CN107588878A - A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features - Google Patents

A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features Download PDF

Info

Publication number
CN107588878A
CN107588878A CN201711059839.2A CN201711059839A CN107588878A CN 107588878 A CN107588878 A CN 107588878A CN 201711059839 A CN201711059839 A CN 201711059839A CN 107588878 A CN107588878 A CN 107588878A
Authority
CN
China
Prior art keywords
mrow
points
kaiser
stress
rock
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.)
Pending
Application number
CN201711059839.2A
Other languages
Chinese (zh)
Inventor
赵康
顾水杰
严雅静
张华林
张俊萍
黎强
朱胜唐
王庆
赵奎
肖婉琪
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jiangxi University of Science and Technology
Original Assignee
Jiangxi University of Science and Technology
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Jiangxi University of Science and Technology filed Critical Jiangxi University of Science and Technology
Priority to CN201711059839.2A priority Critical patent/CN107588878A/en
Publication of CN107588878A publication Critical patent/CN107588878A/en
Pending legal-status Critical Current

Links

Abstract

A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, carries out the axle Experimental on acoustic emission of rock three, obtains rock sample in the actual triaxial stress state numerical value in underground;The interpretation of Kaiser points is carried out with accumulative Ring-down count time graph;Accumulative sound emission Ring-down count is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process;The fractal characteristic of rock is analyzed using the Ring-down count correlation dimension of sound emission;The time of Kaiser points is picked up, the stress value corresponding to reading on stress time curve, stress now is exactly rock sample axial direction history maximum crustal stress.The present invention determines the time range of Kaiser points appearance using improved tangent line graphing method, Treatment Analysis is carried out to test data based on fractal theory knowledge again, then the time that Kaiser points occur is locked, the stress value at Kaiser points is finally read from stress time curve, so as to realize the accurate easy interpretation to Kaiser points.

Description

A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features
Technical field
It is a kind of base the present invention relates to the interpretation method technical field of Acoustic Emission of Rock test measurement crustal stress kasier points The more accurate interpretation method of kasier effect points is tested to Acoustic Emission of Rock in fractal theory knowledge.
Background technology
Acoustic-emission is a kind of direct earth stress measuring method, and crustal stress is measured according to rock kaiser effects, with Traditional method of testing is compared because its is simple and convenient, cheap, and be adapted to indoor extensive batch testing and by wide both at home and abroad General use.But in the interpretation for obtaining Kaiser points with acoustic-emission, also there is some shortcomings.
The big multipair rock sample of Acoustic Emission of Rock experiment at present carries out conventional one-axis compression test, it is impossible to reflects rock mass well The occurrence status of three received strength in underground, cause the Kaiser point values that measure more relatively low than actual value.
The interpretation of Kaiser points is also the key of acoustic-emission measurement crustal stress.The interpretation of current Kaiser points is typically all By the changes of acoustic emission signal some or multiple parameters drastically degree, to determine position that Kaiser points occur.It is conventional Interpretation method have two kinds, a kind of is by some parameter of sound emission and the direct interpretation of the relation of time, sees Fig. 1.This method Foundation be whether to have the generation of a large amount of sound emissions after some time point.But there is no quantitative mark for a large amount of sound emissions Standard, interpretation have certain subjectivity, the more difficult assurance degree of accuracy in application.Another method be according to sound emission some is tired The rate of change drastically change point interpretation of parameter and the relation curve of time is counted, this method has being easier to for obvious flex point for curve Interpretation.As shown in Figure 2.And then carry out auxiliary interpretation by tangent line for what accumulative parameter flex point obscured, the point of intersection of tangents is defined as Kaiser points, as shown in Figure 3.
Above two is in accordance with data on the increase suddenly or bent of a certain parameter for the interpretation method of Kaiser points The unexpected increase of line slope judges, to the standard of this kind of no Quantitative evaluation of change, when this change unobvious, it is difficult to control Make the error of artificial interpretation.
The content of the invention
The purpose of the present invention is to measure Kaiser points for current acoustic-emission to have the defects of interpretation, and is proposed a kind of Based on the basis of the axle Experimental on acoustic emission of rock three, the method to the accurate easy interpretation of Kaiser points is realized.
The purpose of the present invention is achieved through the following technical solutions:
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, comprises the following steps:
The first step:The axle Experimental on acoustic emission of rock three is carried out, obtains rock sample in the actual triaxial stress state numerical value in underground;
Second step:The interpretation of Kaiser points is carried out with accumulative Ring-down count-time graph;Before Data Management Analysis is carried out The noise reduction process of Acoustic Emission of Rock time series, noise reduction mistake are carried out with the small wave systems of Daubechie to sound emission Ring-down count sequential Journey is divided into following 3 steps:
(1) wavelet decomposition is carried out to primary signal:One can be expressed as containing noisy signal model:
S (j)=f (j)+α e (j), (j=0,1, k, n-1), in formula:S (j) is containing noisy primary signal, f (j) For the actual signal of Acoustic Emission of Rock, e (j) is noise signal;It is original to sound emission using Matlab softwares selection db3 wavelet basis Signal carries out 5 layers of decomposition computation;
(2) to carrying out threshold values quantization containing noisy wavelet coefficient:Using the method noise reduction process of fixed threshold values, valve is chosen Value Q is:
Q=sqrt [2lg (length (y))], in formula:Y represents the signal of analysis;It is noisy small to containing after Wavelet transformation Wave system number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, and the wavelet coefficient more than Q is changed into the difference with Q;
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed;
3rd step, accumulative sound emission ring meter is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process Number;Polynomial of degree n fitting specially is carried out to accumulative Ring-down count-time graph first, then to being cut a little on curve Line, last picked up water flat level and the linear increase section point of intersection of tangents are defined as the time of Kaiser points appearance compared with the region of concentration Scope;
4th step:Other neighbouring points are higher than according to the frequency band energy of Kaiser points, fractal dimension is less than the feature of consecutive points, With reference to the less situation of interpretation noise spot of the accumulative Ring-down count curve to Kaiser points of sound emission, using the ring of sound emission Correlation dimension is counted to analyze the fractal characteristic of rock;According to Grassberger and Procaccia propose from time series meter Calculate the G-P computational methods of the correlation dimension of sequence, using the basic parameter sequence of sound emission as research object, then each sequence The sequence sets that a corresponding sample size is n:
X={ x1,x2,x3,…,xn} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), before taking m number as a m of sample space tie up to Amount:
X1={ x1,x2,x3,…,xm} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form n-m+ altogether 1 m dimensional vector, corresponding correlation function are:
In formula (3), H is Heaviside functions, and r is given yardstick;Take
In formula (4), k is proportionality coefficient;
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension is obtained, these scatterplots are such as Fruit can form straight line on { lnW [r (k)], lnr (k) }, just illustrate that the Acoustic Emission Sequence of sample possesses well under given dimension Fractal characteristic, it is believed that the slope of regression straight line is exactly correlation dimension;Each sample is calculated by above-mentioned G-P algorithms Fractal dimension-when m- stress relation figure;Fractal dimension minimum value is read in the approximate Kaiser points time range of estimated reading The place time, interpretation fractal dimension minimum value to the time be Kaiser points occur time;
5th step:Pick up Kaiser points time, in stress time curve read corresponding to stress value, now should Power is exactly rock sample axial direction history maximum crustal stress.
The present invention determines the time range of Kaiser points appearance using improved tangent line graphing method, then is known based on fractal theory Know and Treatment Analysis is carried out to test data, this of consecutive points is then less than according to the fractal dimension at Acoustic Emission of Rock Kaiser points The time that one feature locking Kaiser points occur, the stress value at Kaiser points is finally read from stress time curve, so as to Realize to the accurately easy interpretation of Kaiser points.The present invention at least has the advantages that:
(1) the indoor axle Experimental on acoustic emission of rock three is carried out, triaxial stress state of the geological diagnostics in underground is preferably gone back, measures Kaiser point datas closer to actual value.
(2) after carrying out noise reduction process to Acoustic Emission of Rock Ring-down count sequential, the accumulative Ring-down count with reference to sound emission is bent The advantages of line is less to the interpretation noise spot of Kaiser points, carry out what interpretation obtained from accumulative Ring-down count-time graph Kaiser points are more accurate;
(3) on the basis of Kaiser point time of occurrences are sentenced according at the beginning of improved traditional tangent line graphing method, with reference to rock sound Launch screen further less than the feature of consecutive points of the fractal dimension at Kaiser points and obtain more accurate Kaiser point values, Reduce the influence of human factor in traditional graphing method.
Brief description of the drawings
Fig. 1 is the Kaiser point interpretations of the acoustic emission parameters of prior art, and the relation with acoustic emission parameters and time is direct The position that interpretation Kaiser points occur;
Fig. 2 is the obvious Kaiser points interpretation of accumulative parameter flex point of prior art, with the accumulative parameter of sound emission and when Between relation curve rate of change drastically change point interpretation Kaiser points occur position;
Fig. 3 is the fuzzy Kaiser point interpretations of the accumulative parameter flex point of prior art, and the point of intersection of tangents is defined as Kaiser Point;
Fig. 4 is that fractal dimension and phase space dimension relation curve are associated in the inventive method.
Fig. 5-1~Fig. 5-12 and Fig. 6-1~Fig. 6-12 is the interpretation of the rock Kaiser points of the present invention, wherein,
Fig. 5-1 is that 225 ° of-1 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-2 is that 225 ° of-2 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-3 is that 225 ° of-3 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-4 is that 270 ° of-1 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-5 is that 270 ° of-2 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-6 is that 270 ° of-3 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-7 is that 315 ° of-1 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-8 is that 315 ° of-2 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-9 is that 315 ° of-3 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-10 is that 90 ° of-1 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-11 is that 90 ° of-2 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 5-12 is that 90 ° of-3 sample of horizontal direction adds up acoustic emission rate-time relationship;
Fig. 6-1 be 225 ° of-1 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-2 be 225 ° of-2 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-3 be 225 ° of-3 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-4 be 270 ° of-1 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-5 be 270 ° of-2 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-6 be 270 ° of-3 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-7 be 315 ° of-1 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-8 be 315 ° of-2 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-9 be 315 ° of-3 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-10 be 90 ° of-1 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-11 be 90 ° of-2 sample of horizontal direction correlation dimension-when m- stress relation curve;
Fig. 6-12 be 90 ° of-3 sample of horizontal direction correlation dimension-when m- stress relation curve.
Embodiment
A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, comprises the following steps:
The first step:The axle Experimental on acoustic emission of rock three is carried out, can preferably reflect rock sample in underground under the experiment of three axle confined pressures Actual triaxial stress state, the data of acquisition are closer to actual value;
Second step:The interpretation of Kaiser points is carried out with accumulative Ring-down count-time graph;Before Data Management Analysis is carried out The noise reduction process of Acoustic Emission of Rock time series, noise reduction mistake are carried out with the small wave systems of Daubechie to sound emission Ring-down count sequential Journey is divided into following 3 steps:
(1) wavelet decomposition is carried out to primary signal:One can be expressed as containing noisy signal model:
S (j)=f (j)+α e (j), (j=0,1, k, n-1), in formula:S (j) is containing noisy primary signal, f (j) For the actual signal of Acoustic Emission of Rock, e (j) is noise signal;It is original to sound emission using Matlab softwares selection db3 wavelet basis Signal carries out 5 layers of decomposition computation;
(2) to carrying out threshold values quantization containing noisy wavelet coefficient:Using the method noise reduction process of fixed threshold values, valve is chosen Value Q is:
Q=sqrt [2lg (length (y))], in formula:Y represents the signal of analysis;It is noisy small to containing after Wavelet transformation Wave system number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, and the wavelet coefficient more than Q is changed into the difference with Q;
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed;
The determination of prior art Kaiser points mainly carries out interpretation using characteristics of Acoustic Emission parameter curve, by different The com-parison and analysis of characteristic parameter curve show that the readability of Kaiser points is followed successively by:Accumulative AE Energy-Time curves > adds up AE rings number-time graph > adds up AE event numbers-time graph.But in graphing method intuitive judgment Kaiser points, add up AE Energy-Times curve map is it is possible that multiple catastrophe points, these noise spots will cause larger to the accuracy of sentence read result Influence;And accumulative AE rings number-time graph influenceed by contrast by this respect it is smaller.Therefore, the present invention is from accumulative Ring-down count-time graph carries out the interpretation of Kaiser points.
Additionally due to inevitably there is the interference of various noises in the gatherer process of Rock Acoustic Emission Signal, in order to Influence of the interference signal to accumulative AE rings number-time graph is further reduced, sound is sent out before Data Management Analysis is carried out Penetrate Ring-down count sequential and carry out noise reduction process.Analyze and test by in-depth study, it is determined that using the method for wavelet analysis, with Useful primary signal is extracted from the acoustic emission signal containing various influence of noises, signal to noise ratio is improved, restores trueer Real acoustic emission signal data.Simultaneously for the feature of Rock Acoustic Emission Signal, different types of wavelet function is integrated Comparative analysis and experiment, it is determined that carrying out the noise reduction process of Acoustic Emission of Rock time series with the small wave systems of Daubechie;
3rd step, accumulative sound emission ring meter is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process Number.When determining Kaiser point positions with the mapping of prior art tangential method, big more options level of approximation straightway and linear increase Section makees two tangent lines respectively, and the intersection point of tangent line is defined as to the position of Kaiser points appearance.During the mapping of reality, tangent line The selection of position is larger by the interference of people's subjective factor, the Kaiser points position finally determined often vary with each individual exist it is larger Human error.The present invention makes some improvement using Matlab softwares to conventional tangent line graphing method, first to adding up ring meter Number-time graph carries out polynomial of degree n fitting, then to doing tangent line, last picked up water flat level and line on curve a little Property increase the section point of intersection of tangents compared with the region of concentration be defined as Kaiser points appearance time range;
4th step:Numerous studies show that the frequency band energy of Kaiser points is higher than other neighbouring points, and fractal dimension is less than adjacent Point.According to this feature of Kaiser effects, with reference to interpretation interference of the accumulative Ring-down count curve to Kaiser points of sound emission The less situation of point, the fractal characteristic of rock is analyzed using the Ring-down count correlation dimension of sound emission.According to Grassberger With Procaccia propose the correlation dimension from the time series sequence of calculation G-P computational methods, with the basic parameter of sound emission Sequence answers the sequence sets that a sample size is n as research object, then each sequence pair:
X={ x1,x2,x3,…,xn} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), before taking m number as a m of sample space tie up to Amount:
X1={ x1,x2,x3,…,xm} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form n-m+ altogether 1 m dimensional vector.Corresponding correlation function is:
In formula (3), H is Heaviside functions, and r is given yardstick.In order to control the discreteness of result of calculation typically to take
In formula (4), k is proportionality coefficient;
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension can be obtained, these dissipate If point can form straight line on { lnW [r (k)], lnr (k) }, just illustrate that the Acoustic Emission Sequence of sample possesses under given dimension Good fractal characteristic, it is believed that the slope of regression straight line is exactly correlation dimension.Each is calculated by above-mentioned G-P algorithms Sample fractal dimension-when m- stress relation figure.Fractal dimension is read in the approximate Kaiser points time range of estimated reading most Time where small value, interpretation fractal dimension minimum value institute is to time that the time is the appearance of Kaiser points;
5th step:The time of Kaiser points is picked up, the stress value corresponding to reading in stress time curve, it is believed that now Stress be exactly sample axial direction history maximum stress level.
Using the inventive method, certain large-scale mine has carried out geostress survey experiment at home.Embodiment specifically describes such as Under:
The first step:Live coring.This is tested is in exploitation stage casing scene core-drilling, direction where institute's coring axis Close to 90 ° perpendicular to the ground, 225 °, 270 °, the four directions such as 315 ° of horizontal direction, core diameter is in 50mm or so.
Second step:Sample is processed.To ensure the integrality and homogenieity of rock, in manufactured 47 examinations of this experiment 12 close samples of velocity of wave are chosen in sample to be tested.Specimen size is that the ratio of height to diameter of Pass Test code is 2:1 cylinder Shape sample.The specifying information of sample is shown in Table 1.
The Experimental on acoustic emission sample information table of table 1
3rd step:Test apparatus and parameter setting.Indoor emission experiment needs to use RMT-150C rock mechanics experiments system System and SAEU2S type Full wave shape multiple channel acousto emission detectors carry out the loading of triaxial test and the collection of acoustic emission signal respectively. Two systems coordinate the change that can gather and record basic variable and parameter during testing, and automatically generate each parameter Graph of a relation.
The U-shaped probe of resonance that Acoustic Emission Testing System is 1000kHz with centre frequency, data acquisition is selected during data analysis Complete passage is as research sample.Acoustic emission parameters are shown in Table 2.
The sound emission acquisition parameter of table 2 is set
Threshold value Preamplification gain Analog filter lower limit The analog filter upper limit Sample rate Sampling length
40dB 40dB 100KHz 3MHz 1MSPS 2k
4th step:Using above-mentioned Acoustic Emission of Rock testing equipment, 12 samples of processing are tested, acquisition sound hair Penetrate stimulus.Db3 wavelet basis is selected using Matlab softwares, using the form of fixed threshold values to sound emission Ring-down count sequential Carry out noise reduction process.Sound emission is calculated according to the data after noise reduction process and adds up Ring-down count rate, is first drawn out corresponding tired The relation curve of Ring-down count rate-time is counted, then makees tangent line to every bit on curve, pickup level of approximation straightway and linear increasing The long section point of intersection of tangents is compared with the time range that the region of concentration is that Kaiser points occur.
5th step:The Ring-down count that whole sound emission process is calculated using G-P algorithms associates fractal dimension.By G-P algorithms Process understand that association fractal dimension is influenceed by phase space reconstruction dimension m, so calculating association point calculating each sequence The phase space dimension to be consistent during shape dimension.This just needs first to inquire into phase space dimension with associating the relation of fractal dimension, Phase space dimension corresponding to stable association fractal dimension is selected, to ensure the stability of data.By taking sample 270-2 as an example, meter It is as shown in Figure 4 with the variation tendency for associating fractal dimension that calculation obtains phase space dimension.
From Fig. 4 change curve, taken in phase space dimension and associate the variable gradient of fractal dimension relatively after 4 Steadily, illustrate that sample has good fractal characteristic when Embedded dimensions are 4, therefore take m=4., will when calculating association fractal dimension The parameter that Experimental on acoustic emission obtains takes 1024, i.e. n=1024 as a sequence changed over time, the capacity of sequence.
By G-P algorithms be calculated each sample fractal dimension-when m- stress relation.Each test specimen adds up The relation of acoustic emission rate-time and it is corresponding correlation dimension-when m- stress relation curve such as Fig. 5-1~Fig. 5-12 and Fig. 6-1~ Shown in Fig. 6-12, the time where reading fractal dimension minimum value in the approximate Kaiser points time range of estimated reading, interpretation point Shape dimension minimum value be time that Kaiser points occur to the time, wherein P points are that fractal dimension is minimum in selected time range Point, as Kaiser point, stress value corresponding to the point are the stress of primary rock value of sample axial direction.
Interpretation is carried out to the Kaiser points stress value of each sample, as a result converges into table 3.
The rock sample Kaiser point stress values of table 3
6th step:Three-dimensional ground stress analytical Calculation simultaneously analyzes the accuracy for verifying that the method obtains kasier points.According to following Three formula can utilize the direct stress of three different directions in same level to solve to obtain two principal stresses in horizontal plane Size and Orientation.
The stress value for exploiting three directions of stage casing level is respectively σΙ=9.13MPa, σΙΙ=15.8MPa, σΙΙΙ= 18.13MPa substituting into formula has:
Therefore the size of the maximum horizontal principal stress in exploitation stage casing is σ1=18.63MPa, the size of minimum horizontal principal stress are σ2=8.63MPa.
The factors such as the presence of vertical stress and tectonic activity, superincumbent stratum thickness, temperature, hydraulic pressure are relevant, wherein upper overlying strata Gravity suffered by layer is main influence factor.The large-scale statistics in the whole world shows, in 25~2700m of depth scope It is interior, συIt is about as much as volume-weighted average γ and is equal to 27kN/m3The gravity γ H calculated.Exploit the height of stage casing overlying rock about For 500m.Exploit stage casing estimation vertical stress σG, then have:
σG=γ H=0.027 × 500=13.5MPa
γ is the unit weight of overlying rock in formula, and H is depth
The vertical stress value of sound emission measurement is 11.73Mpa, substantially conforms to overlying rock rule.
Substantial amounts of measured result shows that maximum, the minimum principal stress of world's most area are all distributed in almost horizontal On in-plane, and maximum horizontal principal stress σh,maxWith vertical stress σvRatio typically in the range of 0.5~5.5.With reference to The existing large-scale field data in the world, two horizontal principal stress average σh,avWith vertical principal stress σvRatio σh,avvMostly Number is 0.8~1.5, referring to table 4.
The relation of the countries in the world average level principal stress of table 4 and vertical principal stress
The size that two horizontal principal stress in stage casing are exploited according to the results showed that of 3 direction samples of level is distinguished For σh,max=18.63MPa, σh,min=8.63MPa, average σh,av=13.63MPa.And the experiment knot of vertical principal stress herein Fruit average value is σv=11.73MPa, then understand the horizontal principal stress average of this measuring point and the ratio σ of vertical stressh,avv= 1.16, the ratio σ of maximum horizontal principal stress and vertical principal stressh,maxv=1.59, substantially conform to the statistics rule of geodetic stress Rule.

Claims (1)

1. a kind of easy accurate interpretation method of the geostress survey based on rock kasier point features, it is characterised in that including such as Lower step:
The first step:The axle Experimental on acoustic emission of rock three is carried out, obtains rock sample in the actual triaxial stress state numerical value in underground;
Second step:The interpretation of Kaiser points is carried out with accumulative Ring-down count-time graph;To sound before Data Management Analysis is carried out Transmitting Ring-down count sequential carries out the noise reduction process of Acoustic Emission of Rock time series, noise reduction process point with the small wave systems of Daubechie For following 3 steps:
(1) wavelet decomposition is carried out to primary signal:One can be expressed as containing noisy signal model:
S (j)=f (j)+α e (j), (j=0,1, k, n-1), in formula:S (j) is that f (j) is rock containing noisy primary signal The actual signal of stone sound emission, e (j) are noise signal;Db3 wavelet basis is selected to sound emission primary signal using Matlab softwares Carry out 5 layers of decomposition computation;
(2) to carrying out threshold values quantization containing noisy wavelet coefficient:Using the method noise reduction process of fixed threshold values, threshold values Q is chosen For:
Q=sqrt [2lg (length (y))], in formula:Y represents the signal of analysis;To containing noisy wavelet systems after Wavelet transformation Number and threshold values Q are compared, and will be less than Q wavelet coefficient vanishing, the wavelet coefficient more than Q is changed into the difference with Q;
(3) wavelet coefficient after threshold values quantification treatment is rebuild, the signal for the noise jamming that is removed;
3rd step, accumulative sound emission Ring-down count is calculated with Matlab softwares to the acoustic emission signal data after noise reduction process; Polynomial of degree n fitting specially is carried out to accumulative Ring-down count-time graph first, then to doing tangent line a little on curve, Last picked up water flat level and the linear increase section point of intersection of tangents are defined as the time model of Kaiser points appearance compared with the region of concentration Enclose;
4th step:Other neighbouring points are higher than according to the frequency band energy of Kaiser points, fractal dimension is less than the feature of consecutive points, with reference to The less situation of interpretation noise spot of the accumulative Ring-down count curve to Kaiser points of sound emission, using the Ring-down count of sound emission Correlation dimension analyzes the fractal characteristic of rock;According to what Grassberger and Procaccia was proposed sequence is calculated from time series The G-P computational methods of the correlation dimension of row, using the basic parameter sequence of sound emission as research object, then each sequence pair should The sequence sets that one sample size is n:
X={ x1,x2,x3,…,xn} (1)
Phase space (the m of a m dimension can be constructed by (1) formula<N), a m dimensional vector of the m number as sample space before taking:
X1={ x1,x2,x3,…,xm} (2)
Then one is moved afterwards, then takes m number, forms second vector, and by that analogy, time series can form n-m+1 m altogether Dimensional vector, corresponding correlation function are:
<mrow> <mi>w</mi> <mo>&amp;lsqb;</mo> <mi>r</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> <mo>=</mo> <mfrac> <mn>1</mn> <msup> <mi>N</mi> <mn>2</mn> </msup> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mi>H</mi> <mo>&amp;lsqb;</mo> <mi>r</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>|</mo> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>j</mi> </msub> </mrow> <mo>|</mo> <mo>&amp;rsqb;</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>
In formula (3), H is Heaviside functions, and r is given yardstick;Take
<mrow> <mi>r</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>k</mi> <mfrac> <mn>1</mn> <msup> <mi>N</mi> <mn>2</mn> </msup> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mo>|</mo> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>j</mi> </msub> </mrow> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>
In formula (4), k is proportionality coefficient;
It is various after the processing of MATLAB programs more than, one group of scatterplot under given dimension is obtained, if these scatterplots exist Straight line can be formed on { lnW [r (k)], lnr (k) }, just illustrates that the Acoustic Emission Sequence of sample possesses good point under given dimension Shape feature, it is believed that the slope of regression straight line is exactly correlation dimension;Point of each sample is calculated by above-mentioned G-P algorithms Shape dimension-when m- stress relation figure;In the approximate Kaiser points time range of estimated reading where reading fractal dimension minimum value Time, interpretation fractal dimension minimum value to the time be Kaiser points occur time;
5th step:The time of Kaiser points is picked up, the stress value corresponding to reading in stress time curve, stress now is just It is rock sample axial direction history maximum crustal stress.
CN201711059839.2A 2017-11-01 2017-11-01 A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features Pending CN107588878A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711059839.2A CN107588878A (en) 2017-11-01 2017-11-01 A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711059839.2A CN107588878A (en) 2017-11-01 2017-11-01 A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features

Publications (1)

Publication Number Publication Date
CN107588878A true CN107588878A (en) 2018-01-16

Family

ID=61044662

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711059839.2A Pending CN107588878A (en) 2017-11-01 2017-11-01 A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features

Country Status (1)

Country Link
CN (1) CN107588878A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109100247A (en) * 2018-07-18 2018-12-28 太原理工大学 Class coal petrography stone crustal stress K point test method based on Kaiser effect
CN110514538A (en) * 2019-07-31 2019-11-29 太原理工大学 High-intensitive rock crustal stress K point test method based on Kaiser effect
WO2020248476A1 (en) * 2019-06-10 2020-12-17 华北水利水电大学 Acoustic emission type determination method based on acoustic emission ascending wave band collection parameter

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101162177A (en) * 2007-11-14 2008-04-16 南京银茂铅锌矿业有限公司 Method for measuring ground stress
CN103344493A (en) * 2013-03-29 2013-10-09 安徽理工大学 Measuring method and testing device for stress of primary rock based on sound emission principle
CN106018107A (en) * 2016-05-20 2016-10-12 重庆大学 Method for testing three-dimensional ground stress by aid of acoustic emission processes

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101162177A (en) * 2007-11-14 2008-04-16 南京银茂铅锌矿业有限公司 Method for measuring ground stress
CN103344493A (en) * 2013-03-29 2013-10-09 安徽理工大学 Measuring method and testing device for stress of primary rock based on sound emission principle
CN106018107A (en) * 2016-05-20 2016-10-12 重庆大学 Method for testing three-dimensional ground stress by aid of acoustic emission processes

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
张巧娜: "岩石多因素Kaiser效应特征研究与地应力实测", 《中国优秀硕士学位论文全文数据库工程科技II辑》 *
苗胜军: "《深部硬岩开采岩爆倾向性分析与防治技术》", 31 December 2016, 《冶金工业出版社》 *
赵奎等: "声发射测量地应力综合分析方法与实验验证", 《岩土工程学报》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109100247A (en) * 2018-07-18 2018-12-28 太原理工大学 Class coal petrography stone crustal stress K point test method based on Kaiser effect
CN109100247B (en) * 2018-07-18 2020-11-27 太原理工大学 Coal-like rock ground stress K point testing method based on Kaiser effect
WO2020248476A1 (en) * 2019-06-10 2020-12-17 华北水利水电大学 Acoustic emission type determination method based on acoustic emission ascending wave band collection parameter
CN110514538A (en) * 2019-07-31 2019-11-29 太原理工大学 High-intensitive rock crustal stress K point test method based on Kaiser effect

Similar Documents

Publication Publication Date Title
CN107588878A (en) A kind of easy accurate interpretation method of the geostress survey based on rock kasier point features
CN103670388B (en) A kind of evaluation method of organic carbon content of shale
CN102373923B (en) Reservoir stratum identification method
JP2007517201A (en) Earth electromagnetic wave resistivity measuring method and apparatus
WO2017084454A1 (en) Stratum component optimization determination method and device
CN103678778B (en) Method for radioactive geophysical and geochemical exploration information integration
CN110032975A (en) A kind of pick-up method of seismic phase
CN103698811A (en) Carbonate rock structure ingredient well logging quantitative recognition method and purpose thereof
CN106991509A (en) Log Forecasting Methodology based on radial basis function neural network model
CN107016620A (en) A kind of Assessment of Water-bearing Fault method based on step analysis
CN107367480A (en) Silicon dioxide content test method in Anshan type iron mine based on thermal infrared spectrum
CN105182421B (en) A kind of method of quantitative assessment stratum Brittleness
CN103197348A (en) Method using internal samples at reservoirs to carry out weighting and compile logging crossplot
CN103201649A (en) Method and system for pulse neutron capture sigma inversion
CN100485412C (en) Method for controlling field earthquake prospecting collection process
CN105549101A (en) Transient electromagnetic data differential conductance explanation method
CN104977602B (en) A kind of control method and device of earthquake data acquisition construction
CN108680950B (en) A kind of desert seismic signal method for detecting position based on Self-adaptive Block Matching
CN106777707B (en) Method for quantitatively identifying well logging lithology by using improved spider web diagram
CN110095161A (en) A kind of acquisition system and its method for geological environment exploration
CN113216945A (en) Permeability quantitative evaluation method for tight sandstone reservoir
CN112084672B (en) Method for judging groundwater pollution based on fractal dimension
CN110441823B (en) Stratum contrast uncertainty visualization method based on multi-source data fusion
CN112100930B (en) Formation pore pressure calculation method based on convolutional neural network and Eaton formula
CN108875109B (en) Method and system for predicting abnormal formation pressure

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20180116