CN107870359B - Micro-seismic event recognition methods and device - Google Patents

Micro-seismic event recognition methods and device Download PDF

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CN107870359B
CN107870359B CN201610862629.6A CN201610862629A CN107870359B CN 107870359 B CN107870359 B CN 107870359B CN 201610862629 A CN201610862629 A CN 201610862629A CN 107870359 B CN107870359 B CN 107870359B
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time
seismic
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CN107870359A (en
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杨心超
崔树果
郭全仕
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Sinopec Geophysical Research Institute
China Petrochemical Corp
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China Petrochemical Corp
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/24—Recording seismic data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/61—Analysis by combining or comparing a seismic data set with other data
    • G01V2210/612—Previously recorded data, e.g. time-lapse or 4D

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Acoustics & Sound (AREA)
  • Environmental & Geological Engineering (AREA)
  • Geology (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Geophysics (AREA)
  • Geophysics And Detection Of Objects (AREA)

Abstract

The present invention provides a kind of micro-seismic event recognition methods and devices.This method may comprise steps of: input micro-seismic monitoring record；Waveform similar curves R (t) is obtained by calculating the waveform similarity factor between each road signal at various moments；Adaptive threshold Ht (t) is calculated according to the waveform similar curves R (t)；And time span be TeventDetection window in, will meet R (t) be greater than Ht (t) maximum value Rmax(tl) it is identified as the event in the detection window, and by time t corresponding to the eventlThe shake time is played as the event.The time accuracy of identification of micro-seismic event recognition methods and device of the invention is not influenced by noise energy, can reduce false detection rate, and ensure that the recognition capability to weak micro-seismic event.

Description

Micro-seismic event recognition methods and device
Technical field
The present invention relates to micro-seismic monitoring technical field of data processing, and in particular, to a kind of micro-seismic event identification side Method and device.
Background technique
In field of petroleum exploitation, the application of microseismic is mainly by generating in monitoring hydraulic fracturing process Microseismic signals can monitor fracturing process, evaluate fracturing effect, and then instruct optimization engineering parameter.In north America region, microseism Monitoring technology is widely used to the business necks such as hydraulically created fracture monitoring, the deposit dynamic monitoring that high pressure injection operation generates Domain obtains the highly recognition of petroleum industrial circle, become an abundant information during oil and gas development, it is accurate, timely monitor Technology is that one of the important means of hydraulically created fracture real-time monitoring is carried out in unconventional development of resources.
Since micro-seismic monitoring is that continuous monitoring for a long time, micro-seismic event possibly are present at monitoring note in fracturing process Any time in record depends merely on manual identified event heavy workload, it is therefore desirable to the event automatic identifying method of efficiently and accurately.It is long Short time-window energy ratio function is most common micro-seismic event recognition methods, when this method is by calculating long in window and short time-window The energy ratio of record thinks to detect micro-seismic event when energy ratio is more than given threshold value.Inventors have found that using letter The defect that number energy as criterion of identification there is recognition result to be affected by noise energy in recording is readily detected " false Event ", false detection rate are higher.Therefore, it is necessary to develop a kind of micro-seismic event automatic identifying method and device that accuracy of identification is high.
The information for being disclosed in background of invention part is merely intended to deepen the reason to general background technique of the invention Solution, and it is known to those skilled in the art existing to be not construed as recognizing or imply that the information is constituted in any form Technology.
Summary of the invention
The purpose of the present invention is study a kind of waveform similarity based on multiple tracks microseism signal carry out micro-seismic event from It is dynamic to know method for distinguishing, improve the precision of event recognition.
According to an aspect of the invention, it is proposed that a kind of micro-seismic event recognition methods.This method may comprise steps of: Micro-seismic monitoring record is inputted, the micro-seismic monitoring record includes the signal of the road m wave detector record, wherein every road i wave detector The signal of record is si(t), [1, m] i ∈, t=[t1,t2,...tj,...tn], to record the time, j ∈ [1, n], n adopts for the time Sampling point number；Waveform similar curves R (t) is obtained by calculating the waveform similarity factor between each road signal at various moments；Root Adaptive threshold Ht (t) is calculated according to the waveform similar curves R (t)；It is T in time spaneventDetection window in, will meet R (t) is greater than the maximum value R of Ht (t)max(tl) it is identified as the event in the detection window, and when by corresponding to the event Between tlThe shake time is played as the event.
Preferably, the method further includes exporting the time corresponding to the event and the event.
Preferably, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length.
Preferably, the waveform similarity factor recorded at various moments can be calculated by sliding window, to obtain Waveform similar curves R (t).
Preferably, it includes: similar to the waveform for calculating adaptive threshold Ht (t) according to the waveform similar curves R (t) Curve R (t) carries out Hilbert transform, obtains the envelope H (t) of R (t), based on the desired value E (t) including H (t) and mark Quasi- variance δ (t) calculates adaptive threshold Ht (t), the calculation formula of the adaptive threshold Ht (t) are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
According to another aspect of the invention, it is proposed that a kind of micro-seismic event identification device.The apparatus may include: for defeated Enter the unit of micro-seismic monitoring record, the micro-seismic monitoring record includes the signal s of wave detector recordi(t), wherein i ∈ [1, m], m are the road number in ground micro-seismic monitoring record, t=[t1,t2,...,tn], to record the time, n is time sampling point Number；For obtaining the list of waveform similar curves R (t) by calculating the waveform similarity factor between each road signal at various moments Member；For calculating the unit of adaptive threshold Ht (t) according to the waveform similar curves R (t)；Time span is for identification TeventDetection window event unit, time span be TeventDetection window in, R (t) will be met greater than Ht (t) maximum value Rmax(tj) it is identified as the event in the detection window, and by time t corresponding to the eventjAs described Event plays the shake time.
Preferably, described device further comprises the list for exporting the time corresponding to the event and the event Member.
Preferably, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length.
Preferably, the waveform similarity factor recorded at various moments can be calculated by sliding window, to obtain Waveform similar curves R (t).
Preferably, it includes: similar to the waveform for calculating adaptive threshold Ht (t) according to the waveform similar curves R (t) Curve R (t) carries out Hilbert transform, obtains the envelope H (t) of R (t), based on the desired value E (t) including H (t) and mark Quasi- variance δ (t) calculates adaptive threshold Ht (t), the calculation formula of the adaptive threshold Ht (t) are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
The affinity information and combining adaptive threshold value calculation method that the present invention passes through introducing multiple tracks microseism signal waveform Carry out the automatic identification of micro-seismic event.Due to using multiple tracks waveform similarity criterion, the event recognition precision of this method is not It is influenced by noise energy, the false detection rate of micro-seismic event automatic identification can be substantially reduced.Simultaneously as introducing adaptive Threshold value criterion, relative to conventional fixed threshold method, this method ensure that the recognition capability of weak micro-seismic event.
Methods and apparatus of the present invention has other characteristics and advantages, these characteristics and advantages are attached from what is be incorporated herein It will be apparent in figure and subsequent specific embodiment, or will be in the attached drawing and subsequent specific implementation being incorporated herein It is stated in detail in example, these the drawings and specific embodiments are used together to explain specific principle of the invention.
Detailed description of the invention
Disclosure illustrative embodiments are described in more detail in conjunction with the accompanying drawings, the disclosure above-mentioned and its Its purpose, feature and advantage will be apparent, wherein in disclosure illustrative embodiments, identical reference label Typically represent same parts.
Fig. 1 shows micro-seismic event recognition methods according to an embodiment of the invention.
Fig. 2 is synthesis ground micro-seismic detection record.
Fig. 3 is that micro-seismic event identifies curve.
Specific embodiment
The preferred embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in attached drawing Preferred embodiment, however, it is to be appreciated that may be realized in various forms the disclosure without the embodiment party that should be illustrated here Formula is limited.On the contrary, these embodiments are provided so that this disclosure will be more thorough and complete, and can be by the disclosure Range is completely communicated to those skilled in the art.
Fig. 1 shows the flow chart of micro-seismic event recognition methods according to an embodiment of the invention.
In the present embodiment, this method specifically includes the following steps:
1) input micro-seismic monitoring record, the micro-seismic monitoring record include the signal s of wave detector recordi(t), In, i ∈ [1, m], m are the road number in ground micro-seismic monitoring record, t=[t1,t2,...,tn], to record the time, n is the time Number of sampling points.
The micro-seismic monitoring record inputted can be the data of multiple tracks ground micro-seismic signal, and micro-seismic event may go out Any time in present monitoring record.
2) waveform similar curves R (t) is obtained by calculating the waveform similarity factor between each road signal at various moments.
It can obtain by the following method the waveform similar curves R (t):
T is calculated firstjWaveform similarity factor between each road signal of moment record.The calculating of the waveform similarity factor Formula are as follows:
Wherein, nwin is selected time window length, i.e. R (tj) it is each road with tjNwin time span centered on moment Similarity factor between interior waveform.
Later, pass through continuous sliding window, it can calculate t1,t2,...tj,...tnThe waveform of each moment record Similarity factor, to obtain waveform similar curves R (t).
3) adaptive threshold Ht (t) is calculated according to the waveform similar curves R (t).
Hilbert transform is carried out to R (t) first, obtains the envelope H (t) of R (t).It is counted in a sliding window later Calculate the desired value E (t) and standard variance δ (t) that each moment includes H (t).
The calculation formula of adaptive threshold Ht (t) are as follows:
Ht (t)=E (t)+α δ (t) (2)
Wherein α is the weight coefficient of standard variance.
It 4) is T in time spaneventDetection window in, will meet R (t) be greater than Ht (t) maximum value Rmax(tl) identification For the event in the detection window, and by time t corresponding to the eventlThe shake time is played as the event.
The record time of micro-seismic monitoring can be divided into several detection windows, having for each detection window can It can detect to meet the maximum value R that R (t) is greater than Ht (t)max(tl).The number of detected maximum value in the entirely record time Mesh is then the number of the micro-seismic event identified based on micro-seismic monitoring record, and the time corresponding to each maximum value is then The micro-seismic event plays the shake time.
In one example, micro-seismic event recognition methods according to the present invention further comprises exporting the event and institute State the time corresponding to event.Identified micro-seismic event and institute can be shown in such a way that micro-seismic event identifies curve That states event plays the shake time.
In one example, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length.
In one example, the waveform similarity factor recorded at various moments can be calculated by sliding window, from And obtain waveform similar curves R (t).
In one example, calculating adaptive threshold Ht (t) according to the waveform similar curves R (t) includes: to the wave Shape similar curves R (t) carries out Hilbert transform, obtains the envelope H (t) of R (t), based on the desired value E including H (t) (t) and standard variance δ (t) calculates adaptive threshold Ht (t), the calculation formula of the adaptive threshold Ht (t) are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
The invention also provides a kind of microseism identification devices.The apparatus may include: for inputting micro-seismic monitoring note The unit of record, the micro-seismic monitoring record include the signal of the road m wave detector record, wherein the signal of every road i wave detector record For si(t), [1, m] i ∈, t=[t1,t2,...tj,...tn], to record the time, j ∈ [1, n], n are time sampling point number； For obtaining the unit of waveform similar curves R (t) by calculating the waveform similarity factor between each road signal at various moments；With In the unit for calculating adaptive threshold Ht (t) according to the waveform similar curves R (t)；Time span is T for identificationevent's The unit of the event of detection window is T in time spaneventDetection window in, will meet R (t) be greater than Ht (t) maximum value Rmax(tl) it is identified as the event in the detection window, and by time t corresponding to the eventlShake is played as the event Time.
In one example, micro-seismic event identification device according to the present invention further comprises for exporting the event And the unit of time corresponding to the event.
In one example, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length.
In one example, the waveform similarity factor recorded at various moments can be calculated by sliding window, from And obtain waveform similar curves R (t).
In one example, calculating adaptive threshold Ht (t) according to the waveform similar curves R (t) includes: to the wave Shape similar curves R (t) carries out Hilbert transform, obtains the envelope H (t) of R (t), based on the desired value E including H (t) (t) and standard variance δ (t) calculates adaptive threshold Ht (t), the calculation formula of the adaptive threshold Ht (t) are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
Using example
A concrete application example is given below in the scheme and its effect of the embodiment of the present invention for ease of understanding.This field It should be understood to the one skilled in the art that the example is only for the purposes of understanding the present invention, any detail is not intended to be limited in any way The system present invention.
Fig. 2 shows synthesis ground micro-seismic monitoring records, wherein being respectively present at the time of 200 milliseconds and 500 milliseconds One weak micro-seismic event and a strong micro-seismic event.
Input synthesis ground micro-seismic detection record illustrated in fig. 2；It is calculated between each road signal according to formula (1) Waveform similarity curve R (t), by Fig. 3 solid black lines indicate；Then, the envelope H of R (t) is obtained by Hilbert transform (t), it is indicated by the grey filled lines in Fig. 3；Finally, the self adaptive threshold curve Ht (t) is calculated according to formula (2), by Fig. 3 Black dotted lines indicate.It is T by the way that the record time of micro-seismic monitoring is divided into N number of time spaneventDetection window, every It is found respectively in a detection window and meets the maximum value R that R (t) value is greater than Ht (t) valuemax(tl).As shown in figure 3, by five jiaos of black The position of two maximum values of star representation is the position of two micro-seismic events in composite traces, and the corresponding time 200 Millisecond and 500 milliseconds of respectively two rising for micro-seismic events shake the time.
The presently disclosed embodiments is described above, above description is exemplary, and non-exclusive, and It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill Many modifications and changes are obvious for the those of ordinary skill in art field.The selection of term used herein, purport In the principle, practical application or improvement to the technology in market for best explaining each embodiment, or make the art Other those of ordinary skill can understand each embodiment disclosed herein.

Claims (8)

1. a kind of micro-seismic event recognition methods, which is characterized in that the described method comprises the following steps:
Micro-seismic monitoring record is inputted, the micro-seismic monitoring record includes the signal of the road m wave detector record, wherein the i-th inspection The signal of wave device record is si(t), [1, m] i ∈, t=[t1,t2,...tj,...tn], to record time, j ∈ [1, n], when n is Between number of sampling points；
Waveform similar curves R (t) is obtained by calculating the waveform similarity factor between each road signal at various moments；
Wherein, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length；
Adaptive threshold Ht (t) is calculated according to the waveform similar curves R (t)；And
It is T in time spaneventDetection window in, will meet R (t) be greater than Ht (t) maximum value Rmax(tl) be identified as it is described Event in detection window, and by time t corresponding to the eventlThe shake time is played as the event.
2. micro-seismic event recognition methods according to claim 1 further comprises exporting the event and the event The corresponding time.
3. micro-seismic event recognition methods according to claim 1, wherein calculate each moment by sliding window Waveform similarity factor, to obtain waveform similar curves R (t).
4. micro-seismic event recognition methods according to claim 1, wherein calculated according to the waveform similar curves R (t) Adaptive threshold Ht (t) includes:
Hilbert transform is carried out to the waveform similar curves R (t), obtains the envelope H (t) of R (t), is based on the envelope H (t) desired value E (t) and standard variance δ (t) calculates adaptive threshold Ht (t), and the calculating of the adaptive threshold Ht (t) is public Formula are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
5. a kind of micro-seismic event identification device, which is characterized in that described device includes:
For inputting the unit of micro-seismic monitoring record, the micro-seismic monitoring record includes the signal of the road m wave detector record, In, the signal of every road i wave detector record is si(t), [1, m] i ∈, t=[t1,t2,...tj,...tn], to record time, j ∈ [1, n], n are time sampling point number；
For obtaining the list of waveform similar curves R (t) by calculating the waveform similarity factor between each road signal at various moments Member；Wherein, tjThe calculation formula of waveform similarity factor between each road signal of moment record are as follows:
Wherein, nwin is selected time window length；
For calculating the unit of adaptive threshold Ht (t) according to the waveform similar curves R (t)；And
Time span is T for identificationeventDetection window event unit, time span be TeventDetection window It is interior, maximum value R of the R (t) greater than Ht (t) will be metmax(tl) it is identified as the event in the detection window, and by the event Corresponding time tlThe shake time is played as the event.
It further comprise for exporting the event and described 6. micro-seismic event identification device according to claim 5 The unit of time corresponding to event.
7. micro-seismic event identification device according to claim 5, wherein calculated when each by sliding window The waveform similarity factor for engraving record, to obtain waveform similar curves R (t).
8. micro-seismic event identification device according to claim 5, wherein calculated according to the waveform similar curves R (t) Adaptive threshold Ht (t) includes:
Hilbert transform is carried out to the waveform similar curves R (t), obtains the envelope H (t) of R (t), based on described including H (t) desired value E (t) and standard variance δ (t) calculates adaptive threshold Ht (t), and the calculating of the adaptive threshold Ht (t) is public Formula are as follows:
Ht (t)=E (t)+α δ (t)
Wherein, α is the weight coefficient of standard variance.
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CN112558145A (en) * 2019-09-25 2021-03-26 中国石油化工股份有限公司 Micro-seismic effective event identification method and system based on image processing
CN110646844B (en) * 2019-09-30 2021-01-26 东北大学 Tunnel rock fracture microseismic S wave arrival time picking method based on waveform envelope curve

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