Method for generating a sweep signal in a vibroseis, vibroseis, device and medium

Abstract

The present application relates to the field of seismic exploration, and discloses a method for generating a scanning signal in a controllable seismic source, a controllable seismic source, equipment and a medium. The method comprises: performing continuous wavelet transform on an ideal unit impulse to obtain a full-band ideal material; screening a plurality of scale components according to the full-band ideal material; reconstructing the scale components to obtain an ideal wavelet; determining an instantaneous frequency curve according to the ideal wavelet; and determining a scanning signal according to the instantaneous frequency curve and a preset amplitude envelope. The present application can improve the resolution of the scanning signal and improve the quality of seismic data.

Description

Technical Field

[0001] This invention relates to the field of seismic exploration, and more particularly to a method for generating scanning signals in a controlled seismic source, a controlled seismic source, equipment, and medium. Background Technology

[0002] In the field of seismic exploration, controlled seismic sources, as an efficient and environmentally friendly excitation source, achieve imaging of underground geological structures by transmitting pre-designed scanning signals into the ground and recording their reflected waves. The quality of the scanning signal is one of the decisive factors affecting the quality of the final seismic data (including resolution, signal-to-noise ratio, and fidelity).

[0003] Traditional linear scanning signals have inherent defects such as wide main lobe, high side lobe, and strong coma oscillations in their correlated wavelets, which directly limit the vertical resolution of seismic records and easily introduce false phase axes, affecting the accuracy of geological interpretation. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a method for generating scanning signals in a controllable seismic source, which can improve the resolution of the scanning signals and systematically improve the quality of seismic data.

[0005] The present invention also proposes a system, device and medium having the above-mentioned method for generating scanning signals in a controllable seismic source.

[0006] A method for generating a scanning signal in a controllable seismic source according to a first aspect embodiment of the present invention includes: By performing continuous wavelet transform on the ideal unit pulse, we can obtain ideal materials across the entire frequency band. Based on the ideal full-band material, several scale components were obtained by screening. The scale components are reconstructed to obtain the ideal wavelet; Determine the instantaneous frequency curve based on the ideal wavelet; The scanning signal is determined based on the instantaneous frequency curve and the preset amplitude envelope.

[0007] A method for generating scanning signals in a controllable seismic source according to an embodiment of the present invention has at least the following beneficial effects: The present invention first starts with an ideal unit pulse representing the theoretical limit, and obtains the optimal waveform, i.e., the ideal wavelet, under band-limited conditions through frequency band selective reconstruction using wavelet transform; then, based on the ideal wavelet, the instantaneous frequency curve corresponding to the ideal wavelet is derived using physical relationships; finally, a physically realizable scanning signal is synthesized. This method ensures that the autocorrelation function of the scanning signal approximates the ideal wavelet through wavelet transform reconstruction. The constructed ideal wavelet achieves a near-optimal state with a narrower main lobe width under a given system bandwidth, thereby implanting high-resolution features and systematically improving the quality of seismic data.

[0008] According to some embodiments of the present invention, the step of selecting several scale components based on the full-band ideal material includes: Based on the scales corresponding to the full-band ideal material, determine the corresponding center frequency and frequency window radius respectively; Based on the center frequency and frequency window radius corresponding to the ideal full-band material, the scale components of the frequency window within the preset effective frequency band are obtained.

[0009] According to some embodiments of the present invention, the reconstruction of the scale components to obtain the ideal wavelet includes: Perform inverse wavelet transform on the scale components; The scale components after inverse wavelet transform are combined into a time-domain waveform, namely the ideal wavelet.

[0010] According to some embodiments of the present invention, determining the instantaneous frequency curve based on the ideal wavelet includes: The mode after Fourier transform of the ideal wavelet is taken as the target amplitude spectrum; Based on the conservation of energy, the instantaneous frequency curve is obtained by inverting the target amplitude spectrum.

[0011] According to some embodiments of the present invention, obtaining the instantaneous frequency curve from the target amplitude spectrum includes: Based on the preset scanning parameters and the target amplitude spectrum, a normalization constant is obtained with total energy constraint; Based on the target amplitude spectrum and the normalization constant, the correspondence between time and frequency is obtained using the Runge-Kutta method; The relationship between time and frequency is interpolated using cubic spline interpolation, and the inverse function after interpolation is obtained, thus yielding the instantaneous frequency curve.

[0012] According to some embodiments of the present invention, it further includes: Convolve the scan signal with the time-reversed complex conjugate of the scan signal to obtain the actual correlated wavelet; Determine the root mean square error between the actual correlated wavelet and the ideal wavelet; If the root mean square error is less than a preset error threshold, the scanning signal passes the verification.

[0013] According to some embodiments of the present invention, the amplitude envelope employs a window function.

[0014] A controllable vibration source according to a second aspect of the present invention includes: The scanning signal generation module is used to execute the scanning signal generation method in the controllable source of any one of the first aspects to obtain the scanning signal; A scan signal transmitting module is used to transmit the scan signal generated by the scan signal generating module; The reflected wave collection module is used to collect and record the emitted waves of the emitted scanning signal.

[0015] An electronic device according to a third aspect of the present invention includes: Memory, used to store programs; A processor for executing a program stored in the memory, wherein when the processor executes the program stored in the memory, the processor is configured to perform the method as described in any one of the first aspects.

[0016] According to a fourth aspect of the present invention, a storage medium stores computer-executable instructions for performing the method as described in any one of the first aspects.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0018] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0019] Figure 1 This is a flowchart of a method for generating scanning signals in a controllable seismic source according to an embodiment of the present invention; Figure 2 This is a comparison diagram of the correlation wavelet of the scanning signal generated by a scanning signal generation method in a controllable seismic source according to another embodiment of the present invention and the correlation wavelet of the existing linear scanning signal; Figure 3 This is a comparison diagram of a method for generating scanning signals in a controllable seismic source according to another embodiment of the present invention. The left side shows the relevant seismic record diagram obtained from existing linear scanning signals, and the right side shows the relevant seismic record diagram obtained from the scanning signals generated by the method provided by the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] It should be understood that in the description of the embodiments of the present invention, "multiple" (or "amounts") means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. If "first," "second," etc., are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0022] like Figure 1 As shown, this embodiment of the invention provides a method for generating scanning signals in a controllable seismic source, including: Step S100: Perform continuous wavelet transform on the ideal unit pulse to obtain the full-band ideal material; Step S200: Based on the ideal full-band material, several scale components are selected; Step S300: Reconstruct the scale components to obtain the ideal wavelet; Step S400: Determine the instantaneous frequency curve based on the ideal wavelet; Step S500: Determine the scanning signal based on the instantaneous frequency curve and the preset amplitude envelope.

[0023] This invention begins with an ideal unit pulse representing the theoretical limit, and obtains the optimal waveform, i.e., the ideal wavelet, under band-limited conditions through frequency-selective reconstruction using wavelet transform. Then, based on the ideal wavelet, the instantaneous frequency curve corresponding to this ideal wavelet is derived using physical relationships. Finally, a physically realizable scanning signal is synthesized. This method ensures that the autocorrelation function of the scanning signal approximates the ideal wavelet through wavelet transform reconstruction. That is, the wavelet corresponding to the constructed scanning signal achieves a near-optimal state with a narrower main lobe width under a given system bandwidth, thus implanting high-resolution features at the data acquisition source and systematically improving the quality of seismic data.

[0024] In one embodiment, step S100 specifically includes: Using the ideal unit impulse (δ function) as the "primary blank," which possesses an infinitely flat full-band spectrum, provides unbiased raw material for subsequent construction. For the unit impulse function... Perform continuous wavelet transform (CWT) to obtain its full-band time-frequency representation. .

[0025] (1) in, wavelet basis functions Through scale Peaceful relocation The latter form is preferred for complex Morlet wavelets. As a basis function, it has good time-frequency aggregation properties.

[0026] In the formula: For the mother wavelet (basis function). Indicates its complex conjugate; The scale is used to control the range of frequency analysis; These are translation parameters that control the time and position. The wavelet transform coefficients (time spectrum) of the pulse function are the complete representation of the δ function in the time-frequency plane.

[0027] In one embodiment, in step S200, several scale components are selected based on the ideal full-band material, including: Based on the various scales corresponding to the ideal full-band material, determine the corresponding center frequency and frequency window radius respectively; Based on the center frequency and frequency window radius corresponding to the ideal full-band material, the scale components of the frequency window within the preset effective frequency band are obtained.

[0028] It should be noted that the full-band ideal material refers to several scale components after different scale transformations of the ideal unit pulse.

[0029] Specifically, step S200 involves constraining the theoretically ideal full-band data to the effective frequency band actually usable by the seismic instrument, thereby ensuring the physical feasibility of the design.

[0030] Based on the effective frequency band of the seismic acquisition system This range is determined by instrument performance and exploration targets. Calculate each scale. The corresponding main frequency analysis range. For Morlet wavelets, its scale... The corresponding center frequency is The frequency window radius is Filter out all that meet the criteria. The scale a forms the selected scale set Asel. This step is equivalent to precisely "cropping" out the region corresponding to the effective frequency band on the time-frequency plane.

[0031] It should be noted that f0 refers to the center frequency of the wavelet basis function (preferably the complex Morlet wavelet), which is the core parameter characterizing the frequency characteristics of the basis function in wavelet transform, and has a corresponding relationship with scale a in step S100; The method for obtaining f0 is as follows: combining the effective frequency band of the seismic acquisition system, the exploration target (shallow high resolution / deep strong penetration) and the wavelet basis function type (complex Morlet wavelet is preferred in this invention), it is determined through preset and calculation, specifically as follows: First, the effective frequency band range of the seismic acquisition system is determined (determined by instrument performance and exploration target, such as 7-108Hz in the example); combined with exploration requirements (such as shallow high resolution requiring emphasis on mid-to-high frequencies, and deep exploration requiring emphasis on low frequencies), the approximate value range of f0 is determined (it must fall within the effective frequency band to ensure the rationality of subsequent scale selection); for the complex Morlet wavelet preferred in this invention, its f0 can be determined by preset empirical values ​​or formula calculation: the standard center frequency of the complex Morlet wavelet is usually preset to f0=1 (dimensionless, the corresponding actual frequency needs to be converted in conjunction with the sampling frequency), or it can be adjusted according to the center frequency of the effective frequency band. The conversion formula is f0(actual)=fs / (2πa) (where fs is the sampling frequency of the seismic acquisition system, a is the scale factor, which is negatively correlated with f0. The smaller the scale a, the higher f0(actual)).

[0032] In one embodiment, in step S300, the scale components are reconstructed to obtain an ideal wavelet, including: Perform inverse wavelet transform on the scale components; The scale components after inverse wavelet transform are combined into a time-domain waveform, i.e., an ideal wavelet.

[0033] In this embodiment, the selected time-frequency components are combined into a time-domain waveform, which has the best time-domain cohesion (narrowest main lobe and lowest side lobe) within the effective frequency band. Only for the selected scale set A sel Inverse wavelet transform (ICWT) of the wavelet coefficients within the wavelet: Synthesizing an ideal wavelet: (2) in, Let w be the wavelet admissibility constant. ideal (t) is the ideal wavelet, which is the target shape of the autocorrelation function of the subsequent scanning signal.

[0034] This embodiment is equivalent to shaping the spectrum of δ(t) using an "optimal filter" with a passband shape determined by the wavelet basis function and steep sideband cutoffs. The resulting ideal wavelet has the most concentrated energy within the effective frequency band, the narrowest main lobe width (highest time resolution), and the sidelobe and tail oscillations are suppressed to the greatest extent.

[0035] In one embodiment, in step S400, determining the instantaneous frequency curve based on the ideal wavelet includes: The mode after Fourier transform of the ideal wavelet is used as the target amplitude spectrum; Based on energy conservation, the instantaneous frequency curve is obtained by inverting the target amplitude spectrum.

[0036] In one embodiment, obtaining the instantaneous frequency curve from the target amplitude spectrum inversion includes: Based on the preset scanning parameters and target amplitude spectrum, the normalization constant is obtained with total energy constraint; Based on the target amplitude spectrum and normalization constant, the correspondence between time and frequency is obtained through the Runge-Kutta method; The relationship between time and frequency is interpolated using cubic spline interpolation, and the inverse function after interpolation is obtained, thus yielding the instantaneous frequency curve.

[0037] It is easy to understand that the instantaneous frequency curve is the correspondence between frequency and time, where time is the independent variable.

[0038] Specifically, the ideal wavelet in the time domain is converted into its frequency domain representation, providing a clear target for the spectrum design of the scanning signal; the ideal wavelet in the time domain obtained in step S100 is converted into its frequency domain representation—the target amplitude spectrum, providing a clear target for the spectrum shape of the scanning signal. For ideal wavelet Perform a Fourier transform and take its modulus as the target amplitude spectrum. : (3) This step completes the transformation from "desired waveform" to "desired spectrum," establishing a direct objective for designing the amplitude spectrum of the scanned signal; Based on the target amplitude spectrum, determine how the frequency of the scanning signal should change over time to match its amplitude spectrum; based on the principle of energy conservation of the scanning signal, the square of the amplitude spectrum... With instantaneous frequency change rate The process of obtaining the instantaneous frequency curve, which is inversely proportional to the frequency, includes: Set scan parameters: starting frequency Termination frequency Scan duration T; Solve by integrating the total energy normalization constraint. Substitute the instantaneous rate of change of frequency (Formula (5)) yields

[0039] Integrating over the rate of change of frequency, we obtain : (Formula (4)), using the Runge-Kutta method for numerical solution, several discrete (f,t) points are obtained. The change of t is gradual in the low-frequency range and rapid in the high-frequency range; then smoothed by cubic spline interpolation. ; For functions Finding the inverse function yields the nonlinear instantaneous frequency curve. : , ……(6) This is a core step in reverse engineering, which involves static spectrum targets. Dynamically mapped to frequency-time commands executable by a controllable seismic source hydraulic servo system. This represents a crucial leap from "design goals" to "implementation methods."

[0040] In one embodiment, it further includes: Convolve the scan signal with the time-reversed complex conjugate of the scan signal to obtain the actual correlated wavelet; Determine the root mean square error between the actual correlated wavelet and the ideal wavelet; If the root mean square error is less than the preset error threshold, the scan signal passes the verification.

[0041] Specifically, step S500 synthesizes a time-series signal that can directly drive a controllable seismic source based on the frequency variation law.

[0042] Using instantaneous frequency curves and the selected amplitude envelope (Such as the Tukey window, used for smooth start and end) Substitute the general expression for the scan signal to generate the scan signal. : …(7) in This represents the instantaneous phase. Where A... env (t) is the amplitude envelope function (such as the Tukey window), used to suppress the cutoff effect; Theoretically, this scanning signal autocorrelation function The ideal wavelet is approximately equal to the one constructed in step S100. Because the spectrum of the autocorrelation function is equal to the signal power spectrum, and The amplitude spectrum (after envelope fine-tuning) was designed to approximate ; Calculate the actual correlated wavelet, (Formula (8)) requires that w ideal The root mean square error (RMSE) of (t) is ≤0.05.

[0043] In one specific embodiment, for the eastern ZD exploration area, a nonlinear scanning signal is designed to take into account both deep structural (0.9-1.0 seconds) and shallow high-resolution (0.3-0.5 seconds) imaging. The effective frequency band is 7-108Hz (consistent with traditional linear scanning signals), the sampling frequency fs=250Hz (a standard configuration for seismic acquisition systems, meeting the effective frequency band sampling requirements), and the scanning duration T=10 seconds (shorter than the traditional 12 seconds, improving acquisition efficiency). The core objective is to suppress the related wavelet sidelobes and optimize energy distribution to solve the problem of insufficient resolution in traditional linear scanning. The following describes in detail the parameter values, calculation process, and results of each step in the six steps of the invention, corresponding to the final performance indicators of the embodiment (related wavelet main lobe width 9.15ms, sidelobe peak value -33.3dB, etc.).

[0044] (I) Step 1: Perform continuous wavelet transform on the δ function to obtain full-band time-frequency data. 1. For formula (1), the values ​​of each parameter are as follows: (1) δ(t): Ideal unit impulse function, with the following values: when t=0, δ(t)=1; when t≠0, δ(t)=0 (the standard value of ideal impulse in seismic exploration, used to provide full-band raw data). (2) ψ(t): Mother wavelet (basis function), the complex Morlet wavelet is selected (preferred in the example, taking into account time and frequency clustering), its standard expression is ψ(t)=exp(-t² / 2)·exp(j2πf0t), where f0=1 (dimensional standard value, which will be converted to the actual frequency in combination with the sampling frequency later). (3): The complex conjugate of ψ(t) takes the value ψ*(t)=exp(-t² / 2)·exp(-j2πf0t) (the standard form of the complex conjugate of the complex Morlet wavelet, corresponding to the mother wavelet); (4) a: scale factor, initially the full range of values ​​(before filtering), the value range is a∈[0.1, 20] (combined with the effective frequency band 7-108Hz and the sampling frequency 250Hz preset, covering the scale range corresponding to the full frequency band); (5) τ: translation parameter, the value range is τ∈[0, T] (corresponding to the subsequent scan duration T=10 seconds, covering the entire time axis to ensure the integrity of the time-frequency representation); (6) : Scale normalization coefficients (wavelet transform standard coefficients, used to ensure the energy consistency of wavelet basis functions at different scales).

[0045] 2. The result obtained from formula (1): The wavelet transform coefficients (time-frequency spectrum) of the delta function are calculated. These coefficients are a two-dimensional matrix (dimension is "scale a × translation parameter τ"), covering the full time-frequency range of a∈[0.1,20] and τ∈[0,10s]. This matrix fully characterizes the time-frequency characteristics of the delta function across the entire frequency band and time axis, providing full-band time-frequency material for the scale selection in the subsequent step two. The characteristics of this time-frequency spectrum are: it is distributed across the entire scale (frequency) range, has uniform energy, and its unbiasedness satisfies the requirements for subsequent ideal wavelet synthesis.

[0046] (ii) Step 2: Select scale components based on effective frequency bands (corresponding to Morlet wavelet center frequency and frequency window radius calculations) 1. Core parameters and their calculated values (1) Effective frequency band range: Based on the requirements of the work area in the example, it is determined to be f∈[7Hz, 108Hz] (determined by the performance of the seismic acquisition instrument and the exploration target—deep structure + shallow high resolution). (2) f0 (complex Morlet wavelet center frequency, dimensionless to actual frequency): According to the conversion formula f0(actual)=fs / (2πa), combined with the preset f0=1 (dimensionless) and fs=250Hz, we can derive a=fs / (2πf0(actual)), and then combine the effective frequency band screening scale a. (3) Correspondence between Morlet wavelet scale a and actual frequency: The center frequency f_c (actual) of complex Morlet wavelet is negatively correlated with scale a. The specific corresponding formula is f_c=fs / (2πa) (i.e. f0 (actual) mentioned above), and the frequency window radius Δf=f_c / √2 (the standard calculation formula for the frequency window radius of Morlet wavelet). (4) Screening conditions: The frequency window and the effective frequency band [7Hz, 108Hz] must intersect, that is, f_c-Δf≤108Hz and f_c+Δf≥7Hz (to ensure that the frequency range corresponding to the screened scale falls within the effective frequency band and to ensure physical feasibility).

[0047] 2. Parameter calculation process and screening results: (1) Calculate the range of the corresponding scale a based on the effective frequency band boundary: ① When f_c = 7Hz (lower limit of effective frequency band), a = fs / (2πf_c) = 250 / (2×3.1416×7) ≈ 5.7; ② When f_c = 108Hz (the upper limit of the effective frequency band), a = fs / (2πf_c) = 250 / (2 × 3.1416 × 108) ≈ 0.37; (2) Verification by combining the frequency window radius: For the scale a∈[0.37,5.7], the corresponding frequency window Δf=f_c / √2 all satisfy the condition that it intersects with the effective frequency band [7Hz,108Hz] and there are no invalid frequency components that exceed the effective frequency band; (3) Final screening results: Select the scale set Asel={a | 0.37 ≤ a ≤ 5.7}, and screen out a total of 30 discrete scale points (uniformly distributed, with an interval of 0.18). Complete the "pruning" of the effective frequency band region on the time-frequency plane, retain only the time-frequency components corresponding to the effective frequency band, and remove invalid scales (a<0.37 corresponds to a frequency>108Hz, a>5.7 corresponds to a frequency<7Hz).

[0048] (III) Step 3: Partial reconstruction and synthesis of ideal correlated wavelet (corresponding to formula 2) 1. For formula (2), the values ​​of each parameter are as follows: (1) The wavelet admissibility constant, for the complex Morlet wavelet (f0=1), has the following standard value: =π^(1 / 4)≈0.7071 (a fixed admissibility constant of the complex Morlet wavelet in wavelet transform, ensuring the effectiveness of the inverse transform). (2) A sel The scale set after step two filtering, i.e., a∈[0.37, 5.7], consists of 30 discrete scale points; (3): The wavelet transform coefficients obtained in step one are selected only for A. sel The coefficients within the scale range (excluding coefficients corresponding to invalid scales) are taken as the parts corresponding to "a∈[0.37,5.7], τ∈[0,10s]" in the two-dimensional matrix obtained in step one; (4) 1 / a²: Scale weighting coefficient (standard coefficients of inverse wavelet transform, used to balance the energy contribution of different scale components). (5) ψ((t-τ) / a) The wavelet basis function adjusted by scale a and translation τ is consistent with step one and is a scaled and translated form of complex Morlet wavelet.

[0049] 2. The result obtained from formula (2): The ideal correlation wavelet was calculated. Its core indicators correspond to the final performance of the implementation examples, and the specific results are as follows: (1) Temporal morphology: The main lobe width is 9.15 ms (which meets the core indicators of the embodiment, slightly wider than the traditional linear scan of 8.76 ms, but the side lobe suppression effect is significant). (2) Sidelobe characteristics: The sidelobe peak value is -33.3dB (compared to -13.2dB of traditional linear scanning, it is significantly suppressed and reduces spurious in-phase axis interference). (3) Energy distribution: The energy is most concentrated in the effective frequency band [7Hz, 108Hz], the tail wave oscillation is suppressed to the greatest extent (fast attenuation speed, no obvious tail), the time domain concentration is optimal, and it provides a target wavelet blueprint for the design of subsequent scanning signals (corresponding to the design target of "ideal correlated wavelet" in the embodiment). (iv) Step 4: Extract the target amplitude spectrum (corresponding formula 3) 1. For formula (3), the values ​​of each parameter are as follows: (1) The ideal correlated wavelet synthesized in step three takes the time-domain waveform data obtained in step three (time range t∈[0,10s], sampling interval 1 / fs=4ms, a total of 2500 sampling points). (2) F{·}: Fourier transform operator (using Fast Fourier Transform (FFT), a conventional method for seismic signal processing); (3) |·|: Modulus operation (used to extract amplitude spectrum, remove phase information, and retain only amplitude characteristics).

[0050] 2. The result obtained from formula (3): Calculated The target amplitude spectrum |F{wideal(t)}| has a frequency range consistent with the effective frequency band [7Hz, 108Hz], and its core characteristics correspond to the energy distribution optimization target of the embodiment. (1) Low frequency band (7-15Hz): The amplitude is increased by 39% compared with the traditional linear scanning (laying the foundation for enhanced deep penetration). (2) Mid-to-high frequency band (75-90Hz): The amplitude is increased by 40% compared with the traditional linear scanning (laying the foundation for improving the high resolution of shallow layers). (3) Power frequency interference band (55-65Hz): The amplitude is actively suppressed (more than 25% lower than that of traditional linear scanning), reducing the impact of power frequency interference on the signal; (4) Spectral continuity: The amplitude transitions smoothly within the frequency band without obvious abrupt changes, providing a clear and stable target spectrum for the instantaneous frequency inversion in the subsequent step five.

[0051] (V) Step 5: Invert the nonlinear instantaneous frequency curve The core of this step is based on the principle of energy conservation, which inverts to obtain an executable nonlinear instantaneous frequency curve. The values ​​of the parameters in each formula and the results are as follows: 1. Preset scan parameters (basic input): (1) Starting frequency f_start: usually close to f0 (actual). Combined with the value of f0 (actual) in step two, set f_start=15Hz (within the effective frequency band, taking into account both deep low frequency penetration and shallow high frequency resolution). (2) Termination frequency f_end: Set f_end=100Hz (close to the upper limit of the effective frequency band of 108Hz to avoid excessive amplification of high frequency noise); (3) Scanning time T = 10 seconds (set in the example, which is shorter than the traditional 12 seconds and improves the acquisition efficiency by 16.7%). (4) Target amplitude spectrum |F{wideal(t)}|: The result obtained in step four is used as the core input for energy conservation calculation.

[0052] 2. For formula (5) (energy conservation relationship), parameter values ​​and calculations: (1) |S(f)|: the amplitude spectrum of the scan signal, here we take the target amplitude spectrum |F{wideal(t)}| obtained in step four (i.e. |S(f)|=|F{wideal(t)}|), with frequency f∈[7Hz,108Hz]; (2) df / dt: instantaneous frequency change rate (core unknown); (3) k: normalization constant, determined by the total energy constraint formula (10).

[0053] 3. For formula (4) (time-frequency relationship), parameter values ​​and calculations: (1) k: Calculated in step three, k≈0.012; (2) |S(f)|²: the square of the target amplitude spectrum obtained in step four, i.e., |F{wideal(t)}|²; (3) Integration range: f∈[f_start, f], that is, the integral from the starting frequency of 15Hz to any frequency f; (4) Calculation process: Substitute k and |S(f)|² into the formula, and solve numerically using the Runge-Kutta method (4th order, step size 0.1Hz) to obtain the correspondence between time t and frequency f t(f) (a set of discrete points, a total of 851 points, covering f∈[15Hz,100Hz]). (5) Calculation results: The discrete data of t(f) are obtained, which show a nonlinear relationship (t changes slowly with f in the low frequency range and changes rapidly with f in the high frequency range, which matches the energy distribution optimization requirements).

[0054] 4. For formula (6) (nonlinear instantaneous frequency curve), parameter values ​​and calculations: (1) t(f): The time-frequency correspondence obtained by formula (4) (discrete points); (2) Calculation process: Perform cubic spline interpolation on t(f) (interpolation step size 0.01 seconds), find its inverse function, and obtain f(t) (the curve of instantaneous frequency change with time); (3) Calculation results: A smooth nonlinear instantaneous frequency curve f(t) is obtained, t∈[0,10s]. The core features are: 0-3s (low frequency band), f(t) slowly rises from 15Hz to 30Hz (strengthening low frequency energy and enhancing deep penetration); 3-7s (mid frequency band), f(t) rapidly rises from 30Hz to 85Hz (balancing mid-high frequency energy); 7-10s (high frequency band), f(t) rises from 85Hz to 100Hz (strengthening mid-high frequency energy and improving shallow resolution), which perfectly matches the energy distribution requirements of the target amplitude spectrum in step four.

[0055] (vi) Step Six: Nonlinear Scanning Signal Generation and Verification 1. For formula (7) (scan signal generation), parameter values ​​and calculations: (1) A env (t): Amplitude envelope function, using Tukey window (preferred in the embodiment, used to smooth the start and end of the signal and suppress the truncation effect), window length 10 seconds, transition zone length 1 second (i.e., the first 1 second and the last 1 second are smooth transitions, and the middle 8 seconds are constant amplitude), and the maximum amplitude is set to 1 (normalization processing, adapted to the drive range of controllable source instrument). (2) f(t): The nonlinear instantaneous frequency curve obtained in step five, t∈[0,10s], with one sampling point every 0.01 seconds; (3) φ(t): instantaneous phase, obtained by integration, i.e. φ(t) = 2π∫0 t f(τ)dτ (integration step size 0.01 seconds, initial phase φ(0)=0); (4) Calculation process: Substitute Aenv(t), f(t), and φ(t) into the formula and calculate the time domain data of the scanning signal s(t) point by point (t∈[0,10s], sampling interval 4ms, a total of 2500 sampling points); (5) Calculation results: The nonlinear scanning signal s(t) that can directly drive the controllable source is obtained. The time domain waveform is smooth, with no obvious truncation noise at the beginning and end. The frequency changes nonlinearly with time, which perfectly matches the instantaneous frequency curve in step five and meets the physical signal requirements for field excitation.

[0056] 2. For formula (8) (actual correlation wavelet calculation, closed-loop verification), parameter values ​​and calculations: (1) s(t): The nonlinear scanning signal generated in step six, and the time-domain data is the result obtained in step six; (2) s*(-t): the time-reversed complex conjugate of s(t). For a real signal s(t), s*(-t) = s(-t) (in the example, the scanning signal is a real signal, which simplifies the calculation). (3) *: Convolution operation (using fast convolution method to improve computational efficiency); (4) Calculation process: Perform convolution operation on s(t) and s*(-t) to obtain the actual correlated wavelet w(t); (5) Calculation results and verification: The root mean square error (RMSE) of the actual correlated wavelet w(t) and the ideal correlated wavelet wideal(t) synthesized in step three is approximately 0.032 (≤0.05, which meets the closed-loop verification requirements). Meanwhile, the core indicators of the actual correlated wavelet are consistent with those of the embodiment: main lobe width 9.15ms, side lobe peak value -33.3dB. Spectral analysis shows that the correlation coefficient between the amplitude spectrum of the actual scanning signal and the target amplitude spectrum in step four is as high as 0.987, which verifies the effectiveness of the design method.

[0057] (vii) Overall summary of the implementation plan Through the complete implementation of the above six steps, combined with the parameter values ​​and calculations of each formula, a nonlinear scanning signal adapted to the ZD exploration area in the east was finally generated, achieving the following effects: the shallow main frequency was increased from 70Hz to over 88Hz, the deep main frequency was increased from 38Hz to 45Hz, the overall signal-to-noise ratio was improved by 1.5-2.0 dB, and the scanning time was shortened from 12 seconds to 10 seconds (improving acquisition efficiency by 16.7%). This completely solved the problem of insufficient resolution (wide main lobe and high side lobe) of traditional linear scanning signals, meeting the imaging requirements of deep structures and high-resolution shallow structures in the exploration area, and is completely consistent with the performance indicators described in the example.

[0058] The technical effects of this embodiment include: a fundamental breakthrough in resolution: through the core operation of "pulse decomposition-band selection-partial reconstruction", the constructed correlation wavelet achieves a near-optimal state with a narrower main lobe width under a given system bandwidth; this directly translates into a significant improvement in the longitudinal resolution of seismic records, making it possible to identify thinner rock layers and finer geological structures. Substantial improvement in profile fidelity: such as Figure 2 , Figure 3 As shown, thanks to the effective suppression of ideal wavelet sidelobes and wake oscillations, the false phase axes and interference phenomena caused by wavelet sidelobes in the seismic record are greatly reduced; this makes the seismic profile reflect the sequence of subsurface reflection coefficients more realistically and cleanly, greatly improving the reliability and accuracy of structural interpretation and reservoir prediction. Optimization of signal-to-noise ratio within the effective frequency band: This method is not a simple spread spectrum approach, but rather achieves intelligent allocation of signal energy by optimizing the amplitude spectrum shape (such as enhancing penetrating low frequencies and rationally controlling high frequencies). This broadens the effective frequency band on the one hand, and avoids excessive amplification of ineffective high-frequency noise on the other, thereby improving the overall signal-to-noise ratio while enhancing resolution. This invention also provides a controllable seismic source, comprising: The scanning signal generation module is used to execute the scanning signal generation method in the controllable seismic source described above to obtain the scanning signal; The scan signal transmitting module is used to transmit the scan signal generated by the scan signal generating module; The reflected wave collection module is used to collect and record the emitted waves of the emitted scanning signal.

[0059] This invention also provides an electronic device, which includes, but is not limited to: Memory, used to store programs; The processor is used to execute the program stored in the memory. When the processor executes the program stored in the memory, the processor is used to execute the above-mentioned method for generating scanning signals in a controllable seismic source.

[0060] The processor and memory can be connected via a bus or other means.

[0061] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs, such as the method described in the embodiments of the present invention. The processor implements the above method by running the non-transitory software program and instructions stored in the memory.

[0062] The memory may include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function; the data storage area may store data for executing the methods described above. Furthermore, the memory may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0063] The non-transitory software program and instructions required to implement the above terminal selection method are stored in memory and are executed by one or more processors.

[0064] This invention also provides a storage medium storing computer-executable instructions for performing the above-described methods.

[0065] In one embodiment, the storage medium stores computer-executable instructions that are executed by one or more control processors.

[0066] The embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0067] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0068] This document describes embodiments of the invention, including preferred embodiments known to the inventors for carrying out the invention. Variations of these embodiments will become apparent to those skilled in the art upon reading the foregoing description. The inventors encourage those skilled in the art to adopt such variations as appropriate, and the inventors intend to practice embodiments of the invention in ways other than those specifically described herein. Therefore, the scope of the invention includes all modifications and equivalents of the subject matter set forth in the appended claims, as permitted by applicable law. Furthermore, the scope of the invention covers any combination of the foregoing elements in all possible variations thereof, unless otherwise indicated herein or otherwise clearly contradicted by the context.

Claims

1. A method for generating scanning signals in a controllable seismic source, characterized in that, include: By performing continuous wavelet transform on the ideal unit pulse, we can obtain ideal materials across the entire frequency band. Based on the ideal full-band material, several scale components were obtained by screening. The scale components are reconstructed to obtain the ideal wavelet; Determine the instantaneous frequency curve based on the ideal wavelet; The scanning signal is determined based on the instantaneous frequency curve and the preset amplitude envelope.

2. The method for generating scanning signals in a controllable seismic source according to claim 1, characterized in that, The process of selecting several scale components based on the ideal full-band material includes: Based on the scales corresponding to the full-band ideal material, determine the corresponding center frequency and frequency window radius respectively; Based on the center frequency and frequency window radius corresponding to the ideal full-band material, the scale components of the frequency window within the preset effective frequency band are obtained.

3. The method for generating scanning signals in a controllable seismic source according to claim 1, characterized in that, The process of reconstructing the scale components to obtain the ideal wavelet includes: Perform inverse wavelet transform on the scale components; The scale components after inverse wavelet transform are combined into a time-domain waveform, namely the ideal wavelet.

4. The method for generating scanning signals in a controllable seismic source according to claim 1, characterized in that, Determining the instantaneous frequency curve based on the ideal wavelet includes: The mode after Fourier transform of the ideal wavelet is taken as the target amplitude spectrum; Based on the conservation of energy, the instantaneous frequency curve is obtained by inverting the target amplitude spectrum.

5. The method for generating scanning signals in a controllable seismic source according to claim 4, characterized in that, The process of obtaining the instantaneous frequency curve based on the target amplitude spectrum inversion includes: Based on the preset scanning parameters and the target amplitude spectrum, a normalization constant is obtained with total energy constraint; Based on the target amplitude spectrum and the normalization constant, the correspondence between time and frequency is obtained using the Runge-Kutta method; The relationship between time and frequency is interpolated using cubic spline interpolation, and the inverse function after interpolation is obtained, thus yielding the instantaneous frequency curve.

6. The method for generating scanning signals in a controllable seismic source according to claim 1, characterized in that, Also includes: Convolve the scan signal with the time-reversed complex conjugate of the scan signal to obtain the actual correlated wavelet; Determine the root mean square error between the actual correlated wavelet and the ideal wavelet; If the root mean square error is less than a preset error threshold, the scanning signal passes the verification.

7. The method for generating scanning signals in a controllable seismic source according to claim 1, characterized in that, The amplitude envelope is defined using a window function.

8. A controllable seismic source, characterized in that, include: A scan signal generation module is configured to perform the method as described in any one of claims 1 to 7 to obtain a scan signal; A scan signal transmitting module is used to transmit the scan signal generated by the scan signal generating module; The reflected wave collection module is used to collect and record the emitted waves of the emitted scanning signal.

9. An electronic device, characterized in that, include: Memory, used to store programs; A processor for executing a program stored in the memory, wherein when the processor executes the program stored in the memory, the processor is configured to perform the method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The device stores computer-executable instructions for performing the method as described in any one of claims 1 to 7.

Images