Methods for improving the resolution of acoustic wave long-range detection data

Abstract

The present invention provides a method for improving the resolution of acoustic wave long-range detection data, and the method for improving the resolution of acoustic wave long-range detection data includes: step 1: collecting acoustic wave long-range detection data; step 2: selecting a seismic data; step 3: selecting the first sampling point of the seismic data; step 4: calculating the nth power of the amplitude 2 of the sampling point; step 5: calculating the nth power of the amplitude 2 of all sampling points of the seismic data; step 6: determining the value of n; step 7: processing all data according to steps 2-5; step 8: outputting the acoustic wave long-range detection result profile. The method for improving the resolution of acoustic wave long-range detection data only uses the acoustic wave data to improve the imaging resolution of the acoustic wave data through a simple calculation method, and can achieve the improvement of the imaging resolution of the acoustic wave long-range detection data.

Description

Technical Field

[0001] The invention relates to the field of oil and gas exploration acoustic wave long-range detection data processing, and in particular to a method for improving the resolution of acoustic wave long-range detection data. Background Art

[0002] Seismic record is equal to the convolution of seismic wavelet and reflection coefficient, that is, x(t)=b(t)*f(t), x(t) is seismic record, b(t) is seismic wavelet, f(t) is reflection coefficient, Fourier transform of the above formula gives X(ω)=B(ω)·F(ω), and mathematical operation gives The reflection coefficient obtained by inverse Fourier transform of the above formula is equal to the convolution of the seismic record and the anti-wavelet, that is, f(t) = h(t)*x(t), where h(t) is the anti-wavelet. Deconvolution is to use seismic records and anti-wavelets to obtain the reflection coefficient. First, the anti-wavelet is obtained by using the seismic record, and then the seismic record and the anti-wavelet are convolved to obtain the reflection coefficient. Based on the deconvolution method, the predictive deconvolution method uses seismic records to obtain the convolution factor, and then obtains the predicted seismic record. Then, the seismic record and the predicted record are subtracted to obtain a single reflection record, and the purpose of removing multiple waves and compressing the seismic wavelet is achieved to improve the resolution. These methods of improving resolution require the deconvolution factor, which is generally unknown and difficult to obtain. At the same time, these methods will reduce the signal-to-noise ratio while broadening the spectrum.

[0003] In the Chinese patent application with application number: CN201210031205.7, a method for improving the resolution of seismic data by well control is involved. The method for improving the resolution of seismic data by well control includes calculating the reflection coefficient at each well position; calculating the deconvolution operator at each well position according to the reflection coefficient at each well position; performing inverse distance weighted three-dimensional spatial interpolation on each deconvolution operator to obtain the deconvolution operator of each seismic trace in three-dimensional space; and performing convolution processing on the original seismic trace data according to the deconvolution operator of each seismic trace, and then obtaining a three-dimensional data body after phase correction and trace equalization.

[0004] In the Chinese patent application with application number: CN201310333410.3, a method for improving the resolution of seismic data by constraining inversion using acoustic logging data is involved. The core of the method is to establish a relationship between the high-resolution synthetic record of logging data and seismic data, improve the energy of high-frequency components in seismic data, and thus improve the resolution of seismic data. Since the high-frequency components of seismic data are submerged in noise, the conventional deconvolution method of improving resolution is difficult to achieve the purpose, and the ability to improve resolution is very limited. By combining the high-resolution synthetic record of logging data with seismic data, high-frequency energy can be effectively extracted.

[0005] In the Chinese patent application with application number: CN202010380368.0, a method and device for correcting acoustic wave time difference are involved, wherein the method comprises: determining whether each depth point is an expansion point according to the logging diameter at each depth point and the diameter of the drill bit used for logging; determining the upper limit value of the acoustic wave time difference at each expansion point according to the mud content at each expansion point, and obtaining the corrected measurement value of the acoustic wave time difference at each expansion point according to the upper limit value of the acoustic wave time difference at each expansion point and the acoustic wave time difference measurement value; determining the wellbore irregularity influence factor and the mud path influence factor at each expansion point according to the instrument measurement data at each expansion point; determining the acoustic wave time difference correction value of the interpretation layer section according to the corrected measurement value of the acoustic wave time difference at each expansion point, the wellbore irregularity influence factor and the mud path influence factor.

[0006] The above existing technologies are significantly different from the present invention and fail to solve the technical problem we want to solve. Therefore, how to improve the resolution by simple arithmetic operations using only acoustic wave data is an inevitable requirement for improving the imaging resolution of acoustic wave long-range detection data. For this reason, we have invented a method for improving the resolution of acoustic wave long-range detection data to solve the above technical problems. Summary of the invention

[0007] The purpose of the present invention is to provide a method for improving the resolution of acoustic wave long-range detection data by using only acoustic wave data through a simple calculation method to improve the imaging resolution of acoustic wave data, thereby achieving an improvement in the imaging resolution of acoustic wave long-range detection data.

[0008] The object of the present invention can be achieved by the following technical measures: a method for improving the resolution of acoustic wave long-range detection data, the method for improving the resolution of acoustic wave long-range detection data comprising:

[0009] Step 1: Collect acoustic wave remote detection data;

[0010] Step 2: Select a seismic data;

[0011] Step 3: Select the first sampling point of the seismic data;

[0012] Step 4: Calculate the nth power of the amplitude 2 of the sampling point;

[0013] Step 5: Calculate the nth power of the amplitude 2 of all sampling points of the seismic data;

[0014] Step 6: Determine the value of n;

[0015] Step 7: Process all data according to steps 2-5;

[0016] Step 8: Output the acoustic wave long-range detection result profile.

[0017] The purpose of the present invention can also be achieved by the following technical measures:

[0018] In step 1, the collected acoustic wave long-range detection data is an acoustic wave signal with certain morphological regular characteristics.

[0019] In step 2, the seismic data is composed of the effective signal and noise superposition. The effective signal is composed of frequencies f1,...f n It is generated by superposition of sine waves.

[0020] In step 2, the seismic data is:

[0021] x=s+n

[0022]

[0023] x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

[0024] In step 3, the sampling point amplitude is generated by superimposing the first amplitude of the sine wave of f and the amplitude of the noise.

[0025] In step 3, the amplitude of the sampling point is:

[0026] x(t1)=s(t1)+n(t1)

[0027]

[0028] x(t1) is the amplitude of the first sampling point of the seismic data, s(t1) is the amplitude of the first sampling point of the signal, n(t1) is the amplitude of the first sampling point of the noise, t1 is the time corresponding to the first sampling point, f is the frequency of the amplitude spectrum of s, is the initial phase corresponding to frequency f in the s phase spectrum.

[0029] In step 4, the nth power of the amplitude 2 of the sampling point is calculated, and the formula is as follows:

[0030]

[0031] A1 is the output amplitude value, A is the input amplitude value, and n is 1;

[0032] A1=x=s+n

[0033]

[0034] According to the frequency shift formula of the signal, we can get

[0035]

[0036] x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

[0037] In step 5, the nth power of the amplitude 2 of all sampling points of the data is calculated, and the formula is as follows:

[0038]

[0039] i=1,2,3...,N

[0040]

[0041] x 1i is the i-th output amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum;

[0042] A 1i is the i-th output amplitude value, A i is the i-th input amplitude value, N is the number of sampling points, and n is 1.

[0043] In step 6, the value of n is determined to determine whether the sub-wave is compressed into a pulse. If not, the value of n is increased. If so, the value of n is determined.

[0044] In step 7, all data are processed according to steps 2-5, and the value of n in steps 4 and 5 is equal to the value of n determined in step 6.

[0045] The beneficial effects of the present invention are as follows:

[0046] The method for improving the resolution of acoustic wave long-distance detection data in the present invention utilizes the multiplication of seismic data amplitude according to the frequency shift formula of the signal. After the multiplication, the seismic data undergoes frequency shift, and the frequencies are respectively shifted to 0 Hz and 2 times the original frequency. The random noise amplitude becomes 0 in the product. If the sub-wave is not compressed into a pulse, the frequency shift formula is repeatedly used to multiply the data amplitude to achieve the improvement of the resolution of the seismic data. The resolution of the imaging of acoustic wave long-distance detection data can be improved by using the seismic data itself through simple arithmetic operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of a specific embodiment 1 of a method for improving the resolution of acoustic wave long-range detection data of the present invention;

[0048] Figure 2 It is a schematic diagram of data that is not processed by the present invention in a specific embodiment 1 of the present invention;

[0049] Figure 3This is a schematic diagram of data processed by the present invention in a specific embodiment 1 of the present invention;

[0050] Figure 4 A flowchart of a specific embodiment 2 of a method for improving the resolution of acoustic wave long-range detection data of the present invention;

[0051] Figure 5 It is a schematic diagram of data that is not processed by the present invention in a specific embodiment 2 of the present invention;

[0052] Figure 6 It is a schematic diagram of data processed by the present invention in a specific embodiment 2 of the present invention;

[0053] Figure 7 A flowchart of a specific embodiment 3 of a method for improving the resolution of acoustic wave long-range detection data of the present invention;

[0054] Figure 8 It is a schematic diagram of data that is not processed by the present invention in a specific embodiment 3 of the present invention;

[0055] Fig. 9 It is a schematic diagram of data processed by the present invention in a specific embodiment 3 of the present invention. DETAILED DESCRIPTION

[0056] In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings.

[0057] The method of improving the resolution of acoustic wave remote detection seismic data of the present invention improves the imaging resolution of acoustic wave remote detection data by using a simple arithmetic operation method using a signal. The main steps include:

[0058] Step 1: Input the acoustic wave remote detection data;

[0059] Step 2: Select a data; this seismic data is composed of effective signal and noise superposition. The effective signal is composed of frequencies f1,...f n It is generated by superposition of sine waves.

[0060] x=s+n

[0061]

[0062] x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

[0063] Step 3: Select the first sampling point of the data; the amplitude of the sampling point is generated by superimposing the first amplitude of the sine wave of f and the amplitude of the noise.

[0064] x(t1)=s(t1)+n(t1)

[0065]

[0066] x(t1) is the amplitude of the first sampling point of the seismic data, s(t1) is the amplitude of the first sampling point of the signal, n(t1) is the amplitude of the first sampling point of the noise, t1 is the time corresponding to the first sampling point, f is the frequency of the amplitude spectrum of s, is the initial phase corresponding to frequency f in the s phase spectrum.

[0067] Step 4: Calculate the nth power of the amplitude 2 of the sampling point;

[0068] A1=x=s+n

[0069]

[0070] According to the frequency shift formula of the signal, we can get

[0071]

[0072] x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

[0073] Step 5: Calculate the nth power of the amplitude 2 of all sampling points of the data;

[0074]

[0075] A 1i is the i-th output amplitude value, A i is the i-th input amplitude value, and N is the number of sampling points.

[0076] x 1i is the i-th output amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

[0077] A 1i is the i-th output amplitude value, A i is the i-th input amplitude value, N is the number of sampling points, and n is 1.

[0078] Step 6: Determine the value of n to determine whether the sub-wave is compressed into a pulse. If not, increase the value of n. If yes, determine the value of n.

[0079] Step 7: Process all data according to steps 2-5;

[0080] Step 8: Output the result profile.

[0081] The following are several specific embodiments of the present invention.

[0082] Embodiment 1:

[0083] In a specific embodiment 1 of the present invention, Figure 1 As shown, Figure 1 The present invention is a flow chart of a method for improving the resolution of acoustic wave long-range detection data.

[0084] Step 101, inputting acoustic wave remote detection data;

[0085] Step 102, select a piece of data;

[0086] Step 103, selecting the first sampling point of the data;

[0087] Step 104, calculating the nth power of the amplitude 2 of the sampling point;

[0088] Step 105, calculating the nth power of the amplitude 2 of all sampling points of the data track;

[0089] Step 106, determining the value of n;

[0090] Step 107, process all data according to steps 2-5;

[0091] Step 108, output the result profile.

[0092] The schematic diagram of the data processing of acoustic wave remote detection using the present invention is as follows Figure 3 The schematic diagram of data processing without using the present invention is shown in Figure 2 As shown. It can be seen from the figure that the resolution of the data not processed by the present invention is low, while the imaging resolution of the data processed by the present invention is high. The method of improving the resolution of acoustic wave long-range detection data of the present invention is correct. Since the conventional deconvolution method needs to obtain an unknown deconvolution factor and the calculation is complicated, the effect is not ideal.

[0093] Embodiment 2:

[0094] In a specific embodiment 2 of the present invention, as Figure 4 As shown, Figure 4 The present invention is a flow chart of a method for improving the resolution of acoustic wave long-range detection data.

[0095] Step 101, inputting noise-free filtered data;

[0096] Step 102, select a piece of data;

[0097] Step 103, selecting the first sampling point of the data;

[0098] Step 104, calculating the nth power of the amplitude 2 of the sampling point;

[0099] Step 105, calculating the nth power of the amplitude 2 of all sampling points of the data track;

[0100] Step 106, determining the value of n;

[0101] Step 107, process all data according to steps 2-5;

[0102] Step 108, output the result profile.

[0103] The schematic diagram of the data processing of acoustic wave remote detection using the present invention is as follows Figure 6 The schematic diagram of data processing without using the present invention is shown in Figure 5 As shown. It can be seen from the figure that the resolution of the data not processed by the present invention is low, while the imaging resolution of the data processed by the present invention is high. The method of improving the resolution of acoustic wave long-range detection data of the present invention is correct. Since the conventional deconvolution method needs to obtain an unknown deconvolution factor and the calculation is complicated, the effect is not ideal.

[0104] Embodiment 3:

[0105] In a specific embodiment 3 of the present invention, as Figure 7 As shown, Figure 7 The present invention is a flow chart of a method for improving the resolution of acoustic wave long-range detection data.

[0106] Step 101, inputting noise filtering data;

[0107] Step 102, selecting a piece of data;

[0108] Step 103, selecting the first sampling point of the data;

[0109] Step 104, calculating the nth power of the amplitude 2 of the sampling point;

[0110] Step 105, calculating the nth power of the amplitude 2 of all sampling points of the data track;

[0111] Step 106, determining the value of n;

[0112] Step 107, process all data according to steps 2-5;

[0113] Step 108, output the result profile.

[0114] The schematic diagram of the data processing of acoustic wave remote detection using the present invention is as follows Fig. 9The schematic diagram of data processing without using the present invention is shown in Figure 8 As shown. It can be seen from the figure that the resolution of the data not processed by the present invention is low, while the imaging resolution of the data processed by the present invention is high. The method of improving the resolution of acoustic wave long-range detection data of the present invention is correct. Since the conventional deconvolution method needs to obtain an unknown deconvolution factor and the calculation is complicated, the effect is not ideal.

[0115] The present invention has an ideal effect in processing the actual acoustic wave long-range detection data. This is because the present invention improves the resolution of acoustic wave long-range detection data, improves the resolution by using acoustic wave data through simple arithmetic operations, and is superior to conventional resolution improvement methods in the acoustic wave long-range detection resolution improvement method.

[0116] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0117] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A method for improving the resolution of acoustic wave long-range detection data, characterized in that: The method for improving the resolution of acoustic wave long-range detection data comprises: Step 1: Collect acoustic wave remote detection data; Step 2: Select a seismic data; Step 3: Select the first sampling point of the seismic data; Step 4: Calculate the nth power of the amplitude 2 of the sampling point; Step 5: Calculate the nth power of the amplitude 2 of all sampling points of the seismic data; Step 6: Determine the value of n; Step 7: Process all data according to steps 2-5; Step 8: Output the acoustic wave long-range detection result profile; In step 4, the nth power of the amplitude 2 of the sampling point is calculated, and the formula is as follows: A1=A 2n A1 is the output amplitude value, A is the input amplitude value, and n is 1; A1=x=s+n According to the frequency shift formula of the signal, we can get x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum; In step 6, determine the value of n to determine whether the sub-wave is compressed into a pulse, if not, increase the value of n, if yes, determine the value of n; In step 7, all data are processed according to steps 2-5, and the value of n in steps 4 and 5 is equal to the value of n determined in step 6.

2. The method for improving the resolution of acoustic wave long-range detection data according to claim 1, characterized in that: In step 1, the collected acoustic wave long-range detection data is an acoustic wave signal with certain morphological regular characteristics.

3. The method for improving the resolution of acoustic wave long-range detection data according to claim 1, characterized in that: In step 2, the seismic data is composed of the effective signal and noise superposition. The effective signal is composed of frequencies f1,...f n It is generated by superposition of sine waves.

4. The method for improving the resolution of acoustic wave long-range detection data according to claim 3, characterized in that: In step 2, the seismic data is: x=s+n x is the amplitude of seismic data, s is the signal amplitude, n is the noise amplitude, f is the frequency of the s amplitude spectrum, is the initial phase corresponding to frequency f in the s phase spectrum.

5. The method for improving the resolution of acoustic wave long-range detection data according to claim 1, characterized in that: In step 3, the sampling point amplitude is generated by superimposing the first amplitude of the sine wave of f and the amplitude of the noise.

6. The method for improving the resolution of acoustic wave long-range detection data according to claim 5, characterized in that: In step 3, the amplitude of the sampling point is: x(t1)=s(t1)+n(t1) x(t1) is the amplitude of the first sampling point of the seismic data, s(t1) is the amplitude of the first sampling point of the signal, n(t1) is the amplitude of the first sampling point of the noise, t1 is the time corresponding to the first sampling point, f is the frequency of the amplitude spectrum of s, is the initial phase corresponding to frequency f in the s phase spectrum.

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