Data interpolation method and device for suppressing abnormal amplitude, medium and equipment

Abstract

The invention provides a data interpolation method and device for suppressing abnormal amplitude, a medium and equipment, and belongs to the technical field of geophysical exploration. The method comprises the following steps: firstly, judging whether amplitude energy of input seismic data amplitude needs to be reduced or not, converting seismic data into a frequency wave number spectrum, iteratively extracting the frequency wave number spectrum of an effective signal, and inversely transforming the extracted frequency wave number spectrum into time-space domain data to obtain a final result. According to the method, the residual frequency wavenumber spectrum energy of each iteration is calculated, the iteration convergence is judged, if the energy is smaller than that of the previous iteration, the operation is continued, otherwise, the current iteration is stopped, the conditions of NaN and inf occurring in the calculation process are reduced, and the stability and practicability of the seismic data denoising and interpolation effect are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of geophysical exploration, and particularly relates to a data interpolation method, device, medium and equipment for suppressing abnormal amplitudes. Background Art

[0002] With the in-depth development of oil and gas exploration, exploration and development have gradually shifted to complex oil and gas reservoirs. High-resolution seismic exploration, time-lapse seismic exploration and other exploration technologies have gradually increased the requirements for the quality of seismic data. Due to factors such as surface terrain conditions, seismic data acquisition is often irregular, which seriously affects the migration imaging quality of seismic data. With the development of seismic data interpolation technology, this problem has gradually been solved by the five-dimensional regularization technology. However, the intuitive factor of the effect is affected by the window boundary during the interpolation process. This technology mainly compensates the energy in the overlapping area of the window boundary, so that the energy in the overlapping area and non-overlapping area of the window is basically the same. This technology has been gradually widely applied to seismic data noise suppression and data interpolation, which is of great significance for improving the quality of seismic data.

[0003] However, due to the existence of abnormal amplitudes in seismic data, the problem of non-convergence or even divergence may occur during the iteration process, and abnormal energy clusters appear around the abnormal amplitudes, resulting in poor final denoising or interpolation effects. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art, and provide a data interpolation method, device, medium and equipment for suppressing abnormal amplitudes, which judges whether the frequency-wavenumber energy extracted by the convergence curve is normal during the iteration process, stops the calculation in time when encountering non-convergence or divergence during the iteration, and reduces the occurrence of NaN and inf during the calculation process, thereby improving the stability of the result.

[0005] The present invention is achieved by the following technical solutions:

[0006] In the first aspect of the present invention, a data interpolation method for suppressing abnormal amplitudes is provided. First, it is judged whether the amplitude of the input seismic data needs to reduce the amplitude energy, the seismic data is transformed into the frequency-wavenumber spectrum and the frequency-wavenumber spectrum of the effective signal is iteratively extracted, and the extracted frequency-wavenumber spectrum is inverse-transformed into the time-space domain data to obtain the final result.

[0007] A further improvement of the present invention lies in:

[0008] The method specifically includes the following steps:

[0009] Step 1: Input seismic data;

[0010] Step 2: Judge whether the amplitude of the seismic data needs to reduce the amplitude energy;

[0011] Step 3: Convert the seismic data to the frequency-wavenumber spectrum;

[0012] Step 4: Iteratively extract the frequency-wavenumber spectrum of the effective signal;

[0013] Step 5: Perform an inverse transformation on the extracted frequency-wavenumber spectrum to the time-space domain data to obtain the final result.

[0014] A further improvement of the present invention lies in:

[0015] The specific operations in the said Step 1 include:

[0016] Input the seismic data X(t, x) to be denoised or interpolated, set the maximum amplitude value limit max_amp of the input data. If the amplitude of the input data exceeds max_amp, then set its amplitude to 0.

[0017] A further improvement of the present invention lies in:

[0018] The specific operations in the said Step 2 include:

[0019] Judge whether the average energy of the seismic data amplitude is greater than the set value. If it is greater than the set value, then X(t, x) = X(t, x) × ε, where ε ≤ 1, so that the average energy of X(t, x) is less than the set value. Otherwise, directly proceed to the next step.

[0020] A further improvement of the present invention lies in:

[0021] The specific operations in the said Step 3 include:

[0022] Perform a Fourier transform on the seismic data X(t, x) to obtain the frequency spectrum

[0023] For the frequency spectrum Perform an irregular Fourier transform to obtain the frequency-wavenumber spectrum

[0024] A further improvement of the present invention lies in:

[0025] The specific operations in the said Step 4 include:

[0026] (1) Let f = 0;

[0027] (2) Let iter = 0, generate of the same size as where all the values are 0 + 0i, and i is a complex number;

[0028] (3) Judge Whether NaN and inf appear. If they exist, set the corresponding positions to 0 + 0i, and then jump to (4). If they do not exist, directly jump to (4);

[0029] (4) Find the maximum value of the current frequency slice and find the position (f 1 , k 1 ), denoted as amp;

[0030] (5) Calculate

[0031] (6) Store the energy of the current :

[0032] Judge whether the current energy value s iter is less than the energy value S of the previous iteration iter-1 , if s iter < s iter-1 , then then jump to (7), otherwise, jump to (8);

[0033] (7) iter = iter + 1, judge whether iter is equal to the maximum number of iterations. If so, jump to (8), otherwise, jump to (5);

[0034] (8) f = f + 1, judge whether f is equal to F. If so, jump to (9), otherwise, jump to (2);

[0035] (9) End.

[0036] A further improvement of the present invention lies in:

[0037] The specific operation of step 5 is as follows:

[0038] Calculate to obtain the final result.

[0039] The second aspect of the present invention provides a data interpolation device for suppressing abnormal amplitudes, including:

[0040] An input unit for inputting seismic data;

[0041] A judgment unit for judging whether the amplitude energy of seismic data needs to be reduced;

[0042] A conversion unit for converting seismic data into a frequency-wavenumber spectrum;

[0043] An iteration unit for iteratively extracting the frequency-wavenumber spectrum of effective signals;

[0044] An inverse transformation unit performs an inverse transformation on the extracted frequency-wavenumber spectrum to time-space domain data to obtain a final result.

[0045] In a third aspect of the present invention, there is provided a computer-readable storage medium storing at least one computer-executable program, and when the at least one program is executed by a computer, the computer is caused to execute the steps in the data interpolation method for suppressing abnormal amplitudes as described above.

[0046] In a fourth aspect of the present invention, there is provided a computer device including a memory and a processor, where the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to execute the steps in the data interpolation method for suppressing abnormal amplitudes as described above.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] The present invention solves the problem that it is difficult for conventional algorithms to suppress abnormal amplitudes. By calculating the residual frequency-wavenumber spectrum energy of each iteration to judge the convergence of the iteration, if the energy is smaller than that of the previous iteration, continue; otherwise, stop the current iteration, and reduce the occurrence of NaN and inf in the calculation process, improving the stability and practicality of seismic data denoising and interpolation effects. Description of the Drawings

[0049] Figure 1 is a flowchart of a data interpolation method for suppressing abnormal amplitudes provided by the present invention;

[0050] Figure 2 is the seismic data before processing;

[0051] Figure 3 is the interpolation result using the conventional method;

[0052] Figure 4 is the interpolation result using the method of the present invention. Detailed Embodiments

[0053] The present invention will be further described in detail below with reference to the drawings:

[0054] Aiming at the problem that the final result also has abnormal amplitudes caused by abnormal amplitudes in the original data, the present invention proposes a data interpolation method for suppressing abnormal amplitudes. This method mainly applies the suppression of abnormal amplitudes to existing seismic data interpolation and denoising algorithms to achieve the suppression of aliasing.

[0055] The present invention provides a data interpolation method for suppressing abnormal amplitudes. First, it is determined whether the amplitude of the input seismic data needs to reduce the amplitude energy. The seismic data is transformed into the frequency-wavenumber spectrum and the frequency-wavenumber spectrum of the effective signal is iteratively extracted. The extracted frequency-wavenumber spectrum is inverse-transformed into the time-space domain data to obtain the final result.

[0056]

Example 1

[0057] An embodiment of the present invention provides a data interpolation method for suppressing abnormal amplitudes, as Figure 1 shown. The method specifically includes the following steps:

[0058] Step 1: Input seismic data;

[0059] The specific operation includes:

[0060] Input the seismic data X(t,x) to be denoised or interpolated, and set the maximum amplitude value limit max_amp of the input data. If the amplitude of the input data exceeds max_amp, set its amplitude to 0;

[0061] The input seismic data is time-space domain data.

[0062] Step 2: Determine whether the amplitude of the seismic data needs to reduce the amplitude energy;

[0063] The specific operation includes:

[0064] Judge whether the average energy of the seismic data amplitude is greater than the set value. If it is greater than the set value, then X(t,x) = X(t,x) × ε, so that the average energy of X(t,x) is less than the set value. Preferably, the set value = 100, aiming to ensure the stability of the subsequent spectrum calculation and avoid abnormal situations such as NaN and inf that are likely to occur when using nfft to calculate when the data volume is too large; otherwise, directly proceed to the next step.

[0065] Among them, the value of ε is determined according to the seismic data situation. Observe the basic range of the data amplitude so that the energy of the vast majority of the data is less than the set value 100 after X(t,x) × ε. Generally, ε ≤ 1.

[0066] Step 3: Transform the seismic data into the frequency-wavenumber spectrum;

[0067] The specific operation includes:

[0068] Perform Fourier transform on the seismic data X(t,x) to obtain the frequency spectrum

[0069] Perform non-regular Fourier transform on the frequency spectrum to obtain the frequency-wavenumber spectrum F and K respectively represent the maximum ranges of frequency and wavenumber spectrum processing.

[0070] Step 4: Iteratively extract the frequency-wavenumber spectrum of the effective signal;

[0071] The specific operations include:

[0072] (1) Loop through all frequency slices, and let f = 0;

[0073] (2) The number of iterations for a single frequency slice is 400. Let iter = 0, and generate with the same size as where all the values are 0 + 0i, and i is a complex number;

[0074] (3) Judge whether contains NaN and inf (judged by the isnan function and isinf function in C++; true in the result means yes, and false means no). If it exists, set the corresponding position to 0 + 0i, and then jump to (4). If it does not exist, directly jump to (4);

[0075] (4) Find the maximum value of the current frequency slice , and find the position (f 1 , k 1 ), and record as amp;

[0076] (5) Calculate

[0077] (6) Store the energy of the current :

[0078] Judge whether the current energy value s iter is less than the energy value S iter-1 of the previous iteration. If s iter < s iter-1 , then and then jump to (7). Otherwise, jump to (8);

[0079] (7) iter = iter + 1. Judge whether iter is equal to the maximum number of iterations 400. If so, jump to (8). Otherwise, jump to (5);

[0080] (8) f = f + 1. Judge whether f is equal to F. If so, jump to (9). Otherwise, jump to (2);

[0081] (9) End.

[0082] Step 5: Inverse-transform the extracted frequency-wavenumber spectrum into time-space domain data to obtain the final result.

[0083] Specifically: Calculate That is, the final result is obtained.

[0084] It should be noted that ε here is the same as ε in step 2.

[0085] Figure 2 is the seismic data before processing, Figure 3 and 4 are the results processed by the conventional method and the method of the present invention respectively. When processing by the conventional method, due to abnormal data values or iterative divergence, the obtained results are unstable. By the method of the present invention, abnormal amplitude energy can be effectively suppressed and the stability of the results can be improved.

[0086]

Embodiment 2

[0087] The embodiment of the present invention provides a data interpolation device for suppressing abnormal amplitudes, including:

[0088] An input unit for inputting seismic data, and specifically performing the following operations:

[0089] Input the seismic data X(t, x) to be denoised or interpolated, set the maximum amplitude value limit max_amp of the input data. If the amplitude of the input data exceeds max_amp, then set its amplitude to 0;

[0090] The input seismic data is time-space domain data.

[0091] A judgment unit for judging whether the amplitude of the seismic data needs to reduce the amplitude energy, and specifically performing the following operations:

[0092] Judge whether the average energy of the amplitude of the seismic data is greater than the set value. If it is greater than the set value, then X(t, x) = X(t, x) × ε, so that the average energy of X(t, x) is less than the set value. Preferably, the set value = 100, and the purpose is to ensure the stability of the subsequent calculation of the spectrum and avoid abnormal situations of NaN and inf that are likely to occur when using nfft to calculate when the data volume is too large; otherwise, directly enter the next step.

[0093] Among them, the value of ε is determined according to the situation of the seismic data. Observe the basic range of the data amplitude so that the energy of the vast majority of the data is less than the set value 100 after X(t, x) × ε. Generally, ε ≤ 1.

[0094] A conversion unit for converting the seismic data into a frequency-wavenumber spectrum, and specifically performing the following operations:

[0095] Perform a Fourier transform on the seismic data X(t, x) to obtain the spectrum

[0096] For the spectrum Perform an irregular Fourier transform to obtain the frequency-wavenumber spectrum F and K respectively represent the maximum ranges for frequency and wavenumber spectrum processing.

[0097] An iterative unit for iteratively extracting the frequency-wavenumber spectrum of the effective signal, which specifically performs the following operations:

[0098] (1) Loop through all frequency slices, setting f = 0;

[0099] (2) The number of iterations for a single frequency slice is 400. Set iter = 0 and generate of the same size as where all values are 0 + 0i and i is a complex number;

[0100] (3) Judge whether contains NaN and inf (judged by the C++ functions isnan and isinf, where true in the result means yes and false means no). If it exists, set the corresponding position to 0 + 0i and then jump to (4). If it does not exist, directly jump to (4);

[0101] (4) Find the maximum value of the current frequency slice and find the position (f 1 , k 1 ), and record as amp;

[0102] (5) Calculate

[0103] (6) Store the energy of the current :

[0104] Judge whether the current energy value s iter is less than the energy value S iter-1 of the previous iteration. If s iter < s iter-1 , then and then jump to (7). Otherwise, jump to (8);

[0105] (7) iter = iter + 1. Judge whether iter is equal to the maximum number of iterations 400. If so, jump to (8). Otherwise, jump to (5);

[0106] (8) f = f + 1. Judge whether f is equal to F. If so, jump to (9). Otherwise, jump to (2);

[0107] (9) End.

[0108] An inverse transformation unit performs an inverse transformation on the extracted frequency-wavenumber spectrum to obtain time-space domain data, and the final result is obtained. The specific operations are as follows:

[0109] Calculate That is, the final result is obtained.

[0110]

Embodiment 3

[0111] An embodiment of the present invention provides a computer-readable storage medium. The computer-readable storage medium stores at least one computer-executable program. When the at least one program is executed by the computer, the computer is caused to execute the steps in the data interpolation method for suppressing abnormal amplitudes as described above.

[0112]

Embodiment 4

[0113] An embodiment of the present invention provides a computer device, including a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps in the data interpolation method for suppressing abnormal amplitudes as described above.

[0114] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0115] The above technical solution is only one implementation mode of the present invention. For those skilled in the art, based on the disclosed principle of the present invention, it is very easy to make various types of improvements or deformations, and it is not limited to the technical solution described in the above specific embodiments of the present invention. Therefore, what is described above is only preferred and does not have a restrictive meaning.

Claims

1. A data interpolation method for suppressing abnormal amplitudes, characterized in that, firstly, it is judged whether the amplitude of the input seismic data needs to reduce the amplitude energy, the seismic data is transformed into the frequency-wavenumber spectrum and the frequency-wavenumber spectrum of the effective signal is iteratively extracted, and the extracted frequency-wavenumber spectrum is inverse-transformed into the time-space domain data to obtain the final result.

2. The data interpolation method for suppressing abnormal amplitudes according to claim 1, characterized in that, the method specifically includes the following steps: Step 1: Input seismic data; Step 2: Judge whether the amplitude of the seismic data needs to reduce the amplitude energy; Step 3: Transform the seismic data into the frequency-wavenumber spectrum; Step 4: Iteratively extract the frequency-wavenumber spectrum of the effective signal; Step 5: Inverse-transform the extracted frequency-wavenumber spectrum into the time-space domain data to obtain the final result.

3. The data interpolation method for suppressing abnormal amplitudes according to claim 2, characterized in that, the specific operation in the said Step 1 includes: Input the seismic data X(t, x) to be denoised or interpolated, set the maximum amplitude value limit max_amp of the input data, if the amplitude of the input data exceeds max_amp, then set its amplitude to 0.

4. The data interpolation method for suppressing abnormal amplitudes according to claim 2, characterized in that, the specific operation in the said Step 2 includes: Judge whether the average energy of the seismic data amplitude is greater than the set value, if it is greater than the set value, then X(t, x) = X(t, x) × ε, ε ≤ 1, so that the average energy of X(t, x) is less than the set value, otherwise, directly enter the next step.

5. The data interpolation method for suppressing abnormal amplitudes according to claim 2, characterized in that, the specific operation in the said Step 3 includes: Perform a Fourier transform on the seismic data X(t,x) to obtain the frequency spectrum For the spectrum Perform an irregular Fourier transform to obtain the frequency-wavenumber spectrum k = -K,..., -1, 0, 1,..., K.

6. The data interpolation method for suppressing abnormal amplitudes according to claim 5, characterized in that, the specific operation in the said Step 4 includes: (1) Let f = 0; (2) Let iter = 0 and generate of the same size as where the values are all 0 + 0i and i is a complex number; (3) Judge whether NaN and inf appear. If they exist, set the corresponding positions to 0+0i, and then jump to (4). If they do not exist, directly jump to (4); (4) Find the current frequency slice 's maximum value, and find the position (f 1 , k 1 ), denoted as amp; (5) Calculate (6) Store the current energy: Judge the current energy value s iter whether it is less than the energy value S of the previous iteration iter-1 If s iter < S iter-1 then then jump to (7), otherwise, jump to (8); (7) iter = iter + 1, judge whether iter is equal to the maximum number of iterations, if so, jump to (8), otherwise, jump to (5); (8) f = f + 1, judge whether f is equal to F, if so, jump to (9), otherwise, jump to (2); (9) End.

7. The data interpolation method for suppressing abnormal amplitudes according to claim 6, characterized in that, the specific operation of the said Step 5 is: Calculation That is, the final result is obtained.

8. A data interpolation device for suppressing abnormal amplitudes, characterized in that, comprising: An input unit for inputting seismic data; A judgment unit for judging whether the amplitude of the seismic data needs to reduce the amplitude energy; A conversion unit for transforming the seismic data into the frequency-wavenumber spectrum; An iterative unit for iteratively extracting the frequency-wavenumber spectrum of the effective signal; An inverse transformation unit for inverse-transforming the extracted frequency-wavenumber spectrum into the time-space domain data to obtain the final result.

9. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores at least one computer-executable program, and when the at least one program is executed by the computer, the computer executes the steps in the data interpolation method for suppressing abnormal amplitudes as described in any one of claims 1 - 7.

10. A computer device, characterized in that, It includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor is caused to execute the steps in the data interpolation method for suppressing abnormal amplitudes according to any one of claims 1-7.

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