CN110259433A - A kind of entity drilling machine digital monitoring method - Google Patents
A kind of entity drilling machine digital monitoring method Download PDFInfo
- Publication number
- CN110259433A CN110259433A CN201910574682.XA CN201910574682A CN110259433A CN 110259433 A CN110259433 A CN 110259433A CN 201910574682 A CN201910574682 A CN 201910574682A CN 110259433 A CN110259433 A CN 110259433A
- Authority
- CN
- China
- Prior art keywords
- data
- drilling machine
- unit
- model
- entity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000005553 drilling Methods 0.000 title claims abstract description 87
- 238000012544 monitoring process Methods 0.000 title claims abstract description 68
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000013178 mathematical model Methods 0.000 claims abstract description 30
- 238000003860 storage Methods 0.000 claims abstract description 29
- 238000004088 simulation Methods 0.000 claims abstract description 15
- 238000009434 installation Methods 0.000 claims abstract description 4
- 230000007613 environmental effect Effects 0.000 claims description 21
- 238000005094 computer simulation Methods 0.000 claims description 19
- 238000013499 data model Methods 0.000 claims description 11
- 239000000463 material Substances 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000004891 communication Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000013480 data collection Methods 0.000 claims description 5
- 238000001914 filtration Methods 0.000 claims description 4
- 230000000386 athletic effect Effects 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims description 3
- 238000013461 design Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 6
- 238000007639 printing Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 6
- 238000007726 management method Methods 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000005299 abrasion Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000003129 oil well Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- 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
- E21B44/00—Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
-
- 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
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Geology (AREA)
- Mining & Mineral Resources (AREA)
- Physics & Mathematics (AREA)
- Environmental & Geological Engineering (AREA)
- Fluid Mechanics (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Geophysics (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention discloses a kind of entity drilling machine digitized monitoring system, which can be divided into 6 formants: be respectively field device monitoring unit, site environment monitoring unit, mathematical model, real-time operation unit, client and storage unit.Wherein field device monitoring unit and the installation of site environment monitoring unit are used for collection site device data and site environment information on site, mathematical model is used to store the method needed for calculating, and real-time operation unit can directly export the calculated result of simulation model for the logic calculation of data, the early warning beyond limit value, printing reports, the clients such as operation be recommended to check system monitoring state for operator and service technician；Storage unit is used for historical data archiving; storage unit can be located locally, remote server or cloud; the present invention make the problem of leaning on micro-judgment in the past all realize accurately calculate, quantify display, avoid due to operator's subjective experience occur erroneous judgement, avoid non-programmed halt, improve operational efficiency, reduce operating cost, rationally prepare accessory.
Description
Technical field
The invention belongs to oil drilling equipment control technical fields, are related to a kind of entity drilling machine digital monitoring method.
Background technique
Oil-well rig belongs to type mechanical equipment of working continuously, and drilling well before finishing drilling once not allowing to shut down.And the machine
Several wear-out parts in tool system must regularly replace, and otherwise can will lead to because of hang-up caused by element fault, when serious huge
Huge economic loss.At present to there are two types of the service life evaluation methods of crucial wearing detail: calculating runing time and micro-judgment.
As: use runing time to determine the replacement cycle the cylinder sleeve of drilling pump；Winch brake piece, bearing etc. rely on operator's experience
Judge whether to need replacing.Though the two methods are used till today always, but still lack scientific and accuracy.Since equipment is run
Environment difference, load behavior variation, component self-defect etc. can all have an impact the Acceptable life of component, when only passing through
Between judgment bias it is larger, replacement will cause unnecessary waste too early, and replacement is likely to occur economic loss or safe thing not in time
Therefore.In addition, the accuracy empirically judged is limited to the subjective consciousness of people, uncertain factor is more, is easy to judge by accident.
The method of above two non-science is unfavorable for that tissue is extensive, standardized production, and equipment producer and equipment use
Fang Wufa rationally prepares accessory；Also it is unfavorable for timely maintenance equipment；The accurate operation data of more difficult acquisition equipment simultaneously,
It can not effectively propose plant issue improvement project.
In conclusion both part lifetime evaluation methods all have larger defect at present, temporarily closed without more science
The problem of reason solution.
Summary of the invention
The object of the present invention is to provide a kind of entity drilling machine digital monitoring methods, and solving the prior art can not accurately sentence
The problem of breakdown consumable component service life, realizes the scientific algorithm of equipment operation component remaining life, avoids the non-meter of equipment
It draws and shuts down, promote the accuracy of vulnerable part replacing construction, be conducive to the reserved accessory of producer and user's precise and high efficiency.
The technical scheme adopted by the invention is that a kind of entity drilling machine digital monitoring method, the specific steps are as follows:
Step 1, with the parameter of data collection system collection site equipment and the data of site environment；
Step 2, the parameter of the field device acquired through step 1 and the data of site environment are handled by arithmetic element,
Obtain the real-time status data of field device；
Step 3, field device is observed using the real-time status data of the field device obtained through step 2, parameter
Setting and early warning analysis.
The features of the present invention also characterized in that:
Wherein data collection system includes field device monitoring unit and site environment monitoring unit in step 1, described existing
Field device monitoring unit and site environment monitoring unit are separately connected the input terminal of arithmetic element；
Wherein input has mathematical model inside real-time operation unit, and mathematical model includes: entity drilling machine mathematical model, structure
Part strength model, fatigue of materials computation model, environmental factor computation model, dynamic calculating model, vibration-Structure Calculation
Model, temperature-structural computational model, noise-structural computational model, Mechanics Simulation model, expert data model；
Wherein entity drilling machine mathematical model is by the data model after the digitlization of entire drilling machine physical unit；
Structural member strength model for calculating the Strength Changes of monitored structural member, and formation characteristic curve in real time；
Fatigue of materials computation model is used to calculate the fatigue properties of drilling machine wear-out part, then in conjunction with structural member Strength co-mputation mould
The prediction of result structural member remaining life of type；
Environmental factor computation model returns site environment data by reading the data in site environment detection unit
Shelves；
Dynamic calculating model is used to calculate the kinetic characteristics of drilling machine moving component, according to load characteristic variation prediction portion
Part remaining life；
Vibration-structural computational model, temperature-structural computational model and noise-structural computational model be calculate by vibration,
The loss situation of the variation prediction drill configuration part of temperature and noise；
It include material property, design feature and the operation characteristic of all monitored components in Mechanics Simulation model, using power
The method of student movement row predicts related drill rig components remaining life；
Expert data model is the number of existing running parameter, drilling machine critical component service life and environmental change feature
According to；
Wherein site environment monitoring unit includes environmental data collecting unit, and the environmental data collecting unit is separately connected
Temperature sensor TSQ, humidity sensor HSQ, baroceptor PSQ and air velocity transducer WSQ；
Wherein field device monitoring unit is several dissimilar sensors of apparatus body installation, and field device monitoring is single
Member is also connected with field data acquisition unit, field level data acquisition unit by collected apparatus body parameter by filtering or
Digital sample carries out operation, is then sent to real-time operation unit by bus communication mode；
Wherein the output end of real-time operation unit is also connected with client and storage unit, client be used for field device into
Row observation, the setting of parameter and early warning analysis, storage unit are used to back up the field device by after real-time operation cell processing
Real-time status data；
Specific calculating in the real-time operation unit includes: to implement arithmetic element to include computing unit, and the calculating is single
Member includes: entity borer system structure matrix, entity drilling machine operating parameter table, entity rig operations parameter list, site environment ginseng
Number table, component physical characteristic list, operation and operation history data table；
The entity borer system structure matrix is the geologic structure property structure non-athletic to drilling machine in conjunction with drilling machine operation ground
The digitlization of part shows；
Value in the entity drilling machine operating parameter table is the data of field device monitoring unit feedback；
Value in the entity rig operations parameter list is the actual operational parameters of driller；
Value in the site environment parameter list is the data of site environment monitoring unit feedback；
The component physical characteristic list is to deposit the operation characteristic that component is monitored in drilling machine in the form of digital table
It is stored in model, is used for analysis component active loss situation；
Data in the operation and operation history data table are by going through in real-time operation cell call storage unit
History data, for updating the mathematical model characterisitic parameter in other parameter lists；
Wherein step 3 specifically includes: client is also connected with process data caching, and client is cached real by process data
When obtain implement arithmetic element calculated result, obtain drilling machine actual use situation data and estimate remaining life data, so
Drilling machine is adjusted afterwards, all data are also sent in storage unit by process data caching；
The beneficial effects of the invention are as follows
A kind of entity drilling machine digital monitoring method of the present invention is directed to available sensors key measured directly
Component, can real-time monitoring loss situation and accurate prediction service life；For the direct measuring part of unavailable sensor, pass through number
The indirect computed losses situation of word simulation model and remaining life；It can be by long-range wired or wireless between each module of the system
Communication connection, data can be placed on cloud platform and remotely manage；Mathematical model and arithmetic element are mutually indepedent, can be stored in local or remote
End, hardware platform architecture can flexibly be built；Client man-machine interface directly displays simulation result, efficiently intuitive；Expert's number
According to library system auxiliary operation, the accuracy of simulation calculation is further increased.
Detailed description of the invention
Fig. 1 is a kind of entity drilling machine digital monitoring method overall plan figure of the invention；
Fig. 2 is the field device monitoring unit schematic diagram in a kind of entity drilling machine digital monitoring method of the invention；
Fig. 3 is the site environment monitoring unit schematic diagram in a kind of entity drilling machine digital monitoring method of the invention；
Fig. 4 is the mathematical model schematic diagram in a kind of entity drilling machine digital monitoring method of the invention；
Fig. 5 is the real-time operation unit schematic diagram in a kind of entity drilling machine digital monitoring method of the invention；
Fig. 6 is the client conceptual scheme in a kind of entity drilling machine digital monitoring method of the invention；
Fig. 7 is the storage unit schematic diagram in a kind of entity drilling machine digital monitoring method of the invention.
In figure, 1. field device monitoring unit, 2. site environment monitoring unit, 3. mathematical models, 4. real-time operation units,
5. client, 6. storage units, 7. field level data acquisition units, 8. environmental data collecting units, 9. entity drilling machine number moulds
Type, 10. structural member strength models, 11. fatigue of materials computation models, 12. environmental factor computation models, 13. dynamics meters
Calculate model, 14. vibrations-structural computational model, 15. temperature-structural computational model, 16. noises-structural computational model, 17. mechanics
Simulation model, 18. expert data models, 19. computing units, 20. entity borer system structure matrixs, the operation of 21. entity drilling machines
Parameter list, 22. entity rig operations parameter lists, 23. site environment parameter lists, 24. component physical characteristic lists, 25. operation and
Operation history data table, 26. process datas caching, 27. actual use situations, 28. estimate remaining life, 29. network management moulds
Block, 30. local clients, 31. Terminal Server Clients, 32. are locally stored, the storage of 33. clouds.
Specific embodiment
The following describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
The present invention provides a kind of entity drilling machine digital monitoring method, the specific steps are as follows:
Step 1, with the parameter of data collection system collection site equipment and the data of site environment, as shown in Figure 1, number
It include field device monitoring unit 1 and site environment monitoring unit 2 according to acquisition system, the field device monitoring unit 1 and existing
Field environmental monitoring unit 2 is separately connected the input terminal of real-time operation unit 4, and real-time monitoring result is sent to real-time operation unit
4, as shown in figure 3, site environment monitoring unit 2 includes environmental data collecting unit 8, the environmental data collecting unit 8 is distinguished
Connect temperature sensor TSQ, humidity sensor HSQ, baroceptor PSQ and air velocity transducer WSQ, field device monitoring unit
The 1 several dissimilar sensors installed for apparatus body, field device monitoring unit 1 are also connected with field data acquisition unit
7, collected apparatus body parameter is carried out operation by filtering or digital sample by field level data acquisition unit 7, is then led to
It crosses bus communication mode and is sent to real-time operation unit 4, environmental data collecting unit 8 will pass through edge calculations after data collection,
Calculated result is transmitted in real-time operation unit 4 in the form of bus；
Field device monitoring unit 1 and site environment monitoring unit 2 should as close possible to the operating position of monitored component,
Be conducive to equipment integration transport in this way, the centralized processing of acquisition signal, avoid electromagnetic interference；
As shown in Fig. 2, SQ01, SQ02, SQmn respectively indicate monitored equipment ontology installation different type pass
Real-time measuring data is sent to field level data acquisition unit 7 by sensor, different classes of sensor, and the acquisition of field level data is single
Member 7 passes through certain local operation, such as: effective sensor data are passed through bus communication mode and sent out by filtering, digital sample
It send to real-time operation unit 4；
Multiple field level data can be used and acquire for the quantity of component and component operating position is monitored in entity drilling machine
Unit, each data acquisition unit connect one or more sensors, monitoring data are carried out classification processing；Such as: being located at mud
The field data acquisition unit of pump can acquire vibration, noise, main shaft temperature rise, stroke, flow of slush pump etc.；Positioned at showing for winch
Field data acquisition unit can acquire vibration, bearing temperature rise, motor speed of winch etc.；
Each data acquisition unit has its specific data address, and the sensor of each field level data acquisition unit also has
Its specific signal path address, is wrapped in data format when field device monitoring unit 1 sends data to real-time operation unit 4
Containing two addresses (field level data acquisition unit address and sensor address), in order to subsequent calculating, filing, printing reports
Deng；
Step 2, by the parameter of the field device acquired through step 1 and the data of site environment by implementing arithmetic element 4
Processing obtains the real-time status data of field device, and input has mathematical model 3, real-time operation unit inside real-time operation unit 4
4 operation method is from mathematical model 3, as shown in figure 4, mathematical model 3 includes: that entity drilling machine mathematical model 9, structural member are strong
Spend computation model 10, fatigue of materials computation model 11, environmental factor computation model 12, dynamic calculating model 13, vibration-structure
Computation model 14, temperature-structural computational model 15, noise-structural computational model 16, Mechanics Simulation model 17, expert data mould
Type 18；The output end of real-time operation unit 4 is also connected with client 5 and storage unit 6, and client 5 is used to carry out field device
Observation, the setting of parameter and early warning analysis, storage unit 6 is for backing up through treated the field device of real-time operation unit 4
Real-time status data, in addition, when the field data accumulated in storage unit 6 is enough by real-time operation unit 4 by its
It is sent to mathematical model 3, for changing the characteristic parameter of operational model in mathematical model 3, so as to improve real-time operation unit 4
Calculate accuracy；Mathematical model 3 and storage unit 6 both can be installed on same position with real-time operation unit 4 or be mountable to not
Same position uses wired or wireless communication therebetween；
Entity drilling machine mathematical model 9 is by the data model after the digitlization of entire drilling machine physical unit, which also includes
Interdependence of system when running between each component, it is ensured that mathematical model can maximize the true operation conditions of reflection and portion
Interaction relationship between part；
Structural member strength model 10 for calculating the Strength Changes of monitored structural member in real time, and formation characteristic is bent
Line, real-time operation unit 4 are also to answer other numbers in binding entity drilling machine mathematical model 9 and computing unit 19 calling the model
According to；
Fatigue of materials computation model 11 is used to calculate the fatigue properties of drilling machine wear-out part, then in conjunction with structural member Strength co-mputation
The prediction of result structural member remaining life of model 10；
Environmental factor computation model 12 carries out site environment data by reading the data in site environment detection unit 2
Filing；
Dynamic calculating model 13 is used to calculate the kinetic characteristics of drilling machine moving component, according to load characteristic variation prediction
Component remaining life, such as: the current abrasion condition of winch drum bearing；
Vibration-structural computational model 14, temperature-structural computational model 15 and noise-structural computational model 16 are to calculate to lead to
Cross the loss situation of the variation prediction drill configuration part of vibration, temperature and noise, when actual motion should also combine computing unit 19
Middle related data；
Include material property, design feature and the operation characteristic of all monitored components in Mechanics Simulation model 17, uses
The drill rig components related to data predictions other in computing unit 19 of method binding entity drilling machine mathematical model 9 of mechanics operation are remaining
Service life；
Expert data model 18 is the number of existing running parameter, drilling machine critical component service life and environmental change feature
According to being worked long hours the data such as running parameter, critical component service life, the environmental change feature of summary by the former, from experience
Angle provides reasonable suggestion to work at present.Such as: in certain operation block, 80 hours averages length of working life of mud slurry pump cylinder jacket,
Service life of the drill bit at 1000~1500 meters of well depth is 55 hours etc.；
It can be wired or wireless way by bus communication between real-time operation unit 4 and other units；Real-time operation list
Member 4 is mountable to equipment place of working, distant office or Cloud Server；If being installed on equipment place of working and distant office should have
Standby certain operational capability, need to only plan operational software if being installed on Cloud Server, be responsible for software operation by Cloud Server；
As shown in figure 5, being the inside schematic diagram of real-time operation unit 4.Wherein, computing unit 19 is by real-time operation unit 4
It calls on demand, calculating process data.The data of each affiliated sensor of component have specific number in calculating process, by meter
Any change will not occur for the data number after calculating unit 4, in order to subsequent classification and filing.The calculating being related to includes: reality
Body borer system structure matrix 20, entity drilling machine operating parameter table 21, entity rig operations parameter list 22, site environment parameter list
23, component physical characteristic list 24, operation and operation history data table 25.
Entity borer system structure matrix 20 is the geologic structure property structural member non-athletic to drilling machine in conjunction with drilling machine operation ground
The digitlization of (such as: pedestal, derrick) shows.The matrix reflects structural strength, the toughness etc. of drilling machine entirety, the superiority and inferiority of data
Property indicate whether load structural member can satisfy nominal load demand, as whether: intensity of headframe is able to bear top drives rotation
Whether reaction torque, pedestal intensity are able to bear tubing string weight etc..
Value in entity drilling machine operating parameter table 21 is real-time change, and content monitors single all from field device
Member 1.Real-time operation unit 4 sends data to entity drilling machine operating parameter table 21 according to specific address number and Position Number
In, it is called when being calculated for other models.
Value in entity rig operations parameter list 22 is also real-time change, and the content of storage is that the operation of driller is joined
Count, such as: winch speed, bores disk torque at pump impulse.Real-time operation unit 4 will be counted according to specific address number and Position Number
According to calling when being sent in entity rig operations parameter list 22 for the calculating of other models.
Value in site environment parameter list 23 is real-time change, content all from site environment monitoring unit 2,
When real-time operation unit 4 is sent data in site environment parameter list 23 according to specific Position Number for the calculating of other models
It calls.
Component physical characteristic list 24 is to store the operation characteristic that component is monitored in drilling machine in the form of digital table
In model, it to be used for analysis component active loss situation.The parameter of the list can be according to entity drilling machine operating parameter table 21, entity
The current value of rig operations parameter list 22 and site environment parameter list 23 and constantly change.The numerical value combination mechanics of above three table
Simulation model 17 can calculate the running wastage and prediction service life of particular elements by real-time operation unit 4.
Data in operation and operation history data table 25 are to call going through in storage unit 6 by real-time operation unit 4
History data.The data are mainly used for updating the mathematical model characterisitic parameter in other lists, it may be assumed that with the continuous abrasion of component,
Its operation characteristic may constantly change, if the characterisitic parameter is that fixed value will cause biggish arithmetic eror.By constantly more
The new operational parameter can adjust the physical characteristic of component according to real time status, make the characteristic of the adaptive physical object of mathematical model.
According in entity borer system structure matrix 20, entity drilling machine operating parameter table 21, site environment parameter list 23
Data, physical unit characteristic list 24 and Mechanics Simulation model 17 calculate the current of winch drum bearing by dynamics calculation 14
Abrasion condition, and binding entity rig operations parameter list 22, operation and operation history data table 25 and expert data model 18 are pre-
The remaining life under the following operating condition is surveyed, is only capable of loading by existing operating condition if the data in above three table have neither part nor lot in operation
Predicting Performance Characteristics bearing service life, this difference between actual condition is larger, therefore should be in conjunction with the true following operating condition ginseng of record
It is several that it is estimated, the accuracy of life prediction can be effectively improved.
When drilling machine is when the operation of a well is completed in one's respective area, the operation and history run number in the digitized monitoring system
The loss situation for being monitored component in this duty cycle can be counted according to table 25, convenient for equipment account costs other in same region, estimated
Calculate duty cycle, prepare accessory etc..
For critical component, it should in summary calculate and rationally judge that situation and remaining life is lost in it.Computing unit
19 result will be stored in process data caching 26, and process data caching 26 is stored each calculated result by rule compositor,
It is divided into two types: actually uses situation 27 and estimate remaining life 28, while process data caching 26 also sends out all data
It send into storage unit 6, for the content filing in sensor measurement data, actual use situation 27, prediction remaining life 28.
Actual use situation 27 in data can be sent in mathematical model 3, for update department pattern arithmetic constant,
Correction factor, characterisitic parameter etc..Such as: environmental data, operating parameter.
Step 3, field device is observed using the real-time status data of the field device obtained through step 2, parameter
Setting and early warning analysis: client 5 by process data cache in real time obtain implement arithmetic element 4 calculated result, obtain
Drilling machine actually uses the data of situation and estimates remaining life data, then drilling machine is adjusted, as shown in fig. 6, client 5
It further include network management module 29, local client 30 and Terminal Server Client 31, the network management module 29 is connected in real time
Arithmetic element 4, there are many 29 external connection modes of network management module, can be wired or wireless LAN network, Metropolitan Area Network (MAN), wide area
Net etc., local client is installed on drilling machine Work places, checks drilling machine operating status for Field Force, Terminal Server Client passes through
Communication network is connect with network management module, for remotely monitoring；
Situation 27 is actually used in real-time operation unit 4 to be used in local client 30 and Terminal Server Client 31 with curve
The mode of figure and real time data shows the working condition of monitored component, loss situation etc..Number in actual use situation 27
According to and expert data model 18 in normal data deviation it is larger when can be popped up in local client 30 and Terminal Server Client 31
Warning note message, and provide the problem of being likely to occur consequence with caused by.The data for estimating remaining life 28 can also exist in real time
Local client 30 and Terminal Server Client 31 show, client has replacement component, maintenance downtime, in advance before reaching expected life
Estimate the maintenance report messages such as Expenses Cost, downtime.Convenient for user or equipment supplier's account cost, prepare accessory, coordination
Logistics, arrangement maintenance attendant etc..
As shown in fig. 7, being the principle of compositionality of storage unit, including 32 and cloud storage 33 are locally stored；It is locally stored 32
For the storage of process data or a small amount of historical data, cloud storage 33 is used for historical data archiving, the data of cloud storage 33
All from being locally stored 32, the data structure of cloud storage 33 can be NoSQL (non-relational database), Hadoop
(distributed variable-frequencypump frame) or Bigtable (distributed memory system) etc..
Any digitized monitoring system all may have access to the data in cloud storage 33 after obtaining cloud data access authority
And be downloaded to and be locally stored in 32, read when realizing the operation for the first time of new drilling machine the working characteristics parameter for having drilling machine in one's respective area and
Expert database, convenient for optimization device parameter.Such as: A drilling machine has obtained the operation data of certain operation block and has been stored in cloud
End, B drilling machine, which enters before block operation for the first time, is downloaded to local for the cloud data of A drilling machine, can quickly generate setup parameter, be
System calculates the tutorial messages such as the loss situation, required spare part quantity, the replacement frequency of each critical component automatically.B drilling team can be directed to
This reports material requirement plan, can save production cost, shorten production dispatch cycle, ensure equipment safety operation, avoid it is non-just
Often shut down.
The present invention is based on the technologies such as sensor, Digital Simulation calculating, distributed storage to propose a kind of entity drilling machine number
Change monitoring system, realizes the operation conditions on-line monitoring of crucial vulnerable part in the drilling machine course of work；Mathematical model simulation calculation, essence
Really prediction can not directly measuring part remaining life.Scientific forecasting system downtime prepares accessory in advance, improves and make
Industry efficiency.
Claims (9)
1. a kind of entity drilling machine digital monitoring method, which is characterized in that specific step is as follows:
Step 1, with the parameter of data collection system collection site equipment and the data of site environment；
Step 2, the parameter of the field device acquired through step 1 and the data of site environment are handled by arithmetic element, is obtained
The real-time status data of field device；
Step 3, field device is observed using the real-time status data of the field device obtained through step 2, parameter is set
It sets and early warning analysis.
2. a kind of entity drilling machine digitized monitoring system according to claim 1, which is characterized in that number in the step 1
It include field device monitoring unit (1) and site environment monitoring unit (2), the field device monitoring unit according to acquisition system
(1) and site environment monitoring unit (2) is separately connected the input terminal of arithmetic element in step 2.
3. a kind of entity drilling machine digitized monitoring system according to claim 1, which is characterized in that transported in the step 2
Calculating unit includes real-time operation unit (4), there is mathematical model (3) input inside real-time operation unit (4), mathematical model (3) packet
It includes: entity drilling machine mathematical model (9), structural member strength model (10), fatigue of materials computation model (11), environmental factor meter
It calculates model (12), dynamic calculating model (13), vibration-structural computational model (14), temperature-structural computational model (15), make an uproar
Sound-structural computational model (16), Mechanics Simulation model (17), expert data model (18).
4. a kind of entity drilling machine digitized monitoring system according to claim 3, which is characterized in that
The entity drilling machine mathematical model (9) is by the data model after the digitlization of entire drilling machine physical unit；
The structural member strength model (10) for calculating the Strength Changes of monitored structural member in real time, and formation characteristic is bent
Line；
The fatigue of materials computation model (11) is used to calculate the fatigue properties of drilling machine wear-out part, then in conjunction with structural member intensitometer
Calculate the prediction of result structural member remaining life of model (10)；
The environmental factor computation model (12) is by reading the data in site environment detection unit (2) to site environment data
Filed；
The dynamic calculating model (13) is used to calculate the kinetic characteristics of drilling machine moving component, is changed according to load characteristic pre-
Survey component remaining life；
Vibration-the structural computational model (14), temperature-structural computational model (15) and noise-structural computational model (16) are
Calculate the loss situation of the variation prediction drill configuration part by vibration, temperature and noise；
Include material property, design feature and the operation characteristic of all monitored components in the Mechanics Simulation model (17), adopts
Firmly the method for student movement row predicts related drill rig components remaining life；
The expert data model (18) is existing running parameter, drilling machine critical component service life and environmental change feature
Data.
5. a kind of entity drilling machine digitized monitoring system according to claim 2, which is characterized in that the site environment prison
Surveying unit (2) includes environmental data collecting unit (8), and the environmental data collecting unit (8) is separately connected temperature sensor
TSQ, humidity sensor HSQ, baroceptor PSQ and air velocity transducer WSQ.
6. a kind of entity drilling machine digitized monitoring system according to claim 2, which is characterized in that the field device prison
Several dissimilar sensors that unit (1) is apparatus body installation are surveyed, field device monitoring unit (1) is also connected with live number
According to acquisition unit (7), field level data acquisition unit (7) by collected apparatus body parameter by filtering or digital sample into
Then row operation is sent to real-time operation unit (4) by bus communication mode.
7. a kind of entity drilling machine digitized monitoring system according to claim 1, which is characterized in that the real-time operation list
The output end of first (4) is also connected with client (5) and storage unit (6), and client (5) is for being observed field device, joining
Several settings and early warning analysis, storage unit (6) are used to back up the reality for the field device that passes through that real-time operation unit (4) treated
When status data；
It includes computing unit (19) that specific calculating in the real-time operation unit (4), which includes: real-time operation unit (4), described
Computing unit (19) includes: entity borer system structure matrix (20), entity drilling machine operating parameter table (21), entity rig operations
Parameter list (22), site environment parameter list (23), component physical characteristic list (24), operation and operation history data table (25).
8. a kind of entity drilling machine digitized monitoring system according to claim 7, which is characterized in that
The entity borer system structure matrix (20) is the geologic structure property structure non-athletic to drilling machine in conjunction with drilling machine operation ground
The digitlization of part shows；
Value in the entity drilling machine operating parameter table (21) is the data of field device monitoring unit (1) feedback；
Value in the entity rig operations parameter list (22) is the actual operational parameters of driller；
Value in the site environment parameter list (23) is the data of site environment monitoring unit (2) feedback；
The component physical characteristic list (24) is to deposit the operation characteristic that component is monitored in drilling machine in the form of digital table
It is stored in model, is used for analysis component active loss situation；
Data in the operation and operation history data table (25) are to call storage unit (6) by real-time operation unit (4)
In historical data, for updating the mathematical model characterisitic parameter in other parameter lists.
9. a kind of entity drilling machine digitized monitoring system according to claim 1, which is characterized in that the step 3 is specific
Include: that process data caching (26) obtains the calculated result for implementing arithmetic element (4) in real time, obtains drilling machine actual use situation
It data (27) and estimates remaining life data (28), then drilling machine is adjusted, process data caches (26) also by all numbers
According to being sent in storage unit (6).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910574682.XA CN110259433B (en) | 2019-06-28 | 2019-06-28 | Digital monitoring method for solid drilling machine |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910574682.XA CN110259433B (en) | 2019-06-28 | 2019-06-28 | Digital monitoring method for solid drilling machine |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110259433A true CN110259433A (en) | 2019-09-20 |
| CN110259433B CN110259433B (en) | 2023-03-24 |
Family
ID=67922936
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910574682.XA Active CN110259433B (en) | 2019-06-28 | 2019-06-28 | Digital monitoring method for solid drilling machine |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110259433B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111291499A (en) * | 2020-03-04 | 2020-06-16 | 岭南师范学院 | Gas extraction drilling machine modeling method based on multi-body dynamics |
| CN111723536A (en) * | 2020-06-16 | 2020-09-29 | 岭南师范学院 | Multi-body dynamics analysis method of gas extraction drilling machine system |
| CN112012695A (en) * | 2020-09-27 | 2020-12-01 | 中油国家油气钻井装备工程技术研究中心有限公司 | Petroleum drilling machine auxiliary guiding device based on edge calculation and guiding method thereof |
| CN112595537A (en) * | 2020-12-17 | 2021-04-02 | 弥伦工业产品设计(上海)有限公司 | Equipment health state monitoring method and system based on signal analysis and storage medium |
| CN112859795A (en) * | 2021-02-24 | 2021-05-28 | 上海震业环境科技有限公司 | Safety data acquisition and management method and system for oil and gas equipment |
| CN114636438A (en) * | 2022-01-25 | 2022-06-17 | 四川宏华电气有限责任公司 | Drilling machine online monitoring system based on AR |
| CN116300690A (en) * | 2023-05-17 | 2023-06-23 | 济宁联威车轮制造有限公司 | Radial drilling machine fault monitoring and early warning system based on edge calculation |
| CN118498970A (en) * | 2024-06-26 | 2024-08-16 | 山东石油化工学院 | Marine drilling top tensioning type riser system operation safety analysis system |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1396171A (en) * | 1972-08-08 | 1975-06-04 | Santa Fe Int Corp | Drill bit utilization optimizer |
| US20020148644A1 (en) * | 2000-11-07 | 2002-10-17 | Schultz Roger L. | Differential sensor measurement method and apparatus to detect a drill bit failure and signal surface operator |
| US20030015351A1 (en) * | 1996-03-25 | 2003-01-23 | Halliburton Energy Services, Inc. | Method and system for predicting performance of a drilling system of a given formation |
| US6662110B1 (en) * | 2003-01-14 | 2003-12-09 | Schlumberger Technology Corporation | Drilling rig closed loop controls |
| US20060272859A1 (en) * | 2005-06-07 | 2006-12-07 | Pastusek Paul E | Method and apparatus for collecting drill bit performance data |
| US20100100337A1 (en) * | 2008-10-16 | 2010-04-22 | Oxfordian, Llc | Method to extract parameters from in-situ monitored signals for prognostices |
| US20120016589A1 (en) * | 2010-07-13 | 2012-01-19 | Ke Li | System and method for fatigue analysis of a bottom hole assembly |
| CN102900372A (en) * | 2012-10-16 | 2013-01-30 | 中国石油大学(北京) | Method and device for predicting reasonable service life of PDC (Polycrystalline Diamond Compact) drill bit |
| CN103268088A (en) * | 2013-04-24 | 2013-08-28 | 宝鸡石油机械有限责任公司 | Whole drilling machine set remote on-line monitoring and fault diagnosis system |
| CN104806226A (en) * | 2015-04-30 | 2015-07-29 | 北京四利通控制技术股份有限公司 | Intelligent drilling expert system |
| US20160291201A1 (en) * | 2015-03-30 | 2016-10-06 | Schlumberger Technology Corporation | Pipe tracking system for drilling rigs |
| WO2016179767A1 (en) * | 2015-05-08 | 2016-11-17 | Schlumberger Technology Corporation | Fatigue analysis procedure for drill string |
| US20180095133A1 (en) * | 2016-10-03 | 2018-04-05 | Airbus Operations Limited | Component monitoring |
| US20180119535A1 (en) * | 2015-05-08 | 2018-05-03 | Schlumberger Technology Corporation | Real time drilling monitoring |
| US20180245434A1 (en) * | 2015-05-18 | 2018-08-30 | Halliburton Energy Services, Inc. | Condition based maintenance program based on life-stress acceleration model and cumulative damage model |
| CN109240244A (en) * | 2018-10-26 | 2019-01-18 | 云达世纪（北京）科技有限公司 | Equipment running status health degree analysis method and system based on data-driven |
| US20190078394A1 (en) * | 2017-09-12 | 2019-03-14 | Schlumberger Technology Corporation | System and method for noise, vibration, and light pollution management on rig systems |
| US20190360295A1 (en) * | 2016-09-09 | 2019-11-28 | General Electric Company | System and method for controlling a blowout preventer system in an oil rig |
-
2019
- 2019-06-28 CN CN201910574682.XA patent/CN110259433B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1396171A (en) * | 1972-08-08 | 1975-06-04 | Santa Fe Int Corp | Drill bit utilization optimizer |
| US20030015351A1 (en) * | 1996-03-25 | 2003-01-23 | Halliburton Energy Services, Inc. | Method and system for predicting performance of a drilling system of a given formation |
| US20020148644A1 (en) * | 2000-11-07 | 2002-10-17 | Schultz Roger L. | Differential sensor measurement method and apparatus to detect a drill bit failure and signal surface operator |
| US6662110B1 (en) * | 2003-01-14 | 2003-12-09 | Schlumberger Technology Corporation | Drilling rig closed loop controls |
| US20060272859A1 (en) * | 2005-06-07 | 2006-12-07 | Pastusek Paul E | Method and apparatus for collecting drill bit performance data |
| US20100100337A1 (en) * | 2008-10-16 | 2010-04-22 | Oxfordian, Llc | Method to extract parameters from in-situ monitored signals for prognostices |
| US20120016589A1 (en) * | 2010-07-13 | 2012-01-19 | Ke Li | System and method for fatigue analysis of a bottom hole assembly |
| CN102900372A (en) * | 2012-10-16 | 2013-01-30 | 中国石油大学(北京) | Method and device for predicting reasonable service life of PDC (Polycrystalline Diamond Compact) drill bit |
| CN103268088A (en) * | 2013-04-24 | 2013-08-28 | 宝鸡石油机械有限责任公司 | Whole drilling machine set remote on-line monitoring and fault diagnosis system |
| US20160291201A1 (en) * | 2015-03-30 | 2016-10-06 | Schlumberger Technology Corporation | Pipe tracking system for drilling rigs |
| CN104806226A (en) * | 2015-04-30 | 2015-07-29 | 北京四利通控制技术股份有限公司 | Intelligent drilling expert system |
| WO2016179767A1 (en) * | 2015-05-08 | 2016-11-17 | Schlumberger Technology Corporation | Fatigue analysis procedure for drill string |
| US20180119535A1 (en) * | 2015-05-08 | 2018-05-03 | Schlumberger Technology Corporation | Real time drilling monitoring |
| US20180245434A1 (en) * | 2015-05-18 | 2018-08-30 | Halliburton Energy Services, Inc. | Condition based maintenance program based on life-stress acceleration model and cumulative damage model |
| US20190360295A1 (en) * | 2016-09-09 | 2019-11-28 | General Electric Company | System and method for controlling a blowout preventer system in an oil rig |
| US20180095133A1 (en) * | 2016-10-03 | 2018-04-05 | Airbus Operations Limited | Component monitoring |
| US20190078394A1 (en) * | 2017-09-12 | 2019-03-14 | Schlumberger Technology Corporation | System and method for noise, vibration, and light pollution management on rig systems |
| CN109240244A (en) * | 2018-10-26 | 2019-01-18 | 云达世纪（北京）科技有限公司 | Equipment running status health degree analysis method and system based on data-driven |
Non-Patent Citations (3)
| Title |
|---|
| 张东旭等: "基于现场总线的钻机工作参数监视系统设计", 《石油矿场机械》 * |
| 张鹏飞等: "深水钻机多参数监测系统的集成化网络化设计", 《石油矿场机械》 * |
| 陈志刚: "基于ⅡW标准的露天顶锤式钻机疲劳寿命安全评估系统", 《凿岩机械气动工具》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111291499A (en) * | 2020-03-04 | 2020-06-16 | 岭南师范学院 | Gas extraction drilling machine modeling method based on multi-body dynamics |
| CN111291499B (en) * | 2020-03-04 | 2023-08-01 | 岭南师范学院 | Gas extraction drilling machine modeling method based on multi-body dynamics |
| CN111723536A (en) * | 2020-06-16 | 2020-09-29 | 岭南师范学院 | Multi-body dynamics analysis method of gas extraction drilling machine system |
| CN111723536B (en) * | 2020-06-16 | 2022-10-04 | 岭南师范学院 | Multi-body dynamics analysis method of gas extraction drilling machine system |
| CN112012695A (en) * | 2020-09-27 | 2020-12-01 | 中油国家油气钻井装备工程技术研究中心有限公司 | Petroleum drilling machine auxiliary guiding device based on edge calculation and guiding method thereof |
| CN112595537A (en) * | 2020-12-17 | 2021-04-02 | 弥伦工业产品设计(上海)有限公司 | Equipment health state monitoring method and system based on signal analysis and storage medium |
| CN112859795A (en) * | 2021-02-24 | 2021-05-28 | 上海震业环境科技有限公司 | Safety data acquisition and management method and system for oil and gas equipment |
| CN114636438A (en) * | 2022-01-25 | 2022-06-17 | 四川宏华电气有限责任公司 | Drilling machine online monitoring system based on AR |
| CN116300690A (en) * | 2023-05-17 | 2023-06-23 | 济宁联威车轮制造有限公司 | Radial drilling machine fault monitoring and early warning system based on edge calculation |
| CN118498970A (en) * | 2024-06-26 | 2024-08-16 | 山东石油化工学院 | Marine drilling top tensioning type riser system operation safety analysis system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110259433B (en) | 2023-03-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110259433A (en) | A kind of entity drilling machine digital monitoring method | |
| CA2540336C (en) | Equipment component monitoring and replacement management system | |
| CN108986251B (en) | Predictive replacement of heavy machinery | |
| CA2799402C (en) | Cycle decomposition analysis for remote machine monitoring | |
| CN108241343A (en) | A kind of intelligent plant management platform system | |
| CN102059256B (en) | Equipment operating and process quality state monitoring system for high-speed rolling mill | |
| CN107991870A (en) | A kind of fault pre-alarming and life-span prediction method of Escalator equipment | |
| CN103106542A (en) | Data analyzing and processing system | |
| US10769323B2 (en) | Rig systems self diagnostics | |
| CN108241891A (en) | Resolver and resolution system | |
| CN103632054A (en) | Spare part demand predicting method based on state monitoring and reliability of equipment part | |
| AU2020252893A1 (en) | Device for determining the actual state and/or the remaining service life of a construction, materials-handling and/or conveyor machine | |
| Albano et al. | Advanced sensor-based maintenance in real-world exemplary cases | |
| CN118309644A (en) | Pipeline pump operation flow monitoring method and system based on digital twin | |
| CN214067336U (en) | Motor operation equipment state on-line monitoring management system | |
| Heidarpour et al. | Design and development of an IoT enabled device for remote monitoring of hydraulic hammers | |
| Mohanraj et al. | IoT-enabled Condition Monitoring and Intelligent Maintenance System for Machine | |
| Nikulin et al. | A computer-aided application for modeling and monitoring operational and maintenance information in mining trucks | |
| Abdi-Oskouei et al. | Role of the operator in dragline energy efficiency | |
| Kalra et al. | Decision support system for failure and down time reporting: A tool for achieving production targets from remote mining equipment | |
| AU2015200309B2 (en) | Predicting failure of a mining machine | |
| TWI783593B (en) | Intelligent production line equipment precise preventive maintenance and energy consumption visual monitoring system and method | |
| AU2018256654B2 (en) | Predicting failure of a mining machine | |
| Zhou et al. | Big data-driven oil well optimization: Technological innovation and future outlook | |
| Buchynskyi et al. | Intelligent diagnostic system of the mobile drilling rig hoisting equipments |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200927 Address after: Baoji City, Shaanxi Province, 721002 Dongfeng Road, Jintai District No. 2 Applicant after: BAOJI OILFIELD MACHINERY Co.,Ltd. Applicant after: CHINA NATIONAL PETROLEUM Corp. Applicant after: CNPC national oil and gas drilling equipment Engineering Technology Research Center Co.,Ltd. Address before: Baoji City, Shaanxi Province, 721002 Dongfeng Road, Jintai District No. 2 Applicant before: Baoji Oilfield Machinery Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |