CN116952938A - System and method for intelligently identifying early overflow through drilling fluid bubble image - Google Patents
System and method for intelligently identifying early overflow through drilling fluid bubble image Download PDFInfo
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- CN116952938A CN116952938A CN202310925696.8A CN202310925696A CN116952938A CN 116952938 A CN116952938 A CN 116952938A CN 202310925696 A CN202310925696 A CN 202310925696A CN 116952938 A CN116952938 A CN 116952938A
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- 238000005553 drilling Methods 0.000 title claims abstract description 98
- 239000012530 fluid Substances 0.000 title claims abstract description 92
- 238000000034 method Methods 0.000 title claims abstract description 17
- 229910000037 hydrogen sulfide Inorganic materials 0.000 claims abstract description 29
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 claims abstract description 28
- 238000012544 monitoring process Methods 0.000 claims abstract description 12
- 239000011521 glass Substances 0.000 claims description 36
- 239000007789 gas Substances 0.000 claims description 18
- 239000002351 wastewater Substances 0.000 claims description 14
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 10
- 230000007246 mechanism Effects 0.000 claims description 7
- 238000005070 sampling Methods 0.000 claims description 7
- 238000012216 screening Methods 0.000 claims description 5
- 239000002808 molecular sieve Substances 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- URGAHOPLAPQHLN-UHFFFAOYSA-N sodium aluminosilicate Chemical compound [Na+].[Al+3].[O-][Si]([O-])=O.[O-][Si]([O-])=O URGAHOPLAPQHLN-UHFFFAOYSA-N 0.000 claims description 3
- 238000004140 cleaning Methods 0.000 claims 1
- 238000010992 reflux Methods 0.000 claims 1
- 239000007921 spray Substances 0.000 claims 1
- 239000007788 liquid Substances 0.000 description 6
- 230000009471 action Effects 0.000 description 4
- 230000008859 change Effects 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000002002 slurry Substances 0.000 description 2
- 238000005507 spraying Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
Classifications
-
- 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
-
- 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
- G06N3/0464—Convolutional networks [CNN, ConvNet]
-
- 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
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/02—Knowledge representation; Symbolic representation
-
- 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
-
- 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
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/806—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
-
- 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
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural 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
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
-
- 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
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The application discloses a system and a method for intelligently identifying early overflow through a drilling fluid bubble image, wherein the system comprises a drilling fluid sample acquisition device, a hydrogen sulfide sensor (12), a sample image acquisition device and a computer (10), wherein the drilling fluid sample acquisition device is used for acquiring a drilling fluid sample which is circulated and reflowed in a shaft (1) and transmitting the drilling fluid sample to the sample image acquisition device; the hydrogen sulfide sensor (12) is used for monitoring the hydrogen sulfide content of a drilling fluid sample and transmitting the hydrogen sulfide content to the computer (10) in real time, the sample image acquisition device is used for acquiring a drilling fluid sample image and transmitting the drilling fluid sample image to the computer (10), and early overflow early warning is sent out through the computer (10). The application has early overflow accident early warning capability, can identify and alarm the overflow before the overflow is moved to the wellhead, and provides powerful technical support for safe drilling.
Description
Technical Field
The application relates to the technical field of overflow phenomenon monitoring in drilling, in particular to a system and a method for intelligently identifying early overflow through a drilling fluid bubble image.
Background
In the drilling process, when the stratum pressure is greater than the annular pressure of the well shaft, stratum fluid flows into the well shaft under the action of negative pressure difference at the bottom of the well, and the phenomenon is overflow. The overflow can seriously slow down the development speed of oilfield drilling operation, increase the production cost, reduce the drilling efficiency, can also cause a series of other underground complex accidents such as stuck drilling, well collapse, blowout and the like, even cause a great deal of casualties due to well scrapping, seriously threaten the safety of personnel, equipment, environment and underground oil gas resources, and bring severe social influence and huge economic loss to enterprises. Therefore, it is very necessary to accurately identify and early warn the early overflow to reduce the occurrence of overflow accidents and prevent the occurrence of blowout accidents.
At present, the monitoring of early overflow mainly adopts a means for detecting the liquid level change of the drilling fluid pool and reversely pushing the occurrence condition of overflow, wherein the liquid level change of the drilling fluid pool is mainly finished by manual judgment or detection of a liquid level detector. The manual judgment has certain real-time performance, but the reliability is extremely poor, the theoretical guidance of science and system is lacking, and the sensitivity and universality are limited due to the difference of the level of staff, the degree of experience, the intensity of responsibility and the working state; the liquid level detector is easily affected by factors such as drilling fluid scaling and the like, and high false alarm rate is generated, so that timeliness, accuracy and reliability of early overflow early warning results are difficult to guarantee. In addition, the situation that the actual stratum fluid enters the well shaft is reversely pushed through the change of the liquid level of the drilling fluid pool, and large hysteresis exists, so that the obtained change of the liquid level of the drilling fluid pool is difficult to match with the actual overflow situation.
Therefore, finding a method which is suitable for ground objective application and can timely and accurately find the early overflow phenomenon is a technical problem which needs to be solved in the field.
Disclosure of Invention
The application aims to provide a system and a method for intelligently identifying early overflow through a drilling fluid bubble image, so as to solve the technical problem of how to accurately discover the early overflow phenomenon in time.
The application is realized by adopting the following technical scheme: the system comprises a drilling fluid sample acquisition device, a hydrogen sulfide sensor, a sample image acquisition device and a computer, wherein the drilling fluid sample acquisition device is used for acquiring a drilling fluid sample which is circulated and reflowed in a shaft and transmitting the drilling fluid sample to the sample image acquisition device; the hydrogen sulfide sensor is used for monitoring the hydrogen sulfide content of the drilling fluid sample and transmitting the hydrogen sulfide content to the computer in real time, and the sample image acquisition device is used for acquiring the drilling fluid sample image and transmitting the drilling fluid sample image to the computer, and early overflow early warning is sent out through the computer.
Further, the drilling fluid sample acquisition device comprises a diversion trench, wherein the diversion trench acquires a drilling fluid sample from the drilling fluid which circulates and flows back in the shaft, and the drilling fluid sample is conveyed to the sample image acquisition device through a diversion pipe arranged on the diversion trench.
Further, the guide pipe is provided with an electromagnetic valve and a hydrogen sulfide sensor, and the electromagnetic valve and the hydrogen sulfide sensor are electrically connected with each other.
Further, the diversion trench is connected with the mud pit through the molecular sieve, mud treated by the mud pit is conveyed back to the shaft through the mud pump, and treated wastewater is discharged into the wastewater tank.
Further, the sample image acquisition device comprises a glass sheet, a fluorescent lamp and a camera, wherein the fluorescent lamp provides a fluorescent light source for the glass sheet, and the drilling fluid sample on the glass sheet is photographed through the camera arranged relative to the fluorescent lamp and is transmitted to the computer.
Further, the sample image acquisition device further comprises an electric ash knife, wherein the electric ash knife is electrically connected with the glass sheet and is used for adjusting the tiling state of the drilling fluid sample on the glass sheet.
Further, the sample image acquisition device further comprises an electric eccentric adjustment mechanism, and the electric eccentric adjustment mechanism is electrically connected with the machine and used for adjusting the inclination angle of the glass sheet.
Further, the sample image acquisition device further comprises an electric water sprayer which is electrically connected with the machine and used for spraying water to clean the glass sheet.
Further, the glass sheet is communicated with the wastewater tank through a wastewater pipe.
A method for intelligently identifying early overflow through a drilling fluid bubble image comprises the following steps:
s1: the method comprises the steps that a drilling fluid sample in a shaft is acquired through a drilling fluid sample acquisition device and is transmitted to a sample image acquisition device, and in the process, the hydrogen sulfide content of the drilling fluid sample is monitored through a hydrogen sulfide sensor and is transmitted to a computer for judgment;
s2: continuously photographing the drilling fluid sample through a sample image acquisition device to obtain a plurality of groups of images containing bubbles;
s3: screening and processing a plurality of groups of images containing bubbles through a computer to obtain bubble characteristics of the images, wherein the bubble characteristics comprise the number, the shape and the size of the bubbles, and the bubble characteristics correspond to the sampling well number, the well depth, the horizon and the sampling time;
s4: and calculating the content of gas in the drilling fluid sample based on the bubble characteristics, judging whether the obtained gas content exceeds a normal threshold, and sending early overflow early warning by a computer after the gas content exceeds the normal threshold.
The application has the beneficial effects that: the application can directly utilize the ground measurement mode without depending on the underground measuring instrument to monitor the overflow phenomenon; the application adopts a monitoring principle different from the existing ground overflow monitoring method, and through an image intelligent identification technology, the gas content of the drilling fluid is identified according to the characteristics of the number, the size, the shape and the like of bubbles in the bubble image of the drilling fluid, and the actual overflow condition is further accurately judged, so that the overflow monitoring effect which is suitable for ground application and is more intelligent, earlier, faster and more accurate than the existing ground measurement mode is obtained; the application has early overflow accident early warning capability, can identify and alarm the overflow before the overflow is moved to the wellhead, and provides powerful technical support for safe drilling.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the structure of the present application;
FIG. 2 is a flow chart of the present application;
in the figure, a 1-shaft, a 2-glass sheet, a 3-slurry pump, a 4-slurry tank, a 5-molecular sieve, a 6-wastewater tank, a 7-electric eccentric adjusting mechanism, an 8-fluorescent lamp, a 9-camera, a 10-computer, an 11-electric water sprayer, a 12-hydrogen sulfide sensor, a 13-electromagnetic valve, a 14-diversion trench, a 15-diversion trench and a 16-electric ash knife.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Example 1
Referring to fig. 1, a system for intelligently identifying early overflow through a drilling fluid bubble image comprises a horizontal diversion trench 14 capable of taking a sample from drilling fluid circulated and reflowed in a shaft 1, a glass sheet 2 communicated with the diversion trench 14 through an inclined diversion trench 15, a hydrogen sulfide sensor 12 and an electromagnetic valve 13 arranged on the diversion trench 15, a fluorescent lamp 8 for providing a fluorescent light source for the glass sheet 2, a camera 9 which is arranged relative to the fluorescent lamp 8 and can continuously photograph the drilling fluid sample on the glass sheet 2, and a computer 10 capable of processing images obtained by the camera 9, wherein the hydrogen sulfide sensor 12 and the electromagnetic valve 13 are electrically connected with the computer 10.
In this embodiment, the well bore 1 is a glass well bore.
In this embodiment, the system further includes: an electric ash knife 16 for adjusting the laying state of drilling fluid sample on the glass sheet 2, an electric eccentric adjusting mechanism 7 for adjusting the inclination degree of the glass sheet 2, and an electric water sprayer 11 for spraying water to clean the glass sheet 2. Wherein, the electric ash knife 16, the electric eccentric adjusting mechanism 7 and the electric water sprayer 11 are all electrically connected with the computer 10, and the working state of the electric ash knife is controlled by the computer 10.
In this embodiment, the system further includes: and the mud pit 4 is communicated with the diversion trench 14 through the vibrating screen 5, the mud pit 4 is communicated into the shaft 1 through the mud pump 3, the mud pit 4 is also communicated to the wastewater tank 6, and the wastewater tank 6 is also communicated with the glass sheet 2 and is used for recovering drilling fluid samples on the glass sheet 2 after photographing is completed.
After the drilling fluid discharged from the shaft 1 passes through the diversion trench 14, most of the drilling fluid is treated by the molecular sieve 5 and the mud pit 4, the wastewater is discharged into the wastewater tank 6, and the treated mud is fed into the shaft 1 again through the mud pump 3. While the other part of the drilling fluid discharged from the shaft 1 flows into the glass sheet 2 along the diversion pipe 15 communicated with the diversion trench 14, the hydrogen sulfide sensor 12 arranged on the diversion pipe 15 automatically transmits monitoring data into the computer 10, and the electromagnetic valve 13 is arranged to be controlled to open and close by the computer 10. The fluorescent lamp 8 can illuminate the glass flake, the camera 9 on the fluorescent lamp can continuously shoot the images of the drilling fluid sample on the glass flake, meanwhile, the inclination degree of the glass flake is adjusted through the electric eccentric adjusting device 7, the tiling state of the drilling fluid sample on the glass flake 2 is adjusted through the electric gray knife 16, the images of the fluorescent lamp are clear or the drilling fluid sample is dumped after shooting is finished, and the glass flake after shooting is cleaned through the electric water sprayer 11.
Referring to fig. 2, a method for intelligently identifying early overflow through a drilling fluid bubble image is realized based on the system for intelligently identifying early overflow through the drilling fluid bubble image, and comprises the following steps:
s1: the control of the electromagnetic valve 13 on the diversion pipe 15 by the computer 10 is carried out, a drilling fluid sample flowing out from the diversion groove 14 is obtained according to a set sampling time interval (such as every half hour), in the process, the hydrogen sulfide content of the drilling fluid in the diversion pipe 15 is tested by the hydrogen sulfide sensor 12, after the hydrogen sulfide content exceeds the standard, an abnormal early warning is sent out by the computer 10, and meanwhile, the hydrogen sulfide content is continuously monitored by the hydrogen sulfide sensor 12 and is transmitted to the computer 10;
s2: when the drilling fluid sample flows to the glass sheet 2, the glass sheet 2 is horizontally laid through the electric eccentric adjusting device 7 and the electric ash knife 16, the brightness of the fluorescent lamp 8 is adjusted to enable the fluorescent lamp to illuminate bubbles in the drilling fluid sample on the glass sheet 2, and the illuminated drilling fluid sample is continuously photographed through the camera 9 to obtain a plurality of groups of images containing bubbles;
s3: after photographing is finished, the glass sheet 2 is inclined by the electric eccentric adjusting device 7 and the electric ash knife 16, so that drilling fluid samples in the glass sheet 2 flow into the wastewater tank 6;
s4: the method comprises the steps of screening and processing a plurality of groups of images containing bubbles through a computer 10, obtaining bubble characteristics of the images, including the number, shape and size of the bubbles, and corresponding the bubble characteristics with sampling numbers, well depths, horizons and sampling time of the bubbles;
s5: according to the intelligent gas content identification model stored in the computer 10, calculating the gas content in the drilling fluid sample based on the bubble characteristics obtained in the step S4, judging whether the obtained gas content exceeds a normal threshold, and sending early overflow early warning by the computer 10 after the obtained gas content exceeds the normal threshold; the intelligent gas content identification model comprises a mapping relation between bubble characteristic data and gas content and a normal threshold value of the gas content in drilling fluid, the corresponding gas content can be obtained according to the obtained bubble characteristic data, and whether the gas content exceeds the normal threshold value is judged;
it is conceivable that the screening in step S4 comprises: and (3) judging whether the image is clear or not and judging whether the image can acquire the bubble characteristics or not, and if the available image is not acquired through screening, repeating the steps S1-S2 until the available image is acquired.
The application can directly utilize the ground measurement mode without depending on the underground measuring instrument to monitor the overflow phenomenon; the application adopts a monitoring principle different from the existing ground overflow monitoring method, and through an image intelligent identification technology, the gas content of the drilling fluid is identified according to the characteristics of the number, the size, the shape and the like of bubbles in the bubble image of the drilling fluid, and the actual overflow condition is further accurately judged, so that the overflow monitoring effect which is suitable for ground application and is more intelligent, earlier, faster and more accurate than the existing ground measurement mode is obtained; the application has early overflow accident early warning capability, can identify and alarm the overflow before the overflow is moved to the wellhead, and provides powerful technical support for safe drilling.
For the foregoing embodiments, a series of combinations of actions are described for simplicity of description, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, it should be understood by those skilled in the art that the embodiments described in the specification are preferred embodiments and that the actions involved are not necessarily required for the present application.
In the above embodiments, the basic principle and main features of the present application and advantages of the present application are described. It will be appreciated by persons skilled in the art that the present application is not limited by the foregoing embodiments, but rather is shown and described in what is considered to be illustrative of the principles of the application, and that modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the application, and therefore, is within the scope of the appended claims.
Claims (10)
1. The system for intelligently identifying early overflow through the drilling fluid bubble image is characterized by comprising a drilling fluid sample acquisition device, a hydrogen sulfide sensor (12), a sample image acquisition device and a computer (10), wherein the drilling fluid sample acquisition device is used for acquiring a drilling fluid sample which is circulated and reflowed in a shaft (1) and transmitting the drilling fluid sample to the sample image acquisition device; the hydrogen sulfide sensor (12) is used for monitoring the hydrogen sulfide content of a drilling fluid sample and transmitting the hydrogen sulfide content to the computer (10) in real time, the sample image acquisition device is used for acquiring a drilling fluid sample image and transmitting the drilling fluid sample image to the computer (10), and early overflow early warning is sent out through the computer (10).
2. A system for intelligent identification of early overflow via drilling fluid bubble image according to claim 1, characterized in that the drilling fluid sample acquisition device comprises a diversion trench (14), the diversion trench (14) acquires drilling fluid sample from the drilling fluid circulated back in the well bore (1), and the drilling fluid sample is transferred to the sample image acquisition device via a diversion trench (15) arranged on the diversion trench (14).
3. The system for intelligently identifying early overflow through drilling fluid bubble images according to claim 2, wherein the flow guide pipe (15) is provided with an electromagnetic valve (13) and a hydrogen sulfide sensor (12), and the electromagnetic valve (13) and the hydrogen sulfide sensor (12) are electrically connected with a computer (10).
4. A system for intelligent recognition of early overflow by means of drilling fluid bubble images according to claim 2, characterized in that the diversion trench (14) is connected with the mud pit (4) through the molecular sieve (5), mud treated by the mud pit (4) is conveyed back to the shaft (1) through the mud pump (3), and treated waste water is discharged into the waste water tank (6).
5. A system for intelligent identification of early overflow by drilling fluid bubble image as claimed in claim 1, characterized in that the sample image acquisition means comprises a glass sheet (2), a fluorescent lamp (8) and a camera (9), the fluorescent lamp (8) providing a fluorescent light source for the glass sheet (2), the drilling fluid sample on the glass sheet (2) being photographed by the camera (9) arranged in relation to the fluorescent lamp (8) and transmitted to the computer (10).
6. A system for intelligent identification of early overflow via drilling fluid bubble image as claimed in claim 5 wherein said sample image acquisition means further comprises an electric gray knife (16), said electric gray knife (16) being electrically connected to the computer (10) for adjusting the state of tiling of drilling fluid sample on the glass sheet (2).
7. A system for intelligent identification of early overflow via drilling fluid bubble image as claimed in claim 5, characterized in that the sample image acquisition device further comprises an electric eccentricity adjustment mechanism (7), the electric eccentricity adjustment mechanism (7) being electrically connected to the computer (10) for adjusting the inclination angle of the glass sheet (2).
8. A system for intelligent identification of early overflow via drilling fluid bubble image as claimed in claim 5 wherein said sample image acquisition means further comprises an electric water sprayer (11), said electric water sprayer (11) being electrically connected to a computer (10) for water spray cleaning of glass flakes (2).
9. A system for intelligent identification of early overflow by drilling fluid bubble image according to claim 8, characterized in that the glass sheet (2) is connected to the waste water tank (6) by waste water pipe.
10. A method for intelligently identifying early overflow through a drilling fluid bubble image, which is realized based on the system for intelligently identifying early overflow through the drilling fluid bubble image according to any one of claims 1-9, and is characterized by comprising the following steps:
s1: the drilling fluid sample of the circulating reflux in the shaft (1) is obtained through a drilling fluid sample obtaining device and is transmitted to a sample image obtaining device, in the process, the hydrogen sulfide content of the drilling fluid sample is monitored through a hydrogen sulfide sensor (12), and data are transmitted to a computer (10) for judgment;
s2: continuously photographing the drilling fluid sample through a sample image acquisition device to obtain a plurality of groups of images containing bubbles;
s3: screening and processing a plurality of groups of images containing bubbles through a computer (10), obtaining bubble characteristics of the images, including the number, shape and size of the bubbles, and corresponding the bubble characteristics with sampling numbers, well depths, horizons and sampling time of the bubbles;
s4: and calculating the content of the gas in the drilling fluid sample based on the bubble characteristics, judging whether the obtained gas content exceeds a normal threshold, and sending early overflow early warning by a computer (10) after the gas content exceeds the normal threshold.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2023104150543 | 2023-04-18 | ||
| CN202310415054.3A CN116452823A (en) | 2023-04-18 | 2023-04-18 | Drilling fluid bubble identification method based on image |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116952938A true CN116952938A (en) | 2023-10-27 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310415054.3A Withdrawn CN116452823A (en) | 2023-04-18 | 2023-04-18 | Drilling fluid bubble identification method based on image |
| CN202310925696.8A Pending CN116952938A (en) | 2023-04-18 | 2023-07-26 | System and method for intelligently identifying early overflow through drilling fluid bubble image |
| CN202310925739.2A Pending CN116935067A (en) | 2023-04-18 | 2023-07-26 | Drilling fluid bubble identification method based on image |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310415054.3A Withdrawn CN116452823A (en) | 2023-04-18 | 2023-04-18 | Drilling fluid bubble identification method based on image |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202310925739.2A Pending CN116935067A (en) | 2023-04-18 | 2023-07-26 | Drilling fluid bubble identification method based on image |
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| CN (3) | CN116452823A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117780334A (en) * | 2024-02-27 | 2024-03-29 | 西南石油大学 | Drilling fluid level measuring device and measuring method |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116597392B (en) * | 2023-07-19 | 2023-10-03 | 山东天力润滑油有限公司 | Hydraulic oil impurity identification method based on machine vision |
-
2023
- 2023-04-18 CN CN202310415054.3A patent/CN116452823A/en not_active Withdrawn
- 2023-07-26 CN CN202310925696.8A patent/CN116952938A/en active Pending
- 2023-07-26 CN CN202310925739.2A patent/CN116935067A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117780334A (en) * | 2024-02-27 | 2024-03-29 | 西南石油大学 | Drilling fluid level measuring device and measuring method |
| CN117780334B (en) * | 2024-02-27 | 2024-05-03 | 西南石油大学 | Drilling fluid level measuring device and measuring method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116935067A (en) | 2023-10-24 |
| CN116452823A (en) | 2023-07-18 |
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