CN107664771A - A kind of microseism Full wave shape localization method based on likeness coefficient - Google Patents
A kind of microseism Full wave shape localization method based on likeness coefficient Download PDFInfo
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- 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. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
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- G—PHYSICS
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- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
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Abstract
As exploration and development enters the middle and later periods, in order to improve the rate of oil and gas recovery, micro-seismic monitoring and location technology become more and more important.Algorithm on seismic source location has a lot, and current most of algorithms are all to establish equation on the basis of first arrival time and spread speed the two parameters and solve positioning.The two parameters are difficult to accurately obtain in actual seismic data, therefore positioning precision can be affected.Slant stack is based on for the auspicious grades of this problem Miao Hua and scanning thought proposes microseism all-wave automatic positioning method, effectively prevent problem above.But there is the problems such as noise resistance deficiency in the microseism all-wave automatic positioning method.For this problem, the present invention proposes the microseism all-wave automatic positioning method based on likeness coefficient, first, each data is handled using window weighting during sine；Then, optimize original likeness coefficient algorithm, division arithmetic is changed to subtraction, accelerates operational efficiency, carried out normalized function and judged position.Compared with original method, it is significantly improved in noise resistance, prominent extreme value, and amount of calculation substantially reduces.
Description
Technical field
The present invention relates to seism processing field, is positioned more particularly to microseism.
Background technology
The advantages of micro-seismic technology shows in recent years is so that numerous oil gas fields increase the research and development of the technology one after another
Dynamics, achieve compared with quantum jump in all fields.
Microseismic core is seismic source location, and seismic source location key is divided at 2 points：Object function and solution
Optimization.
First for objective function problem, Geiger in 1912 is proposed earliest according to first arrival time and stratigraphic model will be non-
Linear problem linearizes, and provides least square solution this is earliest object function.Although this method is imperfect but open
Many researchers are sent out, Waldhauser (2000) just proposes double difference method positioning on the basis of the equation, if two places
Distance is compared smaller with earthquake-receiving point or speed heterogeneous body between shake event, then can be regarded as from two focus to reception
The ray path of point is consistent, and the difference between such two observation time, which can consider with two hypocentral distances, direct contact, passes through one
Individual high-precision event calculates another low performance event, medium interference such as is overcome to a certain extent, the problems such as noise jamming.
Have and wave type energy is applied to object function, their theory comes from Aster and Scott to be occurred in the cluster proposed in 1993
Microseism waveform there is similarity theory, then new method is arisen at the historic moment：Most obvious microseism is positioned first, further according to
The similarity theory of ripple searches out small and weak microseism, finally positions these small and weak microseisms, Kummerow (2010) is micro-
Correlation did research between seismic waveform.In order to solve influence of the initial time to model, Hu Fei proposes a kind of for (2015)
Based on the object function of differential form, the influence of initial time is eliminated using three kinds of TRANSFORMATION RATIO difference perfections.
Then for solution optimization above, earliest solution can be classified as the general solution for linearizing nonlinear problem
Method, this will necessarily produce the problems such as being such as absorbed in local extremum.In order to overcome the problem of linearisation is brought by force, start to develop non-thread
Property localization method, these methods do not need initial value, partial derivative, the problem of effectively prevent local extremum, but calculate number
According to starting to become big, efficiency step-down.The method of representative has：Newton method, monte carlo search method, enumerative technique (direct search method) etc..
Under the development of Other subjects, algorithm is also updated, and the evolution algorithm based on biology occurs, using thermodynamics as base
The simulated annealing (Pei etc., 2009) of plinth, based on wave equation inverse time imaging method (Zou and Zhou, 2011
Year).
Because the complicated single solution of underground medium is difficult to be applicable, then many algorithms are compound on the premise of accuracy is ensured
Become in order to which grid search and artificial genetic (2012) is used in combination in an effective route Song Wei fine jade and joint is yellow
Golden mesh segmentation grid data service and simulated annealing (2014), contain Computer Associates International Inc.'s joint particle cluster algorithm and Differential evolution (2014
Year), obtain outstanding locating effect.
Song Weiqi proposes to be disturbed by rate pattern at perforation for (2012) for ground receiver problem, searches out micro-
The velocity equivalent of earthquake and then positioned, this method eliminates the time difference minor issue between neighboring track well, solves
The problem of finally model inversion susceptibility is low, improves inversion accuracy and quality, while enhance model anti-interference.
Receive the problem of microseism signal is weak, and first break picking is forbidden for ground, Zhu Haiwei etc. is proposed for (2013)
Various combination methods under Bayesian frame, this method is caused to have stronger resistance for noise for the accurate assurance of prior information
Power, efficiency has further raising compared with search method.
What wise China proposes inverting new method in (2013) based on three-component geophone data, auxiliary using the superposition repeatedly of energy
Limited with direct wave angle to determine earthquake excitation area, be similarly to grid data service, workload is bigger, but is really
Positioning opens new direction.
Miao Huaxiang is equal to the automatic tomography theory of the mine microseism all-wave proposed in 2012, independent of time and speed
Degree has very high researching value.But the algorithm exists and supports that Noise Resistance Ability is low and extreme value not distinct issues.
The content of the invention
More effectively to overcome drawbacks described above present in the automatic tomography of microseism all-wave, the present invention seeks to pass through
Microseism decision criteria is optimized, so as to improve to Noise Resistance Ability and prominent extreme value.
The purpose of the present invention is to overcome anti-noise ability existing for original method not strong and extreme value not outstanding problem.This method
It is as follows：
Window when first introducing, at the same for pair when window in after each data weighting using window when selecting sinusoidal, such as the row of 5 row 1
Window is as follows when sinusoidal：
0.0800 0.5400 1.0000 0.5400 0.0800
Then in sine under window, the judgment criterion based on likeness coefficient is just changed into formula (1)：
Wherein f (i, l+ki) represent l+k in i-th wave detector recordiThe data at moment, gsin (n, i, l+ki) represent
The l+k that i-th of wave detector records under window in n lengthiThe sine weighting coefficient of the data at moment, t0Represent to use during scanning
Time, vjRepresent the speed used during scanning.
The core concept of formula (1) is：If f (i, l+ki) it is disturbance records, then molecule should be zero in formula (1)；
If effective record, then the value of formula (1) is close to 1.
Know that Sc is closer to 1 from formula (1), then closer to focal point, so, the formula (1) is converted, it is known that：
Then, plus and minus calculation is to be faster than multiplication and division computing forever for computer, so in order to improve operation efficiency,
The use of plus and minus calculation is as far as possible optimal selection, then new thought just produces on this basis：At utmost using plus-minus fortune
Calculate.Two parts above and below on the right of formula (2) equation are wherein made to be set to respectively：
It is available with reference to formula (3) and formula (4)：
A-B=S (5)
From formula (5), it is possible to find：
The bigger closer focus of this numerical value of MSc, A and B numerical difference is bigger away from bigger then MSc on the other hand, from
And closer to focus.
It can be drawn by above theory：A and B difference can greatly be improved arithmetic speed as judgement data.But
It is that S fluctuation range must be any limitation as greatly very much.Then maximum is selected in all S datas first in actual operation
MaxS, then normalized will be made according to below equation (6)：
Using S1 as new judgement data.
In summary, a kind of microseism Full wave shape localization method based on likeness coefficient, this method comprise the following steps：
Step 1：The Probability Area that microseism occurs delimited, establishes the space coordinates relation of wave detector and the region；
Step 2：Select time window length, trace interval, sweep speed interval, scanning space spacing parameter；
Step 3：Read in microseism data；
Step 4：Corresponding sweep time, speed, space are picked up in the microseism data that each wave detector recorded
Window data during that segment record；
Step 5：Sine weighting processing is carried out to window array when these；
Step 6：According to these data calculate A and B, formula such as (3), (4),
Wherein f (i, l+ki) represent l+k in i-th wave detector recordiThe data at moment, gsin (n, i, l+ki) represent
The l+k that i-th of wave detector records under window in n lengthiThe sine weighting coefficient of the data at moment；
Then S is calculated, formula is such as shown in (3)；
Step 7：Maximum maxS is selected in all S datas, normalized is done to the data S calculated, it is public
Formula is such as shown in (6)；The judgement data that S1 is positioned as microseism, the bigger closer focus of the value.
Original division arithmetic is changed to subtraction by the present invention on the basis of likeness coefficient Criterion Method to improve efficiency,
But experiment finds to judge that data overall variation differs greatly, so using method for normalizing compressed data to cause in final step
Overall variation substantially diminishes, prominent extreme value so that setting accuracy further improves.Window during simultaneous selection sine, pass through weighting
Coefficient optimizes the service condition of data, avoids part and disturbs influence to result.
Brief description of the drawings
Fig. 1 is design Simple Theory model, and its area of plane is：300m × 300m, depth 100m.
Divide three layers：Surface p wave interval velocity at deep 35m is 2800m/s, and S wave velocities are 1600m/s.35m to 60m locates P ripples
Speed is 3200m/s, and S wave velocities are 1900m/s.60m to 100m places p wave interval velocity is 3300m/s, and S wave velocities are 2000m/s.
It is 70m that earthquake source, which is wherein designed, in abscissa, at ordinate 70m, depth 70m.Firing time is 0.3s；
Fig. 2 is to build the wave point location drawing, and the dot in figure is exactly geophone station.This geophone station has 25, and is uniformly distributed,
Maximum magnitude covers observation area.Coordinate starts from (50,50), ends at (250,250).Altogether area be 200m ×
200m；
Fig. 3 is the former methodical profile being calculated, and color is bigger closer to red, its value；First width figure is perpendicular
The upward profile of Nogata, its abscissa are section horizontal direction distance, and ordinate is the depth of section.Second width figure is horizontal
Profile on direction, its abscissa are section horizontal direction distance, and ordinate is section longitudinal direction distance.It is evident that the back of the body
Scape disturbs huge, and big in extremal region, i.e., extreme value does not protrude, and shows that positioning precision is not high, it is known that be vulnerable to noise jamming；
Fig. 4 is likeness coefficient microseism positioning proposed by the present invention, and color is bigger closer to red, its value；First width
Figure is the profile on vertical direction, and abscissa is section transverse direction distance, and ordinate is section longitudinal direction distance.Second width figure
The profile being horizontally oriented, its abscissa are section horizontal direction distance, and ordinate is section longitudinal direction distance；From figure
It can be seen that ambient interferences are substantially pressed, extremal region is obviously reduced, i.e., extreme value is significantly highlighted.
Embodiment
The main realization principle of technical scheme, embodiment etc. are retouched in detail below according to accompanying drawing
State.
Cardinal principle：First assume that microseism focus is located at monitored area certain, starts to excite in a certain moment, and with certain
One speed travels to each wave detector, and is detected device and records.Pass through time for continually scanning for, space, speed these ginsengs
Count to calculate judgment criterion data proposed by the present invention, search out extreme value, that is, position microseism focus
Embodiment：First, according to the geophone station observation system of Fig. 1 geophone station geologic structure model and Fig. 2
It is 70m that forward simulation, which goes out by shot point in abscissa, and at ordinate 70m, depth 70m, firing time is ground caused by 0.3s
Shake data.It is consistent with true geological data to ensure, interference data are added in the seismic data.
Then, micro-seismic monitoring region is set, and space coordinates relation is established with geophone station observation system.Setting scans
Only time and sweep spacing, scanning start-stop speed and speed interval, scanning space interval, set time window length.
Then, scanning calculates the time that microearthquake wave arrives each geophone station under these parameters successively, and remembers in wave detector
Record data on, centered on this arrival time, select one when window picks up data.Establish sine weighting coefficient, pair when window in
Data carried out sine weighting processing.Cast out for wave detector record data of problems progress is necessary.
Finally, the data that these are picked up are calculated as proposed by the present invention based on likeness coefficient criterion method,
Wherein maximum is microseism focus.Comparison diagram 3 and Fig. 4, determined using proposed by the present invention based on likeness coefficient microseism
The position more former method of method has more preferable effect, and first can be seen that effect is very good in compacting ambient interferences, and second in prominent pole
Extremal region is obviously reduced in terms of value, shows to be obviously improved effect for prominent extreme value.
Claims (1)
1. a kind of microseism Full wave shape localization method based on likeness coefficient, this method comprise the following steps：
Step 1：The Probability Area that microseism occurs delimited, establishes the space coordinates relation of wave detector and the region；
Step 2：Select time window length, trace interval, sweep speed interval, scanning space spacing parameter；
Step 3：Read in microseism data；
Step 4：Picked up in the microseism data that each wave detector recorded corresponding sweep time, speed, space that
Window data during segment record；
Step 5：Sine weighting processing is carried out to window array when these；
Step 6：A and B is calculated according to these data, formula is as follows：
Wherein f (i, l+ki) represent 1+k in i-th wave detector recordiThe data at moment, g sin (n, i, l+ki) represent in n
The 1+k that i-th of wave detector records under window during individual lengthiThe sine weighting coefficient of the data at moment；
Then S is calculated, formula (3) is as follows：
A-B=S (3)
Step 7：Maximum maxS is selected in all S datas, normalized is done to the data S calculated, had：
The judgement data that S1 is positioned as microseism, the bigger closer focus of the value.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113640878A (en) * | 2021-08-12 | 2021-11-12 | 西南石油大学 | Method for constructing azimuth-apparent velocity radar map by using virtual seismic source scanning |
| CN114325829A (en) * | 2021-12-21 | 2022-04-12 | 同济大学 | Full waveform inversion method based on double-difference idea |
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| CN113640878A (en) * | 2021-08-12 | 2021-11-12 | 西南石油大学 | Method for constructing azimuth-apparent velocity radar map by using virtual seismic source scanning |
| CN113640878B (en) * | 2021-08-12 | 2024-03-29 | 西南石油大学 | Method for constructing azimuth-apparent velocity radar chart by utilizing virtual seismic source scanning |
| CN114325829A (en) * | 2021-12-21 | 2022-04-12 | 同济大学 | Full waveform inversion method based on double-difference idea |
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