CN114076980A - Method and system for thin layer carving - Google Patents
Method and system for thin layer carving Download PDFInfo
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- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
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Abstract
The invention provides a method and a system for thin layer characterization, wherein the method comprises the steps of obtaining a research discrimination angle superposition data body and obtaining a background longitudinal and transverse wave velocity ratio of a research area through prestack inversion. And acquiring a target function for representing the relation between the zero offset data and the actually measured seismic data, wherein the offset data is a longitudinal wave impedance reflectivity convolution wavelet result. And performing inversion processing on the angle-division stacking data volume by using the obtained target function to obtain real zero offset seismic reflection data of the research area. On the basis of obtaining real zero offset reflection data obtained based on inversion, the odd-even component weight coefficient of the zero offset reflection data is obtained, and on the basis, the zero offset reflection data with improved resolution ratio is obtained. The method comprises the steps of obtaining zero offset information by a step-by-step method, and then performing odd-even component decomposition on the basis of the zero offset information, so that the longitudinal resolution of the reflection data is improved, and the whole process is more stable than direct inversion of multi-angle superposed data.
Description
Technical Field
The invention relates to the technical field of seismic exploration processing, in particular to a method and a system for thin layer characterization.
Background
In conventional processing, in order to improve the signal-to-noise ratio of seismic data, seismic data acquired by multiple coverage techniques are often stacked, and the stacked data are used as actual self-excited and self-receiving data, i.e., zero offset data (muelle, ever, et al, seismic data processing method, 2006). In the face of actual seismic data, resolution of stacked data is often reduced due to inaccurate dynamic correction speed, and even if the dynamic correction is completely accurate, seismic data with different offsets have obvious differences (Z.Sun, Y.Zhangand C.Fan, and accurate AVO inversion workflow for pure P-wave calculation and S-wave improvement, 2014,10(32): 47-50). The seismic data resulting from the stacking is not fully equivalent to actual zero offset data. On one hand, the amplitude of the two waves is different under the influence of AVO effect; on the other hand, when the effective reflection angle is large, the stacked data can weaken and even completely cover some reservoirs with obvious AVO effect, namely the tuning effect of AVO, so that the resolution and the precision of seismic data are reduced to a certain extent.
Inversion based on the stacked data can convert seismic data into impedance information reflecting the elastic property of the underground medium, but the inversion is based on the assumption that the stacked data is actual zero offset data, and the two data are actually different in relative amplitude and frequency, so that the inversion accuracy is restricted to a certain extent, and the description accuracy of details of a thin layer and an inner curtain of a reservoir is limited; meanwhile, due to the influence of AVO tuning effect, accurate stratum interpretation is difficult to be carried out by utilizing the superposed data.
The vertical resolution of seismic data directly determines the thin layer carving capability of the seismic data, and the reflection coefficient is found to be composed of an odd component and an even component by Chorra and the like (Chorra, S., J.Castagna, and Y.xu.thin-bed reflection information applications, first Break,2009,27: 17-24.) through a wedge model test, wherein the odd component inhibits the improvement of the longitudinal resolution and is not beneficial to thin layer carving, and the even component can improve the longitudinal resolution of the reflection coefficient, thereby improving the capability of the seismic reflection information carving thin layers. The conventional method for improving the inversion resolution ratio is mainly divided into two methods, the first method is an inversion method through random simulation, but the method has extremely high requirements on the matching degree of well seismic and the quantity and quality of well data, and has the disadvantages of time consumption and weak applicability; the second method is based on a deterministic inversion method, utilizes the odd-even decomposition of a reflection coefficient to improve the longitudinal resolution, and is usually based on the superposition reflection data (enlightening, etc. model constraint base tracking inversion method, oil geophysical prospecting, 2019,55(1):115-122) or directly utilizes multi-angle superposition data to carry out inversion calculation, wherein the former method has limited inversion precision due to the inherent problem of the superposition data, and the latter method has stronger unsuitability in the inversion process due to the overlarge condition number of a Jacobian matrix.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method and a system for thin layer carving, wherein a step-by-step method is utilized, underground real zero offset information is obtained based on pre-stack inversion, relative superposed data is richer and more real for carving the underground real information, the longitudinal resolution is improved, then odd-even component decomposition is carried out on the basis of the zero offset information, the longitudinal resolution of reflected data is further improved, the precision for thin layer carving is improved, and the whole process is more stable in direct inversion relative to multi-angle superposed data.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a method for patterning a thin layer, comprising the steps of: s100, obtaining a study division angle superposition data body, and obtaining a background longitudinal and transverse wave velocity ratio of a study area through pre-stack inversion. S200, obtaining a target function for representing the relation between the zero offset data and the actually measured seismic data, wherein the offset data is a longitudinal wave impedance reflectivity convolution wavelet result. The objective function is obtained by algebraic calculation according to the longitudinal wave impedance reflectivity and the coefficient matrix of the approximate formula, wherein the longitudinal wave impedance reflectivity is the ratio of the impedance difference between the upper layer and the lower layer of the interface to the impedance sum between the upper layer and the lower layer of the interface, and the coefficient matrix of the approximate formula is the ratio of the incident angle to the longitudinal wave speed and the transverse wave speed. S300, inversion processing is carried out on the angle-division stacking data volume by using the obtained objective function, and real zero offset seismic reflection data of a research area are obtained. S400, on the basis of obtaining the real zero offset reflection data obtained by inversion in the step S300, constructing a target function of the odd-even component weight coefficient, obtaining the odd-even component weight coefficient of the zero offset reflection data, and on the basis, obtaining the zero offset reflection data with improved resolution.
According to the method for thin layer scribing of the invention, the influence of superposition and odd component of reflection coefficient on thin layer scribing is considered, the zero offset reflection data is obtained through prestack inversion, the problem that the longitudinal resolution is reduced due to superposition of trace gather data is solved, through odd-even component decomposition inversion, the longitudinal resolution of the seismic data is further improved on the basis of the zero offset reflection data, noise suppression processing is performed on the basis of the obtained high-resolution reflection coefficient, the whole calculation process is calculated step by step, the problem of unsuitability enhancement caused by direct use of angle-divided superposition data calculation is reduced, the problem of detail blurring caused by the superposition effect of full-superposition seismic reflection signals can be solved, the high-resolution zero offset reflection signals can be obtained, underground truer reflection information is recovered, and the capability of the seismic data for thin layer carving is effectively improved.
With respect to the above technical solution, further improvements as described below can be made.
The method for thin layer scribing according to the present invention, in a preferred embodiment, further comprises step S500: noise suppression and filtering processing are performed on the basis of the zero offset reflection data with improved resolution obtained in step S400 to obtain zero offset reflection data with improved longitudinal resolution.
And on the basis of the obtained zero offset reflection data with improved resolution, performing noise suppression by using principal component analysis, and performing abnormal frequency band suppression by using band-pass filtering to obtain high-resolution zero offset reflection information and provide constraint data for geological analysis and elastic parameter extraction of a thin target layer.
Further, in a preferred embodiment, the method for thin layer characterization of the present invention further includes step S600: and performing elastic parameter inversion on the basis of the zero offset reflection data which is obtained in the step S500 and improves the longitudinal resolution, and performing geological evolution analysis on the research area.
Specifically, in a preferred embodiment, step S100 includes the following sub-steps: s101, on the basis of the offset domain common reflection point gather, the layer velocity body is used for converting the angle domain pre-stack gather. S102, based on the pre-stack gather processed in the step S101, L superimposed data volumes D (theta) with different incident angles theta are respectively obtained1),D(θ2)...D(θL). Further, in a preferred embodiment, in step S101, before the transformation of the angle domain prestack gather by using the layer velocity volume, an optimization process targeting prestack inversion is further performed, where the optimization process includes cutting, prestack gather denoising, and gather leveling.
Specifically, in a preferred embodiment, in step S200, zero offset data S is characterizedpThe objective function f (m) of the relationship with the measured seismic data D is:
F(m)＝min||Gm-d||+β·mTWTWm (1)
in the formula (1), G is the incidence angle and the background longitudinal and transverse wave velocity ratio gamma is Vp/VsConstructed coefficient matrix, VpIs the velocity of longitudinal wave, VsFor transverse wave velocity, the specific expression of G is:
g in formula (2)L1＝sec2(θL)，GL2＝-8sin2(θL)/γ2，GL3＝2sin2(θL)/γ2-tan2(θL) The gamma value is obtained by pre-stack inversion;
m in formula (1) is obtained zero offset data SpVertical incidence transverse wave data SsAnd density change rate data SdThe concrete form of the composition is as follows:
m＝[Sp,Ss,Sd]T (3)
in formula (1), d is a matrix formed by a sub-angle stack data volume obtained by observing a seismic gather, and is specifically expressed as:
d＝[D(θ1),D(θ2)...D(θL)]T (4)
in formula (1), W is a flatness matrix, which is used to suppress the influence of noise on the extraction of zero offset data, and is specifically expressed as:
in the formula (1), beta is a weight coefficient, and the weight of the flatness matrix constraint can be adjusted.
Specifically, in a preferred embodiment, step S400 includes the following sub-steps: s401, establishing an objective function for solving the odd-even component weight coefficient based on the zero offset data, and solving the odd-even component reflection weight coefficient based on the zero offset data obtained in the step S300; s402, acquiring zero offset data for improving resolution based on the zero offset parity component reflection coefficient and the parity component weight coefficient matrix obtained in the step S401. In step S401, zero offset seismic data SpDecomposed into odd components roAnd even component reThe correlation between the products of the weighting coefficients o and e, which correspond to the products, can be expressed as:
Sp＝Wsp[ro,re][o,e]T (6)
in step S401, the inversion objective function ψ (m') of the weight coefficients of the parity components based on the zero offset data is:
ψ(m')＝min{||WspFm'-Sp||2+μ||m'||+σ||PFm'-T||2} (7)
in formula (7), P is an integral matrix, WspA wavelet matrix of the seismic data with the zero offset distance, and T is low-frequency information of longitudinal wave impedance obtained by carrying out difference on logging data; mu and sigma are weight adjusting parameters; m ═ o, e]T，F＝[ro,re]Wherein r iso，reAll diracht functions xi form a specific expression as follows:
ro(t,m,n,Δt)＝ξ(t-mΔt)-ξ(t-mΔt+nΔt) (8)
re(t,m,n,Δt)＝ξ(t-mΔt)+ξ(t-mΔt+nΔt) (9)
in the formulas (8) and (9), t is a preset time, Δ t is a sampling interval, m is a sampling point position corresponding to the top interface of the thin layer, and n is a sampling point position corresponding to the bottom interface.
In step S402, the zero offset reflection data r with improved resolution is obtained by using the parity component weight coefficient and the parity component combination obtained in step S401pThe concrete solving formula is as follows: r isp＝Fm' (10)。
The system for thin layer characterization according to the second aspect of the present invention includes a first processing module for obtaining a study discrimination angle superposition data volume and a background longitudinal-transverse wave velocity ratio. And the second processing module is used for acquiring a target function representing the relation between the zero offset data and the actually measured seismic data. And the third processing module is used for carrying out inversion processing according to the obtained target function to obtain the real zero offset seismic reflection data of the research area. And the fourth processing module is used for constructing an objective function of the odd-even decomposition weight coefficient according to the real zero offset seismic reflection data technology, acquiring the weight coefficient of the odd-even component of the zero offset reflection data, and acquiring the zero offset reflection data with improved resolution by combining the odd-even decomposition matrix on the basis.
In the same way, the system for thin layer characterization of the invention considers the influence of the superposition and the odd component of the reflection coefficient on the thin layer characterization, the zero offset reflection data is obtained through prestack inversion, the problem that the longitudinal resolution is reduced due to superposition of trace gather data is solved, through odd-even component decomposition inversion, the longitudinal resolution of the seismic data is further improved on the basis of the zero offset reflection data, noise suppression processing is performed on the basis of the obtained high-resolution reflection coefficient, the whole calculation process is calculated step by step, the problem of unsuitability enhancement caused by direct use of angle-divided superposition data calculation is reduced, the problem of detail blurring caused by the superposition effect of full-superposition seismic reflection signals can be solved, the high-resolution zero offset reflection signals can be obtained, underground truer reflection information is recovered, and the capability of the seismic data for thin layer carving is effectively improved.
With respect to the above technical solution, further improvements as described below can be made.
Further, in a preferred embodiment, the system for thin layer characterization of the present invention further includes an optimization processing module, configured to perform noise suppression and filtering processing on the zero-offset reflection data with improved resolution to obtain zero-offset reflection data with improved longitudinal resolution.
Further, in a preferred embodiment, the system for thin layer characterization of the present invention further includes a post-processing module for performing elastic parameter inversion based on the zero offset reflection data for improving the longitudinal resolution, so as to perform a geological significance analysis on the study area.
Compared with the prior art, the invention has the advantages that: by utilizing a step-by-step method, underground real zero offset information is obtained based on pre-stack inversion, the underground real information is more abundantly and really carved relative to the superposed data, the longitudinal resolution is improved, then odd-even component decomposition is carried out on the basis of the zero offset information, the longitudinal resolution of the reflected data is further improved, the precision of thin layer carving is improved, and the direct inversion of the whole process relative to multi-angle superposed data is more stable.
Drawings
The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings. Wherein:
fig. 1 schematically shows a flow of a method for thin layer characterization according to an embodiment of the present invention;
FIG. 2 schematically illustrates measured well data according to an embodiment of the invention;
FIG. 3 schematically illustrates an angle gather calculated using theoretical well log data;
FIG. 4 schematically shows a comparison of a fully-overlapped gather and a zero-offset gather;
FIG. 5 schematically shows a comparison of zero offset gathers with a high resolution reflection coefficient convolution 25Hz wavelets after parity decomposition;
FIG. 6 schematically shows a comparison of zero offset gathers with a high resolution reflection coefficient convolution 35Hz wavelets after parity decomposition;
FIG. 7 schematically shows the results of comparing zero offset data obtained from inversion of actual observed data with data obtained from a method for thin layer characterization according to an embodiment of the present invention; wherein, fig. 7(a) is a longitudinal wave reflection seismic trace obtained by convolution of measured well data longitudinal wave impedance and rake wavelet with 40Hz dominant frequency, fig. 7(b) is conventional stacked data obtained by observation, fig. 7(c) is a zero offset seismic trace gather obtained by inversion of angle-divided stacked data volume, fig. 7(d) is a reflection seismic trace obtained by the thin layer delineation method provided by the invention, and fig. 7(e) is measured well data longitudinal wave impedance;
FIG. 8 schematically shows conventional full stack data, zero offset data obtained using pre-stack inversion, and a comparison of reflection data obtained by a method of an embodiment of the invention; wherein, fig. 8(a) is conventional stacked data, fig. 8(b) is zero offset data obtained by using pre-stack inversion, and fig. 8(c) is zero offset high resolution reflection seismic data after noise suppression by parity component decomposition, principal component analysis and filtering processing on the basis of the zero offset data in fig. 8 (b);
FIG. 9 schematically shows a comparison of full stack data with high resolution data obtained using a method of an embodiment of the invention and impedance inversion results using both; fig. 9(a) is conventional stacked seismic reflection data, fig. 9(b) is longitudinal wave impedance data obtained by inversion using the reflection data in fig. 9(a), fig. 9(c) is seismic reflection data obtained by the method according to the embodiment of the present invention, and fig. 9(d) is longitudinal wave impedance data obtained by inversion using the reflection data in fig. 9 (c).
In the drawings, like parts are provided with like reference numerals. The figures are not drawn to scale.
Detailed Description
The invention will be further explained in detail with reference to the figures and the embodiments without thereby limiting the scope of protection of the invention.
Example 1
Fig. 1 schematically shows a flow of a method for thin layer characterization according to an embodiment of the present invention.
As shown in fig. 1, the method for thin layer characterization according to the embodiment of the present invention includes the following steps: s100, obtaining a study division angle superposition data body, and obtaining a background longitudinal and transverse wave velocity ratio of a study area through pre-stack inversion. S200, obtaining a target function for representing the relation between the zero offset data and the actually measured seismic data, wherein the offset data is a longitudinal wave impedance reflectivity convolution wavelet result. The objective function is obtained by algebraic calculation according to the longitudinal wave impedance reflectivity and the coefficient matrix of the approximate formula, wherein the longitudinal wave impedance reflectivity is the ratio of the impedance difference between the upper layer and the lower layer of the interface to the impedance sum between the upper layer and the lower layer of the interface, and the coefficient matrix of the approximate formula is the ratio of the incident angle to the longitudinal wave speed and the transverse wave speed. S300, inversion processing is carried out on the angle-division stacking data volume by using the obtained objective function, and real zero offset seismic reflection data of a research area are obtained. S400, on the basis of obtaining the real zero offset reflection data obtained by inversion in the step S300, constructing a target function of the odd-even component weight coefficient, obtaining the odd-even component weight coefficient of the zero offset reflection data, and on the basis, obtaining the zero offset reflection data with improved resolution.
According to the method for thin layer scribing of the invention, the influence of superposition and odd component of reflection coefficient on thin layer scribing is considered, the zero offset reflection data is obtained through prestack inversion, the problem that the longitudinal resolution is reduced due to superposition of trace gather data is solved, through odd-even component decomposition inversion, the longitudinal resolution of the seismic data is further improved on the basis of the zero offset reflection data, noise suppression processing is performed on the basis of the obtained high-resolution reflection coefficient, the whole calculation process is calculated step by step, the problem of unsuitability enhancement caused by direct use of angle-divided superposition data calculation is reduced, the problem of detail blurring caused by the superposition effect of full-superposition seismic reflection signals can be solved, the high-resolution zero offset reflection signals can be obtained, underground truer reflection information is recovered, and the capability of the seismic data for thin layer carving is effectively improved.
Specifically, in the present embodiment, step S100 includes the following sub-steps: s101, on the basis of the offset domain common reflection point gather, the layer velocity body is used for converting the angle domain pre-stack gather. S102, based on the pre-stack gather processed in the step 101, L superimposed data volumes D (theta) with different incident angles theta are respectively obtained1),D(θ2)...D(θL). Further, in this embodiment, in step S101, before the transformation of the angle domain pre-stack gather by using the layer velocity volume, an optimization process targeting pre-stack inversion is further performed, where the optimization process includes cutting, denoising of the pre-stack gather, and leveling of the gather.
Specifically, in the present embodiment, in step S200, zero offset data S is characterizedpThe objective function f (m) of the relationship with the measured seismic data D is:
F(m)＝min||Gm-d||+β·mTWTWm (1)
in the formula (1), G is the incidence angle and the background longitudinal and transverse wave velocity ratio gamma is Vp/VsConstructed coefficient matrix, VpIs the velocity of longitudinal wave, VsIs the speed of transverse waveThe specific expression of G is as follows:
g in formula (2)L1＝sec2(θL)，GL2＝-8sin2(θL)/γ2，GL3＝2sin2(θL)/γ2-tan2(θL) The gamma value is obtained by pre-stack inversion;
m in formula (1) is obtained zero offset data SpVertical incidence transverse wave data SsAnd density change rate data SdThe concrete form of the composition is as follows:
m＝[Sp,Ss,Sd]T (3)
in formula (1), d is a matrix formed by a sub-angle stack data volume obtained by observing a seismic gather, and is specifically expressed as:
d＝[D(θ1),D(θ2)...D(θL)]T (4)
in formula (1), W is a flatness matrix, which is used to suppress the influence of noise on the extraction of zero offset data, and is specifically expressed as:
in the formula (1), beta is a weight coefficient, and the weight of the flatness matrix constraint can be adjusted.
Specifically, in the present embodiment, the step S400 includes the following sub-steps: s401, establishing an objective function for solving the odd-even component weight coefficient based on the zero offset data, and solving the odd-even component reflection weight coefficient based on the zero offset data obtained in the step S300; s402, acquiring zero offset data for improving resolution based on the zero offset parity component reflection coefficient and the parity component weight coefficient matrix obtained in the step S401. In step S401, zero offset seismic data SpDecomposed into odd components roAnd even component reThe correlation between the products of the weighting coefficients o and e, which correspond to the products, can be expressed as:
Sp＝Wsp[ro,re][o,e]T (6)
in step S401, the inversion objective function ψ (m') of the weight coefficients of the parity components based on the zero offset data is:
ψ(m')＝min{||WspFm'-Sp||2+μ||m'||+σ||PFm'-T||2} (7)
in formula (7), P is an integral matrix, WspA wavelet matrix of the seismic data with the zero offset distance, and T is low-frequency information of longitudinal wave impedance obtained by carrying out difference on logging data; mu and sigma are weight adjusting parameters; m ═ o, e]T，F＝[ro,re]Wherein r iso，reAll diracht functions xi form a specific expression as follows:
ro(t,m,n,Δt)＝ξ(t-mΔt)-ξ(t-mΔt+nΔt) (8)
re(t,m,n,Δt)＝ξ(t-mΔt)+ξ(t-mΔt+nΔt) (9)
in the formulas (8) and (9), t is a preset time, Δ t is a sampling interval, m is a sampling point position corresponding to the top interface of the thin layer, and n is a sampling point position corresponding to the bottom interface.
In step S402, the zero offset reflection data r with improved resolution is obtained by using the parity component weight coefficient and the parity component combination obtained in step S401pThe concrete solving formula is as follows: r isp＝Fm' (10)。
Example 2
The method for thin layer characterization according to the embodiment of the present invention preferably further includes, on the basis of embodiment 1, step S500: noise suppression and filtering processing are performed on the basis of the zero offset reflection data with improved resolution obtained in step S400 to obtain zero offset reflection data with improved longitudinal resolution. And on the basis of the obtained zero offset reflection data with improved resolution, performing noise suppression by using principal component analysis, and performing abnormal frequency band suppression by using band-pass filtering to obtain high-resolution zero offset reflection information and provide constraint data for geological analysis and elastic parameter extraction of a thin target layer.
Example 3
Further, the method for thin layer characterization according to the embodiment of the present invention further includes, on the basis of embodiment 2, step S600: and performing elastic parameter inversion on the basis of the zero offset reflection data which is obtained in the step S500 and improves the longitudinal resolution, and performing geological evolution analysis on the research area.
FIG. 2 schematically shows measured well data including compressional velocity, shear velocity, and density data for determining reflection coefficients at different incident angles using the three measured well data according to an embodiment of the present invention. FIG. 3 schematically shows an angle gather calculated using theoretical well log data, in this embodiment, the incident angle is 0 to 36 degrees, and every 4 degrees, and then the reflection coefficient is convolved with the dominant 25Hz Rake wavelet to obtain the gather data of different incident angles, which can be used as the observed seismic data.
FIG. 4 schematically shows a comparison of a fully-overlapped gather and a zero-offset gather. In fig. 4, the trace labeled 1 is a real longitudinal wave reflection data gather (obtained by convolution of a longitudinal wave reflection coefficient obtained by using logging data and a rake wavelet with a dominant frequency of 25 Hz), the trace labeled 2 is a stacked data trace obtained by performing full stacking using the observed seismic data in fig. 3, the trace labeled 3 is a difference between the trace labeled 1 and the trace labeled 2, that is, a difference between real longitudinal wave reflection data and stacked data, the trace labeled 4 is zero offset data obtained by using the present invention, the trace labeled 5 is a difference between the trace labeled 1 and the trace labeled 4, that is, a difference between real longitudinal wave reflection data and zero offset data obtained by using the method of the embodiment of the present invention. As can be seen by comparing the data of the 3 th and 5 th tracks in FIG. 4, the data obtained by the conventional superposition method has errors with the real longitudinal wave reflection data, and the real longitudinal wave reflection data in the box of FIG. 4 (3176 and 3226ms) has two in-phase axes, i.e. represents two reflection layers, but the data in the box of the 2 nd track of superposition data has two thicker reflection axes due to the effect of AVO effect, which results in the decrease of the formation resolution. Therefore, as can be seen from the comparison results of fig. 4, the zero offset information of the embodiment of the present invention recovers the underground true reflection information more than the overlay data and highlights the small layer display.
FIG. 5 schematically shows a comparison of zero offset gathers with a high resolution reflection coefficient convolution 25Hz wavelets after parity decomposition. In fig. 5, the 1 st trace is a real longitudinal wave reflection seismic trace obtained by convolution of a 25Hz wavelet with a real longitudinal wave reflection coefficient, the 2 nd trace is a zero offset reflection seismic trace obtained by inversion of the sub-angle stack data with a main frequency of 25Hz, and the 3 rd trace is a seismic trace obtained by convolution of a 25Hz wavelet with a reflection coefficient which is obtained by decomposition based on the parity component obtained by the method of the invention and has improved resolution. The comparison shows that when the reflection coefficient of resolution is improved after wavelet convolution odd-even decomposition with the main frequency of 25Hz, the obtained seismic channel is consistent with the real longitudinal wave reflection seismic channel and the zero offset seismic channel, namely, the reflection coefficient obtained by the thin layer carving method provided by the invention does not generate unreasonable false axis, namely, the result is credible.
FIG. 6 schematically shows a comparison of zero offset gathers with a high resolution reflection coefficient convolution 35Hz wavelets after parity decomposition. In fig. 6, the 1 st trace is a longitudinal wave reflection seismic trace obtained by convolving 35Hz wavelets with actually measured well data in fig. 2, the 2 nd trace is a zero offset reflection seismic trace obtained by inverting the data obtained by stacking the sub-angles with the main frequency of 25Hz, and the 3 rd trace is a seismic trace obtained by processing the 2 nd trace in step S400 and step 500 of the present invention, wherein the main component analysis involved in step S500 mainly plays a role in removing noise, and the high-frequency filtering mainly filters out reflection coefficients higher than 70Hz and also plays a role in suppressing noise. The method provided by the invention can be used for obtaining a plurality of thin layer reflecting interfaces (in a frame of figure 6) which cannot be drawn by conventional superposed data. In order to verify the authenticity of the thin layer carved by the invention, the 1 st trace and the 3 rd trace in FIG. 6 can be compared, and it can be seen that the reflection layer after the resolution is improved can also be seen in the synthetic record of 35Hz (the 1 st trace in FIG. 6), and the thin layer reflection information can be more highlighted compared with the zero offset seismic reflection trace obtained by inversion (the 2 nd trace in FIG. 6), thereby verifying the feasibility and effectiveness of the invention.
Fig. 7 schematically shows the results of comparing the zero offset data obtained by inversion of actual observation data with the data obtained by the method for thin layer characterization according to the embodiment of the present invention. Fig. 7(a) is a longitudinal wave reflection seismic trace obtained by convolution of measured well data longitudinal wave impedance and a rake wavelet with a dominant frequency of 40Hz, fig. 7(b) is conventional stacked data obtained by observation, fig. 7(c) is a zero offset seismic trace gather obtained by inversion of a component angle stacked data volume, fig. 7(d) is a reflection seismic trace obtained by the thin layer delineation method provided by the invention, and fig. 7(e) is measured well data longitudinal wave impedance. Comparing fig. 7(b) and 7(c), it can be seen that the inverted zero offset data is more consistent with the well synthetic seismic record and reflects the slice delineation relative to the stacked data, for example at the 3025ms dashed line. Fig. 7(d) shows the reflection seismic trace obtained by the thin layer characterization method of the present invention, and it can be known from comparison that the reflection seismic information obtained by the device of the present invention further characterizes richer thin layer information, such as the inside of a square frame in the figure, with respect to zero offset information.
FIG. 8 schematically shows conventional full stack data, zero offset data obtained using pre-stack inversion, and a comparison of reflection data obtained by a method of an embodiment of the invention. Fig. 8(a) is conventional stack data, fig. 8(b) is zero offset data obtained by using prestack inversion, and fig. 8(c) is zero offset high-resolution reflection seismic data after noise suppression by parity component decomposition, principal component analysis, and filtering processing on the basis of the zero offset data in fig. 8 (b). Compared with the prior art, the thin layer describing method has the advantages that the zero offset data has stronger capacity of describing the inner curtain of the reservoir relative to the stacking data, and has more thin layer reflection responses.
FIG. 9 schematically shows a comparison of full stack data with high resolution data obtained using the method of an embodiment of the invention and impedance inversion results using both. Fig. 9(a) is conventional stacked seismic reflection data, fig. 9(b) is longitudinal wave impedance data obtained by inversion using the reflection data in fig. 9(a), fig. 9(c) is seismic reflection data obtained by the method according to the embodiment of the present invention, and fig. 9(d) is longitudinal wave impedance data obtained by inversion using the reflection data in fig. 9 (c). The well crossing line in the graph is actually measured longitudinal wave impedance data, and the inversion result comparison shows that the inversion result obtained by the thin layer characterization method provided by the invention not only improves the longitudinal resolution of the reservoir, enables the thin layer to be more prominent, but also is more consistent with well data, and verifies the reliability of the method provided by the invention.
Example 4
The system for thin layer characterization according to the embodiment of the second aspect of the present invention includes a first processing module, configured to obtain a research differentiation angle superposition data volume and a background longitudinal-transverse wave velocity ratio. And the second processing module is used for acquiring a target function representing the relation between the zero offset data and the actually measured seismic data. And the third processing module is used for carrying out inversion processing according to the obtained target function to obtain the real zero offset seismic reflection data of the research area. And the fourth processing module is used for constructing an objective function of the odd-even decomposition weight coefficient according to the real zero offset seismic reflection data technology, acquiring the weight coefficient of the odd-even component of the zero offset reflection data, and acquiring the zero offset reflection data with improved resolution by combining the odd-even decomposition matrix on the basis.
Further, in this embodiment, the method further includes an optimization processing module, configured to perform noise suppression and filtering processing on the zero-offset reflection data with the improved resolution to obtain zero-offset reflection data with the improved longitudinal resolution. Furthermore, in this embodiment, the apparatus further includes a post-processing module, configured to perform elastic parameter inversion on the basis of the zero-offset reflection data with improved longitudinal resolution, so as to perform a geological significance analysis on the research area.
In the same way, the system for thin layer characterization of the invention considers the influence of the superposition and the odd component of the reflection coefficient on the thin layer characterization, the zero offset reflection data is obtained through prestack inversion, the problem that the longitudinal resolution is reduced due to superposition of trace gather data is solved, through odd-even component decomposition inversion, the longitudinal resolution of the seismic data is further improved on the basis of the zero offset reflection data, noise suppression processing is performed on the basis of the obtained high-resolution reflection coefficient, the whole calculation process is calculated step by step, the problem of unsuitability enhancement caused by direct use of angle-divided superposition data calculation is reduced, the problem of detail blurring caused by the superposition effect of full-superposition seismic reflection signals can be solved, the high-resolution zero offset reflection signals can be obtained, underground truer reflection information is recovered, and the capability of the seismic data for thin layer carving is effectively improved.
While the invention has been described with reference to a preferred embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the technical features mentioned in the embodiments can be combined in any way as long as there is no structural conflict. It is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (10)
1. A method for patterning a thin layer, comprising the steps of:
s100, obtaining a study division angle superposition data body, and obtaining a background longitudinal and transverse wave velocity ratio of a study area through pre-stack inversion;
s200, obtaining an objective function for representing the relation between the zero offset data and the actually measured seismic data, wherein,
the zero offset data is a wavelet result of convolution of the reflectivity of longitudinal wave impedance;
the objective function is obtained by algebraic calculation according to the longitudinal wave impedance reflectivity and a coefficient matrix of an approximate formula, wherein the longitudinal wave impedance reflectivity is the ratio of the impedance difference between the upper layer and the lower layer of the interface to the impedance sum between the upper layer and the lower layer of the interface, and the coefficient matrix of the approximate formula is the ratio of the incident angle to the velocity of the longitudinal wave and the velocity of the longitudinal wave;
s300, performing inversion processing on the angle-division stacking data volume by using the obtained target function to obtain real zero offset seismic reflection data of a research area;
s400, on the basis of obtaining the real zero offset reflection data obtained by inversion in the step S300, constructing a target function of the odd-even component weight coefficient, obtaining the odd-even component weight coefficient of the zero offset reflection data, and on the basis, obtaining the zero offset reflection data with improved resolution.
2. Method for thin layer scribing according to claim 1, further comprising step S500: noise suppression and filtering processing are performed on the basis of the zero offset reflection data with improved resolution obtained in step S400 to obtain zero offset reflection data with improved longitudinal resolution.
3. The experimental device for thin layer characterization according to claim 2, further comprising step S600: and performing elastic parameter inversion on the basis of the zero offset reflection data which is obtained in the step S500 and improves the longitudinal resolution, and performing geological significance analysis on the research area.
4. Experimental setup for thin layer characterization according to any of claims 1 to 3, characterized in that said step S100 comprises the following sub-steps:
s101, on the basis of a common reflection point gather of an offset domain, converting an angle domain pre-stack gather by using a layer velocity body;
s102, based on the pre-stack gather processed in the step S101, L different incidence angles theta are respectively obtained to obtain a superimposed data volume D (theta)1),D(θ2)...D(θL)。
5. The experimental apparatus for thin layer characterization according to claim 4, wherein in step S101, before the transformation of the angle domain prestack gather by using the layer velocity volume, an optimization process targeting prestack inversion is further performed, wherein the optimization process includes ablation, prestack gather de-noising and gather leveling.
6. Experimental device for thin layer characterization according to claim 4, characterized in that in step S200, zero offset data S is characterizedpThe objective function f (m) of the relationship with the measured seismic data D is:
F(m)＝min||Gm-d||+β·mTWTWm (1)
in the formula (1), G is the incidence angle and the background longitudinal and transverse wave velocity ratio gamma is Vp/VsConstructed coefficient matrix, VpIs the velocity of longitudinal wave, VsFor transverse wave velocity, the specific expression of G is:
g in formula (2)L1＝sec2(θL)，GL2＝-8sin2(θL)/γ2，GL3＝2sin2(θL)/γ2-tan2(θL) The gamma value is obtained by pre-stack inversion;
m in formula (1) is obtained zero offset data SpVertical incidence transverse wave data SsAnd density change rate data SdThe concrete form of the composition is as follows:
m＝[Sp,Ss,Sd]T (3)
in formula (1), d is a matrix formed by a sub-angle stack data volume obtained by observing a seismic gather, and is specifically expressed as:
d＝[D(θ1),D(θ2)...D(θL)]T (4)
in formula (1), W is a flatness matrix, which is used to suppress the influence of noise on the extraction of zero offset data, and is specifically expressed as:
in the formula (1), beta is a weight coefficient, and the weight of the flatness matrix constraint can be adjusted.
7. The experimental device for thin layer characterization according to claim 6, wherein the step S400 comprises the following sub-steps:
s401, establishing an objective function for solving the odd-even component weight coefficient based on the zero offset data, and solving the odd-even component reflection weight coefficient based on the zero offset data obtained in the step S300;
s402, acquiring zero offset data for improving resolution based on the zero offset parity component reflection coefficient and the parity component weight coefficient matrix obtained in the step S401;
in said step S401, zero offset seismic data SpDecomposed into odd components roAnd even component reThe correlation between the products of the weighting coefficients o and e, which correspond to the products, can be expressed as:
Sp＝Wsp[ro,re][o,e]T (6)
in step S401, the inversion objective function ψ (m') of the weight coefficients of the parity components based on the zero offset data is:
ψ(m')＝min{||WspFm'-Sp||2+μ||m'||+σ||PFm'-T||2} (7)
in formula (7), P is an integral matrix, WspA wavelet matrix of the seismic data with the zero offset distance, and T is low-frequency information of longitudinal wave impedance obtained by carrying out difference on logging data; mu and sigma are weight adjusting parameters; m ═ o, e]T，F＝[ro,re]Wherein r iso，reAll diracht functions xi form a specific expression as follows:
ro(t,m,n,Δt)＝ξ(t-mΔt)-ξ(t-mΔt+nΔt) (8)
re(t,m,n,Δt)＝ξ(t-mΔt)+ξ(t-mΔt+nΔt) (9)
in the formulas (8) and (9), t is a preset time, delta t is a sampling interval, m is a sampling point position corresponding to a top interface of the thin layer, and n is a sampling point position corresponding to a bottom interface;
in step S402, the zero offset reflection data r with improved resolution is obtained by using the parity component weight coefficient and the parity component combination obtained in step S401pThe concrete solving formula is as follows:
rp＝Fm' (10)。
8. a system for the characterization of thin layers, comprising
The first processing module is used for acquiring a research discrimination angle superposition data volume and a background longitudinal and transverse wave velocity ratio;
the second processing module is used for acquiring a target function representing the relation between the zero offset data and the actually measured seismic data;
the third processing module is used for carrying out inversion processing according to the obtained target function to obtain real zero offset seismic reflection data of the research area;
and the fourth processing module is used for constructing an objective function of the odd-even decomposition weight coefficient according to the real zero offset seismic reflection data technology, acquiring the weight coefficient of the odd-even component of the zero offset reflection data, and acquiring the zero offset reflection data with improved resolution by combining the odd-even decomposition matrix on the basis.
9. The system for thin layer characterization according to claim 8, further comprising an optimization processing module for performing noise suppression and filtering processing on the zero offset reflection data with improved resolution to obtain zero offset reflection data with improved longitudinal resolution.
10. A system for thin layer characterization according to claim 9, further comprising a post-processing module for performing elastic parameter inversion based on zero offset reflection data to improve longitudinal resolution for geologically meaningful analysis of the region of interest.
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