CN117647342B - Coal reservoir ground stress determination method based on acoustic emission wavelet analysis - Google Patents
Coal reservoir ground stress determination method based on acoustic emission wavelet analysis Download PDFInfo
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Abstract
The invention discloses a coal reservoir ground stress measuring method based on acoustic emission wavelet analysis, which comprises the following steps: intercepting a full-diameter core sample, and performing wave velocity measurement on the full-diameter core sample to establish a sample space rectangular coordinate system; after obtaining a directional rock sample by adopting a four-direction coring method, carrying out a coal rock compression acoustic emission experiment on the directional rock sample to obtain a full stress-strain curve and acoustic emission signal data of the coal sample; based on wavelet analysis of acoustic emission signal data, identifying apparent Kaiser points, and further obtaining stress values in corresponding directions; determining in-situ stress of the coal reservoir; according to the invention, wavelet analysis of acoustic emission signals is introduced, the defect that acoustic emission signals of different types are difficult to calculate accurately in a mathematical model can be overcome, meanwhile, based on the principle and advantages of wavelet analysis, the apparent Kaiser point is accurately identified, wavelet transformation analysis is carried out under different wavelet coefficients, the spectral energy distribution of different scales is obtained, the accurate position of the apparent Kaiser point is comprehensively judged, and further, the stress value of the corresponding direction is obtained.
Description
Technical Field
The invention relates to the technical field of coal reservoir ground stress determination method based on acoustic emission wavelet analysis.
Background
The method for measuring the ground stress of the coal reservoir can be divided into two main types in principle, namely direct measurement and indirect measurement. The direct measurement method is to directly measure and record various stresses through coal and rock fracture by a measuring instrument, and determine the stress value of the coal reservoir through calculation by the correlation between the stress values and the stress of the coal reservoir; the indirect measurement method is to determine the stress state of the medium by measuring the deformation of the coal and rock, measure and record the change of some indirect physical quantity related to the stress in the coal and rock by means of some sensing elements or some mediums, such as the deformation, density, permeability, water absorption change and the like of the coal and rock, and further calculate the stress value of the coal reservoir by a known formula.
Direct measurement methods are intuitive and accurate, and have wide application, wherein the developed methods comprise hydraulic fracturing methods, geophysical well logging methods and acoustic emission methods. The hydraulic fracturing method and the geophysical well logging method are carried out firstly in a drilling and completion project, and then the ground stress of a target reservoir is obtained through the fracturing project or the well logging method, so that the whole process is high in cost and relatively complex, and large-scale prediction is difficult to realize in the early stage of coal bed gas exploration and development. Moreover, the principle of the hydraulic fracturing method is based on the elastic mechanical plane strain theory, and the rock homogeneity, isotropy and linear elasticity are assumed, and the water injection axial direction is one of the main stress directions, so that the stress direction cannot be accurately obtained, and the accuracy of the obtained horizontal maximum main stress is poor; the logging method is complex in implementation method, has the problem of multiple solutions, and is large in error of the ground stress value obtained by combining a traditional mathematical model, and low in reliability.
The acoustic emission method is based on the Kaiser effect in acoustic emission activity, however, in the prior art, the uncertainty of obtaining the Kaiser effect point is caused due to two factors, so that the error of ground stress prediction is brought, and the error is mainly:
the conventional analysis method relies on human judgment and reading, and has difficulty and uncertainty in the process of analyzing the acoustic emission signal characteristics and Kaiser effect. The accuracy of the conventional analysis method depends on the integrity of the sample, the complexity of the experimental process and the acoustic emission signal, the application effect on the acoustic emission signal is simple and accords with the classical rule, however, in the practical situation, the acoustic emission signal of most samples is complex, and the acquired result is not an accurate Kaiser point due to the error of the interference signal and the manual reading.
In addition, the Kaiser point is unique, the apparent Kaiser point is not unique, and different apparent Kaiser points correspond to stress values of different periods in the geological evolution process, wherein one apparent Kaiser point is the ground stress nowadays, the point is often difficult to identify among a plurality of steep increase points, and the difficulty and the error for determining the point are large, so that the deviation between the ground stress predicted value and the actual value is large. Therefore, the requirement of accurately predicting the ground stress cannot be met by only analyzing the acoustic emission signal by the existing conventional method.
Disclosure of Invention
The invention aims to provide a coal reservoir ground stress measuring method based on acoustic emission wavelet analysis, which aims to solve the technical problems in the prior art.
In order to solve the technical problems, the invention specifically provides the following technical scheme:
a coal reservoir ground stress measuring method based on acoustic emission wavelet analysis comprises the following steps:
intercepting a full-diameter core sample according to the principle that the axial direction of the sample is consistent with the vertical direction of an in-situ reservoir, measuring the wave velocity of the full-diameter core sample to establish a sample space rectangular coordinate system, and measuring the magnetic declination to determine the included angle of the natural remanence direction of the sample relative to a 0-degree mark line of the sample space rectangular coordinate system; taking a sample space rectangular coordinate system as a reference, performing a coal rock compression acoustic emission experiment on the directional rock sample after the directional rock sample is obtained by adopting a four-direction coring method to obtain a full stress-strain curve of the coal sample and acoustic emission signal data;
based on wavelet analysis of acoustic emission signal data, identifying apparent Kaiser points, and further obtaining stress values in corresponding directions;
Based on the positive stresses corresponding to different directions, the vertical main stress, the horizontal maximum main stress, the horizontal minimum main stress and the horizontal maximum main stress of the in-situ of the coal reservoir are calculated and determined by adopting an acoustic emission method to predict the ground stress mathematical model, so that the in-situ ground stress of the coal reservoir is determined.
Further, the concrete method for establishing the sample space rectangular coordinate system comprises the following steps:
carrying out wave velocity measurement and calculation on the full-diameter core to obtain P wave velocities in different radial directions, thereby obtaining the characteristic of wave velocity anisotropy of the full-diameter core;
according to the basic principle of wave velocity and stress distribution, determining that the direction with the maximum radial wave velocity is the direction of the approximate horizontal minimum main stress, and the direction with the minimum radial wave velocity is the direction of the approximate horizontal maximum main stress;
and establishing a sample space rectangular coordinate system of the full-diameter core sample, wherein an X axis is an approximately horizontal maximum principal stress direction and is marked as 0 degrees, a Y axis is an approximately horizontal minimum principal stress direction and is marked as 90 degrees, and a Z axis is a core axis.
Further, the specific method for determining the included angle between the natural remanence direction of the sample and the 0-degree mark line comprises the following steps:
Carrying out alternating demagnetization or thermal demagnetization cleaning on the paleomagnetic core, measuring magnetic bias angles, magnetic inclination angles and magnetization intensity of each sample under different temperatures and different magnetic field intensities of a space rectangular coordinate system on an alternating demagnetization instrument or a thermal demagnetization instrument, and carrying out statistical calculation to obtain the magnetic bias angle of natural remanence of the full-diameter core sample, wherein the magnetic bias angle is recorded as an included angle beta 1 of the natural remanence direction of the in-situ coal rock relative to a 0-degree mark line; determining a magnetic declination angle beta 2 of the in-situ coal rock sampling site relative to the geographic north; determining the azimuth of the horizontal maximum principal stress according to the azimuth relation between the azimuth beta of the 0-degree mark line relative to the geographic north pole and the azimuth alpha of the horizontal maximum principal stress relative to the geographic north pole; ；/>; and the included angle between the horizontal maximum principal stress direction and the 0 degree mark line in the space rectangular coordinate system is theta. Further, the four-direction coring method includes vertical axial direction, horizontal direction 0 °,45 °, and 90 °.
Further, a uniaxial compression mode is adopted for the coal rock compression acoustic emission experiment of the directional rock sample, and the specific method comprises the following steps:
attaching strain sensors to two sides of each directional rock sample, wherein the two strain sensors are respectively vertical and parallel to the long axis of the directional rock sample, and the planes are 180 degrees apart to respectively measure the axial deformation and the radial deformation of the directional rock sample;
Attaching an acoustic emission probe to the surface of the directional rock sample, and collecting acoustic emission signals;
Applying axial pressure to the directional rock sample, and determining the loading rate by adopting a displacement control mode;
And synchronously monitoring the axial deformation, radial deformation, acoustic emission signals and time of the directional rock sample until the directional rock sample is destroyed, and simultaneously stopping loading and acoustic emission monitoring to complete the experimental process.
Further, the specific method for identifying the apparent Kaiser point based on wavelet analysis of acoustic emission signal data comprises the following steps:
the specific method for identifying the apparent Kaiser point based on wavelet analysis of acoustic emission signal data comprises the following steps:
Carrying out one-dimensional continuous wavelet transformation on acoustic emission signal data of each directional rock sample, carrying out wavelet transformation analysis under different wavelet coefficients, and obtaining spectrum energy distribution characteristics of different scales, wherein the energy distribution characteristics corresponding to different coefficients are similar but have different distribution ranges;
Comparing and analyzing wavelet transformation results under different wavelet coefficients, selecting an optimal wavelet coefficient and a corresponding energy spectrogram, analyzing energy release characteristics of the whole compression process based on the energy spectrogram, analyzing and identifying important energy release time nodes, wherein the Kaiser point is generally positioned in an elastic deformation stage and has abnormal energy release phenomenon, and then comprehensively judging the accurate position of the Kaiser point according to the distribution characteristics of the full stress-strain curve and acoustic emission signal data and abnormal signals.
Further, for deterministic stationary signals:
Applying Fourier transform to acoustic emission signal data to express a frequency domain, wherein a Fourier transform formula is as follows: ; in the/> As a function/>Fourier transform of/>As a function of the origin of the function,I is a calculated parameter, lambda is frequency, and t is time, which is a complex exponential function. Dividing acoustic emission signal data into small time intervals by short-time Fourier transform, analyzing each small time interval by short-time Fourier transform, and determining the frequency existing in the time interval to achieve the purpose of analyzing local signals, wherein the short-time Fourier transform function is as follows:；
In the method, in the process of the invention, As a sliding window function,/>For/>Conjugated function of/>The position of the sliding window is indicated as a translation factor. Further, wavelet analysis is adopted for processing the non-stationary signals, and multi-scale analysis is carried out on the signals through the expansion and contraction of scale factors and the translation of displacement factors, wherein the expression formula is as follows:；
In the method, in the process of the invention, Is a wavelet function; /(I)Representing wavelet function/>Is a conjugate operation of (2); /(I)As a scale factor, corresponding to frequency information; /(I)The shift factor is the displacement of the sub-wavelet relative to the basic mother wavelet, and corresponds to time information.
Wherein wavelet functionThe following formula is satisfied: /(I)；
In the method, in the process of the invention,Is a scale function; /(I)And k is an integer, and is a scale factor.
Further, the acoustic emission method predicts the ground stress mathematical model as:；；/>；；
In the method, in the process of the invention, 、/>、/>Vertical main stress, horizontal maximum main stress, horizontal minimum main stress and MPa respectively;、/>、/> Respectively the measured values of positive stress of apparent Kaiser points of the horizontal cores at 0 DEG, 45 DEG and 90 DEG in the plane and MPa; /(I) Is the actual measurement value of the positive stress of the apparent Kaiser point of the core in the vertical direction, and is MPa; θ is the plane maximum principal stress/>An angle of 0 deg. from the plane.
Compared with the prior art, the invention has the following beneficial effects:
According to the invention, wavelet analysis of acoustic emission signals is introduced, the defect that acoustic emission signals of different types are difficult to calculate accurately in a mathematical model can be overcome, meanwhile, based on the principle and advantages of wavelet analysis, the apparent Kaiser point is accurately identified, wavelet transformation analysis is carried out under different wavelet coefficients, the spectral energy distribution of different scales is obtained, the accurate position of the apparent Kaiser point is comprehensively judged, and further, the stress value of the corresponding direction is obtained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a directional sampling mode of a coal rock full-diameter core sample according to the invention;
FIG. 3 is a schematic diagram of a combined system of uniaxial/triaxial compression experiments and acoustic emission signal monitoring in accordance with the present invention;
FIG. 4 is a graph of stress and acoustic emission versus time for a directional coal sample compression process according to an embodiment of the present invention;
FIG. 5 is a graph of wavelet analysis energy spectrum and wavelet coefficient of an acoustic emission signal according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the inventor, are within the scope of the invention.
As shown in fig. 1, the present invention provides a coal reservoir ground stress measuring method based on acoustic emission wavelet analysis, comprising the following steps:
Intercepting a full-diameter core sample according to the principle that the axial direction of the sample is consistent with the vertical direction of an in-situ reservoir, measuring the wave velocity of the full-diameter core sample to establish a sample space rectangular coordinate system, and measuring the magnetic declination to determine the included angle of the natural remanence direction of the sample relative to a 0-degree mark line of the sample space rectangular coordinate system;
taking a sample space rectangular coordinate system as a reference, performing a coal rock compression acoustic emission experiment on the directional rock sample after the directional rock sample is obtained by adopting a four-direction coring method to obtain a full stress-strain curve of the coal sample and acoustic emission signal data;
based on wavelet analysis of acoustic emission signal data, identifying apparent Kaiser points, and further obtaining stress values in corresponding directions;
Based on the positive stresses corresponding to different directions, the vertical main stress, the horizontal maximum main stress, the horizontal minimum main stress and the horizontal maximum main stress of the in-situ of the coal reservoir are calculated and determined by adopting an acoustic emission method to predict the ground stress mathematical model, so that the in-situ ground stress of the coal reservoir is determined.
Since the acoustic emission signal has deterministic stationary signals and non-stationary signals, it is difficult to perform accurate calculations in the application to mathematical model practice. In the present invention, the following detailed description will be given with reference to specific parameters in order to understand the specific technical solutions of the present invention. The present embodiment is mainly described in six aspects.
First, collection and preparation of coal rock sample
Collecting in-situ bulk coal sample or drilling core of research target coal reservoir, taking out bulk coal sample or drilling core, immediately packaging with plastic film, labeling, transporting to laboratory, and preparing by linear cutting methodThe full-diameter core sample ensures that the axial direction of the full-diameter core sample is vertically consistent with that of an in-situ reservoir, the surface of the cylinder is smooth, the top-bottom interface is free of obvious pits or bulges, and the whole cylinder is free of obvious crack defects.
Second, wave velocity anisotropy test and declination measurement
In a laboratory, the wave velocity measurement device is used for measuring the wave velocity of the full-diameter core sample in different horizontal directions (radial directions), and generally, an oscilloscope, a signal generator, an oscilloscope probe and other devices are used, the oscilloscope can be used for displaying waveforms, the signal generator can generate waves with specific frequencies, and the oscilloscope probe can be used for receiving waveform signals.
Firstly, a signal generator is connected to an oscilloscope, proper frequency and amplitude are set, then two probes are symmetrically placed on two sides of a full-diameter core sample, and the propagation speed of the wave is calculated according to the propagation distance and the time difference.
The P wave velocities in different radial directions are obtained through calculation, so that the anisotropic characteristic of the wave velocity of the core is obtained, the direction of the maximum radial wave velocity is determined to be the direction of the approximate horizontal minimum principal stress according to the basic principles of the wave velocity and the stress distribution, the direction of the minimum radial wave velocity is determined to be the direction of the approximate horizontal maximum principal stress, a full-diameter core sample space rectangular coordinate system can be established, the X axis is the direction of the approximate horizontal maximum principal stress and is marked as 0 degrees, the Y axis is the direction of the approximate horizontal minimum principal stress and is marked as 90 degrees, and the Z axis is the core axis.
In the invention, based on an acoustic emission Kaiser effect mathematical model, the included angle theta between the horizontal maximum principal stress direction and the 0-degree mark line in the space rectangular coordinate system can be directly obtained, and if the azimuth angle beta of the 0-degree mark line relative to the geographic north pole is determined, the azimuth of the horizontal maximum principal stress is obtained.
The specific measurement mode is as follows:
firstly, determining natural residual magnetism measurement of a directional sample of the paleogeomagnetic core, carrying out alternating demagnetization or thermal demagnetization cleaning on the paleogeomagnetic core sample, measuring magnetic bias angles, magnetic inclination angles and magnetization intensity of each sample under different temperatures and different magnetic field intensities in a space rectangular coordinate system on an alternating demagnetization instrument or a thermal demagnetization instrument, and carrying out statistical calculation to obtain the magnetic bias angle of the natural residual magnetism of the full-diameter core, namely an included angle beta 1 of the natural residual magnetism direction of the in-situ coal rock relative to a 0-degree mark line; and then determining a magnetic declination angle beta 2 of the in-situ coal rock sampling place relative to the geographic north, and determining the azimuth of the horizontal maximum principal stress through the azimuth relation between the azimuth beta of the 0-degree mark line relative to the geographic north and the azimuth alpha of the horizontal maximum principal stress relative to the geographic north, wherein the specific formula is as follows: ；/>；
and the included angle between the horizontal maximum principal stress direction and the 0 degree mark line in the space rectangular coordinate system is theta.
In the above, the following is preferable:
theta is obtained by an acoustic emission method ground stress mathematical model; the magnetic declination is measured; /(I) Obtaining magnetic declination data of different areas; alpha is the final angle sought, i.e. the azimuth angle of the horizontal maximum principal stress with respect to the geographic north pole.
Third, preparation of directional sample and Acoustic emission experiment
Taking the space rectangular coordinate system of the full-diameter core sample as a reference, adopting a four-direction coring method in a directional sampling mode, wherein the four directions are X, X degrees Y, Y and Z, namely 0 degrees, 45 degrees and 90 degrees in the vertical axial direction and the horizontal direction, and the drilling specification is respectivelyThe directional sampling mode of the directional cylindrical coal sample is shown in figure 2. After 4 directional coal samples are prepared, a coal rock compression acoustic emission experiment is carried out next to obtain a full stress-strain curve of the coal samples and acoustic emission signal data. The combined system of the uniaxial/triaxial compression test and acoustic emission signal monitoring is shown in fig. 3.
The control loading system adopts RTR-2000 high-pressure rock triaxial dynamic testing equipment of the company GCTS in the United states, which is also called as a rapid rock triaxial testing system 2000, and is mainly used for rock physical parameter testing under normal temperature, normal pressure or high temperature and high pressure environments, the equipment mainly comprises an axial pressure loading system, a confining pressure loading system, a pore pressure loading system, a heating system and a microcomputer control system, the load rigidity reaches 10MN/mm, and the maximum axial pressure 2000kN, the maximum confining pressure 140MPa, the maximum pore pressure 140MPa and the maximum temperature 200 ℃ can be provided. And during loading, displacement control is adopted, and the deformation sensor is used for directly measuring the axial deformation and the radial deformation of the coal sample.
The acoustic emission monitoring system adopts a PCI-II acoustic emission acquisition system developed by the American Physical Acoustic Co (PAC), has the sampling frequency of 40MHz, 18-bit digital-to-analog conversion, has continuous waveform recording capability, and can acquire 20 characteristic parameters including AE events, energy, ringing, rise time and the like. Before the experiment, 2 NANO acoustic emission probes are attached to the surface of a cylindrical sample, and the probes are arranged on two sides of the coal sample to keep symmetry and are used for recording parameters and waveforms of AE events. In order to study the acoustic emission evolution law of the coal sample in the full loading process, the synchronous loading and acoustic emission monitoring are ensured in the experimental process.
If the research object is a deep coal reservoir, a triaxial compression acoustic emission experiment corresponding to the simulated formation depth under the surrounding pressure is required to be carried out, and the application sample is taken from a shallow coal reservoir, so that the uniaxial compression acoustic emission experiment is carried out on 4 prepared coal samples. The operation steps are as follows:
Firstly, attaching strain sensors to two sides of a coal sample, wherein the strain sensors are respectively vertical and parallel to the long axis of the coal sample, the distance between planes is 180 degrees, and the axial deformation and the radial deformation are respectively measured;
Then the acoustic emission probe is stuck on the surface of the coal sample, acoustic emission signals are collected, and a pipeline is connected; and then applying axial pressure to the coal sample, adopting a displacement control mode, and synchronously monitoring information such as axial deformation, radial deformation, acoustic emission signals, time and the like of the coal sample at the loading rate of 0.02 mm/min, and stopping loading and acoustic emission monitoring after the sample is destroyed to complete the experimental process.
Fourth, wavelet analysis and identification of apparent Kaiser point of acoustic emission signal
Stress variation data and acoustic emission signal data of each directional coal sample were obtained through the above experiments, as shown in fig. 4. The acoustic emission signal analysis is an important link in the acoustic emission detection technology, is also an important means for determining how to accurately identify the apparent Kaiser point, and is mainly divided into qualitative analysis and quantitative analysis at present:
the method comprises the steps of storing and recording waveforms of acoustic emission signals, analyzing and processing the waveforms by a mathematical method, and further analyzing the characteristics of the acoustic emission signals;
The other is based on a plurality of simplified waveform characteristic parameters, and the acoustic emission signal characteristics are represented by carrying out statistical analysis on the parameters.
Wavelet analysis is a research method developed by Fourier transformation, in signal analysis, description of signals has two basic forms, namely a time domain form and a frequency domain form, fourier transformation is used for connecting a time domain and a frequency domain, and the problem that a plurality of time domains are difficult to see clearly is caused by researching frequency domain information instead of the time domain information, so that the problem is very clear in the frequency domain. The wavelet transformation adopts a flexible and variable time-frequency window, when the high-frequency signal is detected, the scale factor is reduced, the time window is narrowed, and the height of the frequency window is increased; when detecting low frequency signals, the scale factor increases, the time window widens and the frequency window decreases. Therefore, the wavelet transformation can detect the local time position of the abnormal signal, analyze the characteristics of the abnormal signal, and the signal has very important significance after Fourier transformation and wavelet transformation, and has high applicability and feasibility particularly for processing and analyzing acoustic emission signals.
In signal analysis, a signal is described by using a position in time or space as an argument and a certain numerical feature of the signal as an argument. The time domain form can describe the law of the change of the signal with time, but cannot describe the information of the signal in frequency and phase. Thus, the frequency domain characterization of the signal uses a fourier transform: ; in the/> As a function/>Fourier transform of/>As a primitive function,/>I is a complex exponential function, i is a calculation parameter, lambda is frequency, and t is time;
The short-time Fourier transform is evolved from the Fourier transform, the signal is divided into small time intervals, each time interval is analyzed by the Fourier transform, and the frequency existing in the interval is determined, so that the purpose of analyzing the local signal is achieved. The short-time fourier transform function STFT (λ, τ) for λ, τ is: In the method, in the process of the invention, As a sliding window function,/>Τ is a translation factor representing the position of the sliding window.
Short-time fourier transform can realize a certain degree of time-frequency localization, is suitable for deterministic stationary signals, and for analysis of non-stationary signals, especially signals with variability, local time domain features cannot be analyzed in the frequency domain, so wavelet analysis is introduced.
The research of non-stationary signals with abrupt nature requires describing signals from both time and frequency domains, and the research of all and local characteristics of signals in time and frequency domains, as frequency characteristics occurring at different time positions are required to be obtained, the situation of local abrupt positions of signals is emphasized.
When the non-stationary signal has local abrupt changes, a time window is required to provide frequency information. Local mutations are narrow, requiring a short time window; the local abrupt change is relatively gentle and requires a long window.
The time-frequency analysis method of wavelet analysis solves the problem, for analysis of non-stationary signal, wavelet transformation provides a window whose size, shape and position on time axis can be changed, i.e. the signal can be undergone the process of multi-scale analysis by means of expansion and contraction of scale factor and translation of displacement factor, and continuous wavelet transformationThe expression formula of (2) is: /(I)；
In the method, in the process of the invention,Is a wavelet function; /(I)Representing wavelet function/>Representing wavelet function/>Is a conjugate operation of (2); a is a scale factor and corresponds to frequency information; /(I)The shift factor is the displacement of the sub-wavelet relative to the basic mother wavelet, and corresponds to time information.
The coal rock structure is complex, the coal rock structure has the characteristics of cutting lines, exogenous cracks, microcracks and the like, acoustic emission signals have the characteristics of burst performance and complexity, when the acoustic emission is analyzed and processed by utilizing the wavelet theory, the wavelet basis generally meets corresponding requirements, the Daubechies wavelet has the advantages of compactness and regularities, the localization capability of the time domain and the frequency domain is strong, the Daubechies wavelet basis function has good effect on the analysis and the processing of the coal rock acoustic emission signals, and the Daubechies wavelet basis function meets the following formula:；
In the method, in the process of the invention, Is a scale function; /(I)Is a scale factor, t is time, and k is an integer.
According to the wavelet analysis principle and method, the 4 directional coal sample uniaxial compression acoustic emission signals are subjected to one-dimensional continuous wavelet transformation respectively, daubechies wavelet basis functions (db wavelets) with compactness and regularity are adopted, wavelet transformation analysis is carried out under different wavelet coefficients, spectral energy distribution characteristics of different scales can be obtained, and energy distribution rules corresponding to different coefficients are similar but different in distribution range. And selecting optimal wavelet coefficients for acoustic emission signals of different coal samples, analyzing energy release processes and time nodes of the different coal samples based on an optimal energy spectrogram, comprehensively judging the accurate position of a Kaiser point according to a stress change curve and acoustic emission signal distribution characteristics and abnormal signals, and further obtaining stress values in corresponding directions, wherein the wavelet analysis energy spectrogram and wavelet coefficient curve of the acoustic emission signals of 4 samples are shown in figure 5.
Taking a vertical sample as an example, two obvious abrupt transient signals appear in a spectrogram (fig. 5 (a)), which shows that the coal sample has two important energy release points in the uniaxial compression process, the first point falls at the end of the elastic deformation stage, the second point is in the plastic deformation stage and breaks the transition zone of the destabilization stage, the energy release range of the second point is very large, the energy release of the first point is smaller, and the coal sample has a certain hiding property.
According to the Kaiser effect and stress change rule, the first mutation point shows that a new micro crack is generated in the coal sample at the end stage of the elastic deformation stage, no instability exists, the new micro crack is a precursor of the crack, the determined apparent Kaiser point represents the in-situ ground stress in the direction, and the in-situ ground stress is 9.77 MPa; the second abrupt point is obviously greatly released, corresponds to the coal rock unsteady damage, breaks and produces macroscopic cracks, so that more energy is released, the point is a Kaiser point, and corresponds to the maximum paleo-mechanical stress in the geological history period of the direction.
In addition, the wavelet analysis energy spectrograms of acoustic emission signals of 3 coal samples also have similar distribution characteristics (shown in (b) - (d) in fig. 5), and the apparent Kaiser points can be accurately identified by a wavelet analysis method to obtain corresponding stress values, so that the ground stress of the in-situ coal reservoir is measured.
The acoustic emission energy release points generally appear in an elastic deformation stage, a plastic deformation stage and a damage instability stage, special energy release characteristics exist in individual samples, for example, a coal sample in the 90-degree direction has a plurality of energy release points and has no obvious rule, the energy distribution of a spectrogram has discrete characteristics, the acoustic emission signal interference in the compression process is more, probably due to the influence of the pore crack development of the sample, from the perspective of qualitative analysis of the spectrogram, the discrete nature brings certain discrimination difficulty, the optimization can not be carried out in a mode of adjusting wavelet coefficients and changing resolution, but the energy release relative size of each point can also be used as an important judgment basis through further analysis and judgment of the energy distribution range of each stage, namely, the energy release relative size of each point can be realized through comparing the high energy distribution area in unit time. The coal sample in the 90-degree direction can be judged to be 6 energy release points, the first point and the second point are low in energy, the four later points are high in energy, the sixth point can be easily identified to be a Kaiser point and located in the coal sample destruction stage, the third point and the fourth point are both in the elastic deformation stage and are very close in distance, an observation spectrogram can find that the energy distribution interval of the fourth point is relatively large, the frequency is highest, even the frequency exceeds the high frequency corresponding to the Kaiser point, and the point is judged to be the accurate Kaiser point, and the corresponding stress value is 4.47 MPa. The apparent Kaiser point stress values of the four directional coal samples measured by the wavelet analysis method are 9.77 MPa, 14.54 MPa, 10.95 MPa and 4.47 MPa respectively.
Fifth, the in-situ coal reservoir ground stress is calculated and determined
Through the experiment and analysis process, four stress values corresponding to Kaiser points, namely four positive stresses corresponding to different directions, are obtained, according to the elastic mechanics theory, the existing acoustic emission method is adopted to predict the ground stress mathematical model, and the directions of the vertical main stress, the horizontal maximum main stress, the horizontal minimum main stress and the horizontal maximum main stress of the coal reservoir in situ can be calculated and determined, so that the coal reservoir in-situ ground stress is determined, and the mathematical model formula is as follows:；；/>；；
In the method, in the process of the invention, 、/>、/>Vertical main stress, horizontal maximum main stress, horizontal minimum main stress and MPa respectively;、/>、/> Respectively the measured values of positive stress of apparent Kaiser points of the horizontal cores at 0 DEG, 45 DEG and 90 DEG in the plane and MPa; /(I) Is the actual measurement value of the positive stress of the apparent Kaiser point of the core in the vertical direction, and is MPa; θ is the plane maximum principal stress/>The included angle between the direction of the horizontal maximum principal stress and the 0 degree mark line in the space rectangular coordinate system is the included angle between the direction of the horizontal maximum principal stress and 0 degree mark line in the plane, namely the included angle between the direction of the horizontal maximum principal stress and the 0 degree mark line in the space rectangular coordinate system is defined by the ratio of the horizontal maximum principal stress to the mark lineThe direction is clockwise turned to 0 deg. direction to be positive.
The direction and the value of the included angle theta are known to be obtained, the azimuth of the horizontal maximum principal stress can be obtained through the content of the wave velocity anisotropy test and the declination measurement of the second part, the direction of the three-way earth stress is obtained, the size of the in-situ earth stress of the coal reservoir is also measured through the formula, the vertical principal stress, the horizontal maximum principal stress and the horizontal minimum principal stress can be obtained through calculation and are respectively 9.77 MPa, 14.74 MPa and 4.27 MPa, and the included angle theta between the horizontal maximum principal stress direction and a 0-degree mark line in a space rectangular coordinate system is-8.0065 degrees.
Based on the foregoing, the measurement according to the present invention using the acoustic emission method has the following two advantages:
Firstly, in the field of coal reservoir ground stress prediction, a common hydraulic fracturing method and a well logging method have certain limitations, the measurement accuracy is low, the hydraulic fracturing method cannot accurately acquire the ground stress direction, the horizontal maximum principal stress value is poor in accuracy, the well logging method has the problem of multiple solutions, the obtained ground stress value is large in error and low in reliability, and the two methods have the problems of high cost and relatively complexity, so that large-scale prediction is difficult to realize in the early stage of coalbed methane exploration and development. Compared with the method, the method can obtain accurate ground stress, only a coal reservoir sample is obtained, an acoustic emission experiment is carried out, stress-strain analysis and acoustic emission signal analysis are carried out, the ground stress and the direction thereof can be determined by means of a Kaiser effect and a ground stress prediction model, and the method has the advantages of simplicity, convenience and rapidness, and time and cost are saved.
And secondly, acoustic emission signal wavelet analysis is introduced, so that the apparent Kaiser point can be accurately identified.
The acoustic emission signal is a non-stationary signal with abrupt change property, and is obviously error only by artificial analysis and judgment of Kaiser effect, and the description and analysis are needed from two aspects of time domain and frequency domain, so that all and local characteristics of the signal in the time domain and the frequency domain are researched, frequency characteristics of different time positions are obtained, and the local abrupt change position condition of the signal is grasped.
When the non-stationary signal has local abrupt change, a time window is needed to provide frequency information, the size and shape of the Fourier transform window function are fixed, so that Fourier transform cannot be realized, wavelet analysis can be realized, wavelet transform provides a window, the size, shape and position of the window on a time axis can be changed, and multi-scale analysis can be performed on the signal through expansion and contraction of scale factors and translation of displacement factors.
Based on the principle and advantages of wavelet analysis, daubechies wavelet basis function is selected, wavelet transformation analysis is carried out under different wavelet coefficients, spectrum energy distribution of different scales is obtained, the accurate position of a Kaiser point is comprehensively judged, and then stress values in corresponding directions are obtained.
Taking four selected coal samples as an example, based on the same stress-strain data and acoustic emission signals, the stress values of the apparent Kaiser points obtained by the conventional method and the method are different, the obtained results by the conventional method are 9.21 MPa, 14.37 MPa, 9.89 MPa and 4.07 MPa respectively, the obtained results by the method are 9.77 MPa, 14.54 MPa, 10.95 MPa and 4.47 MPa respectively, the errors are reduced by 5.73 percent, 1.17 percent, 9.68 percent and 8.95 percent respectively, and the accuracy of the predicted ground stress value and the horizontal maximum principal stress direction is also greatly improved.
The four selected coal samples are subjected to experiment, analysis calculation and error analysis, and related data are shown in the following table.
Therefore, the innovation core of the invention is an acoustic emission signal wavelet analysis method, the wavelet analysis describes and analyzes acoustic emission signals from two aspects of time domain and frequency domain, researches all and partial characteristics of the signals in the time domain and the frequency domain, obtains frequency characteristics of different time positions, and mainly grasps the partial mutation position condition of the signals, thereby being capable of accurately identifying Kaiser points. The invention takes acoustic emission signals as analysis objects, selects Daubechies wavelet basis functions based on wavelet analysis principle, performs wavelet transformation analysis under different wavelet coefficients, obtains spectrum energy distribution of different scales, and comprehensively judges apparent Kaiser points and stress values.
The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application, the scope of which is defined by the claims. Various modifications and equivalent arrangements of this application will occur to those skilled in the art, and are intended to be within the spirit and scope of the application.
Claims (9)
1. The coal reservoir ground stress measuring method based on acoustic emission wavelet analysis is characterized by comprising the following steps of:
Intercepting a full-diameter core sample according to the principle that the axial direction of the sample is consistent with the vertical direction of an in-situ reservoir, measuring the wave velocity of the full-diameter core sample to establish a sample space rectangular coordinate system, and measuring the magnetic declination to determine the included angle of the natural remanence direction of the sample relative to a 0-degree mark line of the sample space rectangular coordinate system;
taking a sample space rectangular coordinate system as a reference, performing a coal rock compression acoustic emission experiment on the directional rock sample after the directional rock sample is obtained by adopting a four-direction coring method to obtain a full stress-strain curve of the coal sample and acoustic emission signal data;
based on wavelet analysis of acoustic emission signal data, identifying apparent Kaiser points, and further obtaining stress values in corresponding directions;
Based on the positive stresses corresponding to different directions, the vertical main stress, the horizontal maximum main stress, the horizontal minimum main stress and the horizontal maximum main stress of the in-situ of the coal reservoir are calculated and determined by adopting an acoustic emission method to predict the ground stress mathematical model, so that the in-situ ground stress of the coal reservoir is determined.
2. The coal reservoir ground stress determination method based on acoustic emission wavelet analysis according to claim 1, wherein the concrete method for establishing a sample space rectangular coordinate system is as follows:
carrying out wave velocity measurement and calculation on the full-diameter core to obtain P wave velocities in different radial directions, thereby obtaining the characteristic of wave velocity anisotropy of the full-diameter core;
according to the basic principle of wave velocity and stress distribution, determining that the direction with the maximum radial wave velocity is the direction of the approximate horizontal minimum main stress, and the direction with the minimum radial wave velocity is the direction of the approximate horizontal maximum main stress;
and establishing a sample space rectangular coordinate system of the full-diameter core sample, wherein an X axis is an approximately horizontal maximum principal stress direction and is marked as 0 degrees, a Y axis is an approximately horizontal minimum principal stress direction and is marked as 90 degrees, and a Z axis is a core axis.
3. The coal reservoir ground stress determination method based on acoustic emission wavelet analysis according to claim 2, wherein the specific method for determining the included angle between the natural remanence direction of the sample and the 0 degree mark line is as follows:
Carrying out alternating demagnetization or thermal demagnetization cleaning on the paleomagnetic core, measuring magnetic bias angles, magnetic inclination angles and magnetization intensity of each sample under different temperatures and different magnetic field intensities of a space rectangular coordinate system on an alternating demagnetization instrument or a thermal demagnetization instrument, and carrying out statistical calculation to obtain the magnetic bias angle of natural remanence of the full-diameter core sample, wherein the magnetic bias angle is recorded as an included angle beta 1 of the natural remanence direction of the in-situ coal rock relative to a 0-degree mark line;
determining a magnetic declination angle beta 2 of the in-situ coal rock sampling site relative to the geographic north;
Determining the azimuth of the horizontal maximum principal stress according to the azimuth relation between the azimuth beta of the 0-degree mark line relative to the geographic north pole and the azimuth alpha of the horizontal maximum principal stress relative to the geographic north pole; ；/> ; and the included angle between the horizontal maximum principal stress direction and the 0 degree mark line in the space rectangular coordinate system is theta.
4. A method of determining the earth stress of a coal reservoir based on acoustic emission wavelet analysis according to claim 1, wherein the four-way coring method comprises vertical axial, horizontal 0 °, 45 ° and 90 °.
5. The coal reservoir ground stress determination method based on acoustic emission wavelet analysis according to claim 1, wherein a uniaxial compression mode is adopted for carrying out coal rock compression acoustic emission experiments on the directional rock sample, and the specific method is as follows:
attaching strain sensors to two sides of each directional rock sample, wherein the two strain sensors are respectively vertical and parallel to the long axis of the directional rock sample, and the planes are 180 degrees apart to respectively measure the axial deformation and the radial deformation of the directional rock sample;
Attaching an acoustic emission probe to the surface of the directional rock sample, and collecting acoustic emission signals;
Applying axial pressure to the directional rock sample, and determining the loading rate by adopting a displacement control mode;
And synchronously monitoring the axial deformation, radial deformation, acoustic emission signals and time of the directional rock sample until the directional rock sample is destroyed, and simultaneously stopping loading and acoustic emission monitoring to complete the experimental process.
6. The coal reservoir ground stress determination method based on acoustic emission wavelet analysis according to claim 1, wherein the specific method for identifying apparent Kaiser points based on wavelet analysis of acoustic emission signal data is as follows:
Carrying out one-dimensional continuous wavelet transformation on acoustic emission signal data of each directional rock sample, carrying out wavelet transformation analysis under different wavelet coefficients, and obtaining spectrum energy distribution characteristics of different scales, wherein the energy distribution characteristics corresponding to different coefficients are similar but have different distribution ranges;
Comparing and analyzing wavelet transformation results under different wavelet coefficients, selecting an optimal wavelet coefficient and a corresponding energy spectrogram, analyzing energy release characteristics of the whole compression process based on the energy spectrogram, analyzing and identifying an energy release time node, and comprehensively judging the accurate position of the Kaiser point according to the distribution characteristics of the full stress-strain curve and acoustic emission signal data and abnormal signals, wherein the abnormal energy release phenomenon exists when the Kaiser point is positioned in an elastic deformation stage.
7. A method of coal reservoir crustal stress determination based on acoustic emission wavelet analysis according to claim 6, wherein for deterministic plateau signals:
Applying Fourier transform to acoustic emission signal data to express a frequency domain, wherein a Fourier transform formula is as follows: ；
In the method, in the process of the invention, As a function/>Fourier transform of/>As a primitive function,/>I is a complex exponential function, i is a calculation parameter, lambda is frequency, and t is time; dividing acoustic emission signal data into small time intervals by short-time Fourier transform, analyzing each small time interval by short-time Fourier transform, and determining the frequency existing in the time interval to achieve the purpose of analyzing local signals, wherein short-time Fourier transform functions STFT (lambda, tau) about lambda and tau are as follows: /(I)；
In the method, in the process of the invention,As a sliding window function,/>For/>Τ is a translation factor representing the position of the sliding window.
8. The method for determining the ground stress of the coal reservoir based on acoustic emission wavelet analysis according to claim 6, wherein the nonstationary signals are processed by wavelet analysis, the signals are subjected to multi-scale analysis by scaling factors and translation of displacement factors, and continuous wavelet transformation is performedThe expression formula of (2) is:；
In the method, in the process of the invention, Is a wavelet function; /(I)Representing wavelet function/>Is a conjugate operation of (2); a is a scale factor and corresponds to frequency information; /(I)The shift factor is the displacement of the child wavelet relative to the basic mother wavelet and corresponds to time information;
wherein wavelet function The following formula is satisfied: /(I)；
In the method, in the process of the invention,Is a scale function; g k is a scale factor, t is time, and k is an integer.
9. The coal reservoir ground stress determination method based on acoustic emission wavelet analysis according to claim 1, wherein the acoustic emission method predicted ground stress mathematical model is:；/>；；/>；
In the method, in the process of the invention, 、/>、/>Vertical main stress, horizontal maximum main stress, horizontal minimum main stress and MPa respectively; /(I)、/>、Respectively the measured values of positive stress of apparent Kaiser points of the horizontal cores at 0 DEG, 45 DEG and 90 DEG in the plane and MPa; /(I)Is the actual measurement value of the positive stress of the apparent Kaiser point of the core in the vertical direction, and is MPa; θ is the horizontal maximum principal stress/>An angle of 0 deg. from the plane.
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