CN110472078A - A kind of method that drill bit identity information is entered into drilling data base - Google Patents
A kind of method that drill bit identity information is entered into drilling data base Download PDFInfo
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- CN110472078A CN110472078A CN201910728778.7A CN201910728778A CN110472078A CN 110472078 A CN110472078 A CN 110472078A CN 201910728778 A CN201910728778 A CN 201910728778A CN 110472078 A CN110472078 A CN 110472078A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/51—Indexing; Data structures therefor; Storage structures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/757—Matching configurations of points or features
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The invention discloses a kind of methods that drill bit identity information is entered into drilling data base, this method has preset the Comparison of standards database that record has drill bit identity information, pass through the comparison of the local feature of text information, drill bit in the nameplate and number of Comparison of standards database and drill bit to be logged etc., the identity information that drill bit can automatically and accurately be picked out enables drill bit user efficiently and accurately will be in the identity information typing drilling data base of drill bit.
Description
Technical field
The invention belongs to petroleum drilling technology field, relates in particular to a kind of drill bit identity information and be entered into well data
The method in library
Background technique
In oil drilling, drill bit is the main tool of fractured rock, and wellbore is formed by drill bit fractured rock.Drill bit pair
Tremendous influence is generated in terms of drilling quality, drilling rate, drilling cost.There are many kinds of classes for drill bit, with different drilling sides
Formula classifies to drill bit, can be classified as diamond bit, rock bit and drag bit, column drill head etc..Diamond
Drill bit is divided into normal diamond drill bit, polycrystalline diamond compact bit two major classes；It, can be with using the structure of rock bit as foundation
It is classified as this five parts of hydrophthalmia, bearing, palm, gear wheel and bit body.Producer's enormous amount of drill bit is produced, in order to mention
High bit performance, drill bit producer design production drill bit have their own characteristics each, type and model are various, and the naming method of drill bit and
Rule is different.Although uniformly having carried out IADC number to drill bit in the world, currently, the user of service of drill bit is still by hand
Specification and number are consulted to identify the identity information of drill bit, inefficiency；If drill bit specification, nameplate and number are lost, only
It can be by the identity information of Conventional wisdom conjecture drill bit.Therefore, often there is the brill in typing drilling data base in situ of drilling well
The case where head identity information does not conform to the actual conditions, i.e., drill bit identity information is reported by mistake, has seriously affected being normally carried out for drilling well production.
Summary of the invention
It is an object of the invention to solve the above-mentioned problems in the prior art, a kind of drill bit identity information typing is provided
To the method for drilling data base, the present invention can automatically and accurately pick out the identity information of drill bit, so that drill bit user
It can efficiently and accurately will be in the identity information typing drilling data base of drill bit.
To achieve the above object, The technical solution adopted by the invention is as follows:
A kind of method that drill bit identity information is entered into drilling data base, it is characterised in that the following steps are included:
A, by the identity information typing presetting database of all drill bits, and each drill bit and identity information is made to establish an a pair
It should be related to, form Comparison of standards database；
B, image information is obtained by image acquisition device, judges whether there is image and needs to analyze, if so, step c is then executed,
Otherwise this step is continued to execute；
C, acquired image is subjected to binary conversion treatment, obtains binary image, using small echo Moment Methods, with BP network
It is identified, input binary image is passed through into normalized, Polar coordinates after invariable rotary small echo Moment Feature Extraction, are sent
Enter BP network classifier to be identified, the global characteristics and local feature of objects in images is obtained, according to the global characteristics of object
Judge whether the object in image belongs to drill bit with local feature；If so, executing D step, this step is otherwise continued to execute；
D, the position of locking drill bit in the picture, and drill bit is extracted using cyclic convolution neural network Text region algorithm
Text information in nameplate and number, executes step e if extracting successfully, unsuccessfully executes f step if extracting；
E, according to the words information searching matching criteria comparison database extracted in the nameplate and number of drill bit, if matching
Success, then correspond to the identity information of output the drill bit, and obtained identity information is entered into drilling data base；If matching is lost
It loses, then executes f step；
F, the local feature that drill bit in image is extracted using SURF algorithm, determine the size of each local feature, position and away from
From attribute, the geometric feature of each local feature is then calculated, the type and quantity of each local feature are obtained, further according to each part
The type and number search matching criteria comparison database of feature, if successful match, the identity information of corresponding output the drill bit,
And obtained identity information is entered into drilling data base；If it fails to match, g step is executed；
G, according to the type and quantity of each local feature, judge whether the identity information of newly-built drill bit and supplement typing standard
Comparison database, if so, first by the type of each local feature and quantity typing to Comparison of standards database, and supplement foundation and bore
The one-to-one relationship of head and identity information, then the identity information of corresponding output the drill bit, and the identity information is entered into brill
In well database；Otherwise h step is executed；
H, the identity information typing of drill bit is completed.
It is as follows using the principle of small echo Moment Methods in the step e:
If image is f (x, y), standard square is defined as Mpq=∫ ∫ xpyqF (x, y) dxdy, by x=rcos (θ), y=rsin
(θ), then F under polar coordinate systempq=∫ ∫ f (r, θ) gpejqθRdrd θ selects cubic spline function wavelet, is translated by stretching, extension
Generate wavelet function collection μm,n(r), so | Fmnpq|=| ∫ ∫ f (r, θ) μm,n(r)gpejqθRdrd θ |, m, n represents scale and translation
Variable, by manually being obtained according to the feature of bite type and each component of drill bit through loop test, adjustment m and n can obtain figure
The global characteristics and local feature of object as in.
The identity information of the drill bit includes classification, body construction, is applicable in stratum, cutting toothing, carcass, wing number
Amount, nozzle quantity, production firm, nameplate, model and number information.
The drill bit includes bit matrix, cutting tooth, wing, nozzle, bearing, palm and gear wheel, the local feature of drill bit
Refer to bit matrix feature, cutting tooth feature, wing feature, nozzle characteristics, bearing features, palm feature and gear wheel feature.
Using the present invention has the advantages that
The present invention identification typing of realizing drill bit identity information inexpensive using computer vision, and in image recognition
When, there is good resolution capability to the sample for needing to translate, scale and rotate using small echo moment characteristics, in the feelings of non-plus noise
Under condition, small echo moment characteristics can correctly differentiate test sample, and discrimination is better than geometric moment 30%；Wavelet moment has preferable extract
The ability of image local feature, highest correct recognition rata reach 98%, can not only efficiently reduce calculation amount and memory size, mention
Computationally efficient, and any high resolution ratio can be obtained in limited transformation space, realize the intelligent image of high-accuracy
Drill bit identification.
In addition, used SURF algorithm in drill bit local shape factor, this method does not need the acceleration and specially of hardware
With the cooperation of image processor, it can be achieved that the real-time modeling method based on Feature Points Matching, the image per second for handling 8-24 frame,
Realize that the search that the characteristic point of each component of drill bit is completed in Millisecond, characteristic vector generate, characteristic vector matches, target lock-on
Equal work.It is demonstrated experimentally that SURF algorithm wants fast 3 times or so in arithmetic speed, the intelligent drill bit of high speed, high-accuracy is realized
The acquisition and typing of information change traditional manual identified and typing, avoid artificial identification fault and wrong report.It can be extensive
It applies in oil and gas well drilling industry, is conducive to carry out intelligent drill bit management, be conducive to the identification of drill bit user's efficiently and accurately
With typing drill bit, have a extensive future.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is the schematic diagram of device used herein；
Schematic diagram when Fig. 3 is present invention search matching criteria comparison database；
Specific embodiment
The present invention provides a kind of methods that drill bit identity information is entered into drilling data base, comprising the following steps:
A, by the identity information typing presetting database of all known drill bits, and each drill bit and identity information is made to establish one
One corresponding relationship forms Comparison of standards database.Wherein, the identity information of drill bit includes drill bit classification, body construction, is applicable in ground
Layer, cutting toothing, carcass, wing quantity, nozzle quantity, production firm, nameplate, model and number information etc..
B, image information is obtained by image acquisition devices such as digital cameras, judges whether there is image and needs to analyze, if so,
Step c is then executed, this step is otherwise continued to execute.
C, drill bit includes the components such as bit matrix, cutting tooth, wing, nozzle, bearing, palm and gear wheel, and each component has
Different local features, respectively bit matrix feature, cutting tooth feature, wing feature, nozzle characteristics, bearing features, palm
Feature and gear wheel feature etc..Therefore, acquired image is subjected to binary conversion treatment, obtains binary image, using wavelet moment
Method is identified with BP network, and input binary image is passed through normalized, Polar coordinates, invariable rotary wavelet moment
After feature extraction, it is sent into BP network classifier and is identified, the global characteristics and local feature of objects in images are obtained, according to object
The global characteristics and local feature of body judge whether the object in image belongs to drill bit；If so, executing D step, otherwise continue to hold
This step of row.
In this step, the principle using small echo Moment Methods is as follows:
If image is f (x, y), standard square is defined as Mpq=∫ ∫ xpyqF (x, y) dxdy, by x=rcos(θ), y=rsin
(θ), then F under polar coordinate systempq=∫ ∫ f (r, θ) gpejqθRdrd θ selects cubic spline function wavelet, is translated by stretching, extension
Generate wavelet function collection μm,n(r), so | Fmnpq|=| ∫ ∫ f (r, θ) μm,n(r)gpejqθRdrd θ |, m, n represents scale and translation
Variable, by manually being obtained according to the feature of bite type and each component of drill bit through loop test, adjustment m and n can obtain figure
The global characteristics and local feature of object as in.
In this step, the global characteristics of objects in images and the preparation method of local feature are as follows: the global characteristics of object and
Feature vector a0 and b0 is respectively adopted to indicate in local feature, different objects, the feature of global characteristics and local feature to
Magnitude is different.Using the global characteristics of the available drill bit of BP neural network training and feature vector the value a and b of local feature, if
Feature vector a0, b0 and a, b difference then judge that the object in image belongs to drill bit less than 5%.
D, it using the method combined based on movement and model, the position of locking drill bit in the picture, and is rolled up using circulation
Product neural network (CRNN) Text region algorithm extracts the text information in the nameplate and number of drill bit, executes if extracting successfully
Step e executes f step if extracting failure.
E, according to the words information searching matching criteria comparison database extracted in the nameplate and number of drill bit, if matching
Success, then correspond to the identity information of output the drill bit, and obtained identity information is entered into drilling data base, completes the brill
The typing of head identity information；If it fails to match, f step is executed.
F, the local feature that drill bit in image is extracted using SURF algorithm draws a circle to approve out bit matrix feature in image, cutting
The regions such as tooth feature, wing feature, nozzle characteristics, bearing features, palm feature and gear wheel feature, determine bit matrix feature,
Cutting tooth feature, wing feature, nozzle characteristics, bearing features, the size of palm feature and gear wheel feature, position and apart from category
Property, their geometric feature is then calculated, obtains type and the quantity of each local feature to get bit matrix type sum number out
Amount, cutting tooth structure type and quantity, wing type and quantity, bleed type and quantity, bearing type and quantity, palm type
With the parameters such as quantity, gear wheel type and quantity；Type and number search matching criteria correlation data further according to each local feature
Library, if successful match, the identity information of corresponding output the drill bit, and obtained identity information is entered into drilling data base
In, complete the typing of the drill bit identity information；If it fails to match, g step is executed.
In this step, using SURF algorithm can carry out the search of characteristic point to each component of drill bit, characteristic vector generates,
The work such as characteristic vector matching, target lock-on.
G, according to bit matrix type and quantity, cutting tooth structure type and quantity, wing type and quantity, bleed type
With the parameters such as quantity, bearing type and quantity, palm type and quantity, gear wheel type and quantity, judge whether newly-built drill bit
Identity information simultaneously supplements typing Comparison of standards database, if so, first by the type of each local feature and quantity typing to standard
Comparison database, and the one-to-one relationship for establishing drill bit and identity information is supplemented, then the identity information of corresponding output the drill bit,
And the identity information is entered into drilling data base；Otherwise h step is executed.
H, the identity information typing of drill bit is completed.
The identity information of obtained drill bit both can be manually entered into drilling data base by the present invention, can also be automatically by drill bit
Identity information be entered into drilling data base.
The present invention also provides a kind of devices used for above-mentioned input method comprising database module, image recognition
Module and transmission module.Wherein, database module includes Comparison of standards Database Unit, database matching unit and supplementary training
Unit；Picture recognition module includes image judging unit, image acquisition units, drill bit recognition unit, drill bit lock cell, nameplate
Word recognition unit, component recognition unit.
Comparison of standards Database Unit: being used to form Comparison of standards database, by drill bit classification, body construction, is applicable in ground
The identity informations records such as layer, cutting toothing, carcass, wing quantity, nozzle quantity, production firm, nameplate, model and number information
Enter in Comparison of standards database.
Database matching unit: for searching for matching criteria comparison database.
Supplementary training unit: it for that will fail to identify that the identity information of drill bit supplements typing Comparison of standards database, utilizes
Back-propagation algorithm (BP algorithm) self training, supplement establish the one-to-one relationship of drill bit and identity information, improve drill bit and know
Other accuracy rate.
Image judging unit: it needs to analyze for judging whether there is image.
Image acquisition units: for acquiring the image of drill bit.
Drill bit recognition unit: the drill bit in image for identification；Each component of drill bit has different geometrical characteristics, and utilization is several
What characteristic method and local method for feature analysis, analyze and whether there is drill bit in image.
Drill bit lock cell: for locking the position of drill bit in the picture.
Nameplate word recognition unit: the text in the nameplate and number of drill bit for identification.
Component recognition unit: for identification with analysis bit matrix type and quantity, cutting tooth structure type and quantity, knife
The ginseng such as wing type and quantity, bleed type and quantity, bearing type and quantity, palm type and quantity, gear wheel type and quantity
Number.
Output unit: for exporting matching result, drill bit identity information, and user is prompted to operate in next step.
Data transmission module: for the identity information of drill bit to be transmitted to drilling data base.
Claims (4)
1. a kind of method that drill bit identity information is entered into drilling data base, it is characterised in that the following steps are included:
A, by the identity information typing presetting database of all drill bits, and each drill bit and identity information is made to establish to correspond and close
System forms Comparison of standards database；
B, image information is obtained by image acquisition device, judges whether there is image and need to analyze, if so, then executes step c, otherwise
Continue to execute this step；
C, acquired image is subjected to binary conversion treatment, obtains binary image, using small echo Moment Methods, carried out with BP network
Input binary image is passed through normalized by identification, and Polar coordinates after invariable rotary small echo Moment Feature Extraction, are sent into BP
Network classifier is identified, the global characteristics and local feature of objects in images are obtained, according to the global characteristics drawn game of object
Portion's feature judges whether the object in image belongs to drill bit；If so, executing D step, this step is otherwise continued to execute；
D, the position of locking drill bit in the picture, and using the nameplate of cyclic convolution neural network Text region algorithm extraction drill bit
With the text information in number, step e is executed if extracting successfully, unsuccessfully executes f step if extracting；
E, according to extracting words information searching matching criteria comparison database in the nameplate and number of drill bit, if matching at
Function, then correspond to the identity information of output the drill bit, and obtained identity information is entered into drilling data base；If matching is lost
It loses, then executes f step；
F, the local feature that drill bit in image is extracted using SURF algorithm determines the size of each local feature, position and apart from category
Property, the geometric feature of each local feature is then calculated, obtains the type and quantity of each local feature, further according to each local feature
Type and number search matching criteria comparison database, if successful match, the identity information of corresponding output the drill bit, and will
Obtained identity information is entered into drilling data base；If it fails to match, g step is executed；
G, according to the type and quantity of each local feature, judge whether the identity information of newly-built drill bit and supplement typing Comparison of standards
Database, if so, first by the type of each local feature and quantity typing to Comparison of standards database, and supplement establish drill bit with
The one-to-one relationship of identity information, then the identity information of corresponding output the drill bit, and the identity information is entered into drilling well number
According in library；Otherwise h step is executed；
H, the identity information typing of drill bit is completed.
2. the method that a kind of drill bit identity information according to claim 1 is entered into drilling data base, it is characterised in that: step
It is as follows using the principle of small echo Moment Methods in rapid e:
If image is f (x, y), standard square is defined as Mpq=∫ ∫ xpyqF (x, y) dxdy, by x=rcos (θ), y=rsin (θ), then
F under polar coordinate systempq=∫ ∫ f (r, θ) gpejqθRdrd θ selects cubic spline function wavelet, is generated by stretching, extension translation small
Wave function collection μM, n(r), so | Fmnpq|=| ∫ ∫ f (r, θ) μM, n(r)gpejqθRdrd θ |, m, n represent scale and translation variable, by
It is manually obtained according to the feature of bite type and each component of drill bit through loop test, adjustment m and n can obtain objects in images
Global characteristics and local feature.
3. the method that a kind of drill bit identity information according to claim 1 or 2 is entered into drilling data base, feature exist
In: the identity information of drill bit includes classification, body construction, is applicable in stratum, cutting toothing, carcass, wing quantity, nozzle number
Amount, production firm, nameplate, model and number information.
4. the method that a kind of drill bit identity information according to claim 1 or 2 is entered into drilling data base, feature exist
In: drill bit includes bit matrix, cutting tooth, wing, nozzle, bearing, palm and gear wheel, and the local feature of drill bit refers to drill bit tire
Body characteristics, cutting tooth feature, wing feature, nozzle characteristics, bearing features, palm feature and gear wheel feature.
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Cited By (1)
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| CN110472078B (en) | 2022-08-19 |
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