CN110133715B - Microseism seismic source positioning method based on first-arrival time difference and waveform superposition - Google Patents

Microseism seismic source positioning method based on first-arrival time difference and waveform superposition Download PDF

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CN110133715B
CN110133715B CN201910458434.9A CN201910458434A CN110133715B CN 110133715 B CN110133715 B CN 110133715B CN 201910458434 A CN201910458434 A CN 201910458434A CN 110133715 B CN110133715 B CN 110133715B
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毛庆辉
王鹏
桂志先
陈波
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Yangtze University
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Abstract

A microseism seismic source positioning method based on first arrival time difference and waveform superposition comprises the following steps: s1: inputting a speed model; s2: picking and inputting actual first arrival time, and reading seismic data; s3: calculating a theoretical first arrival time table from all grid points to each detector in the feasible solution area according to the speed model in S1; s4: constructing a time-lapse residual function Tr(ii) a S5: constructing a waveform superposition function Ews(ii) a S6: inputting a weight coefficient beta according to the time-lapse residual function T in S4rAnd the waveform superposition function E in S5wsConstructing an improved objective function; s7: and searching the minimum value of the improved objective function through a grid search method, wherein the corresponding optimal solution is the seismic source position. Aiming at the problem that a positioning method based on a travel time target function is sensitive to first arrival errors, the improved target function is constructed by combining first arrival time difference and waveform superposition information, the anti-noise capability of the positioning method can be enhanced, the convergence of an inversion method can be improved, and the positioning precision of a micro seismic source can be improved.

Description

Microseism seismic source positioning method based on first-arrival time difference and waveform superposition
Technical Field
The invention belongs to the technical field of geophysical exploration and development of petroleum, and particularly relates to a microseism seismic source positioning method based on first-arrival time difference and waveform superposition.
Background
The application result of the hydraulic fracturing micro-seismic monitoring technology is an oil reservoir geophysical technology for monitoring the reconstruction and effect of unconventional reservoir layers such as dense oil-containing gas and shale gas, and can evaluate the fracturing effect, adjust the fracturing design and well pattern arrangement and provide effective guidance for the next development, so that the productivity of unconventional oil and gas reservoirs is improved.
In the hydraulic fracture monitoring data processing, the core part is the positioning of a microseism seismic source. The predecessor basically uses single travel time information or waveform information to establish an objective function, which can be divided into travel time-based ray tracing positioning and waveform-based offset positioning methods. In the actual hydraulic fracturing real-time monitoring operation, the acquired microseism data has the characteristics of low signal-to-noise ratio, weak energy, high background noise and the like, and the accuracy of first arrival picking is greatly influenced. The positioning method based on the travel time information objective function is more sensitive to the first arrival error, and although the positioning method based on the waveform information objective function does not need accurate first arrival time, the calculation amount is huge, so that the positioning efficiency is not high. Therefore, it is necessary to combine travel time information and waveform information to establish an objective function, and develop a microseism seismic source positioning method based on first arrival time difference and waveform superposition.
Disclosure of Invention
The invention aims to overcome the defects of the background technology and provide a microseism seismic source positioning method based on first-arrival time difference and waveform superposition.
In order to achieve the above object, the method for positioning a micro-seismic source based on first arrival time difference and waveform superposition provided by the present invention comprises the following steps for positioning any micro-seismic source (event):
s1: inputting a speed model;
s2: picking and inputting actual first arrival time, and reading seismic data;
s3: calculating a theoretical first arrival time table from all grid points in the feasible solution area to each detector according to the speed model in the step S1;
s4: constructing a travel time residual function T according to equations (1) and (2) based on the actual first arrival time input in step S2 and the theoretical first arrival time table calculated in step S3r；
Figure BDA0002077311450000021
Figure BDA0002077311450000022
In the above formula: m, N are the numbers of observed first arrivals of transverse waves and longitudinal waves;
Figure BDA0002077311450000023
and
Figure BDA0002077311450000024
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the jth detector,
Figure BDA0002077311450000025
and
Figure BDA0002077311450000026
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the jth detector corresponding to the jth detector;
Figure BDA0002077311450000027
and
Figure BDA0002077311450000028
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the ith detector,
Figure BDA0002077311450000031
and
Figure BDA0002077311450000032
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the ith detector corresponding to the time; t isshiftThe method is a constant drift amount between observation and theoretical first arrival so as to solve the problem that the earthquake-initiating time of a micro earthquake focus in actual data monitoring is unknown;
s5: the seismic data read in the step S2 and the identifiable longitudinal wave first arrival time recorded by the mth detector in the microseism event corresponding to the travel time objective function
Figure BDA0002077311450000033
Combining with the theoretical first arrival time table in step S3, modifying the polarity, and then constructing a waveform superposition function E according to the formulas (3), (4) and (5)ws；
Figure BDA0002077311450000034
Figure BDA0002077311450000035
Figure BDA0002077311450000036
In the formula,. DELTA.P、ΔSRespectively counting the number of window samples when longitudinal and transverse waves slide; dt is the sampling interval; n is the number of detectors;
Figure BDA0002077311450000037
respectively assuming the theoretical time of longitudinal and transverse waves from the seismic source point to the ith detector
Figure BDA0002077311450000038
Longitudinal wave theoretical time of m-th detector
Figure BDA0002077311450000039
The difference between the difference of the two phases,
Figure BDA00020773114500000310
the sign coefficients of the amplitude of the longitudinal and transverse waves of the ith detector, uiIs the amplitude value of the ith trace of the seismic data;
s6: inputting the weight coefficient beta according to the time-lapse residual function T in step S4rAnd the waveform superposition function E in step S5wsConstructing an improved objective function according to a formula (6);
Q＝Tr-βEws (6)
s7: and searching the minimum value of the improved objective function through a grid search method, and outputting the corresponding optimal solution at the moment, namely the position of the seismic source.
In the above technical solution, in the step S1, the velocity model may establish an initial velocity model through the acoustic logging data and the geological stratification data, and then perform velocity model correction using the perforation data.
In the above technical solution, in step S3, all grid points in the feasible solution area are determined by giving a solution area with a perforation point as a center, and then gridding the solution area, where each grid point is a possible seismic source point.
In the above technical solution, in the step S5, the polarity correction may be performed by a sign coefficient
Figure BDA0002077311450000041
The method is realized by judging amplitude symbols in a time window in the record of the detector, wherein the signs need to be kept consistent, and the same-direction superposition of waveforms is ensured at the position.
In the above technical solution, in the step S6, the weight coefficient β >0 is inversely proportional to the signal-to-noise ratio of the microseismic data.
In the above technical solution, in the step S7, in the grid search positioning, when it is assumed that the grid point is the source position, TrTo a minimum, EwsIs at a maximum (i.e., - β E)wsMinimum) so the improvement objective function Q is at a minimum.
Compared with the prior art, the invention has the following advantages:
according to the method, travel time and waveform information of the micro-seismic data in the target function are improved, and meanwhile, constraint positioning is carried out, so that the anti-noise capability of the positioning method is enhanced, the convergence of the inversion method is improved, and the positioning precision of the micro-seismic source can be improved.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 is a two-dimensional microseismic borehole observation system based on a homogeneous medium model with horizontal and vertical coordinates representing horizontal distance x and depth z, respectively;
FIG. 3a is a z-component seismic record of a theoretical model;
FIG. 3b is a z-component seismic record of the theoretical model after random noise addition;
FIG. 4a is a diagram of the positioning result based on the travel time objective function method, with the abscissa and ordinate representing the horizontal distance x and the depth z, respectively;
fig. 4b is a diagram of the positioning results of the method of the present invention, with the horizontal and vertical coordinates representing the horizontal distance x and the depth z, respectively.
Detailed Description
The embodiments of the present invention will be described in further detail with reference to the drawings and examples, but they are not intended to limit the present invention and are merely examples. While the advantages of the invention will be apparent and readily appreciated by the description.
The microseism source positioning method based on the first arrival time difference and the waveform superposition, as shown in fig. 1, includes the following steps:
s1: inputting a speed model;
s2: picking and inputting actual first arrival time, and reading seismic data;
s3: calculating a theoretical first arrival time table from all grid points in the feasible solution area to each detector according to the speed model in the step S1;
s4: constructing a travel time residual function T according to equations (1) and (2) based on the actual first arrival time input in step S2 and the theoretical first arrival time table calculated in step S3r；
Figure BDA0002077311450000051
Figure BDA0002077311450000061
In the above formula: m, N are the numbers of observed first arrivals of transverse waves and longitudinal waves;
Figure BDA0002077311450000062
and
Figure BDA0002077311450000063
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the jth detector,
Figure BDA0002077311450000064
and
Figure BDA0002077311450000065
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the jth detector corresponding to the jth detector;
Figure BDA0002077311450000066
and
Figure BDA0002077311450000067
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the ith detector,
Figure BDA0002077311450000068
and
Figure BDA0002077311450000069
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the ith detector corresponding to the time; t isshiftThe method is a constant drift amount between observation and theoretical first arrival so as to solve the problem that the earthquake-initiating time of a micro earthquake focus in actual data monitoring is unknown;
s5: the seismic data read in the step S2 and the identifiable longitudinal wave first arrival time recorded by the mth detector in the microseism event corresponding to the travel time objective function
Figure BDA00020773114500000610
Combining with the theoretical first arrival time table in step S3, modifying the polarity, and then constructing a waveform superposition function E according to the formulas (3), (4) and (5)ws；
Figure BDA00020773114500000611
Figure BDA00020773114500000612
Figure BDA00020773114500000613
In the formula,. DELTA.P、ΔSRespectively counting the number of window samples when longitudinal and transverse waves slide; dt is the sampling interval; n is the number of detectors;
Figure BDA00020773114500000614
respectively assuming the theoretical time of longitudinal and transverse waves from the seismic source point to the ith detector
Figure BDA00020773114500000615
Longitudinal wave theoretical time of m-th detector
Figure BDA00020773114500000616
The difference between the difference of the two phases,
Figure BDA00020773114500000617
the sign coefficients of the amplitude of the longitudinal and transverse waves of the ith detector, uiIs the amplitude value of the ith trace of the seismic data;
s6: inputting the weight coefficient beta according to the time-lapse residual function T in step S4rAnd the waveform superposition function E in step S5wsConstructing an improved objective function according to a formula (6);
Q＝Tr-βEws (6)
s7: and searching the minimum value of the improved objective function through a grid search method, and outputting the corresponding optimal solution at the moment, namely the position of the seismic source.
In the above technical solution, in the step S1, the velocity model may establish an initial velocity model through the acoustic logging data and the geological stratification data, and then perform velocity model correction using the perforation data.
In the above technical solution, in step S3, all grid points in the feasible solution area are determined by giving a solution area with a perforation point as a center, and then gridding the solution area, where each grid point is a possible seismic source point.
In the above-described aspect, in step S5, the first arrival time of the longitudinal wave is substantially accurate
Figure BDA0002077311450000071
The unknown seismic source origin time in the conventional waveform superposition method is replaced.
In the above technical solution, in the step S5, the polarity correction may be performed by a sign coefficient
Figure BDA0002077311450000072
The method is realized by judging amplitude symbols in a time window in the record of the detector, wherein the signs need to be kept consistent, and the same-direction superposition of waveforms is ensured at the position.
In the above technical solution, in step S6, the weight coefficient β (β >0) depends on the signal-to-noise ratio of the microseismic data, and if the signal-to-noise ratio is low, the weight of the waveform superimposition part is important, so β is set to be larger, otherwise β is set to be smaller.
In the above technical solution, in the step S7, in the grid search positioning, when it is assumed that the grid point is the source position, TrTo a minimum, EwsIs at a maximum (i.e., - β E)wsMinimum) so the improvement objective function Q is at a minimum.
Example (b): firstly, establishing a two-dimensional micro-seismic well observation system based on a uniform medium model, wherein the longitudinal wave velocity Vp is 4500m/s, the transverse wave velocity Vs is 2500m/s, and the density is 2.425g/cm3. As shown in fig. 2, the depth z of 10-level detectors in a monitoring well (vertical well) with the horizontal distance x of 2000m is respectively located at 1500-. The position where the micro-seismic source occurs is set to (x, z) — (2200, 1570) m. Then, a 100Hz Rake wavelet is adopted to carry out two-dimensional elastic wave equation forward modeling, the sampling interval is 0.5ms, and a z-component seismic record (figure 3a) of the theoretical model is obtained, and figure 3b is the z-component seismic record of the theoretical model after random noise is added to figure 3 a.
In order to test the stability of the method to the first arrival errors, 200 times of [ -2, 2] ms random errors are added to the first arrivals of the microseismic events of 10 detectors respectively. And then, after a travel time residual error objective function is established according to the formulas (1) and (2), positioning the micro seismic source by adopting a grid search method in the step 7 to obtain a positioning result based on the travel time objective function method (fig. 4 a). And (3) establishing the objective function of the method according to the formulas (1) to (6), and positioning the micro-seismic source by adopting the grid search method in the step (7) to obtain a positioning result of the method (figure 4 b).
As can be seen from comparing fig. 4a and fig. 4b, under a certain first arrival error, the positioning result of fig. 4b is more convergent than that of fig. 4a, i.e. the positioning error of the present invention is much smaller than the positioning method error based on the travel time objective function.
In conclusion, the method is based on the idea of combining the first arrival time difference and the waveform superposition, the micro-seismic source is positioned, the noise resistance and the convergence of the positioning method can be improved, and the positioning precision of the micro-seismic source can be improved.
Details not described in this specification are within the skill of the art that are well known to those skilled in the art.

Claims (5)

1. A microseism seismic source positioning method based on first arrival time difference and waveform superposition is characterized by comprising the following steps:
s1: inputting a speed model;
s2: picking and inputting actual first arrival time, and reading seismic data;
s3: calculating a theoretical first arrival time table from all grid points in the feasible solution area to each detector according to the speed model in the step S1;
all grid points in the feasible solution area are determined by taking a perforation point as a center, a solution area is given, then the area is gridded, and each grid point is a possible seismic source point;
s4: constructing a travel time residual function T according to equations (1) and (2) based on the actual first arrival time input in step S2 and the theoretical first arrival time table calculated in step S3r；
Figure FDA0002728497220000011
Figure FDA0002728497220000012
In the above formula: m, N are the numbers of observed first arrivals of transverse waves and longitudinal waves;
Figure FDA0002728497220000013
and
Figure FDA0002728497220000014
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the jth detector,
Figure FDA0002728497220000015
and
Figure FDA0002728497220000016
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the jth detector corresponding to the jth detector;
Figure FDA0002728497220000017
and
Figure FDA0002728497220000018
respectively the first arrival time of the transverse wave and the longitudinal wave recorded by the ith detector,
Figure FDA0002728497220000019
and
Figure FDA00027284972200000110
respectively calculating time by using the transverse wave theory and the longitudinal wave theory of the ith detector corresponding to the time; t isshiftThe method is a constant drift amount between observation and theoretical first arrival so as to solve the problem that the earthquake-initiating time of a micro earthquake focus in actual data monitoring is unknown;
s5: corresponding the seismic data read in the step S2 and the travel time residual error function in the step S4 to the m-th detection in the microseism eventIdentifiable longitudinal wave first arrival time recorded by wave filter
Figure FDA0002728497220000021
Combining with the theoretical first arrival time table in step S3, modifying the polarity, and then constructing a waveform superposition function E according to the formulas (3), (4) and (5)ws；
Figure FDA0002728497220000022
Figure FDA0002728497220000023
Figure FDA0002728497220000024
In the formula,. DELTA.P、ΔSRespectively counting the number of window samples when longitudinal waves and transverse waves slide; dt is the sampling interval; n is the number of detectors;
Figure FDA0002728497220000025
respectively assuming the theoretical time of longitudinal and transverse waves from the seismic source point to the ith detector
Figure FDA0002728497220000026
Longitudinal wave theoretical time of m-th detector
Figure FDA0002728497220000027
The difference between the difference of the two phases,
Figure FDA0002728497220000028
the sign coefficients of the amplitude of the longitudinal and transverse waves of the ith detector, uiIs the amplitude value of the ith trace of the seismic data;
s6: inputting the weight coefficient beta according to the time-lapse residual function T in step S4rAnd the waveform superposition function E in step S5wsConstructing an improved objective function according to a formula (6);
Q＝Tr-βEws (6)
s7: and searching the minimum value of the improved objective function through a grid search method, and outputting the corresponding optimal solution at the moment, namely the position of the seismic source.
2. The microseism source positioning method based on the first-arrival moveout and the waveform stacking as claimed in claim 1, wherein the method comprises the following steps: in step S1, the velocity model may be an initial velocity model established from the sonic logging data and the geological stratification data, and then corrected using the perforation data.
3. The microseism source positioning method based on the first-arrival moveout and the waveform stacking as claimed in claim 1, wherein the method comprises the following steps: in the step S5, the polarity correction may be performed by a sign coefficient
Figure FDA0002728497220000031
The method is realized by judging amplitude symbols in a time window in the record of the detector, wherein the signs need to be kept consistent, and the same-direction superposition of waveforms is ensured at the position.
4. The microseism source positioning method based on the first-arrival moveout and the waveform stacking as claimed in claim 1, wherein the method comprises the following steps: in step S6, the weighting factor β >0 is inversely proportional to the signal-to-noise ratio of the microseismic data.
5. The microseism source positioning method based on the first-arrival moveout and the waveform stacking as claimed in claim 1, wherein the method comprises the following steps: in the step S7, in the grid search positioning, T is assumed when the grid point is the source positionrTo a minimum, EwsIs at a maximum, i.e., - β EwsTo be minimal, the improvement objective function Q is minimal.
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