CN105629300B - The method for improving complicated structure offset data signal-to-noise ratio - Google Patents
The method for improving complicated structure offset data signal-to-noise ratio Download PDFInfo
- Publication number
- CN105629300B CN105629300B CN201511020713.5A CN201511020713A CN105629300B CN 105629300 B CN105629300 B CN 105629300B CN 201511020713 A CN201511020713 A CN 201511020713A CN 105629300 B CN105629300 B CN 105629300B
- Authority
- CN
- China
- Prior art keywords
- data
- processing
- time
- offset
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
Abstract
The present invention provides a kind of method for improving complicated structure offset data signal-to-noise ratio.The described method includes the following steps that order carries out：Seismic data is gathered, migrated section is obtained after pretreatment, migration processing offset；Time sampling point before the first arrival of migrated section is arranged to null value, and increases data time number of samples；Tectonic level file pickup is carried out to offset data, and carries out full three-dimension layer position linear interpolation processing；Whole data carry out evening up processing；Carry out segmentation dip filtering compacting coherent noise processing；Carry out the smear processing of segmentation time-varying；Merge segment data, and data are extracted again by road and offset distance, be corrected reverse drawing and put down processing, obtain offset data after compacting coherent noise.The present invention can improve the signal-to-noise ratio of seismic data, and the earthquake record of quality higher can be provided for following explanations.
Description
Technical field
The present invention relates to a kind of method for improving complicated structure offset data signal-to-noise ratio, for oil seismic exploration, belong to
Seismic prospecting data processing is that a kind of inclination angle coherent noise in low SNR data is suppressed with explaining field, is improved
The signal-to-noise ratio of seismic data, can provide the earthquake record of quality higher for following explanations.
Background technology
In general, Complex Mountain seismic data noise source is sufficiently complex, noise has significant wave stronger interference, especially
Various types of rule interference and irregular interference development are strong, cause the signal-to-noise ratio of seismic data low, have seriously affected earthquake
The pretreatment of data and migration processing effect, also bring puzzlement to follow-up explanation.
For example, usually as oil-gas exploration is high by the complicated structure areas such as Plain steering hills, mountainous region, these regional earth's surfaces
Cheng Qifu is big, and the speed and thickness change of low velocity layer are big, and attitude of stratum is changed significantly on horizontal and vertical, and on these ground
The seismic data of area's collection compared with the seismic data of Plain there are various types of rules to disturb with irregular interference development by force
Strong, the signal-to-noise ratio of data is very low, even across the pretreatment of noise compacting early period, but can also be remained largely in migration processing
Linear disturbance, have impact on the correct imaging of offset, and the migrated section of low signal-to-noise ratio also brings puzzlement to follow-up explanation.
Due to the influence of complicated acquisition condition, often there is the steep dip phase that pretreatment can not be suppressed completely on migrated section
Dry noise, and the inclination angle of these steep dip coherent noises is sometimes very close with the inclination angle of useful signal, therefore with conventional F-X
The methods of domain filtering, the filtering of F-K domains or K-L are filtered is unable to reach satisfied noise pressing result, because these methods are being handled
During with same parameter the inclination angle coherent noise of all angles is suppressed, it is impossible to space-variant is carried out, in compacting noise
Meanwhile the useful signal of part inclination angle construction can be also sacrificed, this has obviously run counter to the original intention of noise compacting.
The content of the invention
A kind of method for improving complicated structure offset data signal-to-noise ratio proposed by the present invention, can realize inclination angle coherent noise
The best compromise that pressing result is kept with inclination angle useful signal feature.
To achieve these goals, the present invention provides a kind of method for improving complicated structure offset data signal-to-noise ratio.Institute
Stating method includes step：A, seismic data is gathered, migrated section is obtained after pretreatment, migration processing offset；B, will offset
Time sampling point is arranged to null value before the first arrival of section, and increases data time number of samples；C, techonosphere is carried out to offset data
Position file pickup, and carry out full three-dimension layer position linear interpolation processing；D, give correction and even up processing time point value, computation layer position is every
Road time and the difference of its given point in time, the correcting value of correction is evened up as per pass, whole data are carried out to even up processing；E、
Segmentation dip filtering compacting coherent noise processing is carried out to the data of step D；F, segment processing data in step E are segmented
The processing of time-varying smear；G, segment data in step F is merged, and data is extracted again by road and offset distance, and carry out school
It is positive and negative to even up processing, obtain offset data after compacting coherent noise.
Compared with prior art, beneficial effects of the present invention include：By to picking up tectonic level in migrated section, passing through
Layer position interpolation, which is corrected data, evens up processing so that useful signal becomes level of approximation lineups, and coherent noise is also protected
Certain inclination angle is stayed, data are chosen by being segmented, is segmented and carries out dip filtering compacting coherent noise, just can fine level of protection shape
Useful signal, and its fidelity is strengthened by the processing of time-varying smear, extracted finally by the merging of data after reverting to denoising
Offset data, realizes the best compromise that inclination angle coherent noise pressing result is kept with inclination angle useful signal feature；Improve complexity
The treatment effect of structural offset data SNR.
Brief description of the drawings
By the description carried out below in conjunction with the accompanying drawings, above and other purpose of the invention and feature will become more clear
Chu, wherein：
Fig. 1 shows actual seismic data-bias section；
Fig. 2 show an exemplary embodiment using the present invention to the actual seismic data-bias section in Fig. 1 into
Migrated section after row denoising；
Fig. 3 is shown carries out the actual seismic data-bias section of Fig. 1 the offset after denoising using conventional method
Section.
Embodiment
Hereinafter, exemplary embodiment will be combined and carrys out the raising complicated structure offset data noise that the present invention will be described in detail
The method of ratio.
The present invention is directed to propose one kind can be suppressed for complicated structure offset data coherent noise, and then improve it
The method of signal-to-noise ratio.
The core content of the present invention is, to picking up tectonic level in migrated section, school to be carried out to data by layer position interpolation
Just evening up processing so that useful signal becomes level of approximation lineups, and coherent noise also retains certain inclination angle, passes through segmentation
Data are chosen, segmentation carries out dip filtering compacting coherent noise, just can level of protection shape useful signal, and being mixed by time-varying very well
Ripple processing strengthens its fidelity, extracts the offset data after reverting to denoising finally by the merging of data, realizes that inclination angle is concerned with
The best compromise that noise pressing result is kept with inclination angle useful signal feature.
In one exemplary embodiment of the present invention, improve complicated structure offset data signal-to-noise ratio method can by with
Lower step is realized：
(1) seismic data is gathered, migrated section is obtained after pretreatment, migration processing offset.Here, migrated section can
Think time migration profile or depth migration section.
This step can be implemented in the following manner：
The seismic data arrived to field acquisition, pre-processes by static correction, prestack denoising, amplitude compensation, velocity analysis etc.
Afterwards, migration is carried out to seismic data using migration algorithm (for example, time migration or velocity shifts), obtains migrated section.
Here, the pretreatment before the offset such as static correction, prestack denoising, amplitude compensation, velocity analysis and migration algorithm belong to conventional
Operation.
(2) amplitude of the time number of samples before the first arrival time and first arrival time of migrated section is disposed as zero
Value, and increase data time number of samples, and the amplitude of increased time number of samples is zero.For example, the data time of increase
Number of samples can be 1/7 to 1/4 of data sample sum before not increasing, it is followed after data before not increasing.Increase sampling point
The data that number can effectively avoid below when evening up processing may caused by loss of data.
This step can be implemented in the following manner：
(a) since first arrival time sampled point is if nonzero value, then can produce different value to follow-up noise compacting influences, institute
Zero must be arranged to time sampling point before first arrival.
Data are calculated by road to offset data, when data amplitudes value is between -0.000001 and 0.000001, then can determine whether
For sample value before first arrival, then the amplitude is assigned a value of zero, completes the calculating in all roads, sample value is assigned a value of before all road first arrivals
Zero.
(b) since subsequent correction is evened up in processing procedure, it is understood that there may be even up data and exceed data number of samples itself, and damage
The risk of sample value is lost, so must at least increase by 1000 number of samples, and the amplitude of increased 1000 sample value before correction
Value is assigned a value of zero.For example, data sheet is as 5s data, increase 1s data are changed into 6s data, and the amplitude of data is equal between 5s-6s
It is assigned a value of zero.
(3) pickup of tectonic level (that is, layer position time value) file is carried out to offset data, intends the complicated structure of protection with pickup
Lineups layer position (that is, lineups layer position time value) is made, and carries out full three-dimension layer position linear interpolation processing.It is inclined for three-dimensional (3D)
Data are moved, it is necessary to pick up the layer place value on two or three above main profile direction, and a plurality of main profile (two to having picked up
Or the main profile of more than three) in all two main profiles adjacent to each other into line top-stitching interpolation processing, then to every
One main profile carries out this main profile line internal layer position linear interpolation processing.For two-dimentional (2D) offset data, then only need to the 2D
The survey line of data carries out the layer position linear interpolation processing inside survey line.
This step can be implemented in the following manner：
(a) tectonic level file pickup is carried out to offset data, the principle of pickup needs complicated structure to be protected for pickup
Lineups layer position, in case follow-up noise compacting injures the lineups.If data are 3D data, several masters of more pickups are needed
Layer place value on line direction, for example, picking up the layer place value on all main profile directions.
If (b) offset data is 2D data, need to only linear interpolation processing be carried out to the layer place value of pickup, interpolation goes out this
Per layer place value together in layer position, for subsequently calculating its correcting value.
If offset data is 3D data, inserted first with two main profiles for having picked up layer place value into line top-stitching
Value processing, until all equal interpolation of main profile have the layer point value identical with layer position number is picked up, then to every main profile
Layer position linear interpolation inside carrying out, the layer position interpolation inside all main profiles are completed.In view of 2D offset datas equivalent to
A line in 3D offset datas, when carrying out interpolation processing to 2D data, only carries out inside survey line the survey line of the 2D data
Layer position linear interpolation, without into line top-stitching interpolation processing.Here, what is inserted out is all layer position time value, be may be simply referred to as
Time value or layer place value.
Interpolation processing process of the present invention illustrated below to offset data.
For example, 3D data are arranged by main profile Inline and horizontal survey line CrossLine.3D data can have more than tens of
Main profile.There are hundreds and thousands of a CrossLine points below every Inline line.Equivalent to one 2D data of every Inline.3D
Data are considered as the link of N bars 2D data and form.The value of every main profile number uniquely determines, below the main profile
CrossLine periods are equivalent to Taoist monastic name.
The layer position file of pickup includes：No. Inline, this No. Inline it is No. CrossLine corresponding, and should
No. CrossLine corresponding time value；Multiple No. CrossLine and its time can be picked up on every Inline, can also be picked up certainly
Take a plurality of Inline lines.Table 1 gives two main profile (Inline in pickup 3D data：2 and example 24).
1 horizon picking documentation form of table
| Inline | CrossLine | Time |
| 2 | 1200 | 500 |
| 2 | 1800 | 560 |
| 24 | 1180 | 460 |
| 24 | 1790 | 520 |
The file of table 1 has picked up main profile 2 and 24 (referred to as 2 lines and 24 lines), two CrossLine on every main profile
Number, and the two No. CrossLine corresponding time values.First all CrossLine time value interpolation of 2 lines and 24 lines
Out, such as the 2nd line line, to interleave value-based algorithm be dotted line 1500 between 1200 and 1800,1200 points of corresponding time values 500 and
Intermediate value (500+560)/2=530 between 1800 points of corresponding 560 time values, interpolation have gone out 1500 point values for 530, Ran Houzai
So interpolation goes out the value of each period, similarly inserts out the time value of all CrossLine points (all the points) of 2 lines, and 24 lines own
The time value of CrossLine points (all the points).
Then, the value between 2-24 lines is first inserted medium line i.e. 13 line interpolation and gone out, put to each in 13 lines with 2 into row interpolation
The time value interpolation of line and the identical CrossLine points of 24 lines comes out, and similarly inserts out wired value.
In the layer place value write-in data trace header that interpolation is come out, i.e.,：Per there is a layer place value together, easy to subsequently calculate
Correcting value.
(4) give correction and even up processing time point value, computation layer position per pass time and the difference of its given point in time, as
Per pass evens up the correcting value of correction, and whole data are carried out to even up processing.
This step can be implemented in the following manner：
(a) some correction time point value T is given0, for example, some time point value can be chosen on tectonic level (for example, choosing
Some time point value of any one layer of position of complicated structure in pending offset data), gone out using interpolation in step (3)
Every channel layer position time value and correction time point value T0Make the difference, obtain per pass correction amount delta T, and correcting value is written to data trace header
Preserved in file.
(b) per each sample value corresponding time together and the correction amount delta of the track data in trace header in seismic data
T makes the difference, and the time location after processing is evened up as the road sample value, until all sample values in all roads all obtain evening up place
Time location after reason, so as to complete to even up processing to whole data.
(5) segmentation dip filtering compacting coherent noise processing is carried out to the data of step (4).
This step can be implemented in the following manner：
(a) to the two-dimensional migration data or 3-D migration data in step (4), divided by horizontal line direction in trace header
Section selection, the principle of segmentation is that the horizontal survey line position containing complicated structure is as segmentation using in original offset data, if in section
Multistage processing can be then divided into containing multiple complicated structures.
(b) dip filtering compacting coherent noise before processing is carried out to every segment data, dip scanning need to be carried out：
Arbitrary point x in grading excursion data(i,j), i is record Taoist monastic name, and j is sampling period, the recorded trace centered on i-th, choosing
2m+1 roads (m should be greater than 1, less than the total road number of data, for example, the value of m can be 1~10) are taken, form the inclination angle of the sampled point
Scan track data；In certain slope scanning range (p1,p2), slope sweep spacing p, is scanned, and records each scanning slope
The sum of amplitude absolute value：Obtain { the A of each slopei.j(p) } maximum in
When corresponding slope as the coherent noise slope suppressed of needs, dip filtering is carried out to the data on the slope.Wherein,
M is more than 1, less than the total road number of data, for example, the value of m can be 1~10；P1 and p2 values and p2 is more than between -1~1
p1；P can be manually set, for example, p>=0.1, it is appropriate to increase sweep spacing p value, scan efficiency can be properly increased.
(c) to carrying out noise compression process under the coherent noise slope；
Sampling of the seismic data in room and time direction has been differently formed entirely different data characteristics, and due to office
Portion's adding window correlated performance portrays the local steady state relation of seismic data, the characteristics of being more in line with seismic data, here using local
Related weighing medium filtering carries out the compacting of coherent noise.
Partial auto-correlation is expressed as：2N+1 is local window length, and x is current
Data value in window in noise slope direction, s are then the data value in noise slope direction in next window.
Using partial auto-correlation as weight coefficient, medium filtering is carried out：Threshold value is calculated firstBy noise
Data in slope direction are arranged according to order from small to large, and convert the position of corresponding weight coefficient, line up new power
Coefficient sequence, the numerical value in new weight coefficient sequence is added up successively according to the order after arriving first, when plus some power system
Count and cumulative number is equal to or more than threshold value ThWhen, then corresponding data is exported as Weighted median filtering result.
(6) segment processing data in step (5) are carried out with the smear processing of segmentation time-varying.
This step can be implemented in the following manner：
In order to improve the fidelity after denoising, by the data after region filtering processing in step (5) and the segmentation before denoising
Data carry out time-varying smear processing, i.e.,：
yi,j=xi,j*aj+si,j*bj
Wherein, yi,jFor data after the processing of time-varying smear, xi,jFor data after denoising, si,jFor data before denoising, ajAnd bjPoint
Smear scale factor that Wei be after j moment denoisings, before denoising, can be given in implementation process ratio at different moments because
Son, and at different moments between time scale the smear factor at per a moment is then obtained by linear interpolation.Wherein, i is represented
Taoist monastic name is recorded, j represents time sampling point, consistent with i, j implication in step (5)；Scale factor can artificially give, and can pass through sight
Different proportion factorial effect is examined to judge scale factor value, and then adjustment proportional factor.
(7) segment data in step (6) is merged, and data is extracted again by road and offset distance, and be corrected
Reverse drawing puts down processing, obtains offset data after compacting coherent noise.
To make the object, technical solutions and advantages of the present invention more clear, below in conjunction with attached drawing and specifically show
Example carrys out the exemplary embodiment that the present invention will be described in detail.
In the present example embodiment, improve complicated structure offset data signal-to-noise ratio method by following steps come reality
It is existing.Fig. 1 is into Fig. 3, and ordinate is time (unit is millisecond), and abscissa is Taoist monastic name.
The first step, the seismic data arrived to field acquisition, by static correction, prestack denoising, amplitude compensation, velocity analysis etc.
After pretreatment, migration is carried out to seismic data using migration algorithm, obtains migrated section, as shown in Figure 1.
Second step, null value is arranged to the first arrival time of migrated section, and increases data time number of samples；
To migrated section by road calculate each sampling point amplitude of data, when sampling point data amplitude -0.000001 with
Between 0.000001, then it can determine whether for sample value before first arrival, then the amplitude to be assigned a value of zero, until completing all seismic channels
Calculate, then sample value before all seismic channel first arrivals is assigned a value of zero.
Since correction is evened up in processing procedure, it is understood that there may be even up data and exceed data number of samples itself, and lose sampling point
The risk of value, so must at least increase 1000 number of samples before correction, as data have 5000 sampled points in Fig. 1, then increases
It is 6000 sampled points to add 1000 sampling points to data, and increased 1000 sampling point values are zero.
3rd step, tectonic level file pickup is carried out to offset data, and carries out full three-dimension layer position linear interpolation processing.
Tectonic level file pickup (being constructed at the arrow meaning of such as Fig. 1 for the layer position of pickup) is carried out to offset data, is picked up
The principle taken is to need complicated structure lineups layer position to be protected for pickup, in case follow-up noise compacting injures the lineups,
If data bit 3D data, need to pick up the layer place value on several main profile directions more.
If offset data is 2D data, need to only linear interpolation processing be carried out to the layer place value of pickup, interpolation goes out the layer
Per layer place value together in position, for subsequently calculating its correcting value.
If offset data is 3D data, carried out first with having picked up a layer place value and obtaining two main profiles, it is linear between line
Interpolation processing, until all equal interpolation of main profile have the layer point value identical with pickup layer position number, then to every main survey
Layer position linear interpolation inside line progress, the layer position interpolation inside all main profiles are completed.
In the layer position time value write-in data trace header that interpolation is come out, i.e.,：Per there is a layer position time value together, it is easy to
It is follow-up to calculate correcting value.
Processing time point value, computation layer position per pass time and the difference of its given point in time are evened up in 4th step, given correction,
The correcting value of correction is evened up as per pass, whole data are carried out to even up processing.
It is T that can give correction time point value on pickup layer position according to Fig. 10=3500, gone out using interpolation in step (3) every
Channel layer position time value and correction time point value T0Make the difference, obtain per pass time adjustment amount Δ T, and correcting value is written to data track
Preserved in header file.
Being made the difference in seismic data per the time of each sample value together with the correction amount delta T in the road, this is used as
The road sample value evens up the time value after processing, the when meta after all sample values in all roads all obtain evening up processing
Put, so as to complete to even up processing to whole data.
The data of 4th step are carried out segmentation dip filtering compacting coherent noise processing by the 5th step.
To the two-dimensional migration data or 3-D migration data in the 4th step, segmentation choosing is carried out by horizontal line direction in trace header
Select, complicated structure as shown in Figure 1 mainly between 200~400, can be divided into the data three sections here and be handled.
To taking arbitrary point x in the middle segment data containing construction(i,j), i is record Taoist monastic name, and j is sampling period, in being with i-th
Heart recorded trace, chooses 2m+1 roads, forms the dip scanning track data of the sampled point；In certain slope scanning range (p1,p2),
Slope sweep spacing p, is scanned, and records the absolute value of the sum of the amplitude of each scanning slope：Obtain { the A of each slopei.j(p) } corresponding slope is as needing during maximum in
Data on the slope are carried out dip filtering by the coherent noise slope suppressed.
Threshold value is calculated first：Partial auto-correlation is expressed as：
2N+1 is local window length, and x is the data value in noise slope direction in current window, and s is then to make an uproar in next window
Data value in sound slope direction；Data in current window in noise slope direction are arranged according to order from small to large,
And convert the position of corresponding weight coefficient, line up new weight coefficient sequence, by the numerical value in new weight coefficient sequence according to from
Order after arriving first adds up successively, when being equal to or more than threshold value T plus some weight coefficient and cumulative numberhWhen, then output corresponds to
Data are as Weighted median filtering result.
The operation of the 5th step is equally carried out to first segment and the 3rd segment data so that whole data complete segmented noise pressure
System.
6th step, carries out segment processing data in the 5th step the smear processing of segmentation time-varying.
yi,j=xi,j*aj+si,j*bj
Wherein, yi,jFor data after the processing of time-varying smear, xi,jFor data after denoising, si,jFor data before denoising, ajAnd bjPoint
Smear scale factor that Wei be after j moment denoisings, before denoising, can be taking human as given ratio at different moments in implementation process
The factor, and at different moments between time scale the smear factor at per a moment is then obtained by linear interpolation.
7th step, merges segment data in the 6th step, and extracts data again by road and offset distance, and carries out school
It is positive and negative to even up processing, obtain offset data after compacting coherent noise.
If Fig. 1 is the offset data containing complicated structure, but there are certain coherent noise, disturb useful signal.Fig. 2
Effectively suppressed by the migrated section after flow processing of the present invention, coherent interference for Fig. 1, highlight useful signal, effectively
Construction keeps preferable.Fig. 3 is the migrated section after Fig. 1 is handled by conventional method, although also having suppressed coherent interference, such as
In Fig. 3 shown in arrow meaning, conventional method has injured effective construction, and also following explanations bring unnecessary trouble.
In conclusion the method for the present invention can carry out the coherent noise of real data, especially inclination angle coherent noise
Effectively compacting, and useful signal can preferably be protected, so as to keep the ground that real seismic record is reflected well
Layer information and geologic feature, moreover, by the way that with good correctness and reliability, signal-to-noise ratio higher is provided for subsequent treatment
Section.The present invention is suitable for suppressing the coherent noise of migrating seismic data, and it is inclined to be especially directed to complicated structure
Move data and carry out coherent noise compacting, for example, the method for the present invention is applied to signal-to-noise ratio in the data of mountainous region lower ground shakes number
According to its denoising effect is preferable, and fidelity is higher, and application prospect is extensive.
Although having been combined attached drawing and exemplary embodiment above, the invention has been described, those of ordinary skill in the art
It will be apparent to the skilled artisan that in the case where not departing from spirit and scope by the claims, various modifications can be carried out to above-described embodiment.
Claims (3)
- A kind of 1. method for improving complicated structure offset data signal-to-noise ratio, it is characterised in that the method includes the steps：A, seismic data is gathered, migrated section is obtained after pretreatment, migration processing offset；B, time sampling point before the first arrival of migrated section is arranged to null value, and increases data time number of samples；C, tectonic level file pickup is carried out to offset data, and carries out full three-dimension layer position linear interpolation processing；D, give correction and even up processing time point value, computation layer position per pass time and the difference of its given point in time, as per pass The correcting value of correction is evened up, whole data are carried out to even up processing；E, segmentation dip filtering compacting coherent noise processing is carried out to the data of step D；F, segment processing data in step E are carried out with the smear processing of segmentation time-varying；G, segment data in step F is merged, and data is extracted again by road and offset distance, be corrected reverse drawing and put down place Reason, obtains offset data after compacting coherent noise,Wherein, the segmentation time-varying smear processing of the step F is using by before the data after region filtering processing in step E and denoising Segment data carry out time-varying smear processing, its formula is：yi,j=xi,j*aj+si,j*bjWherein, yi,jFor data after the processing of time-varying smear, xi,jFor data after denoising, si,jFor data before denoising, ajAnd bjRespectively Smear scale factor after j moment denoisings, before denoising.
- 2. the method according to claim 1 for improving complicated structure offset data signal-to-noise ratio, it is characterised in that the step Increase 1/7 to 1/4 time sampling point that data time number of samples refers at least increase data sample sum, and the increasing in B The time sampling point added is assigned a value of zero.
- 3. the method according to claim 1 for improving complicated structure offset data signal-to-noise ratio, it is characterised in that the step The tectonic level file pickup that carried out to offset data in C refers to that pickup needs complicated structure lineups layer position to be protected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201511020713.5A CN105629300B (en) | 2015-12-30 | 2015-12-30 | The method for improving complicated structure offset data signal-to-noise ratio |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201511020713.5A CN105629300B (en) | 2015-12-30 | 2015-12-30 | The method for improving complicated structure offset data signal-to-noise ratio |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105629300A CN105629300A (en) | 2016-06-01 |
| CN105629300B true CN105629300B (en) | 2018-05-15 |
Family
ID=56044411
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201511020713.5A Active CN105629300B (en) | 2015-12-30 | 2015-12-30 | The method for improving complicated structure offset data signal-to-noise ratio |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105629300B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107153217B (en) * | 2017-07-10 | 2019-03-29 | 中国石油集团东方地球物理勘探有限责任公司 | A kind of low signal-to-noise ratio regional model road construction method |
| CN110967738A (en) * | 2018-09-30 | 2020-04-07 | 中国石油化工股份有限公司 | Seismic data interpolation processing method and system based on deep learning |
| CN111781644B (en) * | 2019-04-03 | 2022-11-04 | 中国石油天然气股份有限公司 | Linear interference attenuation method and device for shallow and medium stratum seismic data |
| CN112083490B (en) * | 2019-06-12 | 2024-03-01 | 中国石油天然气集团有限公司 | Seismic data noise attenuation method and device |
| CN111624659B (en) * | 2020-06-05 | 2022-07-01 | 中油奥博(成都)科技有限公司 | Time-varying band-pass filtering method and device for seismic data |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2376527B (en) * | 2001-06-16 | 2004-12-15 | Westerngeco Ltd | A method of processing data |
| CN101339252B (en) * | 2008-08-08 | 2010-08-18 | 吉林大学 | Directional lighting seismic exploration method based on single earthquake focus |
| CN103412329B (en) * | 2013-08-06 | 2015-09-16 | 中国海洋石油总公司 | A kind of method improving seismic data resolution |
-
2015
- 2015-12-30 CN CN201511020713.5A patent/CN105629300B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN105629300A (en) | 2016-06-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105629300B (en) | The method for improving complicated structure offset data signal-to-noise ratio | |
| CN107505651B (en) | Seismic first break and back wave combine slope chromatography imaging method | |
| CN110133715B (en) | Microseism seismic source positioning method based on first-arrival time difference and waveform superposition | |
| CN109669212B (en) | Seismic data processing method, stratum quality factor estimation method and device | |
| CN107728200A (en) | Ground micro-seismic fracturing fracture dynamic spread method of real-time | |
| CN107526101A (en) | A kind of collection for obtaining earthquake reflected wave and processing method | |
| CN104280777B (en) | Method for suppressing interference of seismic data multiples on land | |
| CN107490808B (en) | A kind of method for building up of high reliability seismic prospecting observation system | |
| Amoroso et al. | S‐wave identification by polarization filtering and waveform coherence analyses | |
| CN102073067A (en) | Method for increasing automatic pickup efficiency of geological data first-motion waves | |
| AU2007329168A1 (en) | Method of building a sub surface velocity model | |
| CN104620132A (en) | Signal enhancement using diversity shot stacking for reverse time migration (DeSSeRT) | |
| CN110389377B (en) | Microseism offset imaging positioning method based on waveform cross-correlation coefficient multiplication | |
| CN104570116A (en) | Geological marker bed-based time difference analyzing and correcting method | |
| CN109884709A (en) | A kind of converted wave statics method chromatographed when the travelling based on surface wave | |
| CN113552625A (en) | Multi-scale full waveform inversion method for conventional land-domain seismic data | |
| CN111722284A (en) | Method for establishing speed depth model based on gather data | |
| CN104597485B (en) | A kind of miniature fault detection method and fault detection device | |
| AU2006237348B2 (en) | Method of processing seismic data for AVO or AVOA characterisation | |
| CN106443791B (en) | The method for asking for tilted stratum or anisotropic formation shear wave Value of residual static correction | |
| CN115373023A (en) | Joint detection method based on seismic reflection and vehicle noise | |
| CN107918152B (en) | A kind of seismic coherence chromatography imaging method | |
| CN105093324B (en) | A kind of residual static corrections | |
| CN112946742B (en) | Method for picking up accurate superposition velocity spectrum | |
| CN104142513B (en) | Method for improving chromatography inversion accuracy in seismic exploration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: No. 216, No. 216, Huayang Avenue, Tianfu New District, Sichuan, Sichuan Applicant after: China National Petroleum Corporation Chuanqing Drilling Engineering Geophysical Exploration Company Ltd. Address before: No. 216, No. 216, Huayang Avenue, Huayang Town, Shuangliu County, Shuangliu County, Sichuan Applicant before: China National Petroleum Corporation Chuanqing Drilling Engineering Geophysical Exploration Company Ltd. |
|
| CB02 | Change of applicant information | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20180330 Address after: No. 189, fan Yangxi Road, Zhuozhou City, Baoding, Hebei Applicant after: Dongfang Geophysical Exploration Co., Ltd., China Petrochemical Corp. Address before: No. 216, No. 216, Huayang Avenue, Tianfu New District, Sichuan, Sichuan Applicant before: China National Petroleum Corporation Chuanqing Drilling Engineering Geophysical Exploration Company Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20201112 Address after: 100007 Beijing, Dongzhimen, North Street, No. 9, No. Patentee after: CHINA NATIONAL PETROLEUM Corp. Patentee after: BGP Inc., China National Petroleum Corp. Address before: No. 189, fan Yangxi Road, Zhuozhou City, Baoding, Hebei Patentee before: BGP Inc., China National Petroleum Corp. |
|
| TR01 | Transfer of patent right |