A seismic reconstruction method based on low-frequency trend modeling of velocity

Abstract

The application provides a seismic reconstruction method based on low-frequency trend modeling of velocity. The method firstly reconstructs a low-frequency component of well logging wave impedance in a time domain based on a generalized S transform, calculates the low-frequency component of seismic wave impedance based on a seismic velocity data body and a fitting relationship between density and velocity, obtains a corrected three-dimensional space seismic wave impedance low-frequency component data body, calculates a wave impedance value of a target layer after desolidification, calculates a wave impedance desolidification coefficient, obtains a three-dimensional seismic compaction coefficient body, and further establishes a mathematical relationship between multi-channel seismic records, a seismic wavelet and a wave impedance difference. A wave impedance inversion target function after desolidification is established, a nonlinear inversion method is adopted to obtain a seismic record after desolidification correction, and the reconstructed seismic data effectively improve the prediction accuracy of thin reservoirs, reservoir properties and reservoir oil content in deep and low-lying zones.

Description

Technical Field

[0001] The present invention relates to the technical field of geophysical exploration and development, and in particular to a seismic reconstruction method based on velocity low-frequency trend modeling. Background Art

[0002] Because the velocity and density of reservoirs in deep depressions are affected by compaction, increasing burial depth and intensified compaction directly impact the velocity and density variations of the three reservoir types, and thus, the impedance variations. Compaction creates differences in the impedance of sandstone and mudstone in different sedimentary facies on the plane. Vertically, the difference in impedance between sandstone and mudstone along the well logging curve decreases with increasing burial depth. This results in significant overlap of lithologic impedance within the same reservoir type, and the reduced impedance differences produce weak reflections, reducing seismic identification capabilities. The changes in impedance within the same reservoir type caused by compaction directly impact changes in seismic recording characteristics, making it difficult to extract regularity in the seismic attribute changes corresponding to the three effective reservoir types from existing seismic records, making it difficult to select appropriate seismic attributes to describe the three reservoir types.

[0003] Common formation decompaction correction methods include compaction rate recovery, compaction coefficient recovery, decompaction recovery, original formation thickness recovery chart method, sequence stratigraphic analysis, vitrinite maximum reflectance recovery, and geophysical methods. The compaction coefficient recovery method is the most commonly used. The compaction coefficient is a key parameter for inverting basin burial processes. Considering the differences in wave impedance within the same reservoir type caused by compaction directly affects changes in seismic recording characteristics and is a prerequisite for accurately obtaining the compaction coefficient of mudstone in normally compacted sections. The variation in the low-frequency (time domain) or low-wavenumber (depth domain) wave impedance components with depth represents the compaction trend of the formation wave impedance. Therefore, by extracting the low-frequency or low-wavenumber components of the wave impedance, the formation wave impedance compaction coefficient in the time or depth domain can be calculated. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a seismic reconstruction method based on velocity low-frequency trend modeling that overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a seismic reconstruction method based on velocity low-frequency trend modeling is provided, comprising:

[0006] Step S1: convert the logging data into the time domain, perform frequency division processing on the logging wave impedance, and select the low-frequency component that matches the trend as the logging low-frequency component data volume;

[0007] Step S2: calculating the seismic wave impedance low-frequency component based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and correcting the seismic wave impedance low-frequency component using the well logging low-frequency component data volume to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume;

[0008] Step S3: determining the compaction trend line corresponding to the target layer segment based on the corrected three-dimensional seismic wave impedance low-frequency component data volume, calculating the wave impedance value of the target layer after decompaction, and calculating the wave impedance decompaction coefficient;

[0009] Step S4: establishing the wave impedance relationship and the mathematical relationship of the reflection coefficient before and after decompaction, and establishing the mathematical relationship between the multi-channel seismic record and the seismic wavelet and the multi-channel wave impedance difference;

[0010] Step S5: Under the constraint of the trend of the low-frequency component of the wave impedance, establish the wave impedance inversion objective function after decompaction, and use the nonlinear inversion method to obtain the compaction-corrected seismic record.

[0011] Optionally, the step S1: converting the logging data into the time domain, performing frequency division processing on the logging wave impedance, and selecting the low-frequency component that matches the trend as the logging low-frequency component data body specifically includes:

[0012] The time domain logging impedance data volume is calculated from the logging data. The generalized S-transform time-frequency spectrum analysis is used to determine the low-frequency component range of the impedance representing the reservoir compaction trend in the target well section.

[0013] The low-frequency component of logging wave impedance is reconstructed by using generalized inverse S-transform to obtain the low-frequency component of logging wave impedance in time domain.

[0014] Optionally, step S2: calculating the seismic wave impedance low-frequency component based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and correcting the seismic wave impedance component using the well logging low-frequency component to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume specifically includes:

[0015] Based on the seismic migration velocity data and the interpreted main target layer data, the layer-controlled multi-constrained layer velocity inversion MCVI method is used to calculate the seismic layer velocity;

[0016] Analyze the intersection diagram of target layer logging velocity and logging density to obtain the density and velocity fitting formula, and apply it to convert the seismic layer velocity into formation density and calculate the seismic wave impedance body;

[0017] Use generalized S-transform to obtain low-frequency wave impedance body;

[0018] The low-frequency component of the logging wave impedance is used for correction to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume.

[0019] Optionally, step S3: determining the compaction trend line corresponding to the target layer segment based on the corrected three-dimensional spatial seismic wave impedance low-frequency component data volume, and calculating the wave impedance value of the target layer after decompaction. Calculating the wave impedance decompaction coefficient specifically includes:

[0020] According to the characteristics of low-frequency wave impedance value changing with depth due to compaction, the compaction trend line corresponding to the target layer is determined, and the wave impedance value of the target layer after decompaction is calculated;

[0021] The wave impedance compaction coefficient is calculated using the wave impedance values ​​before and after decompaction, and the target layer logging and three-dimensional wave impedance compaction coefficient variation curve with depth are obtained.

[0022] Optionally, in step S3, the difference between the wellbore seismic wave impedance compaction coefficient and the logging wave impedance decompaction coefficient is calculated, and the layer-controlled seismic wave impedance compaction coefficient error data volume is established by using the Kriging interpolation correction technology in combination with the interpretation layer;

[0023] The seismic wave impedance compaction coefficient is corrected to obtain a corrected three-dimensional seismic wave impedance compaction coefficient data volume.

[0024] Optionally, step S4: establishing a mathematical relationship between wave impedance before and after decompaction and a mathematical relationship between reflection coefficients, and establishing a mathematical relationship between multi-channel seismic records, seismic wavelets, and multi-channel wave impedance differences specifically includes:

[0025] According to the nonlinear relationship between reflection coefficient and wave impedance and the differential operator, the relationship between reflection coefficient, multi-channel wave impedance difference and seismic records is established.

[0026] Optionally, step S5: establishing a post-compaction wave impedance inversion objective function under the constraint of the wave impedance low-frequency component trend, and using a nonlinear inversion method to obtain a compaction-corrected seismic record specifically includes:

[0027] A low-frequency constraint objective function is established, and the nonlinear inversion method is used to obtain the wave impedance after compaction correction and the reflection coefficient after decompaction correction.

[0028] The seismic wavelets extracted from the wellside data are used to obtain the decompaction-corrected seismic records through convolution.

[0029] Optionally, the nonlinear inversion method in step S5 adopts a spectral projection gradient algorithm to solve the wave impedance after compaction correction.

[0030] Optionally, the objective function of the wave impedance inversion after decompaction in step S5 specifically includes: the multi-channel wave impedance inversion problem is expressed as

[0031]

[0032] in, w is the row vector of the wavelet time series, X low is the low-frequency component of wave impedance, obtained from logging wave impedance or seismic velocity spectrum; L is the low-pass filter operator; Y is the known multi-channel seismic record, The inverted reflection coefficient time series is sparse and laterally smooth; The synthetic earthquake record is consistent with the actual earthquake record; X low =LX is the trend constraint of the low-frequency component of the wave impedance;

[0033] Optionally, the step S5 of establishing the wave impedance inversion objective function after decompaction further includes: the wave impedance inversion problem after decompaction is expressed as

[0034]

[0035] Where C is the matrix composed of compaction coefficients;

[0036] The semi-logarithm of the wave impedance after decompaction is obtained by inversion c ;

[0037] Calculate the multi-channel reflection coefficient R after decompaction using the difference operator c ;

[0038] Calculate the decompacted seismic record Y using the wavelet extracted from the wellbore seismic record c .

[0039] The present invention provides a seismic reconstruction method based on velocity low-frequency trend modeling, comprising: step S1: converting well logging data into the time domain, performing frequency division processing on the well logging wave impedance, and selecting a low-frequency component consistent with the trend as a well logging low-frequency component data volume; step S2: calculating the seismic wave impedance low-frequency component based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and correcting the seismic wave impedance low-frequency component using the well logging low-frequency component data volume to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume; step S3: determining a compaction trend line corresponding to a target layer segment based on the corrected three-dimensional seismic wave impedance low-frequency component data volume, calculating the wave impedance value of the target layer after decompaction, and calculating the wave impedance decompaction coefficient; step S4: establishing a mathematical relationship between the wave impedance and reflection coefficient before and after decompaction, and establishing a mathematical relationship between multi-channel seismic records, seismic wavelets, and multi-channel wave impedance differences; step S5: establishing a wave impedance inversion objective function after decompaction under the constraint of the wave impedance low-frequency component trend, and obtaining a compaction-corrected seismic record using a nonlinear inversion method. It is used to correct for reservoir compaction in deep sag zones, thereby improving the accuracy of predictions of thin reservoirs, reservoir physical properties, and reservoir oil content in deep sag zones. It is widely applicable to deep oil and gas reservoir exploration in quasi-medium-deep layers in western exploration areas and even in Sinopec exploration areas.

[0040] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 The embodiment of the present invention provides Figure 1 This is a flow chart of the seismic reconstruction method based on velocity low-frequency trend modeling of the present invention;

[0043] Figure 2 Components of different frequency bands of a logging wave impedance curve in a specific embodiment 1 of the present invention;

[0044] Figure 3 This is a schematic diagram of removing low-frequency components from time-domain wave impedance in a specific embodiment 1 of the present invention;

[0045] Figure 4 Schematic diagram of a low-frequency component data volume of three-dimensional wave impedance in a specific embodiment 1 of the present invention;

[0046] Figure 5 Schematic diagram of the planar distribution of the compaction coefficient and the decompaction coefficient of the target layer in a specific embodiment 1 of the present invention;

[0047] Figure 6 This is a schematic diagram of earthquake reconstruction in a specific embodiment 1 of the present invention;

[0048] Figure 7 Components of different frequency bands of a logging wave impedance curve in a specific embodiment 2 of the present invention;

[0049] Figure 8 This is a schematic diagram of removing low-frequency components from time-domain wave impedance in a specific embodiment 2 of the present invention;

[0050] Figure 9 Schematic diagram of a low-frequency component data volume of three-dimensional wave impedance in a specific embodiment 2 of the present invention;

[0051] Figure 10 Schematic diagram of the planar distribution of the compaction coefficient and the decompaction coefficient of the target layer in a specific embodiment 2 of the present invention;

[0052] Figure 11This is a schematic diagram of earthquake reconstruction in a specific embodiment 2 of the present invention. DETAILED DESCRIPTION

[0053] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0054] The terms "comprises" and "comprising" and any variations thereof in the description, embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0055] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0056] like Figure 1 As shown, Figure 1 FIG. 1 is a flow chart of a decompaction seismic reconstruction method based on low-frequency trend modeling according to the present invention, comprising the following steps:

[0057] Step 101: First, the logging data is converted into the time domain, and then the logging wave impedance is subjected to frequency division processing, and the low-frequency component that is consistent with the trend is selected as the logging low-frequency component data body.

[0058] Step 102: Calculate the low-frequency component of seismic wave impedance based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and use the well logging low-frequency component to correct the seismic wave impedance component to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume.

[0059] Step 103: Determine the compaction trend line corresponding to the target layer segment based on the corrected three-dimensional seismic wave impedance low-frequency component data volume, calculate the wave impedance value of the target layer after decompaction, and then calculate the wave impedance decompaction coefficient.

[0060] Step 104: Establishing the wave impedance relationship and the mathematical relationship of the reflection coefficient before and after decompaction, and then establishing the mathematical relationship between the multi-channel seismic record and the seismic wavelet and the multi-channel wave impedance difference.

[0061] Step 105: Under the constraint of the trend of the low-frequency component of the wave impedance, establish a wave impedance inversion objective function after decompaction, and use a nonlinear inversion method to obtain the compaction-corrected seismic record.

[0062] In step 101, first, the well logging data can calculate time domain logging wave impedance data body, determine the wave impedance low frequency component range of the target layer well section representing the compaction trend of the reservoir by generalized S transform time-frequency spectrum analysis, and then reconstruct the logging wave impedance low frequency component by using generalized S inverse transform to obtain the logging time domain wave impedance low frequency component.

[0063] In step 102, based on the seismic migration velocity data body and the interpreted main target layer data, the layer control multi-constraint layer velocity inversion (MCVI) method is used to calculate the seismic layer velocity; secondly, the well logging velocity and well logging density crossplot analysis of the target layer is carried out to obtain the fitting formula of density and velocity, and is applied to the seismic layer velocity to calculate the formation density, calculate the seismic wave impedance body, also use the generalized S transform to obtain the low frequency wave impedance body, and finally use the logging wave impedance low frequency component to correct to obtain the corrected three-dimensional space seismic wave impedance low frequency component data body.

[0064] In step 103, according to the low frequency wave impedance value changing with depth due to compaction, the compaction trend line corresponding to the target layer section is determined, and then the wave impedance value after decompaction of the target layer is calculated; then the wave impedance compaction coefficient is calculated by using the wave impedance values before and after decompaction, so as to obtain the logging and three-dimensional wave impedance compaction coefficient curves changing with depth of the target layer section.

[0065] In step 103, the difference between the seismic wave impedance compaction coefficient and the logging wave impedance decompaction coefficient is calculated, combined with the interpreted horizon, the layer control seismic wave impedance compaction coefficient error data body is established by using the Kriging interpolation correction technology, and then the seismic wave impedance compaction coefficient is corrected to obtain the corrected three-dimensional space seismic wave impedance compaction coefficient data body.

[0066] In step 104, first, according to the nonlinear relationship between the reflection coefficient and the wave impedance and the difference operator, the relationship among the reflection coefficient, the multi-channel wave impedance difference and the seismic record is established.

[0067] In step 105, by using the established low frequency constraint objective function, the compaction corrected wave impedance is obtained by using the nonlinear inversion method, and then the decompaction corrected reflection coefficient is obtained, and the decompaction corrected seismic record is obtained by using the seismic wavelet extracted from the well side data through convolution.

[0068] In step 105, in the nonlinear inversion method, the spectral projection gradient algorithm is used to solve the compaction corrected wave impedance.

[0069] Logging wave impedance low frequency component calculation

[0070] Based on logging data, time domain logging wave impedance data body can be calculated, through generalized S transform time-frequency spectrum analysis, wave impedance low frequency component range of the purpose layer well section representing reservoir compaction trend is determined, then generalized S inverse transform is adopted to reconstruct logging wave impedance low frequency component, and logging time domain wave impedance low frequency component is obtained.

[0071] Three-dimensional space seismic wave impedance low frequency component calculation

[0072] Seismic wave impedance decompaction coefficient calculation needs seismic wave impedance low frequency component, therefore, based on seismic migration velocity, layer-controlled multi-constraint layer velocity inversion method is adopted to calculate seismic layer velocity, low frequency velocity field is obtained through frequency division calculation, density and velocity fitting formula is obtained by using logging density and velocity crossplot, then formation density is converted by using seismic layer velocity, and thus seismic wave impedance low frequency component is obtained. Finally, logging wave impedance low frequency component is used for correction, and corrected three-dimensional space seismic wave impedance low frequency component data body is obtained, which can be expressed by matrix X. low .

[0073] Wherein, layer-controlled multi-constraint layer velocity inversion method improves calculation precision of layer velocity, the method can convert longitudinal and transverse sparse and irregularly distributed velocity spectrum points into regular and fine geologically constrained layer velocity body, and overcomes errors of velocity spectrum analysis caused by artificial picking velocity spectrum and dramatic structural longitudinal and transverse changes. The technology is to make root mean square velocity converted by inverted layer velocity best fit input root mean square velocity in least square sense under velocity longitudinal and transverse change trend constraint and damping constraint conditions.

[0074] Three-dimensional space seismic wave impedance compaction coefficient calculation

[0075] According to low frequency wave impedance value changing with depth due to compaction effect, compaction trend line corresponding to the purpose layer section is determined, and then wave impedance value after decompaction of the purpose layer is calculated. Wave impedance compaction coefficient is calculated by using wave impedance values before and after decompaction. According to difference between well seismic wave impedance compaction coefficient and logging wave impedance decompaction coefficient, combined with interpreted horizon, layer-controlled seismic wave impedance compaction coefficient error data body is established by using Kriging interpolation correction technology, and then seismic wave impedance compaction coefficient is corrected, and corrected three-dimensional space seismic wave impedance compaction coefficient data body is obtained, and multiple compaction coefficients form a matrix C.

[0076] Establishment of wave impedance inversion equation after decompaction

[0077] Compaction-induced variations in impedance within the same reservoir type directly affect changes in seismic recording characteristics. Therefore, multi-channel absolute impedance inversion, constrained by low-frequency impedance trends, can be used to obtain corrected impedance and seismic records. This method overcomes the problem of traditional single-channel impedance inversion, which fails to consider the lateral gradient of impedance. Furthermore, the inversion objective function incorporates constraints on the low-wavenumber component of impedance.

[0078] The multi-channel impedance inversion problem is expressed as

[0079]

[0080] Where, w is the row vector of the wavelet time series, X low is the low-frequency component of wave impedance, which can be obtained from logging wave impedance or seismic velocity spectrum; L is the low-pass filter operator; Y is the known multi-channel seismic record, It means that the inverted reflection coefficient time series is sparse and laterally (along the formation) smooth; represents the constraint on the consistency between synthetic earthquake records and actual earthquake records; X low =LX represents the trend constraint of the low-frequency component of the wave impedance.

[0081] The wave impedance inversion problem after decompaction can be expressed as

[0082]

[0083] Where C is the matrix composed of compaction coefficients.

[0084] The semi-logarithm of the wave impedance after decompaction is obtained by inversion c , and then use the difference operator to calculate the multi-channel reflection coefficient R after decompaction c Finally, the wavelet extracted from the wellside seismic record is used to calculate the decompacted seismic record Y c .

[0085] Reconstructed seismic records after decompaction correction

[0086] According to the established low-frequency constrained objective function, the nonlinear inversion method is used to obtain the wave impedance after compaction correction, and then the reflection coefficient after decompaction correction is obtained. The seismic wavelet extracted from the wellbore data is used to obtain the decompaction corrected seismic record through convolution.

[0087] The present invention provides a seismic reconstruction method based on velocity low-frequency trend modeling. The low-frequency component of seismic wave impedance is calculated using a seismic velocity data volume and a fitting relationship between density and velocity; the low-frequency component of seismic wave impedance is corrected using the low-frequency component of well logging to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume; the compaction trend line corresponding to the target layer segment is determined, the wave impedance value of the target layer after decompaction is calculated, and the wave impedance decompaction coefficient is calculated to obtain a three-dimensional seismic compaction coefficient volume; then, a mathematical relationship between the wave impedance before and after decompaction and the reflection coefficient is established, and then a mathematical relationship between multi-channel seismic records and seismic wavelets and multi-channel wave impedance differences is established; finally, under the constraint of the wave impedance low-frequency component trend, an inversion objective function for the wave impedance after decompaction is established, and a nonlinear inversion method is used to obtain the decompaction-corrected seismic record. The invention is used to correct for the compaction effect of deep-sag reservoirs, thereby improving the prediction accuracy of thin reservoirs, reservoir physical properties, and reservoir oil content in deep-sag reservoirs. It is widely applicable to the exploration of deep oil and gas reservoirs in the quasi-medium-deep layers of western exploration areas and even in the Sinopec exploration areas.

[0088] Example 1:

[0089] In a specific embodiment 1 of the present invention, the seismic reconstruction method based on velocity low-frequency trend modeling of the present invention includes the following steps:

[0090] Step 1: Establish the low-frequency component of logging wave impedance

[0091] The W1 logging wave impedance variation with time in the W1 work area is subjected to generalized S transformation to obtain Figure 2 The wave impedance curve of the well is shown in different frequency band components. It can be seen that the low-frequency energy in the target layer wave impedance range of 0-3Hz represents the formation compaction trend. Therefore, 0-3Hz is selected as the low-frequency component of the target layer of the well to simulate the formation compaction effect. Subtracting the low-frequency component from the original wave impedance can obtain the high-frequency component curve of the wave impedance without compaction, as shown in Figure 3 As shown in the figure, it can be seen that the difference between sand bodies at different depths is not obvious after removing the low-frequency components, and the numerical trends of the sand body wave impedance are consistent.

[0092] Step 2: Establishment of 3D seismic wave impedance low-frequency component data volume

[0093] According to the characteristics of wave impedance value changing with depth, the range of low-frequency component of wave impedance representing reservoir compaction trend in target layer is determined by generalized S transform time-frequency analysis. Then, generalized S inverse transform is used to reconstruct low-frequency component of seismic wave impedance to obtain low-frequency component data of seismic wave impedance. Then, it is corrected by logging low-frequency component. The schematic diagram of low-frequency cross-well section is shown as follows: Figure 4 .

[0094] Step 3: Establishment of the decompaction coefficient of three-dimensional seismic wave impedance

[0095] According to the characteristics of low-frequency wave impedance value due to compaction with depth, the compaction trend line corresponding to the target layer is determined, and then the wave impedance value of the target layer after decompaction is calculated; then the wave impedance compaction coefficient and decompaction coefficient are calculated using the wave impedance values ​​before and after decompaction. The schematic diagram of the target layer plane distribution is shown as follows: Figure 5 .

[0096] Step 4: Decompacting seismic data reconstruction

[0097] The decompaction-corrected seismic impedance is inverted by establishing a low-frequency constrained inversion objective function, and then the decompaction-corrected reflection coefficient is obtained. The seismic wavelet extracted from the wellbore data is used to obtain the decompaction-corrected seismic record through convolution. Figure 6 a is the original seismic profile of the target layer of the wells. The target layers of the three wells are all fine sandstones with similar thickness, but the reflection characteristics are completely different. The difference in phase axis reflection makes it difficult to accurately predict the sand bodies between wells. After the above method, the seismic decompression correction and reconstruction are performed, and the reconstructed profile is shown as follows: Figure 6 b, The reflection amplitude of the target layer sand body near wells W2 and W4 has been enhanced, and the reflection characteristic responses of the target layer sand bodies of the three wells are similar.

[0098] Example 2:

[0099] In a second specific embodiment of the present invention, the seismic reconstruction method based on velocity low-frequency trend modeling of the present invention includes the following steps:

[0100] Step 1: Establish the low-frequency component of logging wave impedance

[0101] The generalized S transformation of the W11 logging impedance over time in the W10 area is obtained. Figure 7 The wave impedance curve of the well is shown in different frequency band components. It can be seen that the low-frequency energy in the target layer wave impedance range of 0-3Hz represents the formation compaction trend. Therefore, 0-3Hz is selected as the low-frequency component of the target layer of the well to simulate the formation compaction effect. Subtracting the low-frequency component from the original wave impedance can obtain the high-frequency component curve of the wave impedance without compaction, as shown in Figure 8 As shown in the figure, it can be seen that the difference between sand bodies at different depths is not obvious after removing the low-frequency components, and the numerical trends of the sand body wave impedance are consistent.

[0102] Step 2: Establishment of 3D seismic wave impedance low-frequency component data volume

[0103] According to the characteristics of wave impedance value changing with depth, the range of low-frequency component of wave impedance representing reservoir compaction trend in target layer is determined by generalized S transform time-frequency analysis. Then, generalized S inverse transform is used to reconstruct low-frequency component of seismic wave impedance to obtain low-frequency component data of seismic wave impedance. Then, it is corrected by logging low-frequency component. The schematic diagram of low-frequency cross-well section is shown as follows: Figure 9 .

[0104] Step 3: Establishment of the decompaction coefficient of three-dimensional seismic wave impedance

[0105] According to the characteristics of low-frequency wave impedance value due to compaction with depth, the compaction trend line corresponding to the target layer is determined, and then the wave impedance value of the target layer after decompaction is calculated; then the wave impedance compaction coefficient and decompaction coefficient are calculated using the wave impedance values ​​before and after decompaction. The schematic diagram of the target layer plane distribution is shown as follows: Figure 10 .

[0106] Step 4: Decompacting seismic data reconstruction

[0107] The decompaction-corrected seismic impedance is inverted by establishing a low-frequency constrained inversion objective function, and then the decompaction-corrected reflection coefficient is obtained. The seismic wavelet extracted from the wellbore data is used to obtain the decompaction-corrected seismic record through convolution. Figure 11 a is the original seismic profile of the target layer of the two wells. The target layers of the two wells are both fine sandstones with similar thickness, but the reflection characteristics are completely different. The difference in phase axis reflection makes it difficult to accurately predict the sand body between the wells. After the above method, the seismic decompression correction and reconstruction are performed, and the reconstructed profile is shown as follows: Figure 11 b, The reflection amplitude of the sand body in the target layer near Well W11 has been improved. The reflection characteristics of the sand bodies in the target layers of the two wells are close, and the amplitude characteristics of the intermediate layer have also been significantly improved.

[0108] In summary, this paper studies a seismic reconstruction method based on velocity low-frequency trend modeling. This method first reconstructs the low-frequency component of the well logging time-domain wave impedance using the generalized S-transform. The low-frequency component of the seismic wave impedance is calculated based on the seismic velocity data volume and the density-velocity fitting relationship. The low-frequency component of the seismic wave impedance is then corrected using the low-frequency component of the well logging data to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume. The compaction trend line corresponding to the target layer segment is determined, and the wave impedance value and wave impedance decompaction coefficient of the target layer after decompaction are calculated to obtain a three-dimensional seismic compaction coefficient volume. A mathematical relationship between the wave impedance and reflection coefficient before and after decompaction is then established, further establishing a mathematical relationship between multi-channel seismic records, seismic wavelets, and multi-channel wave impedance differences. Finally, under the constraint of the low-frequency component trend of the wave impedance, an objective function for the post-decompaction wave impedance inversion is established. A nonlinear inversion method is used to obtain the decompaction-corrected seismic records. The reconstructed seismic data can effectively improve the prediction accuracy of thin reservoirs, reservoir properties, and reservoir oil content in deep-sag reservoirs.

[0109] Beneficial effect: A seismic reconstruction method based on velocity low-frequency trend modeling. This method first reconstructs the low-frequency component of the well logging time domain wave impedance based on the generalized S transform, and calculates the low-frequency component of the seismic wave impedance based on the seismic velocity data volume and the fitting relationship between density and velocity. The low-frequency component of the seismic wave impedance is then corrected using the well logging low-frequency component to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume. The compaction trend line corresponding to the target layer is determined, the wave impedance value of the target layer after decompaction is calculated, and the wave impedance decompaction coefficient is calculated to obtain a three-dimensional seismic compaction coefficient volume. The wave impedance relationship and reflection coefficient mathematical relationship before and after decompaction are then established, and then the mathematical relationship between multi-channel seismic records and seismic wavelets and multi-channel wave impedance differences is established. Finally, under the constraint of the wave impedance low-frequency component trend, the wave impedance inversion objective function after decompaction is established, and the decompaction-corrected seismic records are obtained using a nonlinear inversion method. The reconstructed seismic data effectively improves the prediction accuracy of thin reservoirs, reservoir properties, and reservoir oil content in deep-sag reservoirs.

[0110] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A seismic reconstruction method based on velocity low-frequency trend modeling, characterized in that: The reconstruction method includes: Step S1: convert the logging data into the time domain, perform frequency division processing on the logging wave impedance, and select the low-frequency component that matches the trend as the logging low-frequency component data volume; Step S2: calculating the seismic wave impedance low-frequency component based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and correcting the seismic wave impedance low-frequency component using the well logging low-frequency component data volume to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume; Step S3: determining the compaction trend line corresponding to the target layer segment based on the corrected three-dimensional seismic wave impedance low-frequency component data volume, calculating the wave impedance value of the target layer after decompaction, and calculating the wave impedance decompaction coefficient; Step S4: establishing the wave impedance relationship and the mathematical relationship of the reflection coefficient before and after decompaction, and establishing the mathematical relationship between the multi-channel seismic record and the seismic wavelet and the multi-channel wave impedance difference; Step S5: Under the constraint of the low-frequency component trend of the wave impedance, establish the wave impedance inversion objective function after decompaction, and use the nonlinear inversion method to obtain the compaction-corrected seismic record, including: A low-frequency constraint objective function is established, and the nonlinear inversion method is used to obtain the wave impedance after compaction correction and the reflection coefficient after decompaction correction. Using the seismic wavelet extracted from the wellside data, the decompaction-corrected seismic records are obtained through convolution; The nonlinear inversion method in step S5 adopts the spectral projection gradient algorithm to solve the wave impedance after compaction correction; The step S5 in which the objective function of the wave impedance inversion after decompaction is established specifically includes: The multi-channel impedance inversion problem is expressed as in, w is the row vector of the wavelet time series, X low is the low-frequency component of wave impedance, obtained from logging wave impedance or seismic velocity spectrum; L is the low-pass filter operator; Y is the known multi-channel seismic record, The inverted reflection coefficient time series is sparse and laterally smooth; The synthetic earthquake record is consistent with the actual earthquake record; X low =LX is the trend constraint of the low-frequency component of wave impedance; The step S5 of establishing the wave impedance inversion objective function after decompaction also includes: The wave impedance inversion problem after decompaction is expressed as Where C is the matrix composed of compaction coefficients; The semi-logarithm of the wave impedance after decompaction is obtained by inversion c .

2. The seismic reconstruction method based on velocity low-frequency trend modeling according to claim 1, characterized in that: The step S1: converting the logging data into the time domain, performing frequency division processing on the logging wave impedance, and selecting the low-frequency component that matches the trend as the logging low-frequency component data body specifically includes: The time domain logging impedance data volume is calculated from the logging data. The generalized S-transform time-frequency spectrum analysis is used to determine the low-frequency component range of the impedance representing the reservoir compaction trend in the target well section. The low-frequency component of logging wave impedance is reconstructed by using generalized inverse S-transform to obtain the low-frequency component of logging wave impedance in time domain.

3. The seismic reconstruction method based on velocity low-frequency trend modeling according to claim 1, characterized in that: The step S2: calculating the low-frequency component of seismic wave impedance based on the seismic velocity data volume and the fitting relationship between well logging density and velocity, and correcting the seismic wave impedance component using the well logging low-frequency component to obtain the corrected three-dimensional seismic wave impedance low-frequency component data volume specifically includes: Based on the seismic migration velocity data and the interpreted main target layer data, the layer-controlled multi-constrained layer velocity inversion MCVI method is used to calculate the seismic layer velocity; Analyze the intersection diagram of target layer logging velocity and logging density to obtain the density and velocity fitting formula, and apply it to convert the seismic layer velocity into formation density and calculate the seismic wave impedance body; Use generalized S-transform to obtain low-frequency wave impedance body; The low-frequency component of the logging wave impedance is used for correction to obtain a corrected three-dimensional seismic wave impedance low-frequency component data volume.

4. The seismic reconstruction method based on velocity low-frequency trend modeling according to claim 1, characterized in that: The step S3: determining the compaction trend line corresponding to the target layer segment based on the corrected three-dimensional spatial seismic wave impedance low-frequency component data volume, and calculating the wave impedance value of the target layer after decompaction. Calculating the wave impedance decompaction coefficient specifically includes: According to the characteristics of low-frequency wave impedance value changing with depth due to compaction, the compaction trend line corresponding to the target layer is determined, and the wave impedance value of the target layer after decompaction is calculated; The wave impedance compaction coefficient is calculated using the wave impedance values ​​before and after decompaction, and the target layer logging and three-dimensional wave impedance compaction coefficient variation curve with depth are obtained.

5. The seismic reconstruction method based on velocity low-frequency trend modeling according to claim 1, characterized in that: In step S3, the difference between the wellbore seismic wave impedance compaction coefficient and the logging wave impedance decompaction coefficient is calculated, and the layer-controlled seismic wave impedance compaction coefficient error data volume is established by using the Kriging interpolation correction technology in combination with the interpretation layer; The seismic wave impedance compaction coefficient is corrected to obtain a corrected three-dimensional seismic wave impedance compaction coefficient data volume.

6. The seismic reconstruction method based on velocity low-frequency trend modeling according to claim 1, characterized in that: The step S4: establishing the wave impedance relationship and the mathematical relationship of the reflection coefficient before and after decompaction, and establishing the mathematical relationship between the multi-channel seismic record and the seismic wavelet and the multi-channel wave impedance difference specifically includes: According to the nonlinear relationship between reflection coefficient and wave impedance and the differential operator, the relationship between reflection coefficient, multi-channel wave impedance difference and seismic records is established.

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