WO2013152468A1 - 一种地层品质因子反演方法 - Google Patents
一种地层品质因子反演方法 Download PDFInfo
- Publication number
- WO2013152468A1 WO2013152468A1 PCT/CN2012/001686 CN2012001686W WO2013152468A1 WO 2013152468 A1 WO2013152468 A1 WO 2013152468A1 CN 2012001686 W CN2012001686 W CN 2012001686W WO 2013152468 A1 WO2013152468 A1 WO 2013152468A1
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- WO
- WIPO (PCT)
- Prior art keywords
- frequency
- amplitude spectrum
- vertical seismic
- seismic section
- wave
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000001228 spectrum Methods 0.000 claims abstract description 67
- 238000012544 monitoring process Methods 0.000 claims abstract description 17
- 230000015572 biosynthetic process Effects 0.000 claims description 17
- 238000012887 quadratic function Methods 0.000 claims description 9
- 238000010521 absorption reaction Methods 0.000 claims description 8
- 230000001419 dependent effect Effects 0.000 claims description 7
- 230000005284 excitation Effects 0.000 claims description 6
- 230000001131 transforming effect Effects 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 abstract description 3
- 238000000926 separation method Methods 0.000 abstract 1
- 238000005755 formation reaction Methods 0.000 description 10
- 238000004458 analytical method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012804 iterative process Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/40—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging
- G01V1/42—Seismology; Seismic or acoustic prospecting or detecting specially adapted for well-logging using generators in one well and receivers elsewhere or vice versa
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2200/00—Details of seismic or acoustic prospecting or detecting in general
- G01V2200/10—Miscellaneous details
- G01V2200/14—Quality control
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/63—Seismic attributes, e.g. amplitude, polarity, instant phase
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/67—Wave propagation modeling
- G01V2210/677—Spectral; Pseudo-spectral
Definitions
- the invention relates to a seismic exploration data processing technology, and is a formation quality factor inversion method which utilizes the vertical wave amplitude spectrum property of vertical seismic section (VSP) data and has good stability.
- VSP vertical seismic section
- the absorption attenuation of the stratum is mainly manifested by the attenuation of the amplitude of the seismic wave during the propagation process, the distortion of the phase, and the lowering of the frequency, and the high-frequency part decays faster than the low-frequency part, and the attenuation is faster in the shallow layer than in the deep layer, which seriously reduces the resolution of the seismic data. rate.
- the inversion method of formation quality factor Q mainly uses the logarithmic spectrum ratio method, the center frequency offset method and the peak frequency offset method, the combination of scanning analysis technology and time-frequency analysis, and the multi-window spectrum analysis method for the amplitude spectrum of seismic wavelets. Wait.
- the center frequency offset method and the peak frequency offset method assume seismic wave vibration
- the spectrum can be represented by a Gaussian spectrum; the time-frequency analysis assumes that the seismic wavelet is zero-phase.
- Mathneey and Nowack proposed the instantaneous frequency matching method, which uses an iterative process to modify the causal decay operator, so that the operator acts on the weighted instantaneous frequency at the envelope peak after the reference pulse and the weighted instantaneous frequency at the peak of the target pulse envelope.
- the closest thus the quality factor of the media, they used this method to estimate the attenuation of the crustal diffraction seismic data;
- Dasios et al. used the instantaneous frequency matching method to estimate the attenuation of the full-wave array sonic logging.
- This method overcomes Some disadvantages of the log-ratio method, such as the need to select a variable frequency band range, etc., but this method requires the Hilbert transform method to calculate the instantaneous frequency, and also uses a complex iterative process to match the instantaneous frequency. It is well known that the Hilbert transform pair Noise sensitive, so the use of instantaneous frequency matching in noise-containing seismic signals is limited. Barnes assumes that the source wavelet is an ideal bandpass wavelet, and gives a relationship between instantaneous frequency and Q value and transmission time, but the actual source wavelet and the ideal bandpass wavelet are quite different.
- VSP vertical seismic profile
- the downhole detector receives the vertical seismic section data, and the detector close to the source receives the monitoring wavelet signal corresponding to each vertical seismic section record;
- step 5 In the frequency-wavenumber (FK) spectrum obtained in step 4), multiply the frequency-wavenumber (FK) spectrum corresponding to the up-wave by zero; then perform inverse Fourier transform in the wavenumber direction to obtain the amplitude spectrum; Performing an inverse Fourier transform on the obtained amplitude spectrum in the frequency direction to obtain a wave field two in the time domain;
- a time window is opened from the first sample point in each downlink wave, and the signal in the time window is Fourier transformed to obtain an amplitude spectrum of each frequency; And the amplitude spectrum corresponding to each frequency is divided by the square of its corresponding frequency value to obtain an amplitude spectrum in the exponential form.
- step 6) Repeat step 6) to obtain the amplitude spectrum of the exponential form of each frequency in all the down-going waves.
- step 7 After taking the natural logarithm of the amplitude spectrum 2 in step 7), the quadratic function fitting related to the frequency is performed by the least square method, and the primary term coefficient and the quadratic term coefficient corresponding to the downlink wavelet are obtained;
- step 8) to obtain the primary and quadratic coefficients corresponding to the descending wavelets of all the tracks in the vertical seismic section record;
- step 10 Picking up the first to second of the monitoring wavelet recorded in step 1), and recording the corresponding monitoring wavelet signal for each vertical seismic section, starting from the beginning to the second, opening a time window, within the time window The signal is Fourier transformed to obtain the amplitude spectrum of each frequency of the monitored wavelet; and the amplitude spectrum corresponding to each frequency is divided by the square of its corresponding frequency value to obtain the amplitude spectrum of all the track wavelet indices. four; 11) After taking the natural logarithm of the amplitude spectrum in step 10), the frequency-dependent quadratic function fitting is performed by the least squares method, and the primary coefficient and the quadratic coefficient of the monitored wavelet spectrum are obtained;
- step 11) Repeat step 11) to obtain the primary and secondary coefficients corresponding to the monitored wavelets of all the tracks in the vertical seismic section record;
- step 12) obtaining an average value of the quadratic coefficient of all the tracks in the vertical seismic section record and the corresponding monitoring wavelet quadratic coefficient;
- step 14 After taking the natural spectrum of the amplitude spectrum in step 7), subtract the product of the mean value of the quadratic coefficient of the seismic trace obtained in step 13) and the square of the frequency, and then use the square method to perform frequency-dependent Quadratic function fitting, obtaining primary term coefficients and quadratic coefficients;
- step 15 using the first-order time of each track in the vertical seismic section record divided by the first-order coefficient of the track obtained in step 14) to obtain an equivalent Q (stratigraphic quality factor) value of one;
- step 15 Repeat step 15) to obtain the equivalent formation quality factor value of all vertical seismic section tracks, and statistically smooth the equivalent Q (stratigraphic quality factor) values of all the tracks to obtain the equivalent Q (stratigraphic quality factor). Value two;
- the layer Q ratio quality factor
- step 18 Repeat step 18) until the corresponding layer Q (stratigraphic factor) values for each vertical seismic section record are inverted.
- FIG. 1 Schematic diagram of the downlink wave
- Figure 2 is a schematic diagram of the downlink wave intercepted
- Figure 3 shows the amplitude spectrum of the downlink wave intercepted
- the invention provides a method for inverting the formation quality factor of the downlink wave using the vertical seismic profile (VSP) data and having good stability, and the specific implementation steps are as follows:
- the downhole detector receives the vertical seismic section data, and the detector close to the source receives the monitoring wavelet signal corresponding to each vertical seismic section record;
- step 5 In the frequency-wavenumber (FK) spectrum obtained in step 4), multiply the frequency-wavenumber (FK) spectrum corresponding to the up-wave by zero; then perform inverse Fourier transform in the wavenumber direction to obtain the amplitude spectrum; Performing an inverse Fourier transform on the obtained amplitude spectrum in the frequency direction to obtain a wave field two in the time domain;
- step 6) Repeat step 6) to obtain an amplitude spectrum of the exponential form of each frequency in all the down-going waves.
- step 7 After taking the natural logarithm of the amplitude spectrum in step 7), the frequency-dependent quadratic function fitting is performed by the least square method to obtain the primary term coefficient and the quadratic coefficient corresponding to the downlink wavelet of the channel;
- step 8) to obtain the primary and quadratic coefficients corresponding to the descending wavelets of all the tracks in the vertical seismic section record;
- step 1) Picking up the first to second of the monitoring wavelet recorded in step 1), and recording the corresponding monitoring wavelet signal for each vertical seismic section, starting from the beginning to the second, opening a time window, within the time window
- the signal is Fourier transformed to obtain the amplitude spectrum of each frequency of the monitored wavelet; and the amplitude spectrum corresponding to each frequency is divided by the square of its corresponding frequency value to obtain the amplitude spectrum of all the track wavelet indices.
- step 11 After taking the natural logarithm of the amplitude spectrum in step 10), the frequency-dependent quadratic function fitting is performed by the least squares method, and the primary coefficient and the quadratic coefficient of the monitoring wavelet spectrum of the channel are obtained;
- step 11) Repeat step 11) to obtain the primary and secondary coefficients corresponding to the monitored wavelets of all the tracks in the vertical seismic section record;
- Step 12) Obtain the average of the quadratic coefficients of all the tracks in the vertical seismic section record and the corresponding monitoring wavelet quadratic coefficients;
- step 14 After taking the natural spectrum of the amplitude spectrum in step 7), subtract the product of the mean value of the quadratic coefficient of the seismic trace obtained in step 13) and the square of the frequency, and then use the square method to perform frequency-dependent Quadratic function fitting, obtaining primary term coefficients and quadratic coefficients;
- step 15 using the first-order time of each track in the vertical seismic section record divided by the primary term coefficient of the track obtained in step 14) to obtain an equivalent Q (stratigraphic quality factor) value of one;
- step 15 Repeat step 15) to obtain the equivalent formation quality factor of all vertical seismic section tracks
- the value is one, and the equivalent Q (stratigraphic quality factor) value of all the tracks is statistically smoothed to obtain the equivalent Q (stratigraphic quality factor) value of two;
- the layer Q ratio quality factor
- step 18 Repeat step 18) until the corresponding layer Q (stratigraphic factor) values for each vertical seismic section record are inverted. As shown in Fig. 4, as the depth increases, the layer Q also tends to increase.
- the invention has strong anti-random interference capability, can eliminate the difference of the excitation wave, and not only the algorithm is simple but also greatly saves the workload, and the layer Q value of the inversion has good stability and high precision.
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- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Acoustics & Sound (AREA)
- Environmental & Geological Engineering (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Geophysics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
Description
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Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
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RU2014145635/28A RU2579164C1 (ru) | 2012-04-13 | 2012-12-11 | Способ обращения для определения добротности геологической среды |
EP12874053.7A EP2837953A4 (en) | 2012-04-13 | 2012-12-11 | METHOD FOR INVERTING A GEOLOGICAL QUALITY FACTOR |
US14/394,100 US20150168573A1 (en) | 2012-04-13 | 2012-12-11 | Geologic quality factor inversion method |
Applications Claiming Priority (2)
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CN201210109416.8 | 2012-04-13 | ||
CN201210109416.8A CN103376464B (zh) | 2012-04-13 | 2012-04-13 | 一种地层品质因子反演方法 |
Publications (1)
Publication Number | Publication Date |
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WO2013152468A1 true WO2013152468A1 (zh) | 2013-10-17 |
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Family Applications (1)
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PCT/CN2012/001686 WO2013152468A1 (zh) | 2012-04-13 | 2012-12-11 | 一种地层品质因子反演方法 |
Country Status (5)
Country | Link |
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US (1) | US20150168573A1 (zh) |
EP (1) | EP2837953A4 (zh) |
CN (1) | CN103376464B (zh) |
RU (1) | RU2579164C1 (zh) |
WO (1) | WO2013152468A1 (zh) |
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- 2012-12-11 US US14/394,100 patent/US20150168573A1/en not_active Abandoned
- 2012-12-11 EP EP12874053.7A patent/EP2837953A4/en not_active Withdrawn
- 2012-12-11 WO PCT/CN2012/001686 patent/WO2013152468A1/zh active Application Filing
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CN103376464B (zh) | 2016-04-06 |
US20150168573A1 (en) | 2015-06-18 |
RU2579164C1 (ru) | 2016-04-10 |
EP2837953A4 (en) | 2016-04-06 |
EP2837953A1 (en) | 2015-02-18 |
CN103376464A (zh) | 2013-10-30 |
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