CN110515127B - Method, device, equipment and medium for determining seismic quality factor - Google Patents

Method, device, equipment and medium for determining seismic quality factor Download PDF

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CN110515127B
CN110515127B CN201910919141.6A CN201910919141A CN110515127B CN 110515127 B CN110515127 B CN 110515127B CN 201910919141 A CN201910919141 A CN 201910919141A CN 110515127 B CN110515127 B CN 110515127B
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seismic
amplitude spectrum
seismic data
quality factor
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CN110515127A (en
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刘国昌
李超
王志勇
宋欣悦
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China University of Petroleum Beijing
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Abstract

The application discloses a method, a device, equipment and a medium for determining seismic quality factors, wherein the method comprises the following steps: acquiring pre-stack seismic data, and determining a dip angle field and a time-frequency amplitude spectrum of the pre-stack seismic data; mapping the time-frequency amplitude spectrum into a target time-frequency amplitude spectrum by utilizing a prediction mapping technology; extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting preset conditions to obtain a target amplitude spectrum; and respectively establishing quality factor Q values corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs to invert an objective function so as to determine the quality factor Q values of all seismic horizons of the pre-stack seismic data. Therefore, the dip angle field and the target amplitude spectrum of the pre-stack seismic data are utilized to determine the seismic quality factor of the pre-stack seismic data, the seismic quality factor of the pre-stack seismic data with high accuracy can be obtained under the condition that speed information is not obtained, and the robustness to noise is strong.

Description

Method, device, equipment and medium for determining seismic quality factor
Technical Field
The application relates to the technical field of seismic data processing, in particular to a method, a device, equipment and a medium for determining a seismic quality factor.
Background
The inelasticity and heterogeneity of the subsurface medium can cause attenuation and dispersion of seismic waves during propagation. The attenuation degrees of the seismic waves with different frequencies are different, and the attenuation characteristics of the seismic waves related to the frequencies can be described by a prime factor Q or an attenuation factor 1/Q. The seismic wave attenuation is sensitive to the gas saturation parameter, so the Q value can be used for detecting and identifying the gas reservoir, and the Q value can also be used for predicting the crack direction and the like according to the characteristic that the seismic attenuation changes along with the azimuth angle. In the field of seismic data processing, the resolution of seismic data is reduced due to frequency spectrum change caused by seismic wave attenuation, so that the Q value is always an important parameter for processing the seismic attenuation compensation to improve the resolution. The seismic attenuation factor 1/Q can be used for attenuation compensation of seismic data and can also provide reference information for reservoir description and fluid prediction, so that accurate estimation of the Q value is very important for processing and interpretation of the seismic data.
In the prior art, the quality factor Q is usually obtained by a logarithmic spectrum ratio method, that is, the quality factor Q is obtained by using a spectrum ratio of two seismic waveforms, but this method is sensitive to noise and has instability. In addition, when the quality factor Q is acquired by using the post-stack seismic data, the path of ray propagation is not considered, and the adopted dynamic correction stacking processing can cause the seismic waveform to change, so that the precision of the Q value is reduced; when the quality factor Q is acquired by using the pre-stack seismic data, the velocity information of seismic waveform propagation is needed, and the precision of the Q value depends on the accuracy of the velocity information.
Disclosure of Invention
In view of this, an object of the present application is to provide a method, an apparatus, a device, and a medium for determining a seismic quality factor, which can acquire a seismic quality factor of pre-stack seismic data with high accuracy without acquiring velocity information and have strong robustness to noise. The specific scheme is as follows:
in a first aspect, the application discloses a method for determining seismic quality factors, comprising:
acquiring pre-stack seismic data, and determining a dip angle field of the pre-stack seismic data by utilizing a slope estimation technology;
obtaining a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method;
selecting top and bottom reflection from a seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting preset conditions to obtain a target amplitude spectrum;
respectively establishing quality factor Q values corresponding to the seismic horizons to invert the target function by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs;
and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data.
Optionally, the obtaining pre-stack seismic data and determining the dip angle field of the pre-stack seismic data by using a slope estimation technique further include:
and if the pre-stack seismic data is a seismic shot gather, converting the seismic shot gather into a common central point gather according to the parameters of an observation system, and passing the common central point gather through a preset two-dimensional prediction error filter to obtain a target common central point gather.
Optionally, the determining the dip field of the pre-stack seismic data by using a slope estimation technique includes:
and establishing a relation between a local slope and the pre-stack seismic data by combining the predictability of the same-phase axis, and determining the dip angle field of the pre-stack seismic data by using the relation.
Optionally, the selecting top and bottom reflections from the seismic section as reference points, and mapping the non-zero offset travel-time curve of the pre-stack seismic data to a zero offset travel-time curve by using a predictive mapping technique, includes:
selecting top and bottom reflection from the seismic section as a reference point, and mapping the non-zero offset travel-time curve of the pre-stack seismic data into a zero offset travel-time curve by using a first preset formula;
wherein the first preset formula is as follows:
Figure GDA0002493811830000021
Figure GDA0002493811830000031
represents a zero offset travel time curve, t represents travel time, t0When zero offset travel is indicated, x represents offset, x0Representing zero offset and p representing the local slope of the non-zero travel time curve.
Optionally, the selecting top and bottom reflections from the seismic section as reference points, and mapping the non-zero offset travel-time curve of the pre-stack seismic data to a zero offset travel-time curve by using a predictive mapping technique, includes:
selecting top and bottom reflection from the seismic section as a reference point, and mapping the non-zero offset travel-time curve of the pre-stack seismic data into a zero offset travel-time curve by using a second preset formula;
wherein the second preset formula is as follows: p1,k＝Pk-1,k…P2,3P1,2；
Pi,jAnd the predictor is used for predicting the j-th to zero offset travel time curve by the ith non-zero offset travel time curve.
Optionally, the establishing quality factor Q values inversion objective functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and the multiple sets of target amplitude spectrum pairs respectively includes:
respectively establishing a least square conjugate gradient inversion function corresponding to each seismic horizon by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the least squares conjugate gradient inversion function is:
Figure GDA0002493811830000032
α, 1/Q, represents the attenuation factor, b (p) ln (G (p)) represents the preset function, G is related to the reflection and transmission of the underground medium,
Figure GDA0002493811830000033
represents tiTarget amplitude spectrum corresponding to travel time, f represents frequency, p represents local slope of non-zero travel time curve, t2And t1Representing two different time instants, at represents the time difference corresponding to the two time instants,
Figure GDA0002493811830000034
expressed in a matrix as:
Figure GDA0002493811830000035
m represents the total number of rays employed, N represents the total number of frequency samples selected, flDenotes the l-th sampling frequency, Δ tjT representing the jth ray2Time t and1time difference of time, Bj＝ln(G(pj) A preset function representing the jth ray,
Figure GDA0002493811830000041
indicating the j-th ray at frequency flT of time2Target amplitude spectrum corresponding to time t1And the logarithm value of the target amplitude spectrum ratio corresponding to the moment.
Optionally, the establishing quality factor Q values inversion objective functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and the multiple sets of target amplitude spectrum pairs respectively includes:
respectively establishing regularized least square conjugate gradient inversion functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the regularized least squares conjugate gradient inversion function is:
Figure GDA0002493811830000042
λ1、λ2the regularization parameters of α and B (p), respectively.
In a second aspect, the present application discloses a seismic quality factor determination apparatus, comprising:
the data acquisition module is used for acquiring pre-stack seismic data;
the dip angle field determining module is used for determining the dip angle field of the pre-stack seismic data by utilizing a slope estimation technology;
the time-frequency amplitude spectrum acquisition module is used for acquiring a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method;
the travel time curve mapping module is used for selecting top and bottom reflection from a seismic section as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
the target amplitude spectrum extraction module is used for extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset conditions to obtain a target amplitude spectrum;
the inversion target function determining module is used for respectively establishing quality factor Q values corresponding to the seismic horizons by utilizing the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs;
and the quality factor determining module is used for inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data, and obtaining the quality factor Q values of all seismic horizons of the pre-stack seismic data.
In a third aspect, the present application discloses a seismic quality factor determining apparatus, comprising:
a memory and a processor;
wherein the memory is used for storing a computer program;
the processor is used for executing the computer program to realize the seismic quality factor determination method disclosed in the foregoing.
In a fourth aspect, the present application discloses a computer readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the seismic figure of merit determination method as disclosed above.
Therefore, the method comprises the steps of firstly obtaining pre-stack seismic data, and determining the dip angle field of the pre-stack seismic data by utilizing a slope estimation technology; then, a local attribute time-frequency analysis method is utilized to obtain a time-frequency amplitude spectrum of the pre-stack seismic data; selecting top and bottom reflection from a seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve; extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting preset conditions to obtain a target amplitude spectrum; respectively establishing quality factor Q values corresponding to the seismic horizons to invert the target function by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs; and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data. Therefore, after the pre-stack seismic data are acquired, the pre-stack seismic data are processed to obtain the dip angle field and the target amplitude spectrum of the pre-stack seismic data, the seismic quality factor of the pre-stack seismic data is determined by utilizing the dip angle field and the target amplitude spectrum, the seismic quality factor of the pre-stack seismic data with high accuracy can be acquired under the condition that speed information is not acquired, and the robustness to noise is high.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a seismic quality factor determination method disclosed herein;
FIG. 2 is a diagram of a prestack common midpoint gather disclosed herein;
FIG. 3 is a diagram of a post-stack seismic trace gather disclosed herein;
FIG. 4 is a cross-sectional view of a Q value determined using a prestack common midpoint gather as disclosed herein;
FIG. 5 is a flow chart of a particular seismic figure of merit determination method disclosed herein;
FIG. 6 is a flow chart of a particular seismic figure of merit determination method disclosed herein;
FIG. 7 is a schematic structural diagram of a seismic quality factor determination apparatus according to the present disclosure;
fig. 8 is a schematic structural diagram of a seismic quality factor determining apparatus disclosed in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
At present, the quality factor Q is usually obtained by using a logarithmic spectrum ratio method, that is, the quality factor Q is obtained by using a spectrum ratio of two seismic waveforms, but this method is sensitive to noise and has instability. In addition, when the quality factor Q is acquired by using the post-stack seismic data, the path of ray propagation is not considered, and the adopted dynamic correction stacking processing can cause the seismic waveform to change, so that the precision of the Q value is reduced; when the quality factor Q is acquired by using the pre-stack seismic data, the velocity information of seismic waveform propagation is needed, and the precision of the Q value depends on the accuracy of the velocity information. In view of this, the present application provides a method for determining a seismic quality factor, which can acquire a seismic quality factor of pre-stack seismic data with higher accuracy without acquiring velocity information, and has stronger robustness to noise.
The embodiment of the application discloses a method for determining a seismic quality factor, which is shown in figure 1 and comprises the following steps:
step S11: acquiring prestack seismic data, and determining a dip angle field of the prestack seismic data by utilizing a slope estimation technology.
In this embodiment, the prestack seismic data is a common midpoint gather, if the acquired prestack seismic data is a seismic shot gather, the seismic shot gather is converted into the common midpoint gather according to the parameters of an observation system, the common midpoint gather is passed through a preset two-dimensional prediction error filter to obtain a target midpoint gather, and then the slope estimation technology is used to determine the dip angle field of the target common midpoint gather. Since the local slope includes magnitude and direction, the local slope is referred to as the tilt angle field.
Step S12: and obtaining a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method.
In this embodiment, in order to obtain the frequency spectrum of the pre-stack seismic data by using the spectral ratio method, and the frequency spectrum of the seismic reflection wave in the pre-stack seismic data is affected by the seismic waveform, a local attribute time-frequency analysis method is used to obtain the time-frequency amplitude spectrum of the pre-stack seismic data, so as to reduce the influence of mutual interference of the seismic waveforms on the frequency spectrum.
Step S13: selecting top and bottom reflection from the seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve.
In this embodiment, the time-frequency amplitude spectrum obtained by using the pre-stack seismic data corresponds to a non-zero offset travel-time curve, and the time-frequency amplitude spectrum used when determining the seismic quality factor is the time-frequency amplitude spectrum corresponding to the zero-offset travel-time curve, so that a prediction mapping technology needs to be used to map the non-zero-offset travel-time curve of the pre-stack seismic data to the zero-offset travel-time curve, so as to map the time-frequency amplitude spectrum corresponding to the non-zero-offset travel-time curve to a target time-frequency amplitude spectrum corresponding to the zero-offset travel-time curve.
Step S14: and extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset condition to obtain a target amplitude spectrum.
In this embodiment, an amplitude spectrum needs to be extracted from the target time-frequency amplitude spectrum satisfying a preset condition, so as to obtain a target amplitude spectrum. Specifically, reflection waveforms with the same apparent velocity are found on a pre-stack non-zero offset travel time curve represented by the pre-stack seismic data, and then an amplitude spectrum is extracted from a target time-frequency amplitude spectrum corresponding to the reflection waveforms to obtain a target amplitude spectrum.
Step S15: and respectively establishing quality factor Q value inversion target functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs.
In this embodiment, the dip angle field and the multiple groups of target amplitude spectrum pairs corresponding to the same seismic horizon are combined to establish a quality factor Q value inversion target function of the seismic horizon, so as to establish the quality factor Q value inversion target function corresponding to each seismic horizon. Specifically, the top and bottom reflection of the target layer is automatically tracked by using a predictive mapping technology, and then a target amplitude spectrum corresponding to the reflection spectrum with the same ray parameter on the target layer is subjected to spectrum comparison to obtain the quality factor Q value inversion target function. Wherein the ray parameters include, but are not limited to, a dip angle field.
Step S16: and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data.
It can be understood that after the quality factor Q values corresponding to each seismic horizon are established, the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data are determined by inversion of the quality factor Q values corresponding to each seismic horizon through the quality factor Q values corresponding to each seismic horizon, and the quality factor Q values of all seismic horizons in the pre-stack seismic data are obtained. Because the spectral ratios of the dip angle field and the target amplitude spectrum pair corresponding to each seismic horizon are different, the quality factor Q value inversion target functions corresponding to each established seismic horizon are also different.
It can be understood that, the dip field of the prestack seismic data is used to determine the Q value inversion objective function of the quality factor, so as to determine the seismic quality factor of the prestack seismic data, and avoid the influence of velocity on the seismic quality factor, the coaxial local slope is an attribute parameter of a seismic data domain, and the velocity is an attribute parameter of a seismic model domain, and in the process of determining the seismic quality factor, the accuracy of the seismic quality factor can be improved by using the attribute parameter of the seismic data domain.
In this embodiment, when the pre-stack seismic data is a common midpoint gather, a pre-stack common midpoint gather map is shown in fig. 2, in which the abscissa represents offset in kilometers, and the ordinate represents time in seconds. If the pre-stack seismic data are stacked, the obtained post-stack seismic data result is shown in fig. 3, wherein the abscissa in the figure is distance and the unit is kilometer, and the ordinate represents time and the unit is second. The cross section of the quality factor Q value determined using the prestack common midpoint gather is shown in fig. 4, where the abscissa represents distance in kilometers, and the ordinate represents time in seconds.
Therefore, the method comprises the steps of firstly obtaining pre-stack seismic data, and determining the dip angle field of the pre-stack seismic data by utilizing a slope estimation technology; then, a local attribute time-frequency analysis method is utilized to obtain a time-frequency amplitude spectrum of the pre-stack seismic data; selecting top and bottom reflection from a seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve; extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset condition to obtain a target amplitude spectrum; respectively establishing quality factor Q values corresponding to the seismic horizons to invert the target function by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs; and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data. Therefore, after the pre-stack seismic data are acquired, the pre-stack seismic data are processed to obtain the dip angle field and the target amplitude spectrum of the pre-stack seismic data, the seismic quality factor of the pre-stack seismic data is determined by utilizing the dip angle field and the target amplitude spectrum, the seismic quality factor of the pre-stack seismic data with high accuracy can be acquired under the condition that speed information is not acquired, and the robustness to noise is high.
Referring to fig. 5, an embodiment of the present application discloses a specific method for determining a seismic quality factor, including:
step S21: and acquiring pre-stack seismic data.
Step S22: and establishing a relation between a local slope and the pre-stack seismic data by combining the predictability of the same-phase axis, and determining the dip angle field of the pre-stack seismic data by using the relation.
It is to be understood that, when the pre-stack seismic data is a common midpoint gather, and has on-axis predictability, the determining the dip field of the pre-stack seismic data by using the slope estimation technique includes: and establishing a relation between a local slope and the pre-stack seismic data by combining coaxial predictability, and determining a dip angle field of the pre-stack seismic data by utilizing the relation.
Step S23: and obtaining a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method.
Step S24: selecting top and bottom reflection from a seismic section as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by using a first preset formula so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
wherein the first preset formula is as follows:
Figure GDA0002493811830000091
Figure GDA0002493811830000092
represents a zero offset travel time curve, t represents travel time, t0When zero offset travel is indicated, x represents offset, x0Representing zero offset and p representing the local slope of the non-zero travel time curve.
In this embodiment, when the local slope function of the non-zero travel-time curve is a continuous function, the first preset formula may be adopted to map the non-zero offset travel-time curve of the pre-stack seismic data to a zero offset travel-time curve, so as to map the time-frequency amplitude spectrum corresponding to the non-zero offset travel-time curve to a target time-frequency amplitude spectrum corresponding to the zero offset travel-time curve.
Step S25: and extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset condition to obtain a target amplitude spectrum.
Step S26: respectively establishing a least square conjugate gradient inversion function corresponding to each seismic horizon by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the least squares conjugate gradient inversion function is:
Figure GDA0002493811830000101
α, 1/Q, represents the attenuation factor, b (p) ln (G (p)) represents the preset function, G is related to the reflection and transmission of the underground medium,
Figure GDA0002493811830000102
represents tiTarget amplitude spectrum corresponding to travel time, f represents frequency, p represents local slope of non-zero travel time curve, t2And t1Representing two different time instants, at represents the time difference corresponding to the two time instants,
Figure GDA0002493811830000103
expressed in a matrix as:
Figure GDA0002493811830000104
m represents the total number of rays employed, N represents the total number of frequency samples selected, flDenotes the l-th sampling frequency, Δ tjT representing the jth ray2Time t and1time difference of time, Bj＝ln(G(pj) A preset function representing the jth ray,
Figure GDA0002493811830000105
indicating the j-th ray at frequency flT of time2Target amplitude spectrum corresponding to time t1And the logarithm value of the target amplitude spectrum ratio corresponding to the moment.
Step S27: and determining quality factor Q values of corresponding seismic horizons in the pre-stack seismic data by using least square conjugate gradient inversion functions corresponding to all seismic horizons to obtain the quality factor Q values of all seismic horizons of the pre-stack seismic data.
Referring to fig. 6, an embodiment of the present application discloses a specific method for determining a seismic quality factor, including:
step S31: and acquiring pre-stack seismic data.
Step S32: and establishing a relation between a local slope and the pre-stack seismic data by combining the predictability of the same-phase axis, and estimating the dip angle field of the pre-stack seismic data by using the relation.
Step S33: and obtaining a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method.
Step S34: selecting top and bottom reflection from a seismic section as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by using a second preset formula so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
wherein the second preset formula is as follows: p1,k＝Pk-1,k…P2,3P1,2；
Pi,jAnd the predictor is used for predicting the j-th to zero offset travel time curve by the ith non-zero offset travel time curve.
In this embodiment, when the local slope function of the non-zero travel-time curve is a discrete function, the non-zero offset travel-time curve of the pre-stack seismic data is mapped to a zero offset travel-time curve by using the second preset formula, so as to map the time-frequency amplitude spectrum corresponding to the non-zero offset travel-time curve to a target time-frequency amplitude spectrum corresponding to the zero offset travel-time curve.
Step S35: extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset condition to obtain a target amplitude spectrum
Step S36: respectively establishing regularized least square conjugate gradient inversion functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the regularized least squares conjugate gradient inversion function is:
Figure GDA0002493811830000111
λ1、λ2the regularization parameters of α and B (p), respectively.
It will be appreciated that in actual processing, frequencies within a range of frequency bands may be selected for sampling, and rays selected within a range. In order to obtain a more stable and robust inversion result, the least square conjugate gradient inversion function is regularized, and the inversion result is optimized.
Step S37: and determining quality factor Q values of corresponding seismic horizons in the pre-stack seismic data by using the regularized least square conjugate gradient inversion function corresponding to each seismic horizon to obtain the quality factor Q values of all seismic horizons of the pre-stack seismic data.
Referring to fig. 7, an embodiment of the present application discloses an apparatus for determining a seismic quality factor, including:
the data acquisition module 11 is used for acquiring pre-stack seismic data;
a dip field determination module 12, configured to determine a dip field of the pre-stack seismic data by using a slope estimation technique;
a time-frequency amplitude spectrum obtaining module 13, configured to obtain a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method;
the travel time curve mapping module 14 is configured to select a top-bottom reflection from a seismic profile as a reference point, and map a non-zero offset travel time curve of the prestack seismic data to a zero offset travel time curve by using a prediction mapping technique, so as to map the time-frequency amplitude spectrum corresponding to the non-zero offset travel time curve to a target time-frequency amplitude spectrum corresponding to the zero offset travel time curve;
the target amplitude spectrum extraction module 15 is configured to extract an amplitude spectrum from the target time-frequency amplitude spectrum meeting a preset condition, so as to obtain a target amplitude spectrum;
an inversion target function determining module 16, configured to utilize the dip angle field and the multiple sets of target amplitude spectrum pairs corresponding to each seismic horizon to respectively establish a quality factor Q value inversion target function corresponding to each seismic horizon;
and the quality factor determining module 17 is configured to invert an objective function by using the quality factor Q values corresponding to each seismic horizon, determine the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data, and obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data.
Therefore, the method comprises the steps of firstly obtaining pre-stack seismic data, and determining the dip angle field of the pre-stack seismic data by utilizing a slope estimation technology; then, a local attribute time-frequency analysis method is utilized to obtain a time-frequency amplitude spectrum of the pre-stack seismic data; selecting top and bottom reflection from a seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve; extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset condition to obtain a target amplitude spectrum; respectively establishing quality factor Q values corresponding to the seismic horizons to invert the target function by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs; and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data. Therefore, after the pre-stack seismic data are acquired, the pre-stack seismic data are processed to obtain the dip angle field and the target amplitude spectrum of the pre-stack seismic data, the seismic quality factor of the pre-stack seismic data is determined by utilizing the dip angle field and the target amplitude spectrum, the seismic quality factor of the pre-stack seismic data with high accuracy can be acquired under the condition that speed information is not acquired, and the robustness to noise is high.
Further, as shown in fig. 8, an embodiment of the present application further discloses an earthquake quality factor determining apparatus, including: a processor 21 and a memory 22.
Wherein the memory 22 is used for storing a computer program; the processor 21 is configured to execute the computer program to implement the method for determining seismic quality factor disclosed in the foregoing embodiments.
For the specific process of the seismic quality factor determination method, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
Further, the present application also discloses a computer readable storage medium for storing a computer program, wherein the computer program is executed by a processor to implement the method for determining seismic quality factor disclosed in any of the foregoing embodiments.
For the specific process of the seismic quality factor determination method, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of other elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The method, the device, the equipment and the medium for determining the seismic quality factor provided by the application are introduced in detail, specific examples are applied in the description to explain the principle and the implementation mode of the application, and the description of the above embodiments is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. A method for seismic quality factor determination, comprising:
acquiring pre-stack seismic data, and determining a dip angle field of the pre-stack seismic data by utilizing a slope estimation technology;
obtaining a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method;
selecting top and bottom reflection from a seismic profile as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting preset conditions to obtain a target amplitude spectrum;
respectively establishing quality factor Q values corresponding to the seismic horizons to invert the target function by using the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs;
and inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, and determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data to obtain the quality factor Q values of all seismic horizons in the pre-stack seismic data.
2. The method of claim 1, wherein the obtaining pre-stack seismic data and determining the dip field of the pre-stack seismic data using a slope estimation technique further comprises:
and if the pre-stack seismic data is a seismic shot gather, converting the seismic shot gather into a common central point gather according to the parameters of an observation system, and passing the common central point gather through a preset two-dimensional prediction error filter to obtain a target common central point gather.
3. The method of determining seismic quality factors of claim 2, wherein determining the dip field of the pre-stack seismic data using a slope estimation technique comprises:
and establishing a relation between a local slope and the pre-stack seismic data by combining the predictability of the same-phase axis, and determining the dip angle field of the pre-stack seismic data by using the relation.
4. The method of claim 1, wherein the selecting top and bottom reflections from the seismic section as reference points and mapping the non-zero offset traveltime curve of the pre-stack seismic data to a zero offset traveltime curve using a predictive mapping technique comprises:
selecting top and bottom reflection from the seismic section as a reference point, and mapping the non-zero offset travel-time curve of the pre-stack seismic data into a zero offset travel-time curve by using a first preset formula;
wherein the first preset formula is as follows:
Figure FDA0002493811820000021
Figure FDA0002493811820000022
represents a zero offset travel time curve, t represents travel time, t0When zero offset travel is indicated, x represents offset, x0Representing zero offset and p representing the local slope of the non-zero travel time curve.
5. The method of claim 1, wherein the selecting top and bottom reflections from the seismic section as reference points and mapping the non-zero offset traveltime curve of the pre-stack seismic data to a zero offset traveltime curve using a predictive mapping technique comprises:
selecting top and bottom reflection from the seismic section as a reference point, and mapping the non-zero offset travel-time curve of the pre-stack seismic data into a zero offset travel-time curve by using a second preset formula;
wherein the second preset formula is as follows: p1,k＝Pk-1,k…P2,3P1,2；
Pi,jAnd the predictor is used for predicting the zero-offset travel-time curve of the jth track by the ith non-zero-offset travel-time curve.
6. The method for determining the seismic quality factor according to claim 1, wherein the step of establishing the quality factor Q value inversion objective function corresponding to each seismic horizon by using the dip angle field corresponding to each seismic horizon and a plurality of sets of target amplitude spectrum pairs respectively comprises:
respectively establishing a least square conjugate gradient inversion function corresponding to each seismic horizon by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the least squares conjugate gradient inversion function is:
Figure FDA0002493811820000023
α, 1/Q, represents the attenuation factor, b (p) ln (G (p)) represents the preset function, G is related to the reflection and transmission of the underground medium,
Figure FDA0002493811820000024
represents tiTarget amplitude spectrum corresponding to travel time, f represents frequency, p represents local slope of non-zero travel time curve, t2And t1Representing two different time instants, at represents the time difference corresponding to the two time instants,
Figure FDA0002493811820000025
expressed in a matrix as:
Figure FDA0002493811820000031
m represents the total number of rays employed, N represents the total number of frequency samples selected, flDenotes the l-th sampling frequency, Δ tjT representing the jth ray2Time t and1time difference of time, Bj＝ln(G(pj) A preset function representing the jth ray,
Figure FDA0002493811820000032
indicating the j-th ray at frequency flT of time2Target amplitude spectrum corresponding to time t1And the logarithm value of the target amplitude spectrum ratio corresponding to the moment.
7. The method for determining seismic quality factors according to any one of claims 1 to 6, wherein the establishing quality factor Q value inversion objective functions corresponding to each seismic horizon by using the dip angle field corresponding to each seismic horizon and a plurality of sets of target amplitude spectrum pairs respectively comprises:
respectively establishing regularized least square conjugate gradient inversion functions corresponding to the seismic horizons by using the dip angle field corresponding to each seismic horizon and a plurality of groups of target amplitude spectrum pairs;
wherein the regularized least squares conjugate gradient inversion function is:
Figure FDA0002493811820000033
λ1、λ2the regularization parameters of α and B (p), respectively.
8. An apparatus for determining a seismic quality factor, comprising:
the data acquisition module is used for acquiring pre-stack seismic data;
the dip angle field determining module is used for determining the dip angle field of the pre-stack seismic data by utilizing a slope estimation technology;
the time-frequency amplitude spectrum acquisition module is used for acquiring a time-frequency amplitude spectrum of the pre-stack seismic data by using a local attribute time-frequency analysis method;
the travel time curve mapping module is used for selecting top and bottom reflection from a seismic section as a reference point, and mapping a non-zero offset travel time curve of the pre-stack seismic data into a zero offset travel time curve by utilizing a prediction mapping technology so as to map the time frequency amplitude spectrum corresponding to the non-zero offset travel time curve into a target time frequency amplitude spectrum corresponding to the zero offset travel time curve;
the target amplitude spectrum extraction module is used for extracting an amplitude spectrum from the target time-frequency amplitude spectrum meeting the preset conditions to obtain a target amplitude spectrum;
the inversion target function determining module is used for respectively establishing quality factor Q values corresponding to the seismic horizons by utilizing the dip angle field corresponding to each seismic horizon and the multiple groups of target amplitude spectrum pairs;
and the quality factor determining module is used for inverting the objective function by using the quality factor Q values corresponding to all seismic horizons, determining the quality factor Q values of the corresponding seismic horizons in the pre-stack seismic data, and obtaining the quality factor Q values of all seismic horizons of the pre-stack seismic data.
9. A seismic quality factor determination apparatus comprising:
a memory and a processor;
wherein the memory is used for storing a computer program;
the processor for executing the computer program to implement the seismic figure of merit determination method of any of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the seismic figure of merit determination method according to any one of claims 1 to 7.
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