CN108764530B - Method and device for configuring working parameters of oil well pumping unit - Google Patents
Method and device for configuring working parameters of oil well pumping unit Download PDFInfo
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Abstract
The invention discloses a method and a device for configuring working parameters of an oil well pumping unit, and belongs to the technical field of petroleum. According to the method, each group of production data of the oil pumping units of the oil well is processed, the load utilization rate of the first oil pumping unit when the daily power consumption of a single well in each group of production data is measured to be the minimum value is obtained, the load utilization rates of the plurality of first oil pumping units are processed, and the load utilization rate of the second oil pumping unit is obtained. When the oil pumping unit of the oil well operates at the load utilization rate of the second oil pumping unit, the daily power consumption of a single well is minimum, so that the working parameters of the oil pumping unit are configured based on the load utilization rate of the second oil pumping unit, more reasonable configuration reference standards can be obtained based on actual production data, namely, a method capable of determining reasonable load utilization rate is provided, and the method has guiding significance and practicability on actual production, so that the energy consumption of the oil pumping unit in the operation process can be reduced, and the service life of the oil pumping unit can be prolonged.
Description
Technical Field
The invention relates to the technical field of petroleum, in particular to a method and a device for configuring working parameters of an oil well pumping unit.
Background
In the process of oil exploitation, an oil pumping unit is a main oil extraction device, and for the oil pumping unit, the load utilization rate of the oil pumping unit is one of important influence factors for determining the energy consumption level of an oil pumping well, and the load utilization rate of the oil pumping unit refers to the ratio of the maximum load of an actual suspension point of the oil pumping unit to the maximum load of a nameplate of the oil pumping unit. The load utilization rate of the oil pumping unit is too high, so that the service life of the oil pumping unit is easily reduced; the load utilization rate of the oil pumping unit is too low, and high energy consumption production is easily caused. In order to reduce the energy consumption of the pumping unit in the operation process and prolong the service life of the pumping unit, the reasonable load utilization rate of the pumping unit well needs to be optimized and analyzed.
The current research mainly focuses on the influence factors of the load utilization rate of the pumping unit, for example, along with the increase of stroke, stroke frequency, working fluid level, pump diameter and pump hanging depth, the load utilization rate of the pumping unit is linearly increased in a direct proportion, and all parameters are sequentially sequenced according to the influence weight on the load utilization rate of the pumping unit: stroke, stroke frequency, working fluid level, pump diameter and pump hanging depth.
Although the above research determines the factors affecting the load utilization rate of the pumping unit, no specific method for determining the reasonable load utilization rate of the pumping unit is provided, the guiding significance to the actual production is poor, and the practicability is poor.
Disclosure of Invention
The embodiment of the invention provides a method and a device for configuring working parameters of an oil well pumping unit, which can solve the problem of the deficiency of the prior art, and the technical scheme is as follows:
in one aspect, a method for configuring operating parameters of an oil pumping unit of an oil well is provided, and the method comprises the following steps:
acquiring a production data set, wherein the production data set comprises production data of a plurality of oil wells in a target area;
grouping the production data in the production data set to obtain a plurality of groups of production data;
for each group of production data, performing quadratic polynomial fitting by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and taking the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data;
acquiring a first pumping unit load utilization rate of each group of production data according to the quadratic polynomial of each group of production data, wherein the first pumping unit load utilization rate is the pumping unit load utilization rate when the daily power consumption of a single well in the group of production data is the minimum value;
obtaining an expected value and a standard deviation of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data;
determining a target boundary range of the first pumping unit load utilization rate in normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
acquiring the load utilization rate of a second pumping unit according to the load utilization rates of a plurality of first pumping units in the target boundary range;
and configuring the working parameters of the pumping unit by taking the load utilization rate of the second pumping unit as the target load utilization rate of the pumping unit.
In one possible implementation manner, the grouping the production data in the production data set to obtain multiple sets of production data includes:
and sorting the production data in the production data set from small to large according to the motor load rate, and dividing the production data with the same motor load rate into a group to obtain the multiple groups of production data.
In one possible implementation, the determining the target boundary range of the first pumping unit load utilization in the normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization for each set of production data comprises:
determining a normal distribution graph of the first pumping unit load utilization rate according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
In one possible implementation, the obtaining a second pumping unit load utilization ratio according to a plurality of first pumping unit load utilization ratios within a target boundary range includes:
and obtaining the average value of the load utilization rate of the first pumping unit in the target boundary range, and taking the average value as the load utilization rate of the second pumping unit.
In one possible implementation manner, the configuring the operating parameters of the pumping unit with the second pumping unit load utilization ratio as the target pumping unit load utilization ratio includes:
and the stroke, the stroke frequency, the pump diameter and the pump hanging depth are combined and optimized, the target pumping unit load utilization rate is used as an optimization target, the target stroke frequency, the target pump diameter and the target pump hanging depth are obtained, and the target stroke frequency, the target pump diameter and the target pump hanging depth can enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
In another aspect, an apparatus for configuring operating parameters of an oil pumping unit for an oil well is provided, the apparatus comprising:
the data acquisition module is used for acquiring a production data set, and the production data set comprises the production data of a plurality of oil wells in a target area;
the grouping module is used for grouping the production data in the production data set to obtain a plurality of groups of production data;
the fitting module is used for performing quadratic polynomial fitting on each group of production data by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and taking the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data;
the utilization rate acquisition module is used for acquiring the load utilization rate of a first pumping unit of each group of production data according to the quadratic polynomial of each group of production data, and the load utilization rate of the first pumping unit is the load utilization rate of the pumping unit when the daily power consumption of a single well in the group of production data is the minimum value;
the statistical value acquisition module is used for obtaining expected values and standard deviations of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data;
the boundary range determining module is used for determining a target boundary range of the first pumping unit load utilization rate in normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
the utilization rate acquisition module is further used for acquiring the load utilization rate of the second pumping unit according to the load utilization rates of the plurality of first pumping units within the target boundary range;
and the configuration module is used for configuring the working parameters of the pumping unit by taking the load utilization rate of the second pumping unit as the target load utilization rate of the pumping unit.
In a possible implementation manner, the grouping module is configured to sort the production data in the production data set from small to large according to the motor load rates, and group the production data with the same motor load rate into one group to obtain the multiple groups of production data.
In one possible implementation, the boundary range determining module is configured to determine a normal distribution graph of the first pumping unit load utilization according to an expected value and a standard deviation of the first pumping unit load utilization for each set of production data;
determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
In one possible implementation manner, the utilization rate obtaining module is configured to obtain an average value of the load utilization rates of the first pumping unit within the target boundary range, and the average value is used as the load utilization rate of the second pumping unit.
In a possible implementation manner, the configuration module is configured to perform combined optimization on the stroke, the stroke frequency, the pump diameter and the pump hanging depth, and obtain the target stroke, the target stroke frequency, the target pump diameter and the target pump hanging depth by using the target pumping unit load utilization rate as an optimization target, where the target stroke, the target stroke frequency, the target pump diameter and the target pump hanging depth enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
the load utilization rate of the first pumping unit when the daily power consumption of a single well in each group of production data is measured to be the minimum value is obtained by processing each group of production data of the oil well pumping units, the load utilization rates of the plurality of first pumping units are processed, and the load utilization rate of the second pumping unit is obtained. When the oil well pumping unit operates with the second pumping unit load utilization rate, the daily power consumption of a single well is the minimum, the second pumping unit load utilization rate is the simulated reasonable load utilization rate of the oil well pumping unit, therefore, the working parameters of the pumping unit are configured based on the second pumping unit load utilization rate, more reasonable configuration reference standards can be obtained based on actual production data, namely, a method capable of determining the reasonable load utilization rate is provided, and the method has guiding significance and practicability on actual production, so that the energy consumption of the pumping unit in the operation process can be reduced, and the service life of the pumping unit can be prolonged.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of a method for configuring operating parameters of an oil pumping unit according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for configuring operating parameters of an oil pumping unit according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an operating parameter configuration device of an oil pumping unit of an oil well according to an embodiment of the present invention;
fig. 4 shows a block diagram of a computer device 400 provided in an exemplary embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for configuring operating parameters of an oil pumping unit of an oil well according to an embodiment of the present invention. Referring to fig. 1, the method includes:
101. and acquiring a production data set, wherein the production data set comprises the production data of a plurality of oil wells in the target area.
102. And grouping the production data in the production data set to obtain a plurality of groups of production data.
103. And for each group of production data, performing quadratic polynomial fitting by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data.
104. And acquiring the load utilization rate of a first pumping unit of each group of production data according to the quadratic polynomial of each group of production data, wherein the load utilization rate of the first pumping unit is the load utilization rate of the pumping unit when the daily power consumption of a single well in the group of production data is the minimum value.
105. And obtaining the expected value and the standard deviation of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data.
106. And determining a target boundary range of the first pumping unit load utilization rate in normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data.
107. And acquiring the load utilization rate of the second pumping unit according to the load utilization rates of the plurality of first pumping units in the target boundary range.
108. And configuring the working parameters of the pumping unit by taking the load utilization rate of the second pumping unit as the target load utilization rate of the pumping unit.
According to the method provided by the embodiment of the invention, each group of production data of the oil pumping units of the oil well is processed, so that the load utilization rate of the first pumping unit when the daily power consumption of a single well in each group of production data is measured to be the minimum value is obtained, and the load utilization rates of the plurality of first pumping units are processed to obtain the load utilization rate of the second pumping unit. When the oil well pumping unit operates with the second pumping unit load utilization rate, the daily power consumption of a single well is the minimum, the second pumping unit load utilization rate is the simulated reasonable load utilization rate of the oil well pumping unit, therefore, the working parameters of the pumping unit are configured based on the second pumping unit load utilization rate, more reasonable configuration reference standards can be obtained based on actual production data, namely, a method capable of determining the reasonable load utilization rate is provided, and the method has guiding significance and practicability on actual production, so that the energy consumption of the pumping unit in the operation process can be reduced, and the service life of the pumping unit can be prolonged.
In one possible implementation manner, the grouping the production data in the production data set to obtain multiple sets of production data includes:
and sorting the production data in the production data set from small to large according to the motor load rate, and dividing the production data with the same motor load rate into a group to obtain the multiple groups of production data.
In one possible implementation, the determining the target boundary range of the first pumping unit load utilization in the normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization for each set of production data comprises:
determining a normal distribution graph of the first pumping unit load utilization rate according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
In one possible implementation, the obtaining a second pumping unit load utilization ratio according to a plurality of first pumping unit load utilization ratios within a target boundary range includes:
and obtaining the average value of the load utilization rate of the first pumping unit in the target boundary range, and taking the average value as the load utilization rate of the second pumping unit.
In one possible implementation manner, the configuring the operating parameters of the pumping unit with the second pumping unit load utilization ratio as the target pumping unit load utilization ratio includes:
and the stroke, the stroke frequency, the pump diameter and the pump hanging depth are combined and optimized, the target pumping unit load utilization rate is used as an optimization target, the target stroke frequency, the target pump diameter and the target pump hanging depth are obtained, and the target stroke frequency, the target pump diameter and the target pump hanging depth can enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
All the above optional technical solutions may be combined arbitrarily to form the optional embodiments of the present disclosure, and are not described herein again.
Fig. 2 is a flowchart of a method for configuring operating parameters of an oil pumping unit of an oil well according to an embodiment of the present invention. Referring to fig. 2, the method includes:
201. and acquiring a production data set, wherein the production data set comprises the production data of a plurality of oil wells in the target area.
The target area is a region range governed by an oil field which needs to be configured currently, and may be divided by adopting any division principle, for example, based on the current division, the target area may be a region determined by a certain oil production plant range in the north China oil field.
The production data for each well includes: well number, motor load rate, pumping unit load utilization rate and single-well daily power consumption. In view of the specificity of the petroleum industry, all the recorded well numbers can be collectively labeled as a # 1 well and a # 2 well … …. Of course, the number of wells in the target area can be counted by the production data.
For example, taking the area determined by the range of a certain oil production plant in the north china oil field as an example, the production data in the area is recorded to obtain the production data set shown in table 1.
TABLE 1
202. And grouping the production data in the production data set of the target area to obtain a plurality of groups of production data.
Specifically, when grouping, the production data in the production data set are sorted from small to large according to the motor load rate, and the production data with the same motor load rate are grouped into one group to obtain multiple groups of production data.
For example, based on 733 production data items in the above table 1, 40 production data items can be grouped by motor load rate from small to large.
203. And for each group of production data, performing quadratic polynomial fitting by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data.
Assuming a quadratic polynomial fit to a set of production data, the resulting quadratic polynomial function has the form y ═ ax2+ bx + c, where x represents the pumping unit load utilization,y represents the daily power consumption of a single well, wherein the definition domain of x is the numerical range of the load utilization rate of the pumping unit corresponding to the set of production data. And performing quadratic polynomial fitting on the multiple groups of production data to obtain a quadratic polynomial of each group of production data.
204. And acquiring the load utilization rate of a first pumping unit of each group of production data according to the quadratic polynomial of each group of production data, wherein the load utilization rate of the first pumping unit is the load utilization rate of the pumping unit when the daily power consumption of a single well in the group of production data is the minimum value.
When the load utilization rate of the first pumping unit of each group of production data is obtained, if the second-order polynomial function y of the group of production data is ax2Coefficient of quadratic term a in + bx + c>0, taking its first derivative
And setting the first derivative as 0, and calculating to obtain the value of x when the first derivative is 0, wherein the value of x at the moment is the load utilization rate of the pumping unit when the daily power consumption of the single well in the group of production data is the minimum value.
If the second order polynomial function y of the set of production data is ax2Coefficient of quadratic term a in + bx + c<And 0, finding out the minimum value of the daily power consumption y of the single well in the group of production data, wherein the corresponding x value is the load utilization rate of the pumping unit when the daily power consumption of the single well in the group of production data is the minimum value.
Based on the production data set provided in table 1 above and the processing of steps 203 and 204, the first pump unit load utilization for each set of production data can be obtained as shown in table 2.
TABLE 2
205. And obtaining the expected value and the standard deviation of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data.
In the embodiment of the invention, the normal distribution graph of the load utilization rate of the first pumping unit can be generated according to the expected value and the standard deviation. The expected value is used to represent an average of the first pumping unit load utilization for each set of production data. The standard deviation is used to represent the degree of variation in the first pumping unit load utilization for each set of production data.
For example, based on the data in table 2, the expected value μ of the first pump unit load utilization and the standard deviation σ of 0.084 can be found for each set of production data.
The normal distribution graph can represent the probability of each first pumping unit load utilization.
206. And determining a target boundary range in the normal distribution according to the expected value and the standard deviation of the load utilization rate of the first pumping unit of each group of production data.
The target boundary range refers to:
according to the 3 σ criterion of normal distribution:
the area in the horizontal axis interval (. mu. -sigma.,. mu. + sigma.) is 68.268949%,
represents a probability P { | x- μ | < σ } ═ 2 Φ (1) -1 ═ 0.6826;
the area in the horizontal axis interval (mu-1.96 sigma, mu +1.96 sigma) is 95.449974%,
represents a probability P { | x- μ | <2 σ } ═ 2 Φ (2) -1 ═ 0.9544;
the area in the range of the horizontal axis (mu-2.58 sigma, mu +2.58 sigma) is 99.730020%,
this indicates that the probability P { | x- μ | <3 σ }, 2 Φ (3) -1 ═ 0.9974.
Therefore, it is considered that data other than the horizontal axis intervals (μ -3 σ, μ +3 σ) belong to a coarse error, and after the coarse error is removed, the intervals (μ -3 σ, μ +3 σ) are regarded as the actual value intervals of the random variable x, and (μ - σ, μ + σ) is determined as the target boundary range.
For example: based on the data of table 2, applying the 3 σ criterion yields: the target boundary range for the first pumping unit load utilization for each set of production data is (mu-sigma < x ≦ mu + sigma), i.e., (0.566 < x ≦ 0.734), yielding each first pumping unit load utilization within the target boundary range.
207. And obtaining the average value of the load utilization rate of the first pumping unit in the target boundary range, and taking the average value as the load utilization rate of the second pumping unit.
The average value may represent a general level of first pumping unit load utilizations within the target boundary.
For example: based on the first boundary range, 28 groups of first pumping units are screened out from the data in the table 2, and the average value of the 28 groups of first pumping units is 0.67, namely the simulated reasonable load utilization rate of the oil pumping unit of the oil well.
208. And according to the load utilization rate of the target oil pumping unit, carrying out combined optimization on working parameters of the oil pumping unit, such as stroke, stroke frequency, pump diameter and pump hanging depth.
And the stroke, the stroke frequency, the pump diameter and the pump hanging depth are combined and optimized, the target pumping unit load utilization rate is used as an optimization target, the target stroke frequency, the target pump diameter and the target pump hanging depth are obtained, and the target stroke frequency, the target pump diameter and the target pump hanging depth can enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate. Of course, other factors affecting the load utilization of the pumping unit can be optimized to achieve the target load utilization of the pumping unit.
According to the method provided by the embodiment of the invention, each group of production data of the oil pumping units of the oil well is processed, so that the load utilization rate of the first pumping unit when the daily power consumption of a single well in each group of production data is measured to be the minimum value is obtained, and the load utilization rates of the plurality of first pumping units are processed to obtain the load utilization rate of the second pumping unit. When the oil well pumping unit operates with the second pumping unit load utilization rate, the daily power consumption of a single well is the minimum, the second pumping unit load utilization rate is the simulated reasonable load utilization rate of the oil well pumping unit, therefore, the working parameters of the pumping unit are configured based on the second pumping unit load utilization rate, more reasonable configuration reference standards can be obtained based on actual production data, namely, a method capable of determining the reasonable load utilization rate is provided, and the method has guiding significance and practicability on actual production, so that the energy consumption of the pumping unit in the operation process can be reduced, and the service life of the pumping unit can be prolonged.
Fig. 3 is a schematic structural diagram of an operating parameter configuration device of an oil pumping unit of an oil well, according to an embodiment of the present invention, and referring to fig. 3, the device includes:
the data acquisition module 301 is configured to acquire a production data set, where the production data set includes production data of multiple oil wells in a target area;
a grouping module 302, configured to group the production data in the production data set to obtain multiple sets of production data;
the fitting module 303 is configured to perform quadratic polynomial fitting on each group of production data by using the pumping unit load utilization rate of each group of production data as an independent variable and using the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data;
a utilization rate obtaining module 304, configured to obtain a first pumping unit load utilization rate of each group of production data according to the quadratic polynomial of each group of production data, where the first pumping unit load utilization rate is a pumping unit load utilization rate when the daily power consumption of a single well in the group of production data is the minimum;
a statistical value obtaining module 305, configured to obtain an expected value and a standard deviation of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each set of production data;
a boundary range determining module 306, configured to determine a target boundary range of the first pumping unit load utilization rate in normal distribution according to an expected value and a standard deviation of the first pumping unit load utilization rate of each set of production data;
the utilization rate obtaining module 304 is further configured to obtain a load utilization rate of a second pumping unit according to load utilization rates of a plurality of first pumping units within a target boundary range;
and a configuration module 307, configured to configure the operating parameters of the pumping unit with the load utilization rate of the second pumping unit as a target load utilization rate of the pumping unit.
In a possible implementation manner, the grouping module 302 is configured to sort the production data in the production data set from small to large according to the motor load rates, and group the production data with the same motor load rate into one group, so as to obtain the multiple groups of production data.
In one possible implementation, the boundary range determination module 306 is configured to determine a normal distribution graph of the first pumping unit load utilization based on an expected value and a standard deviation of the first pumping unit load utilization for each set of production data; determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
In one possible implementation, the utilization obtaining module 304 is configured to obtain an average of the first pumping unit load utilization within a target boundary range as the second pumping unit load utilization.
In a possible implementation manner, the configuration module 307 is configured to perform combined optimization on the stroke, the stroke frequency, the pump diameter, and the pump hanging depth, and obtain the target stroke, the target stroke frequency, the target pump diameter, and the target pump hanging depth by using the target pumping unit load utilization rate as an optimization target, where the target stroke, the target stroke frequency, the target pump diameter, and the target pump hanging depth enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
It should be noted that: the working parameter configuration device of the oil well pumping unit provided in the above embodiment is exemplified by only the division of the above functional modules when the working parameter of the oil well pumping unit is configured, and in practical application, the above function distribution can be completed by different functional modules according to needs, that is, the internal structure of the equipment is divided into different functional modules, so as to complete all or part of the above described functions. In addition, the working parameter configuration device of the oil well pumping unit provided by the embodiment and the working parameter configuration method embodiment of the oil well pumping unit belong to the same concept, and the specific implementation process is detailed in the method embodiment and is not described again.
Fig. 4 shows a block diagram of a computer device 400 provided in an exemplary embodiment of the invention. The computer device 400 may be: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion video Experts compression standard Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer IV, motion video Experts compression standard Audio Layer 4), a notebook computer, or a desktop computer. Computer device 400 may also be referred to by other names such as user device, portable computer device, laptop computer device, desktop computer device, and the like.
Generally, the computer device 400 includes: a processor 401 and a memory 402.
In some embodiments, the computer device 400 may also optionally include: a peripheral interface 403 and at least one peripheral. The processor 401, memory 402 and peripheral interface 403 may be connected by bus or signal lines. Each peripheral may be connected to the peripheral interface 403 via a bus, signal line, or circuit board. Specifically, the peripheral device includes: at least one of radio frequency circuitry 404, touch screen display 405, camera 406, audio circuitry 407, positioning components 408, and power supply 409.
The peripheral interface 403 may be used to connect at least one peripheral related to I/O (Input/Output) to the processor 401 and the memory 402. In some embodiments, processor 401, memory 402, and peripheral interface 403 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 401, the memory 402 and the peripheral interface 403 may be implemented on a separate chip or circuit board, which is not limited by this embodiment.
The Radio Frequency circuit 404 is used for receiving and transmitting RF (Radio Frequency) signals, also called electromagnetic signals. The radio frequency circuitry 404 communicates with communication networks and other communication devices via electromagnetic signals. The rf circuit 404 converts an electrical signal into an electromagnetic signal to transmit, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 404 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and so forth. The radio frequency circuitry 404 may communicate with other computer devices via at least one wireless communication protocol. The wireless communication protocols include, but are not limited to: metropolitan area networks, various generation mobile communication networks (2G, 3G, 4G, and 5G), Wireless local area networks, and/or WiFi (Wireless Fidelity) networks. In some embodiments, the rf circuit 404 may further include NFC (Near Field Communication) related circuits, which are not limited in this application.
The display screen 405 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display screen 405 is a touch display screen, the display screen 405 also has the ability to capture touch signals on or over the surface of the display screen 405. The touch signal may be input to the processor 401 as a control signal for processing. At this point, the display screen 405 may also be used to provide virtual buttons and/or a virtual keyboard, also referred to as soft buttons and/or a soft keyboard. In some embodiments, the display screen 405 may be one, providing the front panel of the computer device 400; in other embodiments, the display screen 405 may be at least two, respectively disposed on different surfaces of the computer device 400 or in a folded design; in still other embodiments, the display screen 405 may be a flexible display screen disposed on a curved surface or on a folded surface of the computer device 400. Even further, the display screen 405 may be arranged in a non-rectangular irregular pattern, i.e. a shaped screen. The Display screen 405 may be made of LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), and other materials.
The camera assembly 406 is used to capture images or video. Optionally, camera assembly 406 includes a front camera and a rear camera. Generally, a front camera is disposed on a front panel of a computer apparatus, and a rear camera is disposed on a rear surface of the computer apparatus. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera assembly 406 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.
The audio circuit 407 may include a microphone and a speaker. The microphone is used for collecting sound waves of a user and the environment, converting the sound waves into electric signals, and inputting the electric signals to the processor 401 for processing, or inputting the electric signals to the radio frequency circuit 404 for realizing voice communication. For stereo capture or noise reduction purposes, the microphones may be multiple and located at different locations on the computer device 400. The microphone may also be an array microphone or an omni-directional pick-up microphone. The speaker is used to convert electrical signals from the processor 401 or the radio frequency circuit 404 into sound waves. The loudspeaker can be a traditional film loudspeaker or a piezoelectric ceramic loudspeaker. When the speaker is a piezoelectric ceramic speaker, the speaker can be used for purposes such as converting an electric signal into a sound wave audible to a human being, or converting an electric signal into a sound wave inaudible to a human being to measure a distance. In some embodiments, audio circuitry 407 may also include a headphone jack.
The Location component 408 is used to locate the current geographic Location of the computer device 400 for navigation or LBS (Location Based Service). The Positioning component 408 may be a Positioning component based on the GPS (Global Positioning System) of the united states, the beidou System of china, the graves System of russia, or the galileo System of the european union.
The power supply 409 is used to supply power to the various components in the computer device 400. The power source 409 may be alternating current, direct current, disposable or rechargeable. When power source 409 comprises a rechargeable battery, the rechargeable battery may support wired or wireless charging. The rechargeable battery may also be used to support fast charge technology.
In some embodiments, the computer device 400 also includes one or more sensors 410. The one or more sensors 410 include, but are not limited to: acceleration sensor 411, gyro sensor 412, pressure sensor 413, fingerprint sensor 414, optical sensor 415, and proximity sensor 416.
The acceleration sensor 411 may detect the magnitude of acceleration in three coordinate axes of a coordinate system established with the computer apparatus 400. For example, the acceleration sensor 411 may be used to detect components of the gravitational acceleration in three coordinate axes. The processor 401 may control the touch display screen 405 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signal collected by the acceleration sensor 411. The acceleration sensor 411 may also be used for acquisition of motion data of a game or a user.
The gyro sensor 412 may detect a body direction and a rotation angle of the computer device 400, and the gyro sensor 412 may cooperate with the acceleration sensor 411 to acquire a 3D motion of the user on the computer device 400. From the data collected by the gyro sensor 412, the processor 401 may implement the following functions: motion sensing (such as changing the UI according to a user's tilting operation), image stabilization at the time of photographing, game control, and inertial navigation.
The pressure sensors 413 may be disposed on the side bezel of the computer device 400 and/or on the lower layer of the touch screen display 405. When the pressure sensor 413 is arranged on the side frame of the computer device 400, the holding signal of the user to the computer device 400 can be detected, and the processor 401 performs left-right hand identification or shortcut operation according to the holding signal collected by the pressure sensor 413. When the pressure sensor 413 is disposed at the lower layer of the touch display screen 405, the processor 401 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 405. The operability control comprises at least one of a button control, a scroll bar control, an icon control and a menu control.
The fingerprint sensor 414 is used for collecting a fingerprint of the user, and the processor 401 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 414, or the fingerprint sensor 414 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, processor 401 authorizes the user to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings, etc. The fingerprint sensor 414 may be disposed on the front, back, or side of the computer device 400. When a physical key or vendor Logo is provided on the computer device 400, the fingerprint sensor 414 may be integrated with the physical key or vendor Logo.
The optical sensor 415 is used to collect the ambient light intensity. In one embodiment, the processor 401 may control the display brightness of the touch display screen 405 based on the ambient light intensity collected by the optical sensor 415. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 405 is increased; when the ambient light intensity is low, the display brightness of the touch display screen 405 is turned down. In another embodiment, the processor 401 may also dynamically adjust the shooting parameters of the camera assembly 406 according to the ambient light intensity collected by the optical sensor 415.
Proximity sensors 416, also known as distance sensors, are typically provided on the front panel of the computer device 400. The proximity sensor 416 is used to capture the distance between the user and the front of the computer device 400. In one embodiment, the processor 401 controls the touch display screen 405 to switch from the bright screen state to the rest screen state when the proximity sensor 416 detects that the distance between the user and the front surface of the computer device 400 is gradually decreased; the touch display screen 405 is controlled by the processor 401 to switch from a breath-screen state to a bright-screen state when the proximity sensor 416 detects that the distance between the user and the front surface of the computer device 400 is gradually increasing.
Those skilled in the art will appreciate that the configuration shown in FIG. 4 does not constitute a limitation of the computer device 400, and may include more or fewer components than those shown, or combine certain components, or employ a different arrangement of components.
In an exemplary embodiment, a computer readable storage medium, such as a memory, is also provided that includes instructions executable by a processor in a terminal to perform a method of configuring operating parameters of an oil pumping unit in the following embodiments. For example, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A method for configuring operating parameters of an oil pumping unit of an oil well, the method comprising:
acquiring a production data set, wherein the production data set comprises production data of a plurality of oil wells in a target area;
grouping the production data in the production data set to obtain a plurality of groups of production data;
for each group of production data, performing quadratic polynomial fitting by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and taking the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data;
acquiring a first pumping unit load utilization rate of each group of production data according to the quadratic polynomial of each group of production data, wherein the first pumping unit load utilization rate is the pumping unit load utilization rate when the daily power consumption of a single well in the group of production data is the minimum value;
obtaining an expected value and a standard deviation of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data;
determining a target boundary range of the first pumping unit load utilization rate in normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
acquiring the average value of the load utilization rates of the first pumping units in the target boundary range according to the load utilization rates of the first pumping units in the target boundary range, and taking the average value as the load utilization rate of the second pumping unit;
and configuring the working parameters of the pumping unit by taking the load utilization rate of the second pumping unit as the target load utilization rate of the pumping unit.
2. The method of claim 1, wherein grouping the production data in the production data set to obtain a plurality of sets of production data comprises:
and sorting the production data in the production data set from small to large according to the motor load rate, and dividing the production data with the same motor load rate into a group to obtain the multiple groups of production data.
3. The method of claim 1 wherein determining a target boundary range of the first pump unit load utilization in a normal distribution based on the expected value and standard deviation of the first pump unit load utilization for each set of production data comprises:
determining a normal distribution graph of the first pumping unit load utilization rate according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
4. The method of claim 1, wherein the configuring the operating parameters of the pumping unit with the second pumping unit load utilization as the target pumping unit load utilization comprises:
and the stroke, the stroke frequency, the pump diameter and the pump hanging depth are combined and optimized, the target pumping unit load utilization rate is used as an optimization target, the target stroke frequency, the target pump diameter and the target pump hanging depth are obtained, and the target stroke frequency, the target pump diameter and the target pump hanging depth can enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
5. An operating parameter configuration device for an oil pumping unit of an oil well, the device comprising:
the data acquisition module is used for acquiring a production data set, and the production data set comprises the production data of a plurality of oil wells in a target area;
the grouping module is used for grouping the production data in the production data set to obtain a plurality of groups of production data;
the fitting module is used for performing quadratic polynomial fitting on each group of production data by taking the load utilization rate of the pumping unit of each group of production data as an independent variable and taking the daily power consumption of a single well as a dependent variable to obtain a quadratic polynomial of each group of production data;
the utilization rate acquisition module is used for acquiring the load utilization rate of a first pumping unit of each group of production data according to the quadratic polynomial of each group of production data, and the load utilization rate of the first pumping unit is the load utilization rate of the pumping unit when the daily power consumption of a single well in the group of production data is the minimum value;
the statistical value acquisition module is used for obtaining expected values and standard deviations of the load utilization rate of the first pumping unit according to the load utilization rate of the first pumping unit of each group of production data;
the boundary range determining module is used for determining a target boundary range of the first pumping unit load utilization rate in normal distribution according to the expected value and the standard deviation of the first pumping unit load utilization rate of each group of production data;
the utilization rate obtaining module is further configured to obtain an average value of the load utilization rates of the first pumping units within the target boundary range according to the load utilization rates of the plurality of first pumping units within the target boundary range, and the average value is used as the load utilization rate of the second pumping unit;
and the configuration module is used for configuring the working parameters of the pumping unit by taking the load utilization rate of the second pumping unit as the target load utilization rate of the pumping unit.
6. The device of claim 5, wherein the grouping module is configured to sort the production data in the production data set from small to large according to motor load rates, and group the production data with the same motor load rate into one group, so as to obtain the multiple groups of production data.
7. The apparatus of claim 5 wherein the boundary range determination module is configured to determine a normal distribution plot of the first pump unit load utilization based on an expected value and a standard deviation of the first pump unit load utilization for each set of production data;
determining a range of (μ - σ, μ + σ) in the normal distribution map as the target boundary range, wherein μ represents an expected value of the first pump unit load utilization and σ represents a standard deviation of the first pump unit load utilization.
8. The device of claim 5, wherein the configuration module is configured to perform combined optimization on the stroke, the stroke frequency, the pump diameter, and the pump hanging depth, and obtain the target stroke, the target stroke frequency, the target pump diameter, and the target pump hanging depth with the target pumping unit load utilization rate as an optimization target, where the target stroke, the target stroke frequency, the target pump diameter, and the target pump hanging depth enable the pumping unit load utilization rate of the pumping unit during operation to reach the target pumping unit load utilization rate.
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| CN113032712B (en) * | 2020-10-26 | 2023-12-22 | 中国石油天然气股份有限公司 | Determination method and device for drilling coincidence information, computer equipment and storage medium |
| CN112836856A (en) * | 2021-01-07 | 2021-05-25 | 中国石油大学(华东) | Polynomial regression algorithm-based pumping unit water drive well pump detection period prediction method |
| CN117113127B (en) * | 2023-09-04 | 2024-03-29 | 大庆石油管理局有限公司 | Oil pumping well energy consumption analysis method based on K-means clustering |
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