CN108343429A - A kind of mud signal recognition methods based on Analysis on confidence - Google Patents
A kind of mud signal recognition methods based on Analysis on confidence Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000004458 analytical method Methods 0.000 title claims abstract description 16
- 238000005553 drilling Methods 0.000 claims abstract description 12
- 230000000630 rising effect Effects 0.000 claims abstract description 5
- 239000002002 slurry Substances 0.000 claims abstract description 5
- 239000000872 buffer Substances 0.000 claims description 20
- 230000008569 process Effects 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 5
- 210000001367 artery Anatomy 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 4
- 210000003462 vein Anatomy 0.000 claims description 4
- 241000208340 Araliaceae Species 0.000 claims description 3
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 claims description 3
- 235000003140 Panax quinquefolius Nutrition 0.000 claims description 3
- 235000008434 ginseng Nutrition 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 210000002445 nipple Anatomy 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 230000001133 acceleration Effects 0.000 claims description 2
- 230000009471 action Effects 0.000 claims description 2
- 238000005094 computer simulation Methods 0.000 claims description 2
- 238000009472 formulation Methods 0.000 claims description 2
- 239000007788 liquid Substances 0.000 claims description 2
- 239000000203 mixture Substances 0.000 claims description 2
- 238000005259 measurement Methods 0.000 abstract description 4
- 230000005540 biological transmission Effects 0.000 description 12
- 238000005516 engineering process Methods 0.000 description 9
- 238000012545 processing Methods 0.000 description 7
- 238000000354 decomposition reaction Methods 0.000 description 6
- 238000011156 evaluation Methods 0.000 description 6
- 238000002474 experimental method Methods 0.000 description 3
- 230000008054 signal transmission Effects 0.000 description 3
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Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
- E21B47/12—Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling
- E21B47/14—Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling using acoustic waves
- E21B47/18—Means for transmitting measuring-signals or control signals from the well to the surface, or from the surface to the well, e.g. for logging while drilling using acoustic waves through the well fluid, e.g. mud pressure pulse telemetry
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- Environmental & Geological Engineering (AREA)
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Abstract
The invention discloses a kind of new mud pulse signal recognition methods based on Analysis on confidence, it is characterised in that includes the following steps：Step S1：Measurement while drilling information is transmitted to ground in a manner of mud pulse signal, input is used as by standpipe pressure sensor acquisition pulse signal；Step S2：Input signal is pre-processed, the period that pulsewidth unit is determined according to the fundamental characteristics of signal rising edge and failing edge and the initial signal to be detected in this period；Step S3：It formulates characteristic standard and tentatively weighs whether the signal to be detected exported in S2 is actual signal；Step S4：The similarity of signal and standard slurry pulse signal after using being screened in two groups of different weight computing S3；Step S5：The signal similarity for comparing two kinds of different weight computings, selects a reasonable value as confidence level threshold value so that it is determined that final actual signal.
Description
Technical field
The present invention relates to a kind of mud signal recognition methods, belong to bore technical field of data processing, specifically one
The novel mud signal recognition methods based on Analysis on confidence of kind.
Background technology
Measurement while drilling has become the important means of current complex reservoir exploitation.Its basic principle is in drilling process
The engineering parameter and geological information for being measured nearly drill bit in real time using sensor are passed these information by downhole data transmission technology
It is defeated to arrive ground, it by analysis and handles, is used for geosteering and evaluating reservoir.With going deep into for technology application, one side well
The lower data class for measuring acquisition is more and more, higher and higher to the accuracy requirement of data, on the other hand to data transmission
More stringent requirements are proposed for reliability and transmission speed.Data transmission is an emphasis of measurement while drilling research.
Mud pulse signal transmission mode is the most universal with being applied in brill data transfer mode at present.Which be by
Measurement while drilling information is transmitted to ground in a manner of mud pulse signal, and ground system acquires arteries and veins by standpipe pressure sensor
Signal is rushed, the signals and associated noises after then restoring acquisition carry out signal identification, decoding and real-time display.The advantages of technology
It is：Technology maturation is easy to implement, and at low cost is not limited by site condition.But disadvantage is it is also obvious that mud pulse signal is boring
Transmission in column can be influenced by the various conditions in scene.First, pulse signal can be with transmission range in transmission process
Increase and significantly decays.Secondly, a large amount of noise signal can be adulterated during pulse signal transmission, these noise signals are main
It is caused by the various mechanical oscillation in underground or vibrations.In addition, the selection of mud material also will have a direct impact on pulse signal
Transmission.And in actual well drilled engineering, what the variation that is pumped in the influence of underground complex environment and drilling process also resulted in
The variation of pulse signal.Once ground system can not detect effective impulse signal or decoding error, can cause to orient engineering
Shi Buneng correctly judges underground real-time working condition.Therefore, research how the arteries and veins being tested under irregular strong noise background
Signal is rushed, the signal-to-noise ratio of mud-pulse transmission pulse signal is improved, is the key that mud-pulse transmission technology.The development of new technology
And the fusion of multi-field technology, effectively to reduce the bit error rate of mud pulse signal identification, ensure to measure work accurate and
Reliably provide important technical support.
Such as document 1：Tu Bing, Li Desheng, woods grace cherish MWD mud pulse signal Study of recognition of the based on clustering algorithm
[J] sensing technology journals, 2012,25 (8):It is special to the mud-pulse waveform extracting shape in 3 bit periods in 1172-1176.
Sign, and carry out binary coding 000~111 to it and be used as 16 kinds of reference models, extract mud pulse signal and model to be identified
The feature vector of signal calculates separately the Euclidean distance of its feature vector, the included angle cosine with two features and with two spies
Sign estimates T values as distinguishing indexes, chooses the model with optimal index as final identification signal.
Document 2：Li Hong, Fang Shihui, Lee race wait the Wavelet Detection technique study of mud pulse signals and apply [J] long
River college journal (from section's version), 2010,7 (1):In 68-71. using wavelet analysis method in time domain and frequency domain simultaneously to signal into
Row analysis, efficiently differentiates the Mutational part and noise section of measured signal on different decomposition layers, to eliminate noise letter
Number interference extract useful signal.
Document 3：Li Chuanwei, Yang Liang, Zhu Huanfen wait a kind of mud pulse signal recognition methods [J] logging techniquies of,
2013,37(2):It is sought in the signal by the second order difference of the first difference and difference result of seeking signal amplitude in 187-190.
Extreme point is found out, wave crest is secondly filtered out from extreme point according to pulse signal width feature and constraints, and utilize threshold
Value judges effective rising edge, and sliding window inner area maximum principle is finally taken to determine pulse position；
Patent CN201610784194 disclose it is a kind of based on wavelet packets decomposition tree with bore mud pulse signal drop
Method for de-noising.This method carries out WAVELET PACKET DECOMPOSITION to mud pulse signal first, obtains the complete decomposition tree of wavelet packet, later selection letter
Cease the entropy at cost function calculation each branch node to construct a minimum WAVELET PACKET DECOMPOSITION tree, finally by
Signal is reconstructed in the threshold value quantizing of wavelet packet coefficient, the signal after reconstruct is exactly the available mud after removing noise signal
Pulse signal.
Invention content
The object of the invention：On the idea basis that reliability assessment is analyzed in analogue system, it is proposed that one kind is based on credible
The mud pulse signal recognition methods of analysis is spent, this method reasonably selects evaluation criterion value, i.e., by extracting characteristic attribute value
When dynamic adjustment standard parameter, realize the automatic identification of mud pulse signal.The advantages of invention, is in avoiding conventional method
Influence of the middle human intervention to system identification result eliminates inconvenience and trouble that manual operation is brought.By using actual number
According to simulated experiment and live practical application, all shows that this method recognition effect, computational efficiency are ideal, can be perfectly suitable for brill
The transmission and processing of data.
Mud pulse signal recognition methods based on Analysis on confidence, includes the following steps：
Step S1：By acceleration transducer and fluxgate sensor, engineering parameter data E is obtained, resistivity, gal are passed through
The measuring instruments such as horse, porosity, obtain geologic parameter data G, downhole drilling system by data E, G send to driving it is short
Section, by the coding module on driving pipe nipple by data according to the rule encoding of predefined, referring concurrently to coding-control pulser
It is opened and closed valve, the flow of slurry liquid can change with the action of valve in drilling rod, to change the pressure of mud in drilling rod
Value generates pressure pulse, is used as input D by standpipe pressure sensor acquisition pulse signal；
Step S2：Output signal data D in S1 is pre-processed, there is the base of rising edge and failing edge according to signal
This characteristic determines the period of a pulsewidth unit, is obtained by the data situation in the period initial to be detected
Signal；
Step S3：It formulates characteristic standard and tentatively weighs whether the signal to be detected exported in S2 is actual signal, feature mark
Accurate formulation is divided into two stages：Dynamic tune ginseng in the standard setting and identification process of incipient stage；
Step S31：The characteristic standard for setting the incipient stage will produce 2~3 companies in the incipient stage for obtaining pulse data
Continuous pulse signal, is calculated using the featureAs the characteristic standard value of sequence incipient stage, wherein n indicates to connect
Continuous pulse number, piIt includes four attributes to be characterized attribute component values：It is the high H of filtered output, the bottom edge L of filtered output, trapezoidal
Two bevel edges K1, K2 of signal；
Step S32：Capacity is set as the measured signal buffer pool of N, thresholding H is set into for buffer pool：0.5H0~
1.5H0、L：0.8L0~1.2L0；
Step S33：It reads signal to be detected and handle meets current signature standard p0Signal be input to buffer pool, buffer
Chi Manhou carries out the number of 1~n for the signal in buffer pool and sets gradually signal weight qi, it is bigger which meets number
Weight is higher and q1+…+qn=1 constraint；
Step S34：Update characteristic standardPreserve buffer pool signal data, clearing buffers pond；
Step S35：S33 is repeated until no signal to be detected；
Step S4：For the signal after being screened in S3, using two groups of different weight computings, it is believed with standard slurry pulse
Number similarity；
Step S41：Calculate the value of each similar finite elementWherein yrIndicate that simulation object corresponds to similar finite element
As a result, ysIndicate analogue system corresponds to similar finite element as a result, if similar finite element component value by dynamic variable calculate acquire, calculate
Formula is
Wherein the time started is t1, end time t2, weight βt；
Step S42：It is H according to analytic hierarchy process (AHP) stepi、Li、K1i、K2iFour similar finite element Judgement Matricies R, matrix
Template is as follows：The respective weights of each similar finite element are calculated by geometric average method and specification column average method
βi；
Step S43：Computer sim- ulation system A and the similarity for being imitated object B
Step S5：The signal similarity for comparing two kinds of different weight computings, selects a reasonable value as confidence level thresholding
Value, final actual signal is determined according to confidence level thresholding.
Description of the drawings
Attached drawing 1 is the processing flow schematic diagram of the present invention
Attached drawing 2 is window and waveform relationship figure
Attached drawing 3 is signal waveform geometric shape schematic diagram
Attached drawing 4 is similarity calculation statistical chart
Attached drawing 5 is similarity curve figure
Attached drawing 6 is waveform analysis surface chart
Attached drawing 7 is experimental result statistical form
Attached drawing 8 is experimental result bar chart
Specific implementation mode
1-6 and real data below in conjunction with the accompanying drawings, the invention will be further described：Mud based on Analysis on confidence
Pulse signal recognition methods, specific embodiment include the following steps that step is as shown in Figure 1：
(1) data acquisition.Mud pulse signal is acquired by standpipe pressure sensor, and using Wavelet transformation to acquisition
Signal denoising processing, specific formula are as follows：
Wherein, Ψ indicates that wavelet basis, different wavelet basis are suitable for different signal processings, the Harr used in this patent
Wavelet basis.
(2) Signal Pretreatment.The purpose of Signal Pretreatment is to determine specific position of the signal to be tested in time series
It sets, sets the time window (window size is denoted as N) that width is slightly larger than pulsewidth first, and window is divided into two son of left and right from centre
Window, left window is for judging pulse signal rising edge, and right window is for judging pulse signal failing edge.As window is in the time
The relationship of sliding in sequence, window and waveform can be divided into four kinds of situations as shown in Figure 1.It is required for acquiring in the case of four kinds complete
The maximum max of window, the window's position max_p where recording and judging maximum.The location information reflected according to maximum
It can determine which kind of situation current time, window belong to waveform.
Situation (a)：Peak value of pulse does not enter window (max_p=N).In this case, right window is acquired from window edge N
Signal minimum position Rmin_p, and in clears window N/2 to Rmin_p data.So operation is to ensure in window only
Signal section to be detected is stored, irrelevant data are removed.
Situation (b)：Peak value of pulse enters right window (N/2<max_p<N).In this case be not necessarily to any operation bidirectional after
Continuous moving window.
Situation (c)：Peak value of pulse is in window centre position (N/2=max_p).Window that such case is reflected with
The relationship of waveform is dbjective state.The window's position of minimum and every section of trisection point by calculating left and right child window can be substantially
Determine whether measured signal meets left window and be incremented by, the decision condition that right window is successively decreased.Record signal information and general if meeting
Data before right child window minimum empty.
Situation (d)：Peak value of pulse is in window centre position (N/2>max_p).Under normal conditions, this situation is not
It will appear, prevent the accident of window moving process, just in case there is such case, then window is retracted to the shape of N/2=max_p
State, and recalculated by the processing mode of situation (c).
(3) characteristic standard is formulated.As shown in figure 3, this patent indicates the geometric form of signal waveform using the ladder approximation that connects
State, and trapezoidal high H is selected, the slope K 1 of two bevel edges, the characteristic attribute of K2 and bottom edge L as signal.According to positive pulse signal
Coding characteristic, each coding all have before data transmission the characteristics of one group of synchronizing signal, general synchronizing signal be 2 or 3
Continuous impulse signal.In the incipient stage that pulse data obtains the time of adjacent pulse is calculated using this feature of continuous impulse
Difference, according to waveform local similarity, judges the spy of continuous impulse with characteristic attribute value on meeting the conditioned basic of continuous impulse
It is whether close or consistent to levy attribute value, finally utilizes formulaArithmetic mean of instantaneous value is acquired as the sequence incipient stage
Characteristic standard value, wherein p0It is characterized standard value, pi=(Hi,k1i,k2i,Li)。
In signal acquisition process, setting can store the buffer pool of N number of measured signal, i.e. buffer pool size is N, and is slow
It rushes pond and specifies thresholding, set a certain range (H into thresholding as current signature standard value of buffer pool：0.5H0~1.5H0、L：
0.8L0~1.2L0), which can effectively shield the larger noise of deviation.It is slow that this is initially entered before measured signal judgement
Pond is rushed, is in buffer pool according to adjacent signals waveform similarity by signal 1~n of number in buffer pool after pond to be buffered is full
Signal distribute weights, weights meet number it is bigger, weight is higher, and makes q1+…+qn=1.By formulaIt asks
The characteristic standard adjusted value in identification process is obtained, with the continuous acquisition of signal, the testing data in buffer pool is constantly updated, special
Sign standard also updates therewith, to realize adaptive standard adjustment.
(4) signal similarity is calculated.Similarity, that is, analogue system and the similarity degree for being imitated object, are the phases by the two
What the factors such as weights codetermined is influenced on system current status like first quantity, the value of similar finite element and each similar finite element, similarity is got over
It is more complete that height indicates that simulation object reduction is imitated object.It is B by imitative object if analogue system is A, similar finite element between A, B
Number is n, and the value of each similar finite element is qi, influence weights of each similar finite element to similarity are βi, then the similarity of A and B can determine
Justice is formulaWeights βiIt is calculated by analytic hierarchy process (AHP), and the value q of similar finite elementiPublic affairs can be passed through
FormulaIt obtains.
The above method is applied to mud pulse signal similarity calculation process.Might as well set acquisition signal system as A, standard
Signal system is B, and there are 4 similar finite elements between two signal systems, i.e., correspond to tetra- characteristic attribute values of H, L, k1, k2 respectively, if
The value of each similar finite element is qiThe weights of (i=1,2,3,4), each similar finite element are βi(i=1,2,3,4).Weight computing process is such as
Under：H and L significant coefficients are set as 5 according to analytic hierarchy process (AHP) according to four characteristic attribute interactional significance levels；H with
K1, k2 significant coefficient are 5；L is 5 with k1, k2 significant coefficient.It is in reciprocal relation according to significant coefficient between similar finite element, i.e.,The judgment matrix R for constructing evaluation index is as follows：
It H, L, k1, k2 is acquired by geometric average method corresponds to weights and be：0.5344,0.2384,0.1136,0.1136.By advising
Model column average method, which acquires H, L, k1, k2 and corresponds to weights, is：0.5,0.35,0.075,0.075, bring formula intoIn, as a result statistical chart is as shown in Figure 4.
(5) trust evaluation is analyzed.Mud pulse signal trust evaluation exactly utilizes calculated in (4) wait for
Survey signal similarity result, judgement measured signal whether be actual signal process.During general evaluation, the higher theory of similarity
Bright measured signal is closer with standard signal, selects a reasonable value as confidence level threshold value, higher than can then determining for the thresholding
Property is determined as actual signal, and then qualitative less than the thresholding is determined as noise jamming.Data in Fig. 4 are subjected to statistical disposition：
If A schemes are the weight computing similarity resulting value that geometric average method acquires, A values are denoted as, B schemes are that specification column average method acquires
Weight computing similarity resulting value, be denoted as B values.18 groups of confidence levels are sorted and numbered from big to small, can be obtained from above-mentioned analysis
Confidence level is interference signal less than 0.62, is actual signal more than 0.62, and actual signal can separately be obtained with interference signal
Four groups of broken lines are as shown in Figure 5.It can be obtained by Fig. 5：1. actual signal, which corresponds to similarity value and interference signal, in A schemes apparent point
Boundary, boundary distances correspond to similarity value and interference signal more than actual signal in 0.1, B schemes apparent unobvious, boundary distances
Only 0.02；2. the actual signal similarity value that A schemes acquire successively decreases, change rate ratio B schemes are small, and value is more concentrated, to interference
The similarity value of signal is also in identical rule.It can be obtained by analyzing above：The pulse signal geometric average method of this feature is acquired
Weights function and effect it is ideal.Using the present invention to mud-pulse in real data simulated experiment and live practical application
Signal is identified, and Fig. 6 show signal identification as a result, wherein outlining what the pulse signal come was identified by Analysis on confidence
Signal.As can be seen from Figure 6, this method goes out a part of noise as signal identification, and noise reliability is 0.712 and 0.717.
Although the invention can not complete 100% identification pulse signal, identification error<3% has met Practical Project requirement.
Mud pulse signal recognition methods based on Analysis on confidence is the think of that reliability assessment is analyzed in analogue system
It is proposed on the basis of thinking, rational to select evaluation criterion value by the extraction of characteristic attribute value, the standard ginseng of dynamic adjustment immediately
Number, realizes the automatic identification of mud pulse signal.To Analysis on confidence, clustering recognition, optimal wavelet decomposition tree and Wavelet Detection
These four recognition methods carry out the identification experiment of 10 groups of mud pulse signals respectively under 15Hz frequency acquisitions, count each identification
The recognition time and recognition accuracy of algorithm are averaged as final result, and Fig. 7 and Fig. 8 are final statistical results chart.By
On can obtain, which can be perfectly suitable for the transmission and processing for boring data, and compared with other three kinds of identification sides
Method has faster recognition speed in the case where not losing discrimination.
Claims (3)
1. a kind of mud pulse signal recognition methods based on Analysis on confidence, it is characterised in that include the following steps：
Step S1：By acceleration transducer and fluxgate sensor, obtain engineering parameter data E, by resistivity, gamma,
The measuring instruments such as porosity obtain geologic parameter data G, and downhole drilling system sends data E, G to driving pipe nipple, by
Drive the coding module on pipe nipple by data according to the rule encoding of predefined, referring concurrently to coding-control pulser open and close valve
, the flow of slurry liquid can change with the action of valve in drilling rod, to change the pressure value of mud in drilling rod, generate
Pressure pulse is used as input D by standpipe pressure sensor acquisition pulse signal；
Step S2：Output signal data D in S1 is pre-processed, there is the spy substantially of rising edge and failing edge according to signal
Property, it determines the period of a pulsewidth unit, initial signal to be detected is obtained by the data situation in the period；
Step S3：It formulates characteristic standard and tentatively weighs whether the signal to be detected exported in S2 is actual signal, characteristic standard
Formulation is divided into two stages：Dynamic tune ginseng in the standard setting and identification process of incipient stage；
Step S4：For the signal after being screened in S3, using two groups of different weight computings its with standard slurry pulse signal
Similarity；
Step S5：The signal similarity for comparing two kinds of different weight computings, selects a reasonable value as confidence level threshold value, root
Final actual signal is determined according to confidence level thresholding.
2. a kind of mud pulse signal recognition methods based on confidence level according to claims, it is characterised in that step
S3 includes the following steps：
Step S31：The characteristic standard for setting the incipient stage will produce 2~3 continuous arteries and veins in the incipient stage for obtaining pulse data
Signal is rushed, is calculated using the featureAs the characteristic standard value of sequence incipient stage, wherein n indicates continuous arteries and veins
Rush number, piIt includes four attributes to be characterized attribute component values：The high H of filtered output, bottom edge L, the filtered output of filtered output
Two bevel edges K1, K2；
Step S32：Capacity is set as the measured signal buffer pool of N, thresholding H is set into for buffer pool：0.5H0~1.5H0、L：
0.8L0~1.2L0；
Step S33：It reads signal to be detected and handle meets current signature standard p0Signal be input to buffer pool, buffer pool is full
Afterwards, it carries out the number of 1~n for the signal in buffer pool and sets gradually signal weight qi, which, which meets, numbers bigger weight
Higher and q1+…+qn=1 constraint；
Step S34：Update characteristic standardPreserve buffer pool signal data, clearing buffers pond；
Step S35：S33 is repeated until no signal to be detected.
3. a kind of mud pulse signal recognition methods based on confidence level according to claims, it is characterised in that step
S4 includes the following steps：
Step S41：Calculate the value of each similar finite elementWherein yrIndicate simulation object correspond to similar finite element as a result,
ysIndicate analogue system corresponds to similar finite element as a result, if similar finite element component value by dynamic variable calculate acquire, calculation formula
For
Wherein the time started is t1, end time t2, weight βt；
Step S42：It is H according to analytic hierarchy process (AHP) stepi、Li、K1i、K2iFour similar finite element Judgement Matricies R, matrix template is such as
Under：The respective weights β of each similar finite element is calculated by geometric average method and specification column average methodi；
Step S43：Computer sim- ulation system A and the similarity for being imitated object B
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110792429A (en) * | 2019-11-04 | 2020-02-14 | 中国石油集团川庆钻探工程有限公司 | Method for encoding downhole data by simultaneously utilizing positive and negative pressure pulses and transmission method |
| CN114674363A (en) * | 2022-03-01 | 2022-06-28 | 扬州华辉水泵有限公司 | Slurry pump flow velocity reliability prediction system based on industrial Internet of things |
| CN115296752A (en) * | 2022-08-02 | 2022-11-04 | 中国石油天然气集团有限公司 | Mud pulse data coding and transmitting method, device and equipment |
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