Improvement method of seismic velocity and imaging update based on well-seismic matching deviation correction

Abstract

The present invention relates to the field of seismic exploration, and discloses a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction, the method comprising: making synthetic seismic according to acquired logging data; calculating well-seismic matching deviation according to synthetic seismic and wellside seismic traces acquired at logging location; updating seismic velocity at logging location according to matching deviation; performing differential extrapolation of seismic velocity according to calculated seismic attributes to generate seismic velocity body; performing seismic offset imaging using seismic velocity body to obtain updated seismic imaging; calculating correlation coefficient between seismic traces of updated seismic imaging and synthetic seismic; judging whether coefficient is greater than a set threshold value, if coefficient is greater than the set threshold value, completing updating of velocity and imaging; if coefficient is not greater than the set threshold value, performing the above steps again until coefficient is greater than the set threshold value. The present invention has high computational efficiency, and can efficiently complete updating of seismic velocity and imaging even when seismic work area is large.

Description

Technical Field

[0001] The present invention relates to the field of seismic exploration, and in particular to a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction. Background Art

[0002] Seismic exploration is one of the important means of oil and gas exploration, and imaging is an important part of seismic data processing. Its purpose is to return seismic waves to the underground location where they are generated. Accurate imaging will provide guidance for reservoir prediction and subsequent oilfield development. The quality of migration imaging depends largely on the accuracy of the seismic velocity model. An accurate seismic velocity model can better realize the return of imaging points and provide accurate underground information for subsequent seismic interpretation and other steps.

[0003] Commonly used seismic velocity update methods include velocity analysis, residual curvature analysis, tomographic velocity inversion, and full waveform inversion. The results of velocity analysis are of low accuracy, residual curvature analysis cannot effectively combine well data, tomographic velocity inversion is sensitive to the accuracy of the initial model, and full waveform inversion has problems such as excessive calculation, instability, and dependence on the initial model. Therefore, the existing methods have at least the following problems:

[0004] 1. Over-reliance on the initial model. If the initial velocity model is inaccurate, it may cause a large deviation in the updated velocity model.

[0005] 2. The amount of calculation is large, and the velocity model update may take a long time when the earthquake area is large. Summary of the invention

[0006] The purpose of the present invention is to provide a seismic velocity and imaging update improvement method based on well-seismic matching deviation correction to solve the problems of existing methods such as excessive calculation, instability, and dependence on initial models.

[0007] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction, the method comprising:

[0008] Produce synthetic seismic based on acquired well logging data;

[0009] Calculate the well-seismic matching deviation based on the synthetic seismic and the well-near seismic traces obtained at the well logging location;

[0010] updating the seismic velocity at the well logging location according to the matching deviation;

[0011] The seismic velocity is differentially extrapolated according to the calculated seismic attributes to generate a seismic velocity volume;

[0012] Using seismic velocity bodies to perform seismic migration imaging to obtain updated seismic imaging;

[0013] Calculating the coefficient between the seismic trace of the updated seismic imaging and the synthetic seismic;

[0014] Determine whether the coefficient is greater than the set threshold. If the coefficient is greater than the set threshold, complete the update of velocity and imaging; if the coefficient is not greater than the set threshold, execute again: calculate the well-seismic matching deviation based on the synthetic seismic and the wellside seismic traces obtained at the logging location; update the seismic velocity at the logging location based on the matching deviation; perform differential extrapolation of the seismic velocity based on the calculated seismic attributes to generate a seismic velocity body; use the seismic velocity body to perform seismic migration imaging to obtain updated seismic imaging; calculate the coefficient between the seismic trace of the updated seismic imaging and the synthetic seismic.

[0015] Preferably, before producing synthetic seismic data based on the acquired well logging data, the method further comprises: preprocessing the well logging data, wherein the preprocessing comprises performing wellbore environment correction processing and digital filtering processing on the well logging data.

[0016] Preferably, the logging data includes density logging data and sonic logging data.

[0017] Preferably, producing synthetic seismic data based on the acquired well logging data includes:

[0018] Calculate the logging P-wave velocity based on the sonic logging data;

[0019] Calculate reflection coefficient based on well logging P-wave velocity and density logging data;

[0020] The reflection coefficient is converted from the depth domain to the time domain according to the logging P-wave velocity, and the seismic wavelet and the reflection coefficient in the time domain are selected;

[0021] Based on the one-dimensional convolution model, the seismic wavelet and reflection coefficient in the time domain are simulated and forward modeled to obtain synthetic earthquakes.

[0022] Preferably, calculating the well-seismic matching deviation based on the synthetic seismic and the acquired wellside seismic trace at the well logging location includes:

[0023] Extract the seismic traces near the well according to the well location coordinates of the logging;

[0024] Construct a cumulative error table based on wellside seismic traces and synthetic seismic;

[0025] The accumulated error table is scanned based on the dynamic regression algorithm to obtain the well-seismic matching deviation.

[0026] Preferably, updating the offset velocity at the logging location according to the matching deviation comprises:

[0027] Constructing initial depth relationships for well logging based on sonic logging data;

[0028] The synthetic seismic is corrected according to the well-seismic matching deviation to obtain a new depth relationship;

[0029] Calculate updated logging velocity based on new depth relationship;

[0030] The seismic velocity is updated according to the updated logging velocity.

[0031] Preferably, performing differential extrapolation on the seismic velocity according to the calculated seismic attributes to generate a seismic velocity volume comprises:

[0032] Extract dip volume data from seismic imaging based on dip algorithm;

[0033] The seismic velocity is interpolated and extrapolated according to the dip volume data to obtain the seismic velocity volume.

[0034] Preferably, calculating the well-seismic matching deviation based on the synthetic seismic and the acquired wellside seismic trace at the well logging location includes:

[0035] Extract the seismic traces near the well according to the well location coordinates of the logging;

[0036] Calculate the similarity energy spectrum between the wellbore seismic trace and the synthetic seismic trace based on the local similarity attribute algorithm;

[0037] Pick up strong energy points in the similarity energy spectrum;

[0038] Calculate the well-seismic matching deviation based on the strong energy points.

[0039] The present invention also provides a seismic velocity and imaging updating and improving device based on well-seismic matching deviation correction, the device is used to implement the above-mentioned seismic velocity and imaging updating and improving method based on well-seismic matching deviation correction, the device comprises:

[0040] A production module for producing synthetic seismic data based on the acquired logging data;

[0041] The first calculation module is used to calculate the well-seismic matching deviation based on the synthetic seismic and the acquired wellside seismic trace at the well logging location;

[0042] A first updating module, used for updating the seismic velocity at the logging location according to the matching deviation;

[0043] The second updating module is used for performing differential extrapolation of seismic velocity according to the calculated seismic attributes to generate a seismic velocity volume;

[0044] A third updating module is used to perform seismic migration imaging using the seismic velocity body to obtain updated seismic imaging;

[0045] A second calculation module is used to calculate the correlation coefficient between the updated seismic imaging seismic trace and the synthetic seismic;

[0046] The judgment module is used to judge whether the coefficient is greater than a set threshold.

[0047] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the above-mentioned seismic velocity and imaging update improvement method based on well-seismic matching deviation correction is implemented.

[0048] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned seismic velocity and imaging update improvement method based on well-seismic matching deviation correction is implemented.

[0049] The beneficial effects of the present invention are mainly embodied in:

[0050] 1. The improved seismic velocity and imaging update method based on well-seismic matching deviation correction proposed in the present invention can perform velocity update without over-reliance on the initial model, and the velocity update result is relatively accurate, providing an accurate seismic velocity model for subsequent imaging updates.

[0051] 2. The velocity and imaging update and improvement method based on well-seismic matching deviation proposed in the present invention has high computational efficiency and can efficiently complete the velocity model and imaging update and improvement even when the seismic work area is large.

[0052] 3. The velocity and imaging update and improvement method based on well-seismic matching deviation proposed in the present invention can perform real-time velocity and imaging update and improvement as logging data increases. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction provided by a first embodiment of the present invention;

[0054] Figure 2 is the expected speed model provided by the first embodiment of the present invention;

[0055] Figure 3 is an initial seismic velocity model provided by the first embodiment of the present invention;

[0056] Figure 4 It is a display of the wellside seismic trace and the synthetic seismic trace provided by the first embodiment of the present invention;

[0057] Figure 5 The first embodiment of the present invention provides the establishment of the cumulative error table D and the well-seismic matching deviation;

[0058] Figure 6 It is a diagram of the time-depth relationship before and after updating at the logging point provided by the first embodiment of the present invention;

[0059] Figure 7 It is a comparison diagram of the updated logging velocity, the seismic velocity at the logging point before the update, and the seismic velocity at the logging point after the update provided by the first embodiment of the present invention;

[0060] Figure 8 is a seismic velocity model obtained after the first round of velocity update provided by the first embodiment of the present invention;

[0061] Fig. 9 is a seismic velocity model obtained after the second round of velocity update provided by the first embodiment of the present invention;

[0062] Fig.10 The similarity energy spectrum and well-seismic matching deviation provided by the second embodiment of the present invention;

[0063] Fig.11 It is a block diagram of a seismic velocity and imaging updating and improving device based on well-seismic matching deviation correction provided by a third embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0065] Embodiment 1

[0066] Figure 1 is a flow chart of a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction provided by an embodiment of the present invention, such as Figure 1 As shown, a method for improving seismic velocity and imaging update based on well-seismic matching deviation correction, the method comprising:

[0067] Step S101: Produce synthetic seismic data based on the acquired well logging data;

[0068] In this embodiment, Figure 2 It is the expected velocity model, that is, the model we hope to obtain under ideal conditions; Figure 3 It is an existing initial seismic velocity model, and a channel is extracted from the expected velocity model as the acoustic logging data.

[0069] As a further optimization of this embodiment, before producing synthetic seismic data based on the acquired logging data, the method also includes: preprocessing the logging data, the preprocessing including performing borehole environment correction processing and digital filtering processing on the logging data; in this embodiment, performing borehole environment correction processing on the logging data can reduce the impact of environmental factors such as wellbore collapse and diameter expansion on the logging data; performing digital filtering processing on the logging data can remove abnormal values ​​and burr-like interference in the logging data, wherein the logging data includes density logging data and acoustic logging data.

[0070] In an embodiment of the present invention, synthetic seismic is produced based on the acquired well logging data, including:

[0071] Step a01: Calculate the logging longitudinal wave velocity according to the acoustic logging data;

[0072]

[0073] Among them, DT i (z) represents the acoustic logging data of the i-th well, in us / m; v i (z) represents the logging longitudinal wave velocity of the ith well calculated using the acoustic logging data, in m / s; z is the depth value.

[0074] Step a02: Calculate the reflection coefficient based on the logging P-wave velocity and density logging data;

[0075]

[0076] Among them, r i (z) represents the reflection coefficient in the depth domain of the i-th well; Represents the density logging data of the i-th well.

[0077] Step a03: Convert the reflection coefficient from the depth domain to the time domain according to the logging longitudinal wave velocity, and select the seismic wavelet and reflection coefficient in the time domain, that is, select the appropriate seismic wavelet and reflection coefficient.

[0078] Step a04: Based on the one-dimensional convolution model, the seismic wavelet and reflection coefficient in the time domain are simulated and forward modeled to obtain synthetic earthquakes.

[0079] W i (t) = r i (t)*ω(t);

[0080] Among them, W i (t) represents the synthetic seismic of the i-th well; ω(t) represents the seismic wavelet in the time domain; r i (t) represents the reflection coefficient in the time domain; * represents the convolution operation; t represents the time value.

[0081] Step S102: Calculating the well-seismic matching deviation based on the synthetic seismic and the acquired well-nearby seismic traces at the well logging location;

[0082] Specifically, the wellbore-seismic matching deviation is calculated based on the synthetic seismic and the acquired wellbore seismic traces at the well logging location, including:

[0083] Step b01: Extract the seismic traces near the well according to the well location coordinates, denoted as S(t), such as Figure 4 As shown;

[0084] Step b02: constructing a cumulative error table based on wellside seismic traces and synthetic seismic data;

[0085] E t,l =|S i (t+l)-W i (t)| 2 ;

[0086] Wherein, E represents the Euclidean distance error table established by the wellside seismic trace and the synthetic seismic trace. The error table is a two-dimensional array with 2L+1 rows and T columns, that is, l = -L, ..., -1, 0, 1, ..., L, t = 1, ..., T; E t,l Indicates the value of row l and column t

[0087] Dynamic regularization is used to achieve the optimal iterative accumulation of the Euclidean distance error table E, and the cumulative error table D is established, such as Figure 5 As shown, the algorithm is as follows:

[0088]

[0089] Where D represents the cumulative error table established by the wellside seismic traces and the synthetic seismic traces. The error table is a two-dimensional array with 2L+1 rows and T columns, that is, l = -L, ..., -1, 0, 1, ..., L, t = 1, ..., T; D t,l Represents the value of the lth row and tth column; b is a constraint parameter, which is determined based on the actual data volume and is not greater than T.

[0090] Step b03: Scan the accumulated error table based on a dynamic regression algorithm to obtain the well-seismic matching deviation.

[0091] In this embodiment, the well-seismic matching deviation is e={e1,...,e T}, Figure 5 The curve in represents the well-seismic matching deviation; the dynamic regression algorithm is:

[0092] e T =argmin l (D T,L )#

[0093]

[0094] Step S103: updating the seismic velocity at the logging location according to the matching deviation;

[0095] Specifically, the seismic velocity at the well logging location is updated according to the matching deviation, including:

[0096] Step c01: constructing an initial depth relationship of well logging based on acoustic logging data;

[0097]

[0098] Where TDR(z) is the initial time-depth relationship of the well log; z min 、z max are the starting and ending depths of the sonic logging data; dz represents the sampling interval of the sonic time difference logging data; v(z) represents the velocity calculated using the sonic time difference logging data, in m / s; z is the depth value.

[0099] Step c02: Correct the synthetic seismic according to the well-seismic matching deviation to obtain a new depth relationship;

[0100]

[0101] in, is the new depth relationship after the update of the i-th well logging, such as Figure 6 shown.

[0102] Step c03: Calculate updated logging speed according to the new depth relationship;

[0103]

[0104] in, is the updated logging speed of the i-th well.

[0105] Step c04: Update the seismic velocity according to the updated logging velocity.

[0106]

[0107] in, is the updated seismic velocity at the logging location; vseis(z) is the seismic velocity before the logging location is updated, such as Figure 7 shown.

[0108] Step S104: performing differential extrapolation on the seismic velocity according to the calculated seismic attributes to generate a seismic velocity volume;

[0109] In this embodiment, the seismic attribute may adopt dip volume data; specifically, the seismic velocity is differentially extrapolated according to the calculated seismic attribute to generate a seismic velocity volume, including:

[0110] Step d01: extracting dip volume data from seismic imaging based on a dip algorithm;

[0111] Step d02: Interpolate and extrapolate the seismic velocity based on the dip volume data to obtain the seismic velocity volume, such as Figure 8 shown.

[0112] Step S105: performing seismic migration imaging using the seismic velocity volume to obtain updated seismic imaging;

[0113] Step S106: Calculate the correlation coefficient between the updated seismic imaging seismic trace and the synthetic seismic;

[0114] Step S107: Determine whether the coefficient is greater than a set threshold; if the coefficient is greater than the set threshold, complete the speed and imaging update; if the coefficient is not greater than the set threshold, the threshold can be set according to actual needs, and steps S102 to S106 are executed again until the coefficient is greater than the set threshold. Fig. 9 shown.

[0115] The present invention can perform velocity updates without over-reliance on the initial model, and the velocity update results are relatively accurate, providing an accurate velocity model for subsequent imaging updates. The present invention also has high computational efficiency, and can efficiently complete velocity model and imaging updates and improvements even when the seismic work area is large. And with the increase of logging data, real-time velocity and imaging updates can be performed.

[0116] Embodiment 2

[0117] The difference between this embodiment and the first embodiment is that the wellbore-seismic matching deviation is calculated based on the synthetic seismic and the acquired wellside seismic trace at the well logging location, including:

[0118] Step B01: extracting the seismic traces near the well according to the well location coordinates of the well logging;

[0119] Step B02: Calculate the similarity energy spectrum between the wellbore seismic trace and the synthetic seismic trace based on the local similarity attribute algorithm;

[0120] Step B03: picking up strong energy points in the similarity energy spectrum;

[0121] Step B04: Calculate the well-seismic matching deviation based on the strong energy points; in this embodiment, the well-seismic matching deviation e between the wellside seismic trace and the synthetic seismic can be obtained, such as Fig.10 shown.

[0122] Embodiment 3

[0123] Fig.11 is a block diagram of a seismic velocity and imaging updating and improving device based on well-seismic matching deviation correction provided by a third embodiment of the present invention, such as Fig.11 As shown, a velocity and imaging update improvement device based on well-seismic matching deviation is used to implement the velocity and imaging update improvement method based on well-seismic matching deviation, and the device includes:

[0124] A production module for producing synthetic seismic data based on the acquired logging data;

[0125] The first calculation module is used to calculate the well-seismic matching deviation based on the synthetic seismic and the acquired wellside seismic trace at the well logging location;

[0126] A first updating module, used for updating the seismic velocity at the logging location according to the matching deviation;

[0127] The second updating module is used for performing differential extrapolation of seismic velocity according to the calculated seismic attributes to generate a seismic velocity volume;

[0128] A third updating module is used to perform seismic migration imaging using the seismic velocity body to obtain updated seismic imaging;

[0129] A second calculation module is used to calculate the correlation coefficient between the updated seismic imaging seismic trace and the synthetic seismic;

[0130] The judgment module is used to judge whether the coefficient is greater than a set threshold.

[0131] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the above-mentioned seismic velocity and imaging update improvement method based on well-seismic matching deviation correction is implemented.

[0132] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned seismic velocity and imaging update improvement method based on well-seismic matching deviation correction is implemented.

[0133] The optional implementation modes of the embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above implementation modes. Within the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical scheme of the embodiments of the present invention, and these simple modifications all belong to the protection scope of the embodiments of the present invention.

[0134] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0135] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including a number of instructions to enable a single-chip microcomputer, a chip or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0136] In addition, various implementation modes of the embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed by the embodiments of the present invention.

Claims

1. A method for improving seismic velocity and imaging update based on well-seismic matching deviation correction, characterized in that: The method comprises: Producing synthetic seismic according to the acquired well logging data, wherein the well logging data includes density logging data and sonic logging data; Calculate the well-seismic matching deviation based on the synthetic seismic and the well-side seismic traces obtained at the well logging location; Update the seismic velocity at the logging location according to the well-seismic matching deviation, including: Constructing initial depth relationships for well logging based on sonic logging data; The synthetic seismic is corrected according to the well-seismic matching deviation to obtain a new depth relationship; Calculate updated logging velocity based on new depth relationship; updating the seismic velocity according to the updated logging velocity; The seismic velocity is extrapolated based on the calculated seismic attributes to generate a seismic velocity volume, including: Extract dip volume data from seismic imaging based on dip algorithm; The seismic velocity is interpolated and extrapolated according to the dip volume data to obtain the seismic velocity volume; Using seismic velocity volume to perform seismic migration imaging to obtain updated seismic imaging; Calculate the correlation coefficient between the updated seismic imaging trace and the synthetic earthquake; Determine whether the coefficient is greater than the set threshold. If the coefficient is greater than the set threshold, complete the update of velocity and imaging; if the coefficient is not greater than the set threshold, execute again: calculate the well-seismic matching deviation based on the synthetic seismic and the wellside seismic traces obtained at the logging location; update the seismic velocity at the logging location based on the well-seismic matching deviation; perform differential extrapolation of the seismic velocity based on the calculated seismic attributes to generate a seismic velocity body; use the seismic velocity body to perform seismic migration imaging to obtain updated seismic imaging; calculate the coefficient between the seismic trace of the updated seismic imaging and the synthetic seismic.

2. The method for improving seismic velocity and imaging update based on well-seismic matching deviation correction according to claim 1, characterized in that: Before producing synthetic seismic data according to the acquired well logging data, the method further comprises: preprocessing the well logging data, wherein the preprocessing comprises performing wellbore environment correction processing and digital filtering processing on the well logging data.

3. The method for improving seismic velocity and imaging update based on well-seismic matching deviation correction according to claim 1, characterized in that: Synthetic seismic is produced based on the acquired well logging data, including: Calculate the logging P-wave velocity based on the sonic logging data; Calculate reflection coefficient based on well logging P-wave velocity and density logging data; The reflection coefficient is converted from the depth domain to the time domain according to the logging P-wave velocity, and the seismic wavelet and the reflection coefficient in the time domain are selected; Based on the one-dimensional convolution model, the seismic wavelet and reflection coefficient in the time domain are simulated and forward modeled to obtain synthetic earthquakes.

4. The method for improving seismic velocity and imaging update based on well-seismic matching deviation correction according to claim 1, characterized in that: The wellbore-seismic matching deviation is calculated based on the synthetic seismic and the wellbore seismic traces obtained at the well logging location, including: Extract the seismic traces near the well according to the well location coordinates of the logging; Construct a cumulative error table based on wellside seismic traces and synthetic seismic; The accumulated error table is scanned based on the dynamic regression algorithm to obtain the well-seismic matching deviation.

5. The method for improving seismic velocity and imaging update based on well-seismic matching deviation correction according to claim 1, characterized in that: The wellbore-seismic matching deviation is calculated based on the synthetic seismic and the wellbore seismic traces obtained at the well logging location, including: Extract the seismic traces near the well according to the well location coordinates of the logging; Calculate the similarity energy spectrum between the wellbore seismic trace and the synthetic seismic trace based on the local similarity attribute algorithm; Pick up strong energy points in the similarity energy spectrum; Calculate the well-seismic matching deviation based on the strong energy points.

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