CN108802811A - A kind of normal-moveout spectrum automatic pick method and device - Google Patents
A kind of normal-moveout spectrum automatic pick method and device Download PDFInfo
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Abstract
Disclose a kind of normal-moveout spectrum automatic pick method and device.This approach includes the following steps：1) seismic channel set data calculating speed is based on to compose；2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and records the maximum similarity factor value and corresponding sampling time and sweep speed value；3) global maximum similarity factor point is searched；4) the local maxima similarity factor point on All Time sampled point is picked up；5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.The present invention realizes the automatic calculating of velocity pick process, avoids a large amount of artificial pick-up operation, significantly improves the treatment effeciency of velocity analysis, improve the effect of normal-moveout spectrum automatic Picking.
Description
Technical field
The present invention relates to the data processing techniques of field of seismic exploration, more particularly, to a kind of normal-moveout spectrum automatic Picking
Method and device.
Background technology
During Seismic Exploration Data Processing, link centered on the rate pattern on accurate stratum is obtained, is directly affected folded
Sum it up the effect of migration imaging.The acquisition process of seismic velocity model is divided into three steps, and the first step is normal-moveout spectrum, and second step is speed
The pickup of time pair, third step are the foundation of rate pattern.The pick process of wherein Velocity Time pair is by normal-moveout spectrum
Similarity factor energy group identification process, this process is usually by manually picking up realization.Although manually pickup resolving ability
By force, but working efficiency is low, time-consuming huge, and with being continuously increased for D seismic data processing scale, manually pickup is fast
Degree spectrum is difficult to meet the needs of actual production, how to improve a large amount of normal-moveout spectrum pickup efficiency in process of seismic data processing and has become
The main reason for influence seism processing job schedule.
The main target of normal-moveout spectrum pickup is maximum of points corresponding time and the speed of pickup velocity spectrum energy group, according to
The normal-moveout spectrum Energy maximum value method found on corresponding time depth is usually taken in this purpose, auto-speed spectrum pickup.Directly
The effect of maximizing normal-moveout spectrum pick-up method be difficult meet process demand, therefore usually utilize when window control method, limit
Local maximum is picked up in certain a period of time window.For the abnormal speed point in normal-moveout spectrum automatic Picking, by various restrictive conditions,
Such as according to velocity variations rule, control speed reversion removes the methods of velocity anomaly value, improves the effect of velocity pick.
The information for being disclosed in background of invention part is merely intended to deepen the reason of the general background technology to the present invention
Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form
Technology.
Invention content
It is an object of the invention to solve above-mentioned problem existing in the prior art, it is proposed that a kind of normal-moveout spectrum automatic Picking
Method and device, the shortcomings that existing evaluation method can be overcome and deficiency.The present invention according to the variation characteristic of normal-moveout spectrum energy group,
On the method basis of direct search ceiling capacity group, a set of normal-moveout spectrum energy group automatic search method is designed, speed is realized
The automatic Picking of spectrum is spent, and constraints is set by velocity variations rule, velocity anomaly value is removed, realizes efficiently and accurately
Normal-moveout spectrum automatic pickup function.
According to an aspect of the invention, it is proposed that a kind of normal-moveout spectrum automatic pick method.This method may comprise steps of：
1) seismic channel set data calculating speed is based on to compose；
2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and remembered
Record the maximum similarity factor value and corresponding sampling time and sweep speed value；
3) global maximum similarity factor point is searched；
4) the local maxima similarity factor point on All Time sampled point is picked up；
5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.
Preferably, step 1) includes based on seismic channel set data calculating speed spectrum：The minimum sweep speed of setting, velocity scanning
Interval and velocity scanning line number, scan the dynamic correction of all speed as a result, being moved to friction speed since minimum sweep speed
It corrects result and carries out cross-correlation calculation to obtain the similarity factor value of friction speed.
Preferably, the normal-moveout spectrum automatic pick method further includes：Remove abnormal speed pickup point, wherein the exception
Velocity pick point refers to：Using the speed of automatic Picking to data as target, according to the changing rule of adjacent spot speed, from global phase
Start like energy maximum point, it is described to check whether the speed at consecutive number strong point meets to time increase and time reduction direction respectively
The changing rule of adjacent spot speed is abnormal speed pickup point if being unsatisfactory for.
Preferably, the changing rule of the adjacent spot speed is indicated with following formula：
t1、t2Indicate two sampling time points, t1<t2, v1Indicate sampling time point t1Corresponding speed, v2When indicating sampling
Between point t2Corresponding speed, vminIndicate minimum speed value, vmaxIndicate maximum speed value.
Preferably, the local maxima similarity factor point on step 4) pickup All Time sampled point includes following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as mesh
Mark reduces direction finding similarity factor to time augment direction and time respectively and successively decreases and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, similarity factor is become incremental from successively decreasing
Inflection point is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as
One effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing All Time sampled point
On local maximum point pickup.
Preferably, step 5) includes：On the basis of the pickup result data that step 4) obtains, using least square method curve
Approximating method carries out conic fitting to data to the speed having picked up, obtains matched curve function；When minimum is sampled
Between and the maximum sampling time substitute into the matched curve function respectively, obtain the velocity amplitude of minimal sampling time point and maximum sample
Time point velocity amplitude.
According to another aspect of the invention, it is proposed that a kind of normal-moveout spectrum picks out device automatically.The device includes memory, processing
Device and storage are on a memory and the computer program that can run on a processor, which is characterized in that the processor execution
Following steps are realized when described program：
1) seismic channel set data calculating speed is based on to compose；
2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and remembered
Record the maximum similarity factor value and corresponding sampling time and sweep speed value；
3) global maximum similarity factor point is searched；
4) the local maxima similarity factor point on All Time sampled point is picked up；
5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.
Preferably, step 1) includes based on seismic channel set data calculating speed spectrum：The minimum sweep speed of setting, velocity scanning
Interval and velocity scanning line number, scan the dynamic correction of all speed as a result, being moved to friction speed since minimum sweep speed
It corrects result and carries out cross-correlation calculation to obtain the similarity factor value of friction speed.
Preferably, following steps are also realized when the processor executes described program：Abnormal speed pickup point is removed,
In, the abnormal speed pickup point refers to：Using the speed of automatic Picking to data as target, according to the variation of adjacent spot speed advise
Rule increases to the time since global similar energies maximum point and the time reduces the speed that direction checks consecutive number strong point respectively
The changing rule for whether meeting the adjacent spot speed is abnormal speed pickup point if being unsatisfactory for.
Preferably, the local maxima similarity factor point on step 4) pickup All Time sampled point includes following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as mesh
Mark reduces direction finding similarity factor to time augment direction and time respectively and successively decreases and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, similarity factor is become incremental from successively decreasing
Inflection point is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as
One effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing All Time sampled point
On local maximum point pickup.
The present invention proposes a kind of efficient normal-moveout spectrum automatic pick method and device and normal-moveout spectrum constraints, realizes
The automatic calculating of velocity pick process avoids a large amount of artificial pick-up operation, significantly improves the processing effect of velocity analysis
Rate improves the effect of normal-moveout spectrum automatic Picking, and the normal-moveout spectrum that a set of precise and high efficiency is provided for seismic data process picks up automatically
Take scheme.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages attached from what is be incorporated herein
It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing and subsequent specific implementation being incorporated herein
It is stated in detail in example, these the drawings and specific embodiments are used together to explain the specific principle of the present invention.
Description of the drawings
Exemplary embodiment of the present is described in more detail in conjunction with the accompanying drawings, of the invention is above-mentioned and other
Purpose, feature and advantage will be apparent, wherein in exemplary embodiments of the present invention, identical reference label is usual
Represent same parts.
Fig. 1 is the flow chart for picking out method automatically according to the normal-moveout spectrum of the exemplary implementation scheme of the present invention.
Fig. 2 a are the pickup result figure of the speed pair on normal-moveout spectrum, and Fig. 2 b are seismic traces collection data corresponding with Fig. 2 a
Figure, Fig. 2 c be according to the pickup point velocity amplitude in Fig. 2 a to original trace gather into action correction process after result.
Specific implementation mode
The present invention is more fully described below with reference to accompanying drawings.Although showing the preferred embodiment of the present invention in attached drawing,
However, it is to be appreciated that may be realized in various forms the present invention without should be limited by embodiments set forth here.On the contrary, providing
These embodiments are of the invention more thorough and complete in order to make, and can will fully convey the scope of the invention to ability
The technical staff in domain.
Normal-moveout spectrum automatic pick method according to an exemplary embodiment of the present invention is described in detail below with reference to Fig. 1.
This method may comprise steps of：
Step 1：It is composed based on seismic channel set data calculating speed.
The minimum sweep speed of setting, velocity scanning interval and velocity scanning line number, using dynamic correction processing method, from minimum
Sweep speed starts, and according to the speed interval of setting, scans the dynamic correction of all speed as a result, dynamic correction knot to friction speed
Fruit carries out cross-correlation calculation, obtains similarity factor, that is, speed modal data of friction speed scanning.
Normal-moveout correction (Normally MoveOut) is also named in dynamic correction, abbreviation NMO, for correct in earthquake record by
The time difference caused by offset distance difference.
Step 2：The maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1 is calculated,
And record the maximum similarity factor value and corresponding sampling time and sweep speed value.
According to speed modal data, maximum similar system on each sampled point is searched in the initial time to termination time of sampling
Number, and record maximum similarity factor value and corresponding sampling time and sweep speed value.
Step 3：Search global maximum similarity factor point.
On the basis of maximum similarity factor on each time sampling interval of acquisition, global maximum similar system is searched
Numerical value corresponding sampling time and sweep speed value.
Step 4：Pick up the local maxima similarity factor point on All Time sampled point.
Step 4) may include following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as mesh
Mark reduces direction finding similarity factor to time augment direction and time respectively and successively decreases and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, similarity factor is become incremental from successively decreasing
Inflection point is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as
One effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing All Time sampled point
On local maximum point pickup.
Step 5：Supplement the velocity amplitude of the velocity amplitude and maximum time sampled point of minimum time sampled point.
On the basis of the pickup result data that step 4) obtains, using least square curve fit method, to having picked up
The speed taken carries out conic fitting to data, obtains matched curve function；By minimal sampling time and maximum sampling time
The matched curve function is substituted into respectively, obtains the velocity amplitude of minimal sampling time point and maximum sampling time spot speed angle value.
This method can also include：Remove abnormal speed pickup point.
The abnormal speed pickup point refers to：Using the speed of automatic Picking to data as target, according to adjacent spot speed
Changing rule increases to the time since global similar energies maximum point and the time reduces direction and checks consecutive number strong point respectively
Speed whether meet the changing rule of the adjacent spot speed, be abnormal speed pickup point if being unsatisfactory for.
In an exemplary embodiment, the changing rule of the adjacent spot speed is indicated with following formula：
t1、t2Indicate two sampling time points, t1<t2, v1Indicate sampling time point t1Corresponding speed, v2When indicating sampling
Between point t2Corresponding speed, vminIndicate minimum speed value, vmaxIndicate maximum speed value.
Normal-moveout spectrum in accordance with an exemplary embodiment of the invention picks out device and includes memory, processor and deposit automatically
Store up the computer program that can be run on a memory and on a processor.The processor realizes following step when executing described program
Suddenly：
1) seismic channel set data calculating speed is based on to compose；
2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and remembered
Record the maximum similarity factor value and corresponding sampling time and sweep speed value；
3) global maximum similarity factor point is searched；
4) the local maxima similarity factor point on All Time sampled point is picked up；
5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.
In an exemplary embodiment, step 1) includes based on seismic channel set data calculating speed spectrum：
The minimum sweep speed of setting, velocity scanning interval and velocity scanning line number, scan institute since minimum sweep speed
There is the dynamic correction of speed as a result, carrying out cross-correlation calculation to the dynamic correction result of friction speed to obtain the similar system of friction speed
Numerical value.
In an exemplary embodiment, following steps are also realized when the processor executes described program：Removal is abnormal fast
Spend pickup point, wherein the abnormal speed pickup point refers to：Using the speed of automatic Picking to data as target, according to consecutive points
The changing rule of speed increases to the time since global similar energies maximum point and time reduction direction inspection is adjacent respectively
Whether the speed of data point meets the changing rule of the adjacent spot speed, is abnormal speed pickup point if being unsatisfactory for.
In an exemplary embodiment, the local maxima similarity factor point on step 4) pickup All Time sampled point includes
Following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as mesh
Mark reduces direction finding similarity factor to time augment direction and time respectively and successively decreases and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, similarity factor is become incremental from successively decreasing
Inflection point is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as
One effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing All Time sampled point
On local maximum point pickup.
The present invention utilizes the changing rule of normal-moveout spectrum energy group, devises a set of normal-moveout spectrum automatic pick method, realizes
The automatic Picking effect of normal-moveout spectrum local maxima energy group.And it according to the changing rule of stack velocity, devises adjacent speed and picks up
Length velocity relation restrictive condition a little is taken, the abnormal speed point in velocity pick is effectively eliminated, improves the effect of velocity pick
Fruit.The normal-moveout spectrum automatic Picking scheme of a set of precise and high efficiency is provided for seismic data process.
Using example
Normal-moveout spectrum automatic pick method proposed by the present invention is applied to the areas A, Fig. 2 a be on normal-moveout spectrum speed to picking up
It is seismic traces collection datagram corresponding with Fig. 2 a to take result figure, Fig. 2 b, and Fig. 2 c are according to the pickup point velocity amplitude in Fig. 2 a
To original trace gather into action correction process after result.
It will be understood by those skilled in the art that above to the purpose of the description of the embodiment of the present invention only for illustratively saying
The advantageous effect of bright the embodiment of the present invention is not intended to limit embodiments of the invention to given any example.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes will be apparent from for the those of ordinary skill in art field.The selection of term used herein, purport
In the principle, practical application or improvement to the technology in market for best explaining each embodiment, or make the art
Other those of ordinary skill can understand each embodiment disclosed herein.
Claims (10)
1. a kind of normal-moveout spectrum automatic pick method, which is characterized in that the normal-moveout spectrum automatic pick method includes the following steps：
1) seismic channel set data calculating speed is based on to compose；
2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and records institute
State maximum similarity factor value and corresponding sampling time and sweep speed value；
3) global maximum similarity factor point is searched；
4) the local maxima similarity factor point on All Time sampled point is picked up；
5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.
2. normal-moveout spectrum automatic pick method according to claim 1, which is characterized in that step 1) is based on seismic channel set data
Calculating speed is composed：
The minimum sweep speed of setting, velocity scanning interval and velocity scanning line number, scan all speed since minimum sweep speed
The dynamic correction of degree to the dynamic correction result of friction speed as a result, carry out cross-correlation calculation to obtain the similarity factor of friction speed
Value.
3. normal-moveout spectrum automatic pick method according to claim 1, which is characterized in that the normal-moveout spectrum automatic pick method
Further include：Remove abnormal speed pickup point, wherein the abnormal speed pickup point refers to：With the speed of automatic Picking to data
For target, according to the changing rule of adjacent spot speed, since global similar energies maximum point, increase respectively to the time and the time
Reduce direction and check whether the speed at consecutive number strong point meets the changing rule of the adjacent spot speed, is different if being unsatisfactory for
Constant velocity pickup point.
4. normal-moveout spectrum automatic pick method according to claim 3, which is characterized in that the variation of the adjacent spot speed is advised
Rule is indicated with following formula：
t1、t2Indicate two sampling time points, t1<t2, v1Indicate sampling time point t1Corresponding speed, v2Indicate sampling time point
t2Corresponding speed, vminIndicate minimum speed value, vmaxIndicate maximum speed value.
5. normal-moveout spectrum automatic pick method according to claim 1, which is characterized in that step 4) picks up All Time sampling
Local maxima similarity factor point on point includes following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as target, point
Do not reduce direction finding similarity factor to time augment direction and time to successively decrease and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, by similarity factor from the inflection point for becoming incremental of successively decreasing
It is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as one
Effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing on All Time sampled point
The pickup of local maximum point.
6. normal-moveout spectrum automatic pick method according to claim 1, which is characterized in that step 5) includes：It is obtained in step 4)
On the basis of the pickup result data taken, using least square curve fit method, the speed having picked up carries out data
Conic fitting obtains matched curve function；It is bent that minimal sampling time and maximum sampling time are substituted into the fitting respectively
Line function obtains the velocity amplitude of minimal sampling time point and maximum sampling time spot speed angle value.
7. a kind of normal-moveout spectrum automatic pick-up device, which is characterized in that the normal-moveout spectrum automatic pick-up device includes memory, processing
Device and storage are on a memory and the computer program that can run on a processor, which is characterized in that the processor execution
Following steps are realized when described program：
1) seismic channel set data calculating speed is based on to compose；
2) the maximum similarity factor value on each sampling time point is searched based on the normal-moveout spectrum that step 1) is calculated, and records institute
State maximum similarity factor value and corresponding sampling time and sweep speed value；
3) global maximum similarity factor point is searched；
4) the local maxima similarity factor point on All Time sampled point is picked up；
5) velocity amplitude of the velocity amplitude and maximum time sampled point of supplement minimum time sampled point.
8. normal-moveout spectrum automatic pick-up device according to claim 7, which is characterized in that step 1) is based on seismic channel set data
Calculating speed is composed：
The minimum sweep speed of setting, velocity scanning interval and velocity scanning line number, scan all speed since minimum sweep speed
The dynamic correction of degree to the dynamic correction result of friction speed as a result, carry out cross-correlation calculation to obtain the similarity factor of friction speed
Value.
9. normal-moveout spectrum automatic pick-up device according to claim 7, which is characterized in that the processor executes described program
When also realize following steps：Remove abnormal speed pickup point, wherein the abnormal speed pickup point refers to：With automatic Picking
Speed is target to data, according to the changing rule of adjacent spot speed, since global similar energies maximum point, respectively to the time
Increase and the time reduces direction and checks whether the speed at consecutive number strong point meets the changing rule of the adjacent spot speed, if not
Meet is then abnormal speed pickup point.
10. normal-moveout spectrum automatic pick-up device according to claim 7, which is characterized in that step 4) pickup All Time is adopted
Local maxima similarity factor point on sampling point includes following sub-step：
4.1) using global maximum similarity factor point as initial point, using maximum similarity factor on each sampling time point as target, point
Do not reduce direction finding similarity factor to time augment direction and time to successively decrease and incremental variations region；
4.2) the similarity factor region of variation that successively decreases is determined as non-picking region, by similarity factor from the inflection point for becoming incremental of successively decreasing
It is determined as next local maximum region；
4.3) when searching similarity factor and incrementally becoming the inflection point successively decreased, time and the speed of the inflection point are recorded, as one
Effective pickup point；
4.4) pickup point is made into starting point, continually looks for next local maximum point, until completing on All Time sampled point
The pickup of local maximum point.
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| CN110514862A (en) * | 2019-08-16 | 2019-11-29 | 西安交通大学 | A kind of high-speed rail speed of service estimation method using velocity scanning |
| CN112540404A (en) * | 2019-09-20 | 2021-03-23 | 中国石油化工股份有限公司 | Automatic speed analysis method and system based on deep learning |
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| 刘琳 等: "基于优化约束的Viterbi算法速度谱自动拾取方法", 《2015中国地球科学联合学术年会论文集（二十三）——专题55煤炭资源与矿山安全地球物理》 * |
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| CN110514862A (en) * | 2019-08-16 | 2019-11-29 | 西安交通大学 | A kind of high-speed rail speed of service estimation method using velocity scanning |
| CN110514862B (en) * | 2019-08-16 | 2020-10-27 | 西安交通大学 | High-speed rail running speed estimation method utilizing speed scanning |
| CN112540404A (en) * | 2019-09-20 | 2021-03-23 | 中国石油化工股份有限公司 | Automatic speed analysis method and system based on deep learning |
| CN112540404B (en) * | 2019-09-20 | 2024-04-12 | 中国石油化工股份有限公司 | Automatic speed analysis method and system based on deep learning |
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