be set to a value of 0, that is, there is no need to adjust the distance measurement between the two data points.

[0116] Then, the product of the distance adjustment weight and the distance metric between any two data points on the original dispersion curve is taken as the distance adjustment amount between any two data points, and the sum of the distance metric and the distance adjustment amount between any two data points is taken as the adjusted distance metric between any two data points.

[0117] Then, based on the adjusted distance metric between any two data points, all data points on the original dispersion curve are clustered to obtain multiple clusters. In one embodiment of the present invention, the existing DBSCAN clustering algorithm or other clustering algorithms can be used to implement the clustering operation, which is not limited or elaborated here.

[0118] The fewer data points a cluster contains, the more likely the data points in that cluster are interference noise points formed by sound waves propagating in different known and unknown media. Therefore, clusters containing fewer than a preset threshold number of data points can be removed, and curve fitting can be performed on the data points in all the remaining clusters. The fitted curve can then be used as an adjustment dispersion curve. The preset threshold number ranges from 10 to 20. In one embodiment of the present invention, the preset threshold number is set to 10. The preset threshold number can also be set by the implementer according to the specific implementation scenario, and is not limited here. In the embodiments of the present invention, existing least squares methods or other fitting methods can be used to achieve curve fitting, and are not limited here.

[0119] Once the adjusted dispersion curve is obtained, it can be used to accurately analyze geological features such as thin interlayers and formation interfaces around the casing well, providing precise acoustic data support for oil and gas reservoir evaluation, wellbore stability analysis, and development plan formulation.

[0120] One embodiment of the present invention provides a dipole acoustic logging correction device, which includes a memory, a processor and a computer program, wherein the memory is used to store the corresponding computer program, the processor is used to run the corresponding computer program, and the computer program can implement the methods described in steps S1 to S4 when running in the processor.

[0121] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0122] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for correcting post-dipole acoustic logging, characterized in that, The method includes: The acoustic signal of the casing well is transformed in the frequency domain to obtain the phase and amplitude of each frequency, and the original dispersion curve of the acoustic signal is constructed. The horizontal axis of the original dispersion curve is the frequency and the vertical axis is the phase velocity. The thickness, acoustic propagation speed and acoustic impedance of each known medium in the casing well are also obtained. Based on the fluctuations of the original dispersion curve, the original dispersion curve is segmented to obtain multiple dispersion segment curves. Based on the acoustic wave propagation speed and thickness of each known medium, and the frequency range occupied by each dispersion segment curve, the matching dispersion segment curve for each known medium is selected from the dispersion segment curves. Based on the phase difference and amplitude difference of each frequency between the frequency ranges of the matching dispersion segment curves of any two known media, and combined with the acoustic impedance of any two known media, the first signal distortion coefficient between any two known media is obtained. Based on the differences between the phase velocity and the theoretical phase velocity, the differences between the amplitude and the theoretical amplitude at each frequency within the frequency range of the matched dispersion piecewise curve for each known medium, and the acoustic impedance of each known medium, the medium interpretation degree of the original dispersion curve is obtained; based on the differences between the energy of the matched dispersion piecewise curves of all known media and the energy of the original dispersion curve, and the medium interpretation degree, the second signal distortion coefficient of the unknown medium is obtained. Based on the first signal distortion coefficient and the second signal distortion coefficient, the clustering process of each data point on the original dispersion curve is adjusted to obtain an adjusted dispersion curve.

2. The dipole acoustic logging correction method according to claim 1, characterized in that, The process of obtaining multiple dispersion piecewise curves includes: The second derivative of the original dispersion curve is calculated to obtain the second derivative value of each data point on the original dispersion curve; Data points whose second derivative values ​​are greater than a preset mutation threshold are taken as mutation data points of the original dispersion curve. By using each mutation data point, the original dispersion curve is segmented to obtain multiple dispersion segmented curves.

3. The dipole acoustic logging correction method according to claim 1, characterized in that, The process of selecting the matching dispersion segment curve for each known medium from the various dispersion segment curves includes: Take any known medium as the target known medium, use the sound wave propagation speed of the target known medium as the numerator, use twice the thickness of the target known medium as the denominator, and use the ratio as the resonant sound wave frequency of the target known medium. The range of all frequencies between the original frequency of the acoustic signal from the casing well and the resonant acoustic frequency of the target known medium is defined as the finite acoustic frequency range of the target known medium. The numerator is the number of frequencies contained in the intersection between the finite acoustic frequency range of the target known medium and the frequency range occupied by each dispersion segment curve, and the denominator is the number of frequencies contained in the frequency range occupied by each dispersion segment curve. The ratio is used as the degree of matching between each dispersion segment curve and the target known medium. The dispersion segment curve corresponding to the maximum value of the matching degree is used as the matching dispersion segment curve of the target known medium.

4. The dipole acoustic logging correction method according to claim 1, characterized in that, The process of obtaining the first signal distortion coefficient between any two known media includes: The average value of the phase of all frequencies within the frequency range occupied by the matched dispersion piecewise curve of each known medium is taken as the overall phase value of each known medium. The average amplitude of the amplitude of all frequencies within the frequency range occupied by the matched dispersion piecewise curve of each known medium is taken as the overall amplitude value of each known medium. The absolute value of the difference between the acoustic impedances of any two known media is used as the numerator, the sum of the acoustic impedances of any two known media is used as the denominator, and the ratio is used as the reflection coefficient between any two known media. Based on the reflection coefficient between any two known media, the difference between the overall phase value and the difference between the overall amplitude value between any two known media are weighted to obtain the first signal distortion coefficient between any two known media.

5. The dipole acoustic logging correction method according to claim 4, characterized in that, The step of weighting the difference in the overall phase value and the difference in the overall amplitude value between any two known media based on the reflection coefficient between any two known media to obtain the first signal distortion coefficient between any two known media includes: Based on the calculation formula for the first signal distortion coefficient, the first signal distortion coefficient between any two known media is obtained. The calculation formula for the first signal distortion coefficient is as follows: ； in, Indicates the first species and first The first signal distortion coefficient between known media; Indicates the first species and first Reflection coefficients between known media; Indicates the first The overall phase value of a known medium; Indicates the first The overall phase value of a known medium; Indicates the first The overall amplitude value of a known medium; Indicates the first The overall amplitude value of a known medium.

6. The dipole acoustic logging correction method according to claim 1, characterized in that, The medium interpretation of obtaining the original dispersion curve includes: The average absolute value of the difference between the phase velocity and the theoretical phase velocity at all frequencies within the frequency range of the matched dispersion piecewise curve for each known medium is normalized by negative correlation to obtain the phase velocity accuracy for each known medium. The amplitude accuracy of each known medium is obtained by performing negative correlation normalization on the average of the absolute values ​​of the differences between the amplitudes of all frequencies and the theoretical amplitudes in the frequency range of the matched dispersion piecewise curve for each known medium. The average value of the phase velocity accuracy and the amplitude accuracy is taken as the overall accuracy for each known medium. By utilizing the overall realism of each known medium, the acoustic impedance of each known medium is weighted, summed, and normalized to obtain the medium interpretation of the original dispersion curve.

7. The dipole acoustic logging correction method according to claim 1, characterized in that, The second signal distortion coefficient obtained from the unknown medium includes: The total energy value of the original dispersion curve is obtained by integral calculation of the original dispersion curve. The energy value of the matching dispersion piecewise curve for each known medium is obtained by integral calculation. The sum of the energy values ​​of the matching dispersion piecewise curves for all known media is used as the reference energy value of the original dispersion curve. Based on the formula for calculating residual energy, the residual energy value of the unknown medium is obtained. The formula for calculating residual energy is as follows: ； in, Represents the residual energy value of the unknown medium; This indicates the media interpretation degree of the original dispersion curve; This represents the total energy value of the original dispersion curve; The reference energy value representing the original dispersion curve; The residual energy value of the unknown medium is used as the numerator, the reference energy value of the original dispersion curve is used as the denominator, and the ratio is used as the second signal distortion coefficient of the unknown medium.

8. The dipole acoustic logging correction method according to claim 1, characterized in that, The obtained adjusted dispersion curve includes: Use the Euclidean distance between any two data points on the original dispersion curve as the distance metric between any two data points; Based on the first signal distortion coefficient between any two known media and the second signal distortion coefficient of the unknown medium, the distance metric between any two data points on the original dispersion curve is adjusted to obtain the adjusted distance metric between any two data points. Based on the adjusted distance metric between any two data points, all data points on the original dispersion curve are clustered to obtain multiple clusters. Clusters containing fewer than a preset threshold of data points are removed, and the data points in all remaining clusters are subjected to curve fitting. The fitted curve is then used as the dispersion adjustment curve.

9. The dipole acoustic logging correction method according to claim 8, characterized in that, The method of obtaining the adjusted distance metric between any two data points includes: For any two data points on the original dispersion curve, if the two data points belong to different matched dispersion piecewise curves, the first signal distortion coefficient between the known mediums corresponding to the matched dispersion piecewise curves where the two data points are located is used as the distance adjustment weight between the two data points. If one data point belongs to a matched dispersion piecewise curve and the other data point belongs to a non-matched dispersion piecewise curve, then the average of the first signal distortion coefficient and the second signal distortion coefficient of the unknown medium between the known medium corresponding to the matched dispersion piecewise curve where one data point is located and the known medium corresponding to the nearest matched dispersion piecewise curve is used as the distance adjustment weight between the two data points. If two data points belong to the same matched dispersion piecewise curve or two data points belong to a non-matched dispersion piecewise curve, then the distance adjustment weight between the two data points is set to a value of 0. The product of the distance adjustment weight and the distance metric between any two data points on the original dispersion curve is used as the distance adjustment amount between any two data points. The sum of the distance metric and the distance adjustment amount between any two data points is used as the adjusted distance metric between any two data points.

10. A dipole acoustic logging correction device, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 9.

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