Note: Descriptions are shown in the official language in which they were submitted.
,
METHOD AND SYSTEM FOR SEISMIC DATA PROCESSING
Cross Reference to Related Application
The present application claims benefit of Chinese patent application
CN201610812740.4, entitled "Method and system for seismic data processing" and
filed on September 9, 2016, the entirety of which is incorporated herein by
reference.
Field of the Invention
The present disclosure relates to the technical field of digital signal
processing,
and particularly to a method for seismic data processing and a system for
seismic data
processing.
Background of the Invention
The target of oil and gas exploration has turned to complex types from simple
types, i.e., to subtle lithostratigraphic oil-gas reservoir from structural
oil-gas reservoir.
It can be seen that, the seismic data processing technology has become more
and more
important. It is an important link to improve resolution of the seismic data.
The cost of
high resolution seismic data collection is relatively high. The traditional
data collection
equipment has a narrow frequency band, and data signal with a low frequency
band
below 5 Hz cannot be collected. The processing result under present technology
cannot
meet the requirement of lithostratigraphic oil-gas reservoir exploration, and
the
processing technology of seismic data with high resolution is urgently needed.
The resolution of seismic signal includes a vertical resolution and a
horizontal
resolution. The resolution generally mentioned refers to the vertical
resolution. There
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are many factors influencing the resolution, and the main factors will be
stated below.
First, attenuation due to rock absorption influences the resolution. During
transmission
procedure of seismic wave in underground medium, the amplitude of the seismic
wave
would attenuate to some extent. The attenuation of amplitude has an
exponential
relationship with transmission distance, frequency, and reciprocal of Q value.
Second,
sampling rate influences the resolution. During seismic data processing
procedure, a
series of discrete data are recorded. The time sampling rate directly
determines the
highest frequency of the data. For example, when the sampling rate is 1 ms,
the highest
frequency of the data could be 500 Hz. With respect to the seismic data
collected at
present, the sampling rate thereof can only basically meet the requirement of
resolution
when an alias filter is used. Third, a frequency bandwidth of a wavelet
influences the
resolution. The resolution of seismic exploration is determined by duration or
pulse
width of a seismic wavelet. When a frequency bandwidth of a pulse is given, a
minimum pulse width is determined. That is, a potential maximum resolution can
be
determined. Therefore, the resolution depends on the frequency bandwidth of
the
wavelet. If the resolution is to be improved, an effective frequency band of
the wavelet
should be widened, and the wavelet should be compressed, which is a main
problem to
be solved during high resolution processing of seismic data. Fourth, wavelet
phase
influences the resolution. When the wavelets have identical amplitude
spectrums,
zero-phase wavelet has the highest resolution. This is because that, a
wavelength of the
zero-phase wavelet is smaller than a wavelength of other wavelet, an amplitude
of the
zero-phase wavelet is small at an edge thereof, and a reflection time thereof
appears at
the peak of the wavelet. Therefore, under an ideal situation, the wavelet
should in
zero-phase. However, under present technology, a phase of a wavelet cannot be
determined accurately, and the accurate phase information cannot be extracted.
The
phase information of the wavelet can only be estimated by a statistical
method, so that
the phase of the wavelet is near to zero as much as possible so as to improve
the
resolution thereof. At present, most de-convolution methods are based on the
aforesaid
principle.
It is shown by published technical documents and papers that, at present, the
high
resolution seismic data processing technology is based on various improved
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de-convolution algorithms, such as deterministic wavelet de-convolution
method,
time-varying spectral whitening method, eigenvalue resolution improving
method,
independent component analysis (ICA) method, and blind de-convolution method.
Compared with traditional de-convolution methods, a much higher resolution can
be
realized by the aforesaid methods. However, according to the aforesaid
methods,
lineups and false lineups can hardly be discriminated from each other. It is
very
important for seismic data processing and explanation to improve the
resolution of the
seismic data to a level higher than that achieved according to traditional
de-convolution method on the premise that no false lineups is generated.
Moreover,
under present technology, the frequency band of the seismic data can hardly be
expanded both to high frequency end and to low frequency end in a uniform
manner. If
the frequency band of the seismic data is expanded to high frequency end
blindly, the
waveform distortion of the seismic wavelet would be generated, or the
kinematical
characteristics of the seismic wavelet would be changed, and thus the velocity
modeling and imaging accuracy thereof would be adversely affected.
Summary of the Invention
The present disclosure aims to expand frequency band of seismic data to high
frequency band and low frequency band uniformly on the premise that waveform
distortion of seismic wavelet is not generated and kinematical characteristics
of
seismic wavelet is not changed. In this manner, the loss of data at low
frequency end
resulted from limited frequency band of traditional data acquisition equipment
can be
effectively compensated, and the resolution of the seismic data can be
apparently
improved, thereby providing technological support to the following seismic
data
inversion, imaging processing and explanation.
In order to achieve the aforesaid purpose, the present disclosure provides a
method and a system for seismic data processing based on frequency division
iteration.
According to a first aspect, the present disclosure provides a method for
seismic
data processing, which comprises steps of:
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obtaining an original single-trace seismic data;
applying a Fourier transform and a Hilbert transform to the original single-
trace
seismic data respectively so as to obtain a Fourier transform result and a
Hilbert
transform result;
obtaining, with respect to each frequency to be processed in a preset
frequency
division range, a processing result corresponding to the frequency to be
processed
according to the original single-trace seismic data, the Fourier transform
result, and the
Hilbert transform result; and
obtaining an output result according to processing results corresponding to
all
frequencies to be processed in the frequency division range.
Preferably, the step of obtaining a processing result corresponding to the
frequency to be processed according to the original single-trace seismic data,
the
Fourier transform result, and the Hilbert transform result comprises:
obtaining a processing result K,. (t) corresponding to the frequency f to be
processed according to Kr(t)= x(t)e' ) cos(270)¨ h(t)e' c(`) sin(270) ,
wherein the
processing result Kr(t) is a real part of a constructed output function K(t) ,
x(t) is
the original single-trace seismic data, Xr(t) is a real part of the Fourier
transform
result, and h(t) is the Hilbert transform result.
Preferably, the method further comprises a step of constructing an output
function
K(t) .
Preferably, the step of constructing the output function K(t) comprises sub
steps of:
constructing a first analytic function E(t) , and enabling the first analytic
function E(t) to meet a following expression: E(t)= x(t)+ jh(t);
constructing a second analytic function Y(t) , and enabling the second
analytic
function Y(t) to meet a following expression: Y(t) = X, (t)+ j2n- ft ;
constructing a third analytic function Z(t) according to the second analytic
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function Y(t), and enabling the third analytic function Z(t) to meet a
following
expression: Z(t) = ex'(') * cos(270) + jex'(t) * sin(27-cft) ; and
obtaining the output function K(t) by multiplying the first analytic function
E(t) with the third analytic function Z(t), and enabling the output function
K(t) to
meet a following expression:
K(t)= lx(t)ex'(f) cos(270) ¨ h(t)ex'(1)sin(277-ft)}
+ j{x(t)ex'(') sin(270) + h(t)et ) cos(270)}
Preferably, the step of obtaining an output result according to processing
results
corresponding to all frequencies to be processed in the frequency division
range
comprises:
obtaining the output result by summing up the processing results corresponding
to
all frequencies to be processed in the frequency division range.
According to a second aspect, the present disclosure provides a system for
seismic data processing, which comprises:
a data obtaining module, configured to obtain an original single-trace seismic
data;
a Fourier transform module, configured to apply a Fourier transform to the
original single-trace seismic data so as to obtain a Fourier transform result;
a Hilbert transform module, configured to apply a Hilbert transform to the
original single-trace seismic data so as to obtain a Hilbert transform result;
a processing result determination module, configured to obtain, with respect
to
each frequency to be processed in a preset frequency division range, a
processing
result corresponding to the frequency to be processed according to the
original
single-trace seismic data, the Fourier transform result, and the Hilbert
transform result;
and
an output result determination module, configured to obtain an output result
according to processing results corresponding to all frequencies to be
processed in the
frequency division range.
Preferably, the processing result determination module is specifically
configured
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to obtain a processing result K JO corresponding to the frequency f to be
processed
according to Kr(t)= x(t)ex (I) cos(270)¨ h(t)ex '(µ) sin(27rft) , wherein the
processing
result Kr (t)is a real part of a constructed output function K(t) , x(t) is
the original
single-trace seismic data, Xr(t) is a real part of the Fourier transform
result, and
h(t) is the Hilbert transform result.
Preferably, the system further comprises a constructing module which is
configured to construct the output function K(t).
Preferably, the constructing module comprises:
a first constructing unit, configured to construct a first analytic function
E(t),
and enable the first analytic function E(t) to meet a following expression:
E(t)= x(t)+ jh(t);
a second constructing unit, configured to construct a second analytic function
Y(t), and enable the second analytic function Y(t) to meet a following
expression:
Y(t)= X r(t)+ j271- ft ;
a third constructing unit, configured to construct a third analytic function
Z(t)
according to the second analytic function Y(t), and enable the third analytic
function
Z(t) to meet a following expression: Z(t) = ex'(1) * cos(270) + je'c(1) *
sin(271-ft) ;
and
an output function determination unit, configured to obtain the output
function
K(t) by multiplying the first analytic function E(t) with the third analytic
function
Z(t), and enable the output function K(t) to meet a following expression:
K(t) = {x(t)ex-(t) cos(270) ¨ h(t)ex-(t) sin(270)}
+ j{x(t)exr (1) sin(270) + h(t)ex'(') cos(270)}
Preferably, the output result determination module is specifically configured
to
obtain the output result by summing up the processing results corresponding to
all
frequencies to be processed in the frequency division range.
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Compared with the prior art, one embodiment or a plurality of embodiments
according to the present disclosure may have the following advantages or
beneficial
effects.
According to the present disclosure, the loss of data at low frequency end
resulted
from limited frequency band of traditional data acquisition equipment can be
effectively compensated, and the frequency band of seismic data can be
apparently
expanded in a uniform manner. Therefore, the resolution of seismic data can be
significantly improved. At the same time, waveform distortion resulted from
frequency
band expansion can be avoided, and kinematical characteristics of seismic
wavelet is
maintained unchanged.
Other features and advantages of the present disclosure will be further
explained
in the following description, and partially become apparent, or be understood
through
the examples of the present disclosure. The objectives and advantages of the
present
disclosure will be achieved through the structure specifically pointed out in
the
description, claims, and the accompanying drawings.
Brief Description of the Drawings
The accompanying drawings provide further understandings of the present
disclosure and constitute one part of the description. The drawings are used
for
interpreting the present disclosure together with the embodiments, not for
limiting the
present disclosure. In the drawings:
Fig. 1 is a flow chart of a method for seismic data processing according to
one
embodiment of the present disclosure;
Fig. 2 is a flow chart of another method for seismic data processing according
to
one embodiment of the present disclosure;
Fig. 3 is a flow chart of a method for constructing an output function
according to
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=
one embodiment of the present disclosure;
Fig. 4 schematically shows a structure of a system for seismic data processing
according to one embodiment of the present disclosure;
Fig. 5 schematically shows a structure of another system for seismic data
processing according to one embodiment of the present disclosure;
Fig. 6 schematically shows a structure of a constructing module according to
one
embodiment of the present disclosure;
Fig. 7a schematically shows a theoretical wavelet;
Fig. 7b schematically shows a wavelet that is processed by a method according
to
one embodiment of the present disclosure (a frequency division range thereof
is (0, 10)
Hz);
Fig. 7c is a spectrum of an original wavelet;
Fig. 7d is a spectrum of a processed wavelet;
Fig. 8a schematically shows a Common Middle Point (CMP) gather record and
velocity spectrum thereof in a target region before the method of one
embodiment of
the present disclosure is used;
Fig. 8b schematically shows a CMP gather record and velocity spectrum thereof
in a target region after the method of one embodiment of the present
disclosure is used;
Fig. 9a is an original spectrum of the CMP gather record in the target region
before the method of one embodiment of the present disclosure is used;
Fig. 9b is a spectrum of the CMP gather record in the target region after the
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method of one embodiment of the present disclosure is used (a frequency
division
range thereof is (0, 10) Hz);
Fig. 10a is an original stacked sectional view of line 444 in the target
region;
Fig. 10b is a stacked sectional view thereof after line 444 as shown in Fig.
10a is
processed by the method of one embodiment of the present disclosure;
Fig. lla is an original stacked sectional view of line 452 in the target
region;
Fig. 11b is a stacked sectional view thereof after line 452 as shown in Fig.
lla is
processed by the method of one embodiment of the present disclosure;
Fig. 12a is an original stacked sectional view of line 460 in the target
region; and
Fig. 12b is a stacked sectional view thereof after line 460 as shown in Fig.
12a is
processed by the method of one embodiment of the present disclosure.
Detailed Description of the Embodiments
The present disclosure will be explained in details with reference to the
embodiments and the accompanying drawings, whereby it can be fully understood
how
to solve the technical problem by the technical means according to the present
disclosure and achieve the technical effects thereof, and thus the technical
solution
according to the present disclosure can be implemented. It should be noted
that, as
long as there is no structural conflict, all the technical features mentioned
in all the
embodiments may be combined together in any manner, and the technical
solutions
obtained in this manner all fall within the scope of the present disclosure.
At present, the high resolution seismic data processing technology is based on
various improved de-convolution algorithms. Compared with traditional
de-convolution method, a much higher resolution can be realized by the
improved
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de-convolution algorithms. However, according to the improved de-convolution
algorithms, lineups and false lineups can hardly be discriminated. It is very
important
for seismic data processing and explanation to improve the resolution of the
seismic
data to a level higher than that achieved according to traditional de-
convolution
method on the premise that no false lineups is generated. Moreover, under
present
technology, the frequency band of the seismic data can hardly be expanded both
to
high frequency end and to low frequency end in a uniform manner. If the
frequency
band of the seismic data is expanded to high frequency end blindly, the
waveform
distortion of the seismic wavelet would be generated, or the kinematical
characteristics
of the seismic wavelet would be changed, and thus the velocity modeling and
imaging
accuracy thereof would be adversely affected.
In order to solve the aforesaid technical problem, an embodiment of the
present
disclosure provides a method for seismic data processing.
Embodiment 1
Fig. 1 is a flow chart of a method for seismic data processing according to
one
embodiment of the present disclosure. As shown in Fig. 1, according to the
embodiment of the present disclosure, the method mainly comprises step 101 to
step
106.
In step 101, an original single-trace seismic data is obtained. Here, the
original
single-trace seismic data is represented by x(t) .
In step 102, a Fourier transform is applied to the original single-trace
seismic data
so as to obtain a Fourier transform result.
Specifically, mutual transformation of a signal can be realized between a time
domain and a frequency domain by a Fourier transform and an inverse Fourier
transform. In general, a Fourier transform is applied to the original single-
trace seismic
data x(t) according to expression (1) so as to obtain a Fourier transform
result
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X(w) . An inverse Fourier transform is applied to the Fourier transform result
X(w)
according to expression (2) so as to obtain the original single-trace seismic
data x(t).
+00
X(w) = f x(t" dt = X ,(w)+ iX,(w) (1)
1 +"
x(t)= ¨ X(w)e"tclw (2)
271-
In expression (1), X r(w) is a real part of the Fourier transform result. An
inverse Fourier transform is applied to X,. (w) so as to obtain a real part Xr
(t) of an
inverse Fourier transform result. X, (w) is an imaginary part of the Fourier
transform
result, wherein an amplitude function thereof is Amp(w) = JXr2(w) x-12 ,
) and a
X, (w)
phase function thereof is tan(0) = ___
Xr (w)
In frequency domain, a typical role of the Fourier transform is to decompose a
signal into amplitude spectrum so as to perform spectrum analysis on the
signal. When
the original seismic signal has a low frequency, the wavelet has a low main
frequency
and a narrow frequency band in frequency domain. Therefore, the signal has a
relatively low resolution, which is not conducive to the following signal
analysis and
seismic explanation. The resolution depends on the frequency bandwidth of the
wavelet. If the resolution is to be improved, an effective frequency band of
the wavelet
should be widened, and the wavelet should be compressed, which is a main
problem to
be solved by the present disclosure.
In step 103, a Hilbert transform is applied to the original single-trace
seismic data
so as to obtain a Hilbert transform result.
Specifically, Hilbert transform is an important tool in signal analysis. A
Hilbert
transform is applied to the original single-trace seismic data x(t) according
to
expression (3) so as to obtain a Hilbert transform result h(t).
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x(t) ,
h(t)=¨ ¨ar (3)
t -
In step 104, with respect to each frequency to be processed in a preset
frequency
division range, a processing result corresponding to the frequency to be
processed is
obtained according to the original single-trace seismic data, the Fourier
transform
result, and the Hilbert transform result.
Specifically, the processing result Kr (t)corresponding to the frequency f to
be
processed is obtained according to expression (4).
Kr(t)= x(t)ex'(1)cos(27rft)¨ h(t)ex'wsin(2;rft) (4)
In expression (4), the processing result K,. (t) is a real part of a
constructed
output function K(t) . The output function K(t) can be constructed on-line or
off-line, and the specific constructing method will be illustrated in detail
hereinafter
with reference to Fig. 2. x(t) is the original single-trace seismic data, X,
(t) is a real
part of the Fourier transform result, and h(t) is the Hilbert transform
result.
In step 105, whether processing results corresponding to all frequencies to be
processed in the frequency division range are obtained is determined.
In step 106, if a determination result of step 105 is yes, an output result is
obtained according to processing results corresponding to all frequencies to
be
processed in the frequency division range. If a determination result of step
105 is no,
step 104 is returned.
Specifically, the frequency division range is preset off-line. Here, (fmin,
fn.)
represents the frequency division range, wherein fn. represents a lower limit
of the
frequency division range, and fmax represents an upper limit of the frequency
division
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range. It can be been that, the frequency division range herein can be seen as
a set of
the frequency f to be processed.
When it is determined that not all processing results corresponding to all
frequencies to be processed in the frequency division range are obtained, step
104 is
returned, so that processing procedure continues.
When it is determined that processing results corresponding to all frequencies
to
be processed in the frequency division range are obtained, the output result
is obtained
according to all processing results obtained therein. According to one
preferred
embodiment of the present disclosure, the output result can be obtained by
summing
up the processing results corresponding to all frequencies to be processed in
the
frequency division range. That is, the output result y(t) can be obtained
according to
expression (5).
Y(t)=Kr(t) (5)
According to the method for seismic data processing of the present embodiment,
the processing result corresponding to each frequency to be processed in the
frequency
division range can be obtained in sequence, and a final output result can be
obtained
according to all processing results. Moreover, when the processing result
corresponding to each frequency to be processed is calculated, the original
single-trace
seismic data, the Fourier transform result and the Hilbert transform result
are
introduced. The Hilbert transform result is used for constraining three
instantaneous
properties (i.e., instantaneous amplitude, instantaneous frequency, and
instantaneous
phase) of the data. It can be seen that, according to the present embodiment,
the
constraint on the original single-trace seismic data and the three
instantaneous
properties thereof are added, so that the distortion of signal can be avoided
during
transformation procedure in frequency domain.
In a word, according to the present embodiment, the high resolution processing
of
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the seismic data is performed based on single-trace frequency division
iteration,
whereby the resolution of the seismic data can be effectively improved while
the
kinematical characteristics of the wavelet can be maintained unchanged. The
frequency
band of the seismic data can be expanded both to high frequency end and to low
frequency end, and thus effective frequency band of the signal can be
apparently
expanded. Specifically, during high resolution processing of the seismic data
based on
single-trace frequency division iteration, analytic functions are constructed
on the basis
of Fourier transform and Hilbert transform, and the high resolution processing
of the
seismic data in single-trace and single frequency can be performed in
different
dimensions. In this manner, waveform distortion resulted from frequency band
expansion can be avoided. Therefore, according to the present embodiment, the
resolution of the seismic data can be significantly improved, thereby
providing
technological support to the following processing and explanation.
Embodiment 2
Fig. 2 is a flow chart of a method for seismic data processing according to
the
embodiment of the present disclosure. As shown in Fig. 2, according to the
present
embodiment, step 201 is added on the basis of the steps in embodiment 1.
In step 201, an output function K(t) is constructed. Here, the output function
K(t) can be constructed on-line or off-line.
Fig. 3 is a flow chart of a method for constructing the output function
according
to the embodiment of the present disclosure. As shown in Fig. 3, according to
the
present embodiment, the method for constructing the output function K(t)
mainly
comprises step 301 to step 304.
In step 301, a first analytic function E(t) is constructed, and the first
analytic
function E(t) meets expression (6).
E(t)= x(t)+ jh(t) (6)
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Specifically, the first analytic function E(t) is constructed based on the
original
single-trace seismic data x(t) and the Hilbert transform result h(t) , so that
the
constraint on the input signal (i.e., the original single-trace seismic data)
and the three
instantaneous properties of the signal are added. Here, the three
instantaneous
properties of the signal refer to instantaneous amplitude, instantaneous
frequency, and
instantaneous phase of the signal.
In step 302, a second analytic function Y(t) is constructed, and the second
analytic function Y(t) meets expression (7).
Y(t) = X r(t)+ j271-ft (7)
In step 303, a third analytic function Z(t) is constructed according to the
second
analytic function Y(t), and the third analytic function Z(t) meets expression
(8).
Z(t) = ex (t) * cos(2R-ft)+ jex'(1) *sin(271-ft) (8)
Specifically, the constructing of the second analytic function Y(t) is for
constructing the third analytic function Z(t) , and the constructing method
can
facilitate the derivation of the expressions.
The third analytic function Z(t) is constructed based on the real part X, (t)
of
Fourier transform result of the original single-trace seismic data x(t) and
trigonometric functions sin(271-ft) and cos(271-ft) of the frequency f to be
processed.
In expression (8) of the third analytic function Z(t), exponential function is
used for
amplitude constraint, and the trigonometric functions are used for phase
constraint.
In step 304, the output function K(t) is obtained by multiplying the first
analytic function E(t) with the third analytic function Z(t), and thus the
output
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function K(t) meets expression (9).
K(t)= fx(t)ex'(`)cos(27rft) ¨ h(t)ex'(') sin(270)}
(9)
+ j{x(t)exr (`) sin(270) + h(t)ex'(`) cos(271-ft)}
Specifically, a product of the first analytic function E(t) and the third
analytic
function Z(t) serves as the output function K(t) . It can be seen that, the
output
function K(t) is a single-trace and single frequency function that is
constructed
under the above constraints, i.e., constraints on the input signal,
constraints on the
three instantaneous properties of the signal, and constraints on the amplitude
and the
phase of the signal. With these constraints, the distortion of the signal can
be avoided
during transformation procedure in frequency domain.
According to the present embodiment, the constructing of the first analytic
function, the second analytic function, and the third analytic function is
used for
deriving the output function. In this manner, the constraints are added, and
at the same
time, the derivation thinking of the output function is clear. The single-
trace and single
frequency output function K(t) is a core function according to the present
embodiment. In the output function, the constraints on the input signal,
constraints on
the three instantaneous properties of the signal, and constraints on the
amplitude and
the phase of the signal are added, so that the distortion of the signal can be
avoided
during transformation procedure in frequency domain.
In a word, according to the method for seismic data processing of the present
embodiment, the high resolution processing of the seismic data is performed
based on
single-trace frequency division iteration, whereby the resolution of the
seismic data
can be effectively improved while the kinematical characteristics of the
wavelet can be
maintained unchanged. The frequency band of the seismic data can be expanded
both
to high frequency end and to low frequency end, and thus effective frequency
band of
the signal can be apparently expanded. Specifically, during high resolution
processing
of the seismic data based on single-trace frequency division iteration,
analytic
functions are constructed on the basis of Fourier transform and Hilbert
transform, and
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the high resolution processing of the seismic data in single-trace and single
frequency
can be performed in different dimensions. In this manner, waveform distortion
resulted
from frequency band expansion can be avoided. Therefore, according to the
present
embodiment, the resolution of the seismic data can be significantly improved,
thereby
providing technological support to the subsequent processing and explanation.
The present embodiment will be further illustrated in detail hereinafter with
reference to Fig. 7a to Fig. 12b in order to verify the beneficial effects
thereof better.
Specifically, the correctness and effectiveness of the method according to the
present
embodiment will be verified by processing both theoretical data and actual
data.
Specifically, Fig. 7a shows a Ricker wavelet. Fig. 7b schematically shows a
processing result of the wavelet with high resolution that is processed by a
method
according to the present embodiment (a frequency division range thereof is (0,
10) Hz).
Comparing Fig. 7a with Fig. 7b, it can be seen that, after being processed by
the
method of the present embodiment, the resolution of the wavelet can be
apparently
improved, and a time corresponding to a main lobe of the wavelet does not
change. Fig.
7c is a spectrum of an original wavelet, and Fig. 7d is a spectrum of a
processed
wavelet. Comparing Fig. 7c with Fig. 7d, it can be seen that, after being
processed, the
main frequency of the wavelet can be improved, and the frequency band thereof
can be
apparently expanded. Specifically, the frequency band can be expanded not only
to
high frequency end, but also to low frequency end to some extent. In this
manner, the
wavelet can have more frequency components.
A comparative result of an original actual seismic data and the data after
being
processed by the method of the present embodiment is shown below. The
three-dimensional seismic data in a research area in west China is shown.
According to
the present embodiment, the single-trace processing method is used, and the
data is
processed before stacking. However, the data can also be processed after
stacking
according to other embodiments.
Fig. 8a shows a Common Middle Point (CMP) gather record and velocity
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spectrum in a target region thereof before the method of the present
embodiment is
used. Fig. 8b shows a CMP gather record and velocity spectrum thereof in a
target
region after the method of the present embodiment is used. Comparing Fig. 8a
with Fig.
8b, it can be seen that, a physical position of a velocity spectrum energy
group before
the method is used coincides with that after the method is used, which shows
that the
kinematical characteristics of the wavelet is not changed by the method of the
present
embodiment.
Fig. 9a is an original spectrum of the CMP gather record in the target region
before the method of the present embodiment is used. As shown in Fig. 9a,
before
being processed by the method of the present embodiment, the seismic data has
a
narrow frequency band and a low resolution. In particular, the data in low
frequency
band below 5 Hz lack seriously due to the limited frequency band of the data
acquisition equipment. Fig. 9b is a spectrum of the CMP gather record in the
target
region after the method of the present embodiment is used (a frequency
division range
thereof is (0, 10) Hz). Comparing Fig. 9a with Fig. 9b, it can be seen that,
the
frequency band of the data can be effectively expanded. In particular, the
data in low
frequency band can be compensated effectively.
Fig. 10a is an original stacked sectional view of line 444 (CMP1380-1520, 2 to
3
seconds) in the target region, and Fig. 10b is a stacked sectional view
thereof after line
444 as shown in Fig. 10a is prestack processed by the method of the present
embodiment. As shown in Fig. 10a and Fig. 10b, the white thick lines are used
for
highlighting the signal for clear comparison therebetween. The highlighting
marks can
be made in other ways different from those shown herein.
Fig. 1 1 a is an original stacked sectional view of line 452 (CMP760-900, 2 to
3
seconds) in the target region, and Fig. 1 lb is a stacked sectional view
thereof after line
452 as shown in Fig. 1 1 a is prestack processed by the method of the present
embodiment. As shown in Fig. 1 la and Fig. 11b, the white thick lines are used
for
highlighting the signal for clear comparison therebetween. The highlighting
marks can
be made in other ways different from those shown herein.
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Fig. 12a is an original stacked sectional view of line 460 (CMP1560-1700, 2 to
3
seconds) in the target region, and Fig. 12b is a stacked sectional view
thereof after line
460 as shown in Fig. 12a is prestack processed by the method of the present
embodiment. As shown in Fig. 12a and Fig. 12b, the white thick lines are used
for
highlighting the signal for clear comparison therebetween. The highlighting
marks can
be made in other ways different from those shown herein.
Through comparing Fig. 10a with Fig. 10b, comparing Fig. 1 1 a with Fig. 11b,
and comparing Fig. 12a with Fig. 12b, it can be seen that, after prestack
processing by
applying the method of the present embodiment, the resolution of the seismic
data can
be apparently improved, and no false lineups is generated. As a result, the
phenomenon
that lineups and false lineups can hardly be discriminated from each other
would not
occur. Therefore, the seismic data, after being processed by the method of the
present
embodiment, can provide technological support to the subsequent processing and
explanation works.
In a word, according to the present embodiment, the loss of data at low
frequency
end resulted from limited frequency band of traditional data acquisition
equipment can
be effectively compensated, and the frequency band of seismic data can be
apparently
expanded in a uniform manner. Therefore, the resolution of seismic data can be
significantly improved. At the same time, waveform distortion resulted from
frequency
band expansion can be avoided, and kinematical characteristics of seismic
wavelet is
maintained unchanged.
Adopting broadband acquisition equipment would significantly improve seismic
acquisition cost. Therefore, the traditional data acquisition equipment with a
low cost
will play its role in a rather long period of time. The method of the present
embodiment is especially applicable for the high resolution processing of
seismic data
that is collected by traditional data acquisition equipment.
Embodiment 3
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Corresponding to embodiment 1 and embodiment 2, the present embodiment
provides a system for seismic data processing.
Fig. 4 schematically shows a structure of a system for seismic data processing
according to the present embodiment. As shown in Fig. 4, according to the
present
embodiment, the system for seismic data processing mainly comprises a data
obtaining
module 401, a Fourier transform module 402, a Hilbert transform module 403, a
processing result determination module 404, and an output result determination
module 405, wherein the data obtaining module 401 is connected with the
Fourier
transform module 402 and the Hilbert transform module 403 respectively, the
Fourier
transform module 402 and the Hilbert transform module 403 both are connected
with
the processing result determination module 404, and the processing result
determination module 404 is connected with the output result determination
module
405.
Specifically, the data obtaining module 401 is configured to obtain an
original
single-trace seismic data.
The Fourier transform module 402 is configured to apply a Fourier transform to
the original single-trace seismic data so as to obtain a Fourier transform
result.
The Hilbert transform module 403 is configured to apply a Hilbert transform to
the original single-trace seismic data so as to obtain a Hilbert transform
result.
The processing result determination module 404 is configured to obtain, with
respect to each frequency to be processed in a preset frequency division
range, a
processing result corresponding to the frequency to be processed according to
the
original single-trace seismic data, the Fourier transform result, and the
Hilbert
transform result.
In particular, the processing result determination module 404 is configured to
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obtain a processing result K JO corresponding to the frequency f to be
processed
according to Kr(t)= x(t)exr(1) cos(27rft) ¨ h(t)ex'(') sin(27rft) , wherein
the processing
result Kr (t)is a real part of a constructed output function K(t) , x(t) is
the original
single-trace seismic data, Xr(t) is a real part of the Fourier transform
result, and
h(t) is the Hilbert transform result.
The output result determination module 405 is configured to obtain an output
result according to processing results corresponding to all frequencies to be
processed
in the frequency division range. Specifically, the output result determination
module
405 is configured to obtain the output result by summing up the processing
results
corresponding to all frequencies to be processed in the frequency division
range.
According to the system for seismic data processing of the present embodiment,
the processing result corresponding to each frequency to be processed in the
frequency
division range can be obtained in sequence, and a final output result can be
obtained
according to all processing results. Moreover, when the processing result
corresponding to each frequency to be processed is calculated, the original
single-trace
seismic data, the Fourier transform result and the Hilbert transform result
are
introduced. The Hilbert transform result is used for constraining three
instantaneous
properties (i.e., instantaneous amplitude, instantaneous frequency, and
instantaneous
phase) of the data. It can be seen that, according to the present embodiment,
the
constraint on the original single-trace seismic data and the three
instantaneous
properties thereof are added, so that the distortion of signal can be avoided
during
transformation procedure in frequency domain.
In a word, according to the present embodiment, the high resolution processing
of
the seismic data is performed based on single-trace frequency division
iteration,
whereby the resolution of the seismic data can be effectively improved while
the
kinematical characteristics of the wavelet can be maintained unchanged. The
frequency
band of the seismic data can be expanded both to high frequency end and to low
frequency end, and thus effective frequency band of the signal can be
apparently
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expanded. Specifically, during high resolution processing of the seismic data
based on
single-trace frequency division iteration, analytic functions are constructed
on the basis
of Fourier transform and Hilbert transform, and the high resolution processing
of the
seismic data in single-trace and single frequency can be performed in
different
dimensions. In this manner, waveform distortion resulted from frequency band
expansion can be avoided. Therefore, according to the present embodiment, the
resolution of the seismic data can be significantly improved, thereby
providing
technological support to the subsequent processing and explanation.
Embodiment 4
As shown in Fig. 5, according to the present embodiment, a constructing module
501 is added on the basis of the system according to embodiment 3. The
constructing
module 501 is connected with the processing result determination module 404.
The
constructing module 501 is configured to construct the output function K(t) .
Fig. 6 schematically shows a structure of the constructing module 501
according
to the present embodiment. As shown in Fig. 6, according to the present
embodiment,
the constructing module 501 mainly comprises a first constructing unit 601, a
second
constructing unit 602, a third constructing unit 603, and an output function
determination unit 604, wherein the first constructing unit 601 is connected
with the
output function determination unit 604, and the second constructing unit 602
is
connected with the output function determination unit 604 through the third
constructing unit 603.
Specifically, the first constructing unit 601 is configured to construct a
first
analytic function E(t) , and enable the first analytic function E(t) to meet a
following expression: E(t)= x(t)+ jh(t).
The second constructing unit 602 is configured to construct a second analytic
function Y(t), and enable the second analytic function Y(t) to meet a
following
expression: Y(t)= X r(t)+ j2R-ft .
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The third constructing unit 603 is configured to construct a third analytic
function
Z(t) according to the second analytic function Y(t), and enable the third
analytic
function Z(t) to meet a following
expression:
Z(t) = ex'(`) * cos(27rft) + jeAc(t) * sin(27rft) .
The output function determination unit 604 is configured to obtain the output
function K(t) by multiplying the first analytic function E(t) with the third
analytic
function Z(t), and enable the output function K(t) to meet a following
expression:
K(t)= {x(t)e' ) cos(27t-ft) ¨ h(t)e)c(t)sin(270)}
.
+ j{x(t)ex'(1) sin(270) + h(t)exr(1)cos(27rft)}
According to the present embodiment, the constructing of the first analytic
function, the second analytic function, and the third analytic function is
used for
deriving the output function. In this manner, the constraints are added, and
at the same
time, the derivation of the output function is clear. The single-trace and
single
frequency output function K(t) is a core function according to the present
embodiment. In the output function, the constraints on the input signal, the
three
instantaneous properties of the signal, and amplitude and phase of the signal
are added,
so that the distortion of the signal can be avoided during transformation
procedure in
frequency domain.
It should be noted that, with respect to the specific operational steps of the
modules and units according to embodiment 3 and embodiment 4, reference can be
made to the illustration of the method of the present disclosure hereinabove
combining
Figs. 1 to 3, and Figs. 7a to 12b, and the details of which are no longer
repeated here.
In a word, according to the present embodiment, the loss of data at low
frequency
end resulted from limited frequency band of traditional data acquisition
equipment can
be effectively compensated, and the frequency band of seismic data can be
apparently
expanded in a uniform manner. Therefore, the resolution of seismic data can be
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CA 2974134 2017-07-19
significantly improved. At the same time, waveform distortion resulted from
frequency
band expansion can be avoided, and kinematical characteristics of seismic
wavelet is
maintained unchanged. Adopting broadband acquisition equipment would
significantly
improve seismic acquisition cost.. Therefore, the traditional data collection
equipment
with a low cost will play its role in a rather long period of time. The method
of the
present embodiment is especially applicable for the high resolution processing
of
seismic data that is collected by traditional data acquisition equipment.
Apparently, it can be understood by those skilled in the art that, each of the
modules and steps of the present disclosure can be realized with a general
computing
device. They can be centralized in one single computing device, or can be
distributed
in a network consisting of a plurality of computing devices. Optionally, they
can be
realized with program codes executable in computing devices, and can thus be
stored
in storage devices to be executed by the computing devices. Alternatively,
they can be
made into integrated circuit modules respectively, or a plurality of modules
or steps of
them can be made into one single integrated circuit module. In this manner,
the present
disclosure is not limited to any specific combination of hardware and
software.
The above embodiments are described only for better understanding, rather than
restricting, the present disclosure. Any person skilled in the art can make
amendments
to the implementing forms or details without departing from the spirit and
scope of the
present disclosure. The protection scope of the present disclosure shall be
determined
by the scope as defined in the claims.
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