CN105807316B - Ground observation microseism velocity model corrections method based on amplitude superposition - Google Patents
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Abstract
The present invention relates to a kind of ground observation microseism velocity model corrections method based on amplitude superposition, from reverse-time migration amplitude of vibration addition method principle, and combine very fast simulated reannealing, seismic phase first break information need not be picked up, by monitoring Voice segment situation at shooting point, velocity model corrections are carried out.And precision is relocated with shooting point, judge whether rate pattern can be used for follow-up microseism to position.Can effectively overcome maximum existing for existing algorithm and maximum regardless of situation, accurately find Voice segment maximum E, be accurately positioned perforating site, effective correction rate model.Noise jamming can effectively be suppressed using inverse time amplitude excursion superposition algorithm, preferable locating effect can be still obtained in the case where signal to noise ratio is relatively low.For rate pattern closer to realistic model, perforation positioning will be more accurate.Precision is relocated according to shooting point, judges whether rate pattern can be used for follow-up microseism to position.
Description
Technical field
The present invention relates to a kind of oil field compression fracture microseism positioning, is exactly specifically to be carried out by the monitoring materials of microseism
Velocity model corrections, so as to improve follow-up microseism positioning precision.
Technical background
At present, the exploration for Low permeable oil and gas reservoirs and exploitation has become the new focus of domestic and international oil and gas industry, and leads to
Cross hydraulic fracturing technology exploitation Low permeable oil and gas reservoirs turns into a kind of popular tendency.Warpinski is in SPE Journal within 2005
On deliver it is entitled《Improved microseismic fracture mapping using perforation timing
measurements for velocity calibration》Article in point out in the technology implementation process, fracture extension is led
Surrounding rock rupture is caused, so as to trigger a series of micro-seismic event of Observable records.Eisner in 2010 etc. is in The
That is delivered on Leading Edge is entitled《Microseismicity-constrained fracture models for
reservoir simulation》Article and Maxwell etc. delivered on Geophysics it is entitled《Petroleum
reservoir characterization using downhole microseismic monitoring》Article point out
By being accurately positioned to micro-seismic event, it can be determined that fracture strike, evaluate fracturing effect and analysis inverting focal mechanism
Etc..Therefore, the demand for improving micro-seismic event positioning precision becomes more urgent.Perforation event is positioned to its actual value
Place, and it is the key for reaching above-mentioned purpose to establish an effective rate pattern.2010, Bardainne etc. existed
That is delivered on Geophysical Prospecting is entitled《Constrained tomography of realistic
velocity models in microseismic monitoring using calibration shots》Article point out
The Technology of Seismic Tomography can be used as microseism locating speed model correcting algorithm by using for reference in seismic prospecting, but in seismic source information
Measure it is less, geoceiver lazy weight and coverage it is less in the case of, using the Technology of Seismic Tomography it is difficult to obtain
More fine work area rate pattern.
Current existing micro-seismic monitoring velocity model corrections method establishes fairly simple structure model of soil layer over the ground mostly
Lower velocity structure is described, and known perforating site, inverting positioning is carried out to perforating site, to reduce positioning risk.But
Bardainne and Gaucher points out that such method needs to pick up P ripples or S ripple first break informations from earthquake record, therefore it is required that ground
There is higher signal to noise ratio in shake record, such method is commonly used to observe data processing in well.But for surface array formula
For observation, especially when reservoir is deeper, perforation record has low signal-to-noise ratio feature, utilizes existing microseism rate pattern
The result that bearing calibration obtains is unsatisfactory.And the situation of well-log information excalation also usually occurs in Practical Project, need
To use the mathematical methods such as interpolation to be filled up, influence the degree of accuracy of rate pattern to a certain extent.
Inverse time amplitude excursion stacking method does not need first break picking information, is superimposed by the way that geological data is translated, obtains energy
Amount focuses on maximum of points and carries out perforation positioning, is that current microseism positioning field applies one of more method.But finding
During Voice segment maximum of points, the situation that maximum and maximum are difficult to differentiate between is commonly present, this will directly affect perforation positioning accurate
Degree, causes velocity model corrections misalignment.
Therefore, in actual speed model trimming process, how improving perforation positioning precision, overcoming low signal-to-noise ratio, increase
Add depth of reservoirs, obtain more accurately rate pattern, be this area urgent need to resolve so as to improve micro-seismic event positioning precision
Problem.
The content of the invention
It is an object of the invention to for above-mentioned problems of the prior art, using the reverse-time migration amplitude of vibration addition method as base
Plinth, and combine simulated annealing method, there is provided a kind of ground observation microseism velocity model corrections method based on amplitude superposition.
Idea of the invention is that missed using log data deviation and Gauusian noise jammer as perforation positioning caused by principal element
Difference, precision is relocated to improve perforation using velocity model corrections as a kind of error compensation.Perforation positioning precision is higher, gained speed
It is more accurate to spend model.
Based on the ground observation microseism velocity model corrections method of amplitude superposition, comprise the following steps：
A, three-dimensional target region is established centered on shooting point, selects reference channel M；
Initial temperature T0, minimum temperature Tmin, dwell time T, simulated annealing calculating parameter are set b,；
D, initial velocity model is established, defines E (V)=0；
E, initial velocity vector V is obtained, reads perforation data；
F, travel-time difference of each road relative to library track is calculated；
G, each track data is translated and be superimposed, obtain Energy maximum value E and its coordinate under existing rate pattern；
H, E value is assigned to E (V)；
I, E (V) coordinate dead time reaches T；
J, energy is the coordinate at (V) place as the perforation elements of a fix；
K, whether meet perforation positioning precision, be；
L, terminate.
Simulated annealing calculating parameter setting described in step b, is the characteristics of observation according to ground array microseism, sets
Six simulated annealing calculating parameters：
First parameter is velocity vector V, V=[Vp1,Vp2,Vp3,...,Vpn],Vpi
For i-th layer of p wave interval velocity, initial velocity vector V is just obtained according to well-log information；
Second parameter is object function E (V), and in log data, selection is any to be used as library track M together, using penetrating
The method of line tracking asks for theoretical travel-time difference of other each roads relative to the library track：
Δtcal=[t1-tM,t2-tM,...,tN-tM] (1)
The perforation wave recording obtained according to the theoretical travel-time difference to each road wave detector carries out reverse-time migration superposition, is superimposed energy
It is as follows to measure (object function) mathematic(al) representation：
Wherein A is amplitude of vibration size of i-th of volume elements at the jth moment, and the center point coordinate of i-th of volume elements is (xi,yi,zi),
M is wave detector number, and N is time window length；
3rd parameter is simulated annealing initial temperature T0, it is as follows to obtain the solution method of initial temperature, first to initial temperature
One very little of degree on the occasion of the number that a perseverance is more than 1 being then constantly multiplied by, until meeting that the acceptance probability of any model is approached
Untill 1；
4th parameter is annealing cooling parameter, extremely fast simulated annealing cooling profiles such as following formula：
Tk=T0exp(-ck1/2N) (3)
Wherein k is iterations, T0For initial annealing temperature, c is that given constant is used for adjustment algorithm annealing temperature, here
Allow c=0.5；N is to need the number of plies of regulating the speed；
5th parameter is stochastic variable x, and for vector of regulating the speed, it is as follows to specifically give formula：
WithFor the minimax boundary value of the i-th interval velocity, whereinX is stochastic variable, produces x
Expression formula is as follows：
Wherein sgn is sign function, and x spans are between [- 1,1]；
6th parameter is acceptance probability, and as E (V ') >=E (V), V ' replacements V is as current optimal solution, as E (V ') ＜ E
(V) when, with probability
Substitute current optimal solution, wherein TkTemperature value during iteration secondary for kth.
Simulated annealing calculating parameter stopping criterion for iteration is：
A, Simulated annealing is reduced to lowest set temperature Tmin；
B, perforation spot placement accuracy reaches setting value；
C, when energy value reaches certain value at shooting point, iterate to calculate still without being substituted, pass through by long period T
Above-mentioned parameter is adjusted, to reach the balance of computational accuracy and computational efficiency.
Beneficial effect：In existing velocity model corrections method, most of method is in accordance with perforation positioning precision
Judge whether rate pattern is accurate.The higher geographical rate pattern for illustrating rate pattern closer to reality of perforation positioning precision,
Accurate rate pattern can position for follow-up micro-seismic event and provide good foundation.The present invention is superimposed in inverse time amplitude excursion
Simulated annealing is used on the basis of algorithm, can effectively overcome maximum and maximum existing for other existing algorithms not
Situation about dividing, accurately finds Voice segment maximum E, is accurately positioned perforating site, effective correction rate model.Using inverse
When amplitude excursion superposition algorithm can effectively suppress noise jamming, preferable positioning can be still obtained in the case where signal to noise ratio is relatively low
Effect.The present invention need not pick up seismic phase first break information, by monitoring Voice segment situation at shooting point, carry out rate pattern school
Just.Because for rate pattern closer to actual geographic model, the positioning of its perforation will be more accurate.Essence can be relocated according to shooting point
Degree, judges whether rate pattern can be used for follow-up microseism to position.
Brief description of the drawings：
The ground observation microseism velocity model corrections method flow diagram that Fig. 1 is superimposed based on amplitude；
Fig. 2 wave detectors are structured the formation and shooting point forward simulation figure；
The waveform synthetic data result figures of Fig. 3 (a) 96；
Fig. 3 (b) utilizes ripple stack result figure at initial velocity model shooting point；
Addition of waveforms result figure at shooting point after the correction of Fig. 3 (c) this paper algorithms；
Fig. 4 (a), (b) are to shooting point positioning result figure using initial velocity model；
Fig. 4 (c), (d) carry out positioning result figure after the inventive method corrects to perforation；
96 track data composite result figures after Fig. 5 superposition Gaussian noises；
Addition of waveforms comparative result figure at Fig. 6 shooting points；
Positioning result figures of the Fig. 7 (a) in X-Y plane；
Positioning result figures of the Fig. 7 (b) in X-Z plane.
Embodiment：
The present invention is described in further detail with reference to the accompanying drawings and examples：
Based on the ground observation microseism velocity model corrections method of amplitude superposition, comprise the following steps：
A, three-dimensional target region is established centered on shooting point, selects reference channel M；
Initial temperature T0, minimum temperature Tmin, dwell time T, simulated annealing calculating parameter are set b,；
D, initial velocity model is established, defines E (V)=0；
E, initial velocity vector V is obtained, reads perforation data；
F, travel-time difference of each road relative to library track is calculated；
G, each track data is translated and be superimposed, obtain Energy maximum value E and its coordinate under existing rate pattern；
H, E value is assigned to E (V)；
I, E (V) coordinate dead time reaches T；
J, energy is the coordinate at (V) place as the perforation elements of a fix；
K, whether meet perforation positioning precision, be；
L, terminate.
Simulated annealing calculating parameter setting described in step b, is the characteristics of observation according to ground array microseism, sets
Six simulated annealing calculating parameters：
First parameter is velocity vector V, V=[Vp1,Vp2,Vp3,...,Vpn],Vpi
For i-th layer of p wave interval velocity, initial velocity vector V is just obtained according to well-log information；
Second parameter is object function E (V), and in log data, selection is any to be used as library track M together, using penetrating
The method of line tracking asks for theoretical travel-time difference of other each roads relative to the library track：
Δtcal=[t1-tM,t2-tM,...,tN-tM] (1)
The perforation wave recording obtained according to the theoretical travel-time difference to each road wave detector carries out reverse-time migration superposition, is superimposed energy
It is as follows to measure (object function) mathematic(al) representation：
Wherein A is amplitude of vibration size of i-th of volume elements at the jth moment, and the center point coordinate of i-th of volume elements is (xi,yi,zi),
M is wave detector number, and N is time window length；
3rd parameter is simulated annealing initial temperature T0, it is as follows to obtain the solution method of initial temperature, first to initial temperature
One very little of degree on the occasion of the number that a perseverance is more than 1 being then constantly multiplied by, until meeting that the acceptance probability of any model is approached
Untill 1；
4th parameter is annealing cooling parameter, extremely fast simulated annealing cooling profiles such as following formula：
Tk=T0exp(-ck1/2N) (3)
Wherein k is iterations, T0For initial annealing temperature, c is that given constant is used for adjustment algorithm annealing temperature, here
Allow c=0.5；N is to need the number of plies of regulating the speed；
5th parameter is stochastic variable x, and for vector of regulating the speed, it is as follows to specifically give formula：
WithFor the minimax boundary value of the i-th interval velocity, whereinX is stochastic variable, is produced
X expression formulas are as follows：
Wherein sgn is sign function, and x spans are between [- 1,1]；
6th parameter is acceptance probability, and as E (V ') >=E (V), V ' replacements V is as current optimal solution, as E (V ') ＜ E
(V) when, with probability
Substitute current optimal solution, wherein TkTemperature value during iteration secondary for kth.
Simulated annealing calculating parameter stopping criterion for iteration is：
A, Simulated annealing is reduced to lowest set temperature Tmin；
B, perforation spot placement accuracy reaches setting value；
C, when energy value reaches certain value at shooting point, iterate to calculate still without being substituted, pass through by long period T
Above-mentioned parameter is adjusted, to reach the balance of computational accuracy and computational efficiency.
Embodiment 1：
Clear, complete description is carried out to the present invention with simulated formation model below in conjunction with the accompanying drawings.Specific implementation step is such as
Under：
A, as shown in Fig. 2 stratigraphic model and perforation forward modeling process schematic, ground acquisition station arranges into star shapes, and totally 6
Bar survey line, 16 wave detectors of every survey line, altogether 96.First arrival time difference observation in model calculating is by true to stratigraphic model
Value carries out forward modeling ray tracing and calculates acquisition, and waveform, each road Ricker wavelet amplitude maximum are described using 10Hz Ricker wavelet
For 1.The three-dimensional coordinate defined at shooting point is Xs=236m, Ys=-158m, Zs=-947m, and defined centered on shooting point
One sufficiently large three-dimensional target region.
B, needed target area being divided into many size identical volume elements according to positioning.In this experiment by target area
The volume elements that the length of side is 10m is divided into, each volume elements is considered as the potential site point that a micro-seismic event occurs.Set initial
Temperature T0, minimum temperature TminWith maximum dead time Ts。
C, 96 Wave datas are simulated according to stratigraphic model, shown in Data Synthesis result such as Fig. 3 (a), and provides initial speed
Model is spent, initial velocity vector is V=[800,1000,1700,2200,2700], wherein 1~5 layer of velocity amplitude is followed successively by；
800m/s,1000m/s,1700m/s,2200m/s,2700m/s。
Select to be used as library track any one in 96 track datas, using the method for ray tracing according to formula (1)
Δtcal=[t1-tM,t2-tM,...,tN-tM] (1)
Ask for theoretical travel-time difference Δ t of other each roads relative to the library trackcal, under the rate pattern by remaining 95
T is translated on data time1-tM, row amplitude of going forward side by side superposition.All volume elements are traveled through, the region self-energy is obtained and focuses on maximum E,
And the coordinate of Voice segment maximum of points.
D, speed adjustment is carried out to destination layer using extremely fast simulated annealing.Initial annealing temperature T is set0, by formula (3)
Temperature T after annealing is calculatedk, regulated the speed model according to formula (4), (5), shooting point carried out under new rate pattern and is reset
Position：
By formula：Tk=T0exp(-ck1/2N) (3)
Temperature T after annealing is calculatedk, c=0.5 is set, and k is iterations, is first the geologic structure number of plies for 1, N, N
=5.According to formula：
Stochastic variable x is calculated, further according to following formula：
Regulate the speed model, whereinWithFor the minimax boundary value of the i-th interval velocity,For former rate pattern,For the rate pattern after adjustment, shooting point reorientation is carried out under this rate pattern；
E, all volume elements are traveled through, find the Voice segment maximum E (V) under new rate pattern, and are compared with E, if E (V)
＞ E, then using new Energy maximum value E (V) as the object function in extremely fast simulated annealing method, if E (V) ＜ E, E (V)
With probability P alternative objective function.Wherein probability P calculation formula is：
E (V) is former Energy maximum value, and E (V') is the energy value currently calculated.
F, after simulated annealing terminates, if perforation positioning precision meets the requirements, show that rate pattern now more connects
Nearly actual geographic rate pattern, or the true geographical rate pattern of Approximate Equivalent, can be used for follow-up micro-seismic event positioning.
If perforation positioning precision is unsatisfactory for required precision, illustrate that rate pattern now is larger compared with actual geographic rate pattern error, then
Also need to change initial temperature T0, carry out temper and regulate the speed model, untill perforation position error is sufficiently small, i.e. speed
The close enough actual geographic rate pattern of model.
Velocity model corrections flow is as shown in Figure 1.
(b) and (c) in Fig. 3 is that the result obtained after the inventive method calculates with first break pickup method is respectively adopted, from
The addition of waveforms result that it can be seen from the figure that is calculated using the rate pattern of the inventive method structure is more preferable, and Fig. 4 is difference
Rate pattern after being corrected using initial velocity model and the inventive method carries out the result of perforation positioning, can from figure
Go out, the rate pattern after the inventive method corrects can obtain higher perforation positioning precision.
In order to verify that the method for the present invention still has preferable positioning precision in the case of compared with low signal-to-noise ratio, in Fig. 3
(a) Gaussian noise that signal to noise ratio is S/N=0.1 is added in data, the generated data added after noise is as shown in figure 5, Fig. 6 is
The result obtained after the inventive method calculates with first break pickup method is respectively adopted, as can be seen from the figure using the inventive method
The addition of waveforms result that the rate pattern of structure is calculated is more preferable.Be respectively adopted the inventive method correction after rate pattern and
Initial velocity model carries out perforation positioning, and positioning result is as shown in fig. 7, as can be seen from the figure the inventive method has well
Noise resisting ability, preferable positioning result can be obtained in the case of low signal-to-noise ratio.Above test result indicates that, using this hair
Bright algorithm can effectively improve perforation positioning precision, and perforation is set to that precision is higher, illustrate the rate pattern after correction closer to
Actual geographical rate pattern.Good rate pattern provides more accurate foundation for follow-up microseism positioning.
Claims (3)
- A kind of 1. ground observation microseism velocity model corrections method based on amplitude superposition, it is characterised in that including following step Suddenly：A, three-dimensional target region is established centered on shooting point, selects reference channel M；Initial temperature T is set b,0, minimum temperature Tmin, dead time T, simulated annealing calculating parameter；D, initial velocity model is established, defines E (V)=0；E, initial velocity vector V is obtained, reads perforation data；F, travel-time difference of each road relative to library track is calculated；G, each track data is translated and be superimposed, obtain Energy maximum value E and its coordinate under existing rate pattern；H, E value is assigned to E (V)；I, E (V) coordinate dead time reaches T；J, energy is the coordinate at V as the perforation elements of a fix；K, whether meet perforation positioning precision, be；L, terminate.
- 2. according to the ground observation microseism velocity model corrections method based on amplitude superposition described in claim 1, its feature It is, the simulated annealing calculating parameter setting described in step b, is the characteristics of observation according to ground array microseism, sets six Individual simulated annealing calculating parameter：First parameter is velocity vector V, V=[Vp1,Vp2,Vp3,...,Vpn],VpiFor i-th layer of p wave interval velocity, initial velocity vector V is just obtained according to well-log information；Second parameter is object function E (V), and in log data, selection is any to be used as library track M together, is chased after using ray The method of track asks for theoretical travel-time difference of other each roads relative to the library track：Δtcal=[t1-tM,t2-tM,...,tN-tM] (1)The perforation wave recording obtained according to the theoretical travel-time difference to each road wave detector carries out reverse-time migration superposition, stack power mesh The mathematic(al) representation of scalar functions is as follows：<mrow> <mi>E</mi> <mrow> <mo>(</mo> <mi>V</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mo>&lsqb;</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <mi>A</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>&rsqb;</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>Wherein A is amplitude of vibration size of i-th of volume elements at the jth moment, and the center point coordinate of i-th of volume elements is (xi,yi,zi), M is Wave detector number, N are time window length；3rd parameter is simulated annealing initial temperature T0, it is as follows to obtain the solution method of initial temperature, first to initial temperature one Very little on the occasion of the number that a perseverance is more than 1 being then constantly multiplied by, until meeting to be close to 1 to the acceptance probability of any model Only；4th parameter is annealing cooling parameter, extremely fast simulated annealing cooling profiles such as following formula：Tk=T0exp(-ck1/2N) (3)Wherein k is iterations, T0For initial annealing temperature, c is that given constant is used for adjustment algorithm annealing temperature, allows c=here 0.5；N is to need the number of plies of regulating the speed；5th parameter is stochastic variable x, and for vector of regulating the speed, it is as follows to specifically give formula：Vi k+1=Vi k+x*(Vi max-Vi min) (4)Vi maxWith Vi minFor the minimax boundary value of the i-th interval velocity, wherein Vi∈[Vi min,Vi max], x is stochastic variable, produces x Expression formula is as follows：<mrow> <mi>x</mi> <mo>=</mo> <mi>sgn</mi> <mrow> <mo>(</mo> <mi>&mu;</mi> <mo>-</mo> <mn>0.5</mn> <mo>)</mo> </mrow> <msub> <mi>T</mi> <mi>k</mi> </msub> <mo>&lsqb;</mo> <msup> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <mfrac> <mn>1</mn> <msub> <mi>T</mi> <mi>k</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mrow> <mo>|</mo> <mn>2</mn> <mi>&mu;</mi> <mo>-</mo> <mn>1</mn> <mo>|</mo> </mrow> </msup> <mo>-</mo> <mn>1</mn> <mo>&rsqb;</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>Wherein sgn is sign function, and x spans are between [- 1,1]；6th parameter is acceptance probability, and as E (V ') >=E (V), V ' replacements V is as current optimal solution, as E (V ') ＜ E (V) When, with probability<mrow> <mi>P</mi> <mrow> <mo>(</mo> <mi>V</mi> <mo>&RightArrow;</mo> <msup> <mi>V</mi> <mo>&prime;</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <mi>exp</mi> <mo>&lsqb;</mo> <mfrac> <mrow> <mi>E</mi> <mrow> <mo>(</mo> <mi>V</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>E</mi> <mrow> <mo>(</mo> <msup> <mi>V</mi> <mo>&prime;</mo> </msup> <mo>)</mo> </mrow> </mrow> <msub> <mi>T</mi> <mi>k</mi> </msub> </mfrac> <mo>&rsqb;</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>Substitute current optimal solution, wherein TkTemperature value during iteration secondary for kth.
- 3. according to the ground observation microseism velocity model corrections method based on amplitude superposition described in claim 2, its feature It is, simulated annealing calculating parameter stopping criterion for iteration is：A, Simulated annealing is reduced to lowest set temperature Tmin；B, perforation spot placement accuracy reaches setting value；C, when energy value reaches certain value at shooting point, iterated to calculate by long period T still without being substituted, pass through adjustment Above-mentioned parameter, to reach the balance of computational accuracy and computational efficiency.
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| CN107132578B (en) * | 2017-04-06 | 2019-06-18 | 吉林大学 | A kind of microseism ground monitoring velocity model corrections algorithm |
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