CN113863847A - Constant-speed drilling device and stratum evaluation method - Google Patents
Constant-speed drilling device and stratum evaluation method Download PDFInfo
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- CN113863847A CN113863847A CN202111093198.9A CN202111093198A CN113863847A CN 113863847 A CN113863847 A CN 113863847A CN 202111093198 A CN202111093198 A CN 202111093198A CN 113863847 A CN113863847 A CN 113863847A
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- drilling
- stratum
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- speed
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B3/00—Rotary drilling
- E21B3/02—Surface drives for rotary drilling
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B19/00—Handling rods, casings, tubes or the like outside the borehole, e.g. in the derrick; Apparatus for feeding the rods or cables
- E21B19/24—Guiding or centralising devices for drilling rods or pipes
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP 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
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP 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
- E21B44/02—Automatic control of the tool feed
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP 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
- E21B44/02—Automatic control of the tool feed
- E21B44/04—Automatic control of the tool feed in response to the torque of the drive ; Measuring drilling torque
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
- E21B49/003—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells by analysing drilling variables or conditions
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
- E21B2200/20—Computer models or simulations, e.g. for reservoirs under production, drill bits
Abstract
The invention discloses a constant-speed drilling device and a method for evaluating stratums, belonging to the technical field of geological exploration, and the technical scheme is as follows: the drilling machine comprises a drill rod and a propelling mechanism, wherein the propelling mechanism comprises a propelling screw rod parallel to the axis of the drill rod, and the propelling screw rod is connected with a propelling nut seat; the drill rod is fixed with the pushing nut seat, and a plurality of guide shafts which are in sliding connection with the pushing nut seat are uniformly arranged in the circumferential direction of the drill rod; the propelling screw rod is connected with a power source, and the power source drives the propelling screw rod to rotate so that the nut seat drives the drill rod to move along the guide shaft. According to the invention, through acquiring the drilling information and processing the drilling information based on the deep learning algorithm, effective layer judgment can be realized, and the quantification of the drilling speed is realized.
Description
Technical Field
The invention relates to the technical field of geological exploration, in particular to a constant-speed drilling device and a method for evaluating a stratum.
Background
In the geological exploration technology, the drilling process monitoring technology reflects the in-situ information of rocks by monitoring the while-drilling parameters, and overcomes the defects of time consumption and labor consumption of the traditional drilling method. However, the drilling process monitoring technology only monitors drilling parameters, and the discreteness of the acquired data is large, so that quantitative analysis is difficult to perform. In addition, in the constant control of drilling parameters, due to the diversity of stratum changes, the pressure and the torque are strongly changed along with the stratum, and the prior art cannot timely make reflection adjustment.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a constant-speed drilling device and a method for evaluating strata, which can realize effective stratum evaluation and realize drilling speed quantification by acquiring drilling information and processing based on a deep learning algorithm.
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, embodiments of the present invention provide a constant speed drilling apparatus comprising a drill rod and a propulsion mechanism, the propulsion mechanism comprising a propulsion screw parallel to the axis of the drill rod, the propulsion screw being connected to a propulsion nut holder; the drill rod is fixed with the pushing nut seat, and a plurality of guide shafts which are in sliding connection with the pushing nut seat are uniformly arranged in the circumferential direction of the drill rod;
the propelling screw rod is connected with a power source, and the power source drives the propelling screw rod to rotate so that the nut seat drives the drill rod to move along the guide shaft.
As a further implementation, the push nut seat is mounted with a pressure sensor.
As a further implementation manner, the propulsion mechanism is installed in the shell, and a power meter is also installed in the shell.
As a further implementation manner, the power source comprises a servo motor and a speed reducer, and the servo motor is connected with the propelling screw rod through the speed reducer.
In a second aspect, embodiments of the present invention also provide a method for evaluating a formation by a constant velocity drilling apparatus, including:
arranging a constant-speed drilling device in a target area;
the starting device records drilling pressure and power data;
after drilling to a set depth, deriving pressure and power data, and processing the data to obtain a curve of the high energy consumption area and the low energy consumption area changing along with the depth;
after multiple drilling operations are carried out in a target area, drilling data are processed based on a depth feedforward neural network algorithm, and the intensity characteristic information distribution condition of an initial stratum of a drill hole along with the depth is obtained;
obtaining a basic stratum intensity distribution model based on a line-surface expansion extension prediction algorithm of deep learning;
and eliminating the abnormal stratum information prediction result to obtain an accurate drilling stratum distribution model.
As a further implementation, when the formation is relatively stable, the bit pressure and the rig energy consumption value do not change much; when the sudden increase or the sudden decrease of the bit pressure and the consumed energy value of the drilling machine occur, the change of the drilling stratum is indicated.
As a further implementation mode, different types of geological features are marked, geological information of all drill holes is inserted into a geological modeling model, and coordinates and parameter information of all drill holes are unified through modeling software.
As a further implementation mode, a line-surface extension prediction algorithm based on deep learning is used for learning and establishing a correlation relation model among the drill holes, and extension prediction is carried out on inter-hole parameters to obtain a basic stratum intensity distribution model.
As a further implementation, with the evaluation prediction range set, the parameters that are not within the evaluation prediction range are deleted.
As a further implementation mode, the drilling speed is not higher than 50mm/min in a hard rock stratum investigation test, and the drilling speed is not higher than 150mm/min in a soft soil stratum investigation test.
The invention has the following beneficial effects:
(1) the drill rod is driven by the lead screw to axially move along the guide shafts, and stable drilling is realized through the guide effect of the guide shafts; pressure information in the drilling process is obtained through the pressure sensor, drilling energy information is obtained through the power meter, and basis is provided for further layer judgment.
(2) According to the invention, the curve of energy consumption changing with the depth is obtained through the bit pressure and the energy consumption value of the drilling machine, the rock and soil strength information can be shown to a certain extent, and the information of energy consumption changing with the depth is the unified coordinate information for later modeling, so that the coordinate information can be favorably unified for deep learning and prediction.
(3) The method is based on a line-surface extended extension prediction algorithm of deep learning, a correlation relation model among all drill holes is established, and extended extension prediction is carried out on hole parameters to obtain a basic stratum intensity distribution model; and the abnormal stratum information prediction result is removed, an accurate drilling stratum distribution model is obtained, and the accuracy of the stratum distribution model is ensured.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic block diagram of the present invention according to one or more embodiments;
the device comprises a servo motor 1, a speed reducer 2, a propelling screw rod 3, a propelling nut seat 4, a propelling nut seat 5, a guide sleeve 6, a guide shaft 7, a drill rod 8, a first mounting plate 9 and a second mounting plate.
Detailed Description
The first embodiment is as follows:
the embodiment provides a constant-speed drilling device, which comprises a drill rod 7 and a propelling mechanism, wherein the drill rod 7 is connected with the propelling mechanism, and drilling is realized under the action of the propelling mechanism; the drill bit is arranged at the end of the drill rod 7.
In this embodiment, the drill bit may be a roller cone core bit or a PDC bit.
Furthermore, the propelling mechanism comprises a power source, a propelling screw rod 3, a propelling nut seat 4 and a guide shaft 6, and a drill rod 7 is fixed with the propelling nut seat 4 and is perpendicular to the propelling nut seat 4. The propelling nut seat 4 is in threaded connection with the propelling screw rod 3, and the propelling nut seat 4 can move along the axial direction of the propelling screw rod 3.
The propelling screw rod 3 is connected with a power source, and the propelling screw rod 3 is driven to rotate by the power source. In this embodiment, the power source includes a servo motor 1 and a speed reducer 2, and the servo motor is connected with a propelling screw rod 3 through the speed reducer.
The servo motor 1 is connected with the controller, the controller can accurately control the rotating speed of the servo motor 1 in a position mode, the number of turns N (r/min) required to be rotated per minute of the servo motor 1 is calculated according to the set drilling speed V (mm/min) divided by the drilling depth L (mm/r) of one turn of the servo motor 1, the number of pulses required to be output can be calculated through the rotating speed, and therefore constant-feeding control over the drilling speed is achieved.
Furthermore, the guide shafts 6 are distributed along the circumference of the push nut seat 4 and are uniformly distributed relative to the drill rod 7; the pushing nut seat 4 is provided with a guide sleeve 5, and a guide shaft 6 penetrates through the guide sleeve 5. One end of the guide shaft 6 is connected with a first mounting plate 8, and the other end of the guide shaft is connected with a second mounting plate 9; the propelling screw rod 3 is connected with a first mounting plate 8 and a second mounting plate 9 through bearings.
In the present embodiment, the pushing nut seat 4 is provided with a pressure sensor for detecting the pressure value generated by the pushing of the pushing nut seat 4.
The propelling mechanism is arranged in the shell, and the power meter is further arranged in the shell and used for detecting energy consumed in the drilling process.
Example two:
the embodiment provides a method for evaluating a stratum by using a constant-speed drilling device, which comprises the following steps of:
(1) according to engineering investigation needs, select suitable drill bit, be connected drill bit and drilling rod, debug the device.
(2) And arranging the constant-speed drilling device in a target area (an area to be subjected to geological exploration and judgment).
(3) And starting the constant-speed drilling device and setting the constant drilling speed. Considering protecting the drilling machine and the drill bit, the set speed is not higher than 50mm/min in the investigation test of the hard rock layer, and the set speed is not higher than 150mm/min in the investigation test of the soft soil layer. Drilling is started while drilling pressure and power data are recorded.
When the stratum is stable, the bit pressure and the energy consumption value of the drilling machine are not changed greatly due to the constant drilling speed (namely the volume of the damaged rock-soil body is constant in unit time), and the drilling stratum is changed when the bit pressure and the energy consumption value of the drilling machine are suddenly increased or decreased.
(4) And after the drilling machine drills to the target depth, the drilling machine stops drilling, the pressure of the drill bit and the consumption energy value of the drilling machine are recorded and exported, and data processing is carried out according to the pressure value change and the energy consumption value, so that the curve of the high-energy consumption area (high-intensity area) and the curve of the low-energy consumption area (low-intensity area) changing along with the depth can be obtained.
The energy consumption and depth variation curve indicates rock and soil mass strength information to a certain extent, and the energy consumption and depth variation information is unified coordinate information for later modeling, so that the coordinate information is favorably unified and changed, and deep learning and prediction are performed.
(5) And (4) withdrawing the constant-speed drilling device, moving to the next position, and repeating the steps (3) to (4).
(6) After multiple drilling operations are carried out in a target area, according to the obtained drilling information, the drilling parameters are identified and matched by adopting a depth feedforward neural network algorithm to preliminarily evaluate the strength of rock and soil bodies of the drilling stratum, and the strength characteristic information distribution condition of the drilling initial stratum along with the depth is obtained.
Different types of geological features are marked, including intensity information, rock/soil types and various types of basic data. And inserting the geological information of each drill hole into a geological modeling model, and unifying the coordinate and parameter information of each drill hole through modeling software. The drilling information comprises constant speed, rotating speed, monitoring pressure, torque and power, and a unified azimuth coordinate system is established for all the drilling information; after the coordinates are unified, prediction analysis can be carried out through a deep learning method after all drilling information of the point is clear.
The drilling machine acquires drilling information (longitudinal information) in a drill hole, and the drilling information of a gap between the drill hole and the drill hole needs to be transversely extended through learning prediction. And establishing a correlation relation model among the drill holes based on a line-surface extended extension prediction algorithm of deep learning, and performing extended extension prediction on hole parameters to obtain a basic stratum intensity distribution model.
The intensity variation range of the stratum in a small range is not large, the line-surface expansion extension prediction algorithm is based on the principle, after drilling coordinates are unified, a reasonable intensity interval of gaps among drilling holes is predicted through learning of multiple groups of data based on predicted intensity information of the points in known multiple drilling holes in the plane, and the predicted stratum information of the plane after line-surface expansion is obtained through predicting intensity interval information between the drilling holes and the drilling holes in the plane according to the multiple-point information.
And eliminating abnormal (overlarge deviation value) stratum information prediction results to obtain an accurate drilling stratum distribution model. By setting a reasonable evaluation prediction range, deleting rock mass structural plane influence parameters and mechanical influence parameters outside the upper edge and the lower edge of the reasonable range, keeping the while-drilling parameters inside the upper edge and the lower edge, mainly taking numerical values inside an upper quartile line and a lower quartile line, and increasing the generalization capability of the deep learning prediction model.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. The constant-speed drilling device is characterized by comprising a drill rod and a propelling mechanism, wherein the propelling mechanism comprises a propelling screw rod parallel to the axis of the drill rod, and the propelling screw rod is connected with a propelling nut seat; the drill rod is fixed with the pushing nut seat, and a plurality of guide shafts which are in sliding connection with the pushing nut seat are uniformly arranged in the circumferential direction of the drill rod;
the propelling screw rod is connected with a power source, and the power source drives the propelling screw rod to rotate so that the nut seat drives the drill rod to move along the guide shaft.
2. A constant velocity drilling apparatus as claimed in claim 1, wherein the push nut mount is fitted with a pressure sensor.
3. A constant velocity drilling apparatus according to claim 1, wherein the propulsion mechanism is mounted within a housing, the housing further having a dynamometer mounted therein.
4. The constant-speed drilling device according to claim 1, wherein the power source comprises a servo motor and a speed reducer, and the servo motor is connected with the propelling screw rod through the speed reducer.
5. A method of evaluating an earth formation using a constant velocity drilling apparatus according to any of claims 1-4, comprising:
arranging a constant-speed drilling device in a target area;
the starting device records drilling pressure and power data;
after drilling to a set depth, deriving pressure and power data, and processing the data to obtain a curve of the high energy consumption area and the low energy consumption area changing along with the depth;
after multiple drilling operations are carried out in a target area, drilling data are processed based on a depth feedforward neural network algorithm, and the intensity characteristic information distribution condition of an initial stratum of a drill hole along with the depth is obtained;
obtaining a basic stratum intensity distribution model based on a line-surface expansion extension prediction algorithm of deep learning;
and eliminating the abnormal stratum information prediction result to obtain an accurate drilling stratum distribution model.
6. The method for evaluating a formation according to claim 5, wherein when the formation is relatively stable, the bit pressure does not vary much from the energy value consumed by the drilling machine; when the sudden increase or the sudden decrease of the bit pressure and the consumed energy value of the drilling machine occur, the change of the drilling stratum is indicated.
7. The method of claim 5, wherein the geological features of different categories are labeled, the geological information of each borehole is inserted into a geological modeling model, and the coordinates and parameter information of each borehole are unified by modeling software.
8. The method for evaluating a stratum by using a constant-speed drilling device as claimed in claim 5, wherein a line-surface extended prediction algorithm based on deep learning is used for learning and establishing a correlation model among drilling holes, and extended prediction is performed on inter-hole parameters to obtain a basic stratum intensity distribution model.
9. The method for evaluating an earth formation of a constant velocity drilling apparatus according to claim 5, wherein the parameter which is not within the evaluation prediction range is deleted by the set evaluation prediction range.
10. The method for evaluating a stratum with a constant-speed drilling device according to claim 5, wherein a drilling speed is not higher than 50mm/min in a hard rock stratum investigation test and not higher than 150mm/min in a soft soil stratum investigation test.
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| CN202111093198.9A CN113863847B (en) | 2021-09-17 | 2021-09-17 | Constant-speed drilling device and stratum evaluation method |
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| CN202111093198.9A CN113863847B (en) | 2021-09-17 | 2021-09-17 | Constant-speed drilling device and stratum evaluation method |
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| CN113863847B CN113863847B (en) | 2023-04-07 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114458193A (en) * | 2022-01-26 | 2022-05-10 | 四川大学 | Reel formula drilling rod self-adaptation direction fixing device |
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2021
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| CA2199579A1 (en) * | 1996-03-11 | 1997-09-11 | Colin Wray Shaw | Rotary rock drill |
| US20060212224A1 (en) * | 2005-02-19 | 2006-09-21 | Baker Hughes Incorporated | Use of the dynamic downhole measurements as lithology indicators |
| CN106599442A (en) * | 2016-12-09 | 2017-04-26 | 中国石油天然气集团公司 | Recognition and evaluation method and device for physical properties of while-drilling reservoir based on comprehensive logging parameters |
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| CN114458193A (en) * | 2022-01-26 | 2022-05-10 | 四川大学 | Reel formula drilling rod self-adaptation direction fixing device |
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