CN112253102B - Method and device for determining oil well casing gas release pressure - Google Patents
Method and device for determining oil well casing gas release pressure Download PDFInfo
- Publication number
- CN112253102B CN112253102B CN202011220579.4A CN202011220579A CN112253102B CN 112253102 B CN112253102 B CN 112253102B CN 202011220579 A CN202011220579 A CN 202011220579A CN 112253102 B CN112253102 B CN 112253102B
- Authority
- CN
- China
- Prior art keywords
- pressure
- casing
- sample
- coefficient
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000003129 oil well Substances 0.000 title claims abstract description 75
- 238000000034 method Methods 0.000 title claims abstract description 51
- 239000007788 liquid Substances 0.000 claims abstract description 112
- 238000004519 manufacturing process Methods 0.000 claims abstract description 99
- 238000012360 testing method Methods 0.000 claims description 44
- 238000007599 discharging Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 abstract description 7
- 230000008569 process Effects 0.000 abstract description 6
- 238000000605 extraction Methods 0.000 abstract description 5
- 238000004904 shortening Methods 0.000 abstract description 3
- 239000003921 oil Substances 0.000 description 23
- 238000004364 calculation method Methods 0.000 description 12
- 239000012530 fluid Substances 0.000 description 12
- 230000000087 stabilizing effect Effects 0.000 description 9
- 238000013461 design Methods 0.000 description 7
- 230000008901 benefit Effects 0.000 description 5
- 239000009096 changqing Substances 0.000 description 5
- 230000007547 defect Effects 0.000 description 5
- 230000006870 function Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 4
- 230000001276 controlling effect Effects 0.000 description 4
- 238000011084 recovery Methods 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 239000010779 crude oil Substances 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000005086 pumping Methods 0.000 description 3
- 238000007667 floating Methods 0.000 description 2
- 238000012417 linear regression Methods 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 230000008054 signal transmission Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- 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
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B47/00—Survey of boreholes or wells
- E21B47/06—Measuring temperature or pressure
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Mining & Mineral Resources (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Fluid Mechanics (AREA)
- Computer Hardware Design (AREA)
- Data Mining & Analysis (AREA)
- Geometry (AREA)
- Geochemistry & Mineralogy (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Environmental & Geological Engineering (AREA)
- Mathematical Optimization (AREA)
- Databases & Information Systems (AREA)
- Pure & Applied Mathematics (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Mathematical Analysis (AREA)
- Medical Informatics (AREA)
- Computational Mathematics (AREA)
- Algebra (AREA)
- Geophysics (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
- Measuring Fluid Pressure (AREA)
Abstract
The application discloses a method and a device for determining the deflation pressure of an oil well casing, and belongs to the technical field of oil extraction in an oil field. The embodiment of the application provides a method for determining the gas release pressure of an oil well casing, which is characterized in that model training is carried out through sample casing pressure and sample liquid production amount to obtain a regression equation, and the regression equation learns the relation between the casing pressure and the liquid production amount in the training process, so that the target casing pressure corresponding to the target liquid production amount can be directly determined by means of the regression equation, thereby shortening the time for determining the casing pressure and improving the efficiency for determining the casing pressure.
Description
Technical Field
The application relates to the technical field of oil extraction in oil fields. In particular to a method and a device for determining the deflation pressure of an oil well casing.
Background
Casing pressure is an important parameter for controlling oil well production, and the magnitude of casing pressure directly influences the liquid production amount of the oil well. In the production process of an oil well, in order to increase the liquid production amount of the oil well, a casing is generally deflated, the casing pressure is reduced, the pressure difference between the casing and a stratum is controlled, and oil is driven into the casing through the pressure difference, so that the liquid production amount of the oil well is increased.
In the related technology, the pressure of the casing is reduced for a plurality of times according to experience by related personnel, then the liquid production amount of the oil well after the pressure of the casing is reduced each time is recorded, and then the casing pressure corresponding to the highest liquid production amount is searched from the recorded data.
However, in the prior art, when determining the casing pressure, a related person is required to make a plurality of attempts by relying on working experience, which results in low efficiency of determining the casing pressure.
For example, lin Xin et al, 2013, 1, published on "effect of casing pressure on oil well production in Changqing oilfield" on oil and gas engineering, "one notes herein that: the method is used for promoting the application of the casing gas constant pressure recovery process in the Changqing oilfield, improving the recovery and utilization of associated gas of the oil production well casing of the Changqing oilfield, and necessarily discussing the influence of the oil production well casing pressure on the liquid production amount of the oil well. First, the relation between the casing pressure of the oil well and the liquid production amount of the oil well is discussed in theory, and the analysis considers that the pump port pressure of the oil well is a critical point of the influence of the casing pressure on the liquid production amount of the oil well. And then according to the calculation formula of the pump port pressure of the pumping unit of the Changqing oilfield, the pump port pressure of the oil production well of the section of the Changqing oilfield and the set value of reasonable casing pressure are obtained. The determination of reasonable casing pressure provides an important theoretical basis for the application of the casing gas constant pressure recovery process in long-term oilfield and the recovery and utilization of associated gas of the casing of the oil production well.
Shen Xi 2016A graduate paper by Shuoshi research university, "design and implementation of reasonable casing gas pressure control System for oil well", which was done in electronic science and technology university, "one notes: the oil gas resource is taken as the basis of national economic development, the yield of the produced oil gas resource has very important practical significance for national life and national defense development, the stable and reasonable casing pressure is crucial for the oil production of a high gas-oil ratio well, however, for different well conditions and pump conditions, the control quantity of the casing pressure is also quite different for ensuring stable oil well production, so that the research and control of the casing pressure achieve the aim of stabilizing the oil well liquid production to improve the oil well liquid production and economic benefit, and the research subject has very important practical significance. However, the traditional oil well casing pressure control adopts casing pressure control modes such as a constant pressure valve and a pressure relief valve, and casing pressure judgment still needs to be carried out by taking manual experience as a standard, so that the casing pressure control has strong randomness, low automation degree and low oil and gas resource exploitation amount. Therefore, the mathematical calculation model of the reasonable casing pressure of the oil well is deduced based on the relation research of the casing pressure and the liquid production amount, and a set of reasonable casing pressure control system which can be suitable for the oil well with high gas-oil ratio is researched according to the mathematical calculation model, and each system module is designed and developed, so that the functions of data real-time acquisition, data remote transmission, casing pressure real-time monitoring, casing pressure control valve real-time control and the like can be realized. The following results were achieved by the study of the casing pressure control system: (1) by analyzing the theoretical calculation aspect of the reasonable casing pressure of the high gas-oil ratio type oil well, the influence factors and the implementation modes of the reasonable casing pressure are combed, the main design index and the functional requirement of the system are determined by combining the actual oil extraction process of the oil field and the traditional casing pressure control method, and the overall scheme design of the system is completed; (2) according to the determined system scheme, the hardware overall structure of the system is designed, and an acquisition system, a transmission system and a lower computer control system which are applicable to a casing pressure control system are developed in combination with system matched equipment; (3) and the SQL Server 2008 database management platform is utilized to monitor a matched database of the system, and the development of an oil well reasonable casing pressure control software system with functions of data management, casing pressure control analysis, remote control and the like is realized based on a C# programming language under a VS framework.
The "casing gas pressure control System research and design for stabilizing oil well production" by the graduate paper of the Shuzo university, southwest in the year 2016, is herein pointed out: the oil well with high gas-oil ratio contains a large amount of free gas which is distributed in the annular space of the oil sleeve, and during the oil extraction process, the gas is dissolved in the crude oil and is not fully filled with the crude oil along with the pumping of the crude oil, so that the pumping efficiency is reduced, and the yield is influenced. The traditional method for controlling the casing pressure is to install devices such as a pressure relief valve on a well, but the traditional control device needs to judge the casing pressure according to manual experience and has the defects of operational randomness, low automation degree and the like. Secondly, install the gas anchor in the pump suction mouth department in pit and carry out oil-gas separation, but oil-gas separation effect is limited. Aiming at the defects of the traditional control device and under the condition that the influence factor of the pump filling is not full caused by the gas, the relation between the pressure in the oil well and the liquid production amount is researched, the mathematical model is improved according to the pressure gradient of the oil well to determine the reasonable casing pressure, and meanwhile, the designed control system stabilizes the casing pressure of the oil well within the reasonable pressure range, so that the purpose of improving the pump efficiency and stabilizing the liquid production amount of the oil well is achieved. The main achievements are as follows: (1) and researching the principle of the relation between reasonable casing pressure and stable yield and establishing a reasonable casing pressure calculation model. According to the oil extraction process and the sleeve control pressure regulating method of the oil field, the change process of the pressure in the shaft in the process of controlling the sleeve pressure is analyzed in detail, and the internal mechanism of sleeve pressure formation and the affected factors are researched. Compared with the existing method for realizing stable yield by additionally installing an air anchor, preventing pump leakage, a ground parameter adjustment method and the like, the method has the advantages that the working fluid level and the sinking degree are changed by controlling the casing pressure, and the scheme for improving the pump filling coefficient and stabilizing the yield is provided. And establishing a dynamic equation model for calculating reasonable casing pressure, obtaining a functional relation between the liquid yield and the casing pressure, the gas-liquid ratio, the pump efficiency and the like according to historical production data of the oil field and by combining multiple linear regression theory analysis, obtaining a calculation formula of the reasonable casing pressure and the liquid yield, and taking the calculation formula as a basis and a criterion for judging whether the casing pressure is reasonable. The calculation model has the advantages that the oil well pressure subsection physical model is adopted, and meanwhile, historical production data are combined for analysis, so that the calculation result is more accurate and reasonable, and the effect is obvious. (2) And designing and completing a casing pressure control system for stabilizing the oil well yield. A set of casing pressure control system for stabilizing the oil well output is designed by researching the traditional casing pressure control device and method. Compared with the traditional control devices such as a constant pressure valve and a pressure release valve, the system has the advantages that reasonable sleeve pressure is calculated by software, the valve is not required to be manually adjusted, and the system is more automatic. The system consists of an upper computer pressure calculation software system, a pressure sensor, a processing circuit, a signal transmission circuit, a control circuit, an electromagnetic valve and the like. The pressure sensor and the processing circuit collect actual casing pressure values, the upper computer software system calculates reasonable casing pressure of the oil well, the control unit obtains the reasonable casing pressure values through the signal transmission circuit, and outputs control signals to drive the valve to act according to the control strategy, so that the actual pressure values of the oil well are ensured to be stabilized within the calculated reasonable casing pressure range, the liquid production amount of the oil well is stabilized, and impact on stratum energy caused by uneven deflation can be avoided in the system pressure control process. (3) The pressure calculation software system was studied and implemented. The system mainly comprises a pressure calculation module, a system main interface, a data interaction interface, a data transmission interface and other functional modules, wherein the MATLAB writes a pressure calculation model program, compiles and generates a dynamic link library file, and the pressure calculation module directly calls the file to calculate when in operation. The innovation point of the software system is to provide a manual data input interface, and a field engineer can judge reasonable casing pressure values according to experience and input through the interface so as to control casing pressure. And (3) verifying the accuracy of the pressure calculation software system, and displaying the result: the reasonable sleeve pressure value obtained by the calculation software is accurate, the actual production requirement is met, and the relative error between the calculated liquid yield and the actual liquid yield is within 5%. (5) And (5) performing system test to verify that the system meets design indexes and requirements. After the system design is completed, the system is subjected to software and hardware joint test, and whether the system works normally or not is verified. The control system is subjected to a deflation test and a pressure stabilizing test, and the actual test shows that: the control is quick and accurate, the voltage stabilizing capability is strong, and the system meets the design index and the requirement. Compared with the traditional mechanical or spring casing pressure control device, the system overcomes the defect of manual operation, has high automation and intelligent degree, and can achieve the aim of improving the pump efficiency and stabilizing the oil well yield.
From the above, the above-mentioned scholars have studied the relation between the casing pressure and the liquid production amount in theory, and have certain defects for guiding production on site.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining the casing gas release pressure of an oil well, which can solve the problem of low casing pressure efficiency. The specific technical scheme is as follows:
in one aspect, an embodiment of the present application provides a method for determining a casing gas release pressure of an oil well, the method comprising:
determining parameters of a casing gas-discharging oil well, and establishing a functional expression Y=a+bX of a regression equation, wherein the parameters comprise liquid production amount and casing pressure;
wherein Y represents the liquid production amount, X represents the casing pressure, a represents a first regression coefficient, and b represents a second regression coefficient;
collecting a plurality of sample casing pressures of a sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures;
determining the first regression coefficient and the second regression coefficient by the following equation (1);
formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Indicating the i-th sample liquid yield;
substituting the first regression coefficient and the second regression coefficient into the function expression to obtain the regression equation;
performing correlation coefficient check, first saliency check and second saliency check on the regression equation by the following formulas (2), (3) and (4), respectively;
formula (2):
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid yield, n represents the total sample amount, t b Representing a first significant coefficient, F representing a second significant coefficient;
and determining a target casing pressure of a target well based on the regression equation when the correlation coefficient test, the first significance test, and the second significance test pass.
In one possible implementation, the determining the target casing pressure of the target well based on the regression equation includes:
obtaining a target liquid yield required to be achieved by a target oil well;
and inputting the target liquid yield into the regression equation to obtain the target casing pressure.
In another possible implementation manner, before the determining the first regression coefficient and the second regression coefficient by the following formula (1) and obtaining the regression equation, the method further includes:
determining an average value of the plurality of sample sleeve pressures to obtain the average sleeve pressure;
and determining the average value of the liquid yields of the plurality of samples to obtain the average liquid yield.
In another possible implementation manner, before the correlation coefficient check, the first saliency check, and the second saliency check are performed on the regression equation by the following formulas (2), (3), and (4), respectively, the method further includes:
and inputting the pressure of each sample sleeve into the regression equation to obtain the predicted liquid yield corresponding to the pressure of the sample sleeve.
In another possible implementation, the total sample amount is 30.
In another possible implementation, the regression equation is: y= -0.3479+12.3883x.
In another possible implementation, the method further includes:
when the correlation coefficient is greater than 0.361, the correlation coefficient is determined to pass the test.
In another possible implementation, the method further includes:
when the first saliency coefficient is greater than 2.0484, determining that the first saliency check passes.
In another possible implementation, the method further includes:
when the second saliency coefficient is greater than 4.2, determining that the second saliency test passes.
In another aspect, an embodiment of the present application provides an apparatus for determining a casing gas release pressure of an oil well, the apparatus comprising:
the first determining module is used for determining parameters of the casing gas-discharging oil well, and establishing a functional expression Y=a+bX of a regression equation, wherein the parameters comprise liquid production amount and casing pressure;
wherein Y represents the liquid production amount, X represents the casing pressure, a represents a first regression coefficient, and b represents a second regression coefficient;
the collecting module is used for collecting a plurality of sample casing pressures of the sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures;
a second determining module configured to determine the first regression coefficient and the second regression coefficient by the following formula (1);
formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Indicating the i-th sample liquid yield;
the substituting module is used for substituting the first regression coefficient and the second regression coefficient into the function expression to obtain the regression equation;
the checking module is used for checking the correlation coefficient, the first saliency and the second saliency of the regression equation through the following formulas (2), (3) and (4);
formula (2):
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid yield, n represents the total sample amount, t b Representing a first significant coefficient, F representing a second significant coefficient;
a third determination module for determining a target casing pressure for a target well based on the regression equation when the correlation coefficient test, the first significance test, and the second significance test pass.
In one possible implementation manner, the third determining module is configured to obtain a target liquid production amount required to be achieved by the target oil well; and inputting the target liquid yield into the regression equation to obtain the target casing pressure.
In another possible implementation, the apparatus further includes:
a fourth determining module, configured to determine an average value of the plurality of sample casing pressures, to obtain the average casing pressure; and determining the average value of the liquid yields of the plurality of samples to obtain the average liquid yield.
In another possible implementation, the apparatus further includes:
and the input module is used for inputting the pressure of each sample sleeve into the regression equation to obtain the predicted liquid production amount corresponding to the pressure of the sample sleeve.
In another possible implementation, the total sample amount is 30.
In another possible implementation, the regression equation is: y= -0.3479+12.3883x.
In another possible implementation, the apparatus further includes:
and a fifth determining module, configured to determine that the correlation coefficient passes the test when the correlation coefficient is greater than 0.361.
In another possible implementation, the apparatus further includes:
a sixth determination module is configured to determine that the first saliency test passes when the first saliency coefficient is greater than 2.0484.
In another possible implementation, the apparatus further includes:
a seventh determining module configured to determine that the second saliency test passes when the second saliency coefficient is greater than 4.2.
The technical scheme provided by the embodiment of the application has the beneficial effects that:
the embodiment of the application provides a method for determining the gas release pressure of an oil well casing, which is characterized in that model training is carried out through sample casing pressure and sample liquid production amount to obtain a regression equation, and the regression equation learns the relation between the casing pressure and the liquid production amount in the training process, so that the target casing pressure corresponding to the target liquid production amount can be directly determined by means of the regression equation, thereby shortening the time for determining the casing pressure and improving the efficiency for determining the casing pressure.
Drawings
FIG. 1 is a flow chart of a method for determining the casing discharge pressure of an oil well provided by an embodiment of the present application;
FIG. 2 is a block diagram of an apparatus for determining the casing discharge pressure of an oil well according to an embodiment of the present application.
Detailed Description
In order to make the technical scheme and advantages of the present application more clear, the following further describes the embodiments of the present application in detail.
The embodiment of the application provides a method for determining the deflation pressure of an oil well casing, taking an execution main body as a computer device for illustration, referring to fig. 1, the method comprises the following steps:
step 101: the computer equipment determines parameters of the casing gas-discharging oil well and establishes a functional expression of a regression equation.
Parameters of the casing-bleeds well include fluid production and casing pressure.
In this step, the functional expression can be expressed as: y=a+bx.
Wherein Y represents the liquid production amount, X represents the casing pressure, a represents the first regression coefficient, and b represents the second regression coefficient.
It should be noted that the computer device may be a desktop computer, a notebook computer, a mobile phone, a tablet computer, or a server. In the embodiment of the present application, this is not particularly limited.
Step 102: the computer equipment collects a plurality of sample casing pressures of the sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures.
In this step, a sample casing pressure corresponds to a sample fluid production, and the sample casing pressure and the sample fluid production are all data of the same oil well.
In the embodiment of the present application, the manner in which the computer apparatus obtains the sample casing pressure and the sample liquid production amount is not particularly limited. For example, the computer device may be connected to a pressure sensor for measuring casing pressure and a level gauge for measuring well fluid production, and the computer device may obtain a sample casing pressure measured by the pressure sensor and a sample fluid production corresponding to the sample casing pressure measured by the level gauge. For another example, the computer device may obtain the sample casing pressure and its corresponding sample fluid production volume entered by the relevant technician.
The total sample amount may be set and changed as needed, and in the embodiment of the present application, this is not particularly limited. For example, the total sample amount may be 30, 50 or 100. When the total sample amount is 30, the computer device obtains 30 sample casing pressures and 30 sample liquid yields corresponding to the 30 sample casing pressures, and in the embodiment of the present application, the total sample amount is taken as 30 for illustration. Wherein the sample sleeve pressure can be X 1 、X 2 …X i …X n The liquid yield of the sample can be expressed by Y 1 、Y 2 …Y i …Y n Where i is a sample number and n is a total sample, and specific values can be seen in table 1.
TABLE 1 sample casing pressure and sample fluid production corresponding thereto
Step 103: the computer equipment determines the average value of the plurality of sample casing pressures to obtain the average casing pressure; and determining the average value of the liquid production amounts of the plurality of samples to obtain the average liquid production amount.
In this step, the average casing pressure may be usedIt means that the average liquid production can be used +.>And (3) representing.
Then
Step 104: the computer device determines a first regression coefficient and a second regression coefficient by equation (1).
Formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Represents the liquid yield of the ith sample.
For the data in Table 1, according to this formula, the size of b was determined to be 12.3883 and the size of a was determined to be-0.3479.
Step 105: the computer equipment substitutes the first regression coefficient and the second regression coefficient into the function expression to obtain a regression equation.
For the data in table 1, substituting a, b into the functional expression, respectively, yields the regression equation as: y= -0.3479+12.3883x.
In the embodiment of the present application, the manner of establishing the functional expression of the regression equation for the computer device is not particularly limited. In one possible implementation, the computer device may create a scatter plot from the data in table 1 and a functional expression from the relationship of sample casing pressure and sample fluid production in the scatter plot. For example, a linear regression equation is established when the relation between the pressure of the sample sleeve and the liquid production amount of the sample in the scatter diagram is expressed as a linear relation; and establishing a curve regression equation when the relation between the pressure of the sample sleeve and the liquid production amount of the sample in the scatter diagram is expressed as a curve relation.
Step 106: the computer equipment inputs the pressure of each sample sleeve and the corresponding sample liquid yield into a regression equation to obtain the predicted liquid yield corresponding to the pressure of the sample sleeve.
In this step, the liquid production amount can be predicted by Y' i Represented by Y' i ＝-0.3479+12.3883X。
For the data in table 1, each sample casing pressure is taken into the regression equation obtained in step 105, and the predicted liquid production amount corresponding to the sample casing pressure is obtained, and the specific data is shown in table 2.
TABLE 2 sample casing pressure, sample fluid production, predicted fluid production and related data
Step 107: the computer apparatus performs correlation coefficient check, first saliency check, and second saliency check on the regression equation by the following formulas (2), (3), and (4), respectively.
Formula (2):
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid production amount, t b Representing a first significant coefficient and F representing a second significant coefficient.
Based on the data in tables 1 and 2, the correlation coefficient R was 0.9477 and the first significance coefficient t was obtained by the above formulas (2), (3) and (4), respectively b 15.7232, the second significant coefficient F is 247.1493.
In one possible implementation, the correlation coefficient has a threshold of 0.361 when the degree of freedom n-2 is 28 and the significance level α is 0.05. When the correlation coefficient obtained according to the formula (2) is greater than 0.361, the computer device determines that the correlation coefficient test passes.
In one possible implementation, the critical value of the first saliency coefficient is 2.0484 when the degree of freedom n-2 is 28 and the saliency level α is 0.05. When the first saliency coefficient obtained according to formula (3) is greater than 2.0484, the computer device determines that the first saliency coefficient test passes.
In one possible implementation, the critical value of the second saliency coefficient is 4.2 when the degree of freedom n-2 is 28 and the saliency level α is 0.05. When the second significant coefficient obtained according to formula (4) is greater than 4.2, the computer device determines that the second significant coefficient passes the test.
When the correlation coefficient test, the first significant coefficient test, and the second significant coefficient test are all passed, the computer device executes step 108. When any one of the tests fails, it is indicated that the relationship between the casing pressure and the liquid production volume does not satisfy the linear relationship, and the computer device may reestablish a regression equation according to the relationship between the casing pressure and the liquid production volume, where the regression equation may be a parabolic equation or an exponential equation, and in the embodiment of the present application, the relationship is not specifically limited. The computer device performs a test based on the reconstructed regression equation until the test passes to obtain the regression equation.
Step 108: when the correlation coefficient test, the first significance test, and the second significance test pass, the computer device determines a target casing pressure for the target well based on the regression equation.
In the step, when the correlation coefficient test, the first significance coefficient test and the second significance coefficient test are all passed, the computer equipment acquires the target liquid production amount required to be achieved by the target oil well; and inputting the target liquid yield into a regression equation to obtain the target casing pressure.
The target liquid production amount is the liquid production amount achieved by the target oil well according to the production requirement. The target liquid production amounts required to be achieved by different oil wells are different.
In this step, the computer device may obtain the target liquid production amount by any means, which is not particularly limited in the embodiment of the present application. For example, the computer device may obtain a target liquid production amount stored in a database, or the computer device may obtain a target liquid production amount input by a user.
After the computer equipment obtains the target liquid yield, the target liquid yield can be directly input into a regression equation to obtain the target casing pressure. Compared with the prior art that related personnel are required to rely on working experience to carry out multiple attempts, the method provided by the embodiment of the application can rapidly determine the target casing pressure, and the efficiency of determining the target casing pressure is improved.
In one possible implementation, the computer device may directly adjust the current casing pressure to the target casing pressure after the target casing pressure is obtained.
In another possible implementation, the computer device may also determine a pressure float value first, determine a pressure variation range based on the pressure float value and the target casing pressure, and control the current casing pressure within the pressure variation range.
For example, the target casing pressure is 1MPa, and the computer device may directly adjust the current casing pressure to 1MPa; alternatively, the computer device may determine the pressure floating value, for example, 0.2, and then the pressure change range is 0.8-1.2 MPa, and the computer device controls the current casing pressure to be in the range of 0.8-1.2 MPa. The pressure floating value may be set and changed as needed, and in the embodiment of the present application, this is not particularly limited.
The embodiment of the application provides a method for determining the gas release pressure of an oil well casing, which is characterized in that model training is carried out through sample casing pressure and sample liquid production amount to obtain a regression equation, and the regression equation learns the relation between the casing pressure and the liquid production amount in the training process, so that the target casing pressure corresponding to the target liquid production amount can be directly determined by means of the regression equation, thereby shortening the time for determining the casing pressure and improving the efficiency for determining the casing pressure.
The technical scheme of the application will be described in detail through specific examples.
Application example 1
The oil well with the number of West 35-9-2 has a stroke of 4.2m, a stroke frequency of 3.1 times/min and a target liquid yield of 14m 3 . Inputting the pressure into a regression equation Y= -0.3479+12.3883X to obtain the target casing pressure of 1.15MPa. In field application, the pressure change range can be set according to the target casing pressure, and the casing pressure is controlled within the range of 0.9-1.3 MPa, so that the production requirement is met.
Application example 2
The oil well with the number of Xi 1602 has a stroke of 6m and a stroke frequency of 2.7 times/min, and the target liquid yield is 20m 3 . Inputting the pressure into a regression equation Y= -0.3479+12.3883X to obtain the target casing pressure of 1.64MPa. In field application, the pressure change range can be set according to the target casing pressure, and the casing pressure is controlled within the range of 1.4-1.8 MPa, so that the production requirement is met.
According to the method for determining the casing gas release pressure of the oil well, provided by the embodiment of the application, a mathematical model is established according to different oil well production conditions, and the casing pressure is determined according to the model, so that the defect that a field technician determines the casing pressure empirically is overcome. The method has been applied on site for more than 100 times, the success rate is 100%, and the method is largeGreatly improves the liquid yield of the oil well, and improves the average liquid yield of a single well by 1.2-2.0 m 3 。
The embodiment of the application provides a device for determining the deflation pressure of an oil well casing, and referring to fig. 2, the device comprises:
a first determining module 201, configured to determine parameters of the casing gas-discharging oil well, and establish a functional expression y=a+bx of a regression equation, where the parameters include a liquid production amount and a casing pressure;
wherein Y represents liquid production amount, X represents casing pressure, a represents a first regression coefficient, and b represents a second regression coefficient;
the collection module 202 is configured to collect a plurality of sample casing pressures of the sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures;
a second determining module 203, configured to determine a first regression coefficient and a second regression coefficient according to the following formula (1);
formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Indicating the i-th sample liquid yield;
the substitution module 204 is configured to substitute the first regression coefficient and the second regression coefficient into a functional expression, so as to obtain a regression equation;
a checking module 205, configured to perform correlation coefficient check, first saliency check, and second saliency check on the regression equation according to the following formulas (2), (3), and (4), respectively;
formula (2):/>
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid yield, n represents the total sample amount, t b Representing a first significant coefficient, F representing a second significant coefficient;
a third determination module 206 is configured to determine a target casing pressure for the target well based on the regression equation when the correlation coefficient test, the first significance test, and the second significance test pass.
In one possible implementation, a third determination module 206 is configured to obtain a target fluid production amount required to be achieved by the target well; and inputting the target liquid yield into a regression equation to obtain the target casing pressure.
In another possible implementation, the apparatus further includes:
a fourth determining module, configured to determine an average value of the plurality of sample casing pressures, to obtain an average casing pressure; and determining the average value of the liquid production amounts of the plurality of samples to obtain the average liquid production amount.
In another possible implementation, the apparatus further includes:
and the input module is used for inputting the pressure of each sample sleeve into a regression equation to obtain the predicted liquid production amount corresponding to the pressure of the sample sleeve.
In another possible implementation, the total sample amount is 30.
In another possible implementation, the regression equation is: y= -0.3479+12.3883x.
In another possible implementation, the apparatus further includes:
and a fifth determining module, configured to determine that the correlation coefficient passes the test when the correlation coefficient is greater than 0.361.
In another possible implementation, the apparatus further includes:
a sixth determination module for determining that the first saliency test passed when the first saliency coefficient is greater than 2.0484.
In another possible implementation, the apparatus further includes:
and a seventh determining module, configured to determine that the second saliency coefficient passes when the second saliency coefficient is greater than 4.2.
The embodiment of the application provides a determining device for the gas release pressure of an oil well casing, which is used for model training through the sample casing pressure and the sample liquid yield to obtain a regression equation.
The foregoing description is only for the convenience of those skilled in the art to understand the technical solution of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of determining the casing discharge pressure of an oil well, the method comprising:
determining parameters of a casing gas-discharging oil well, and establishing a functional expression Y=a+bX of a regression equation, wherein the parameters comprise liquid production amount and casing pressure;
wherein Y represents the liquid production amount, X represents the casing pressure, a represents a first regression coefficient, and b represents a second regression coefficient;
collecting a plurality of sample casing pressures of a sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures;
determining the first regression coefficient and the second regression coefficient by the following equation (1);
formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Indicating the i-th sample liquid yield;
substituting the first regression coefficient and the second regression coefficient into the function expression to obtain the regression equation;
performing correlation coefficient check, first saliency check and second saliency check on the regression equation by the following formulas (2), (3) and (4), respectively;
formula (2):
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid yield, n represents the total sample amount, t b Representing a first significant coefficient, F representing a second significant coefficient;
and determining a target casing pressure of a target well based on the regression equation when the correlation coefficient test, the first significance test, and the second significance test pass.
2. The method of claim 1, wherein the determining the target casing pressure for the target well based on the regression equation comprises:
obtaining a target liquid yield required to be achieved by a target oil well;
and inputting the target liquid yield into the regression equation to obtain the target casing pressure.
3. The method of claim 1, wherein before determining the first regression coefficient and the second regression coefficient by the following equation (1) to obtain the regression equation, the method further comprises:
determining an average value of the plurality of sample sleeve pressures to obtain the average sleeve pressure;
and determining the average value of the liquid yields of the plurality of samples to obtain the average liquid yield.
4. The method of claim 1, wherein before performing the correlation coefficient check, the first saliency check, and the second saliency check on the regression equation by the following equations (2), (3), and (4), respectively, the method further comprises:
and inputting the pressure of each sample sleeve into the regression equation to obtain the predicted liquid yield corresponding to the pressure of the sample sleeve.
5. The method of claim 1, wherein the total sample amount is 30.
6. The method of claim 5, wherein the regression equation is: y= -0.3479+12.3883x.
7. The method according to claim 1, wherein the method further comprises:
when the correlation coefficient is greater than 0.361, the correlation coefficient is determined to pass the test.
8. The method according to claim 1, wherein the method further comprises:
when the first saliency coefficient is greater than 2.0484, determining that the first saliency check passes.
9. The method according to claim 1, wherein the method further comprises:
when the second saliency coefficient is greater than 4.2, determining that the second saliency test passes.
10. A device for determining the casing discharge pressure of an oil well, said device comprising:
the first determining module is used for determining parameters of the casing gas-discharging oil well, and establishing a functional expression Y=a+bX of a regression equation, wherein the parameters comprise liquid production amount and casing pressure;
wherein Y represents the liquid production amount, X represents the casing pressure, a represents a first regression coefficient, and b represents a second regression coefficient;
the collecting module is used for collecting a plurality of sample casing pressures of the sample oil well and a plurality of sample liquid production amounts corresponding to the plurality of sample casing pressures;
a second determining module configured to determine the first regression coefficient and the second regression coefficient by the following formula (1);
formula (1):
wherein ,mean casing pressure>Represents average liquid production amount, i represents sample number, X i Represents the ith sample cell pressure, Y i Indicating the i-th sample liquid yield;
the substituting module is used for substituting the first regression coefficient and the second regression coefficient into the function expression to obtain the regression equation;
the checking module is used for checking the correlation coefficient, the first saliency and the second saliency of the regression equation through the following formulas (2), (3) and (4);
formula (2):
equation (3):
equation (4):
wherein R represents a correlation coefficient, Y' i Represents the predicted liquid yield, n represents the total sample amount, t b Representing a first significant coefficient, F representing a second significant coefficient;
a third determination module for determining a target casing pressure for a target well based on the regression equation when the correlation coefficient test, the first significance test, and the second significance test pass.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011220579.4A CN112253102B (en) | 2020-11-05 | 2020-11-05 | Method and device for determining oil well casing gas release pressure |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011220579.4A CN112253102B (en) | 2020-11-05 | 2020-11-05 | Method and device for determining oil well casing gas release pressure |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112253102A CN112253102A (en) | 2021-01-22 |
| CN112253102B true CN112253102B (en) | 2023-09-26 |
Family
ID=74268144
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011220579.4A Active CN112253102B (en) | 2020-11-05 | 2020-11-05 | Method and device for determining oil well casing gas release pressure |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112253102B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015143626A1 (en) * | 2014-03-25 | 2015-10-01 | 中国石油天然气股份有限公司 | Two-flow well test analysis method and system on basis of indicator diagram |
| CN106777628A (en) * | 2016-06-29 | 2017-05-31 | 中国石油大学(华东) | Consider the oil reservoir injectivity and productivity plate method for drafting of non-Darcy flow |
| CN109271747A (en) * | 2018-11-08 | 2019-01-25 | 中国石油天然气股份有限公司 | Determine the approximating method of 38 millimeters of oil well outputs and wellhead back pressure of oil well pump diameter |
| CN110107275A (en) * | 2018-01-30 | 2019-08-09 | 中国石油天然气股份有限公司 | A kind of screening technique of high energy consumption rod-pumped well |
| CN110295889A (en) * | 2019-05-30 | 2019-10-01 | 中国石油天然气股份有限公司 | Determine the approximating method of 44 millimeters of oil well outputs and wellhead back pressure of oil well pump diameter |
| CN110965970A (en) * | 2018-09-29 | 2020-04-07 | 北京国双科技有限公司 | Method and device for determining correlation between water injection well and oil production well |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0524134D0 (en) * | 2005-11-26 | 2006-01-04 | Univ Edinburgh | Improvements in and relating to hydrocarbon recovery from a hydrocarbon reservoir |
| CN104820873B (en) * | 2015-05-13 | 2017-12-26 | 中国环境科学研究院 | A kind of acute reference prediction method of fresh water based on metal quantitative structure activity relationship |
-
2020
- 2020-11-05 CN CN202011220579.4A patent/CN112253102B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015143626A1 (en) * | 2014-03-25 | 2015-10-01 | 中国石油天然气股份有限公司 | Two-flow well test analysis method and system on basis of indicator diagram |
| CN106777628A (en) * | 2016-06-29 | 2017-05-31 | 中国石油大学(华东) | Consider the oil reservoir injectivity and productivity plate method for drafting of non-Darcy flow |
| CN110107275A (en) * | 2018-01-30 | 2019-08-09 | 中国石油天然气股份有限公司 | A kind of screening technique of high energy consumption rod-pumped well |
| CN110965970A (en) * | 2018-09-29 | 2020-04-07 | 北京国双科技有限公司 | Method and device for determining correlation between water injection well and oil production well |
| CN109271747A (en) * | 2018-11-08 | 2019-01-25 | 中国石油天然气股份有限公司 | Determine the approximating method of 38 millimeters of oil well outputs and wellhead back pressure of oil well pump diameter |
| CN110295889A (en) * | 2019-05-30 | 2019-10-01 | 中国石油天然气股份有限公司 | Determine the approximating method of 44 millimeters of oil well outputs and wellhead back pressure of oil well pump diameter |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112253102A (en) | 2021-01-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107506948B (en) | Shale oil gas comprehensive yield analysis method based on dynamic drainage volume | |
| CN106761681B (en) | Electric pump well fault real-time diagnosis system and method based on time sequence data analysis | |
| CN111287740B (en) | Abnormal high-pressure reservoir dynamic reserve calculation method based on true strain | |
| CN108894777B (en) | Method for determining physical properties and fracture characteristic parameters of reservoir of split-layer fractured multi-layer commingled production hydrocarbon reservoir | |
| CN113338904B (en) | Offshore oil well productivity evaluation method | |
| CN104453981B (en) | A kind of colliery minery coal bed gas well parameter monitoring system and method | |
| US11905812B2 (en) | Intra-layer reinforcement method, and consolidation and reconstruction simulation experiment system and evaluation method for gas hydrate formation | |
| CN104405374A (en) | Method for measuring stress sensitivity of tight gas reservoir | |
| CN109958431A (en) | A method of oil well daily fluid production rate is calculated based on inflow performance relationship curve | |
| CN108222909B (en) | Shale gas well repeated fracturing well selection evaluation method | |
| CN112253102B (en) | Method and device for determining oil well casing gas release pressure | |
| CN109184661B (en) | Monitoring method and system for identifying high-yield liquid position of bottom water reservoir horizontal well | |
| CN113027387B (en) | Oil well interval pumping control system and method | |
| CN107939367B (en) | A kind of pressure break water horse power determines method | |
| US11773714B1 (en) | Experimental method for determining flow patterns in vertical wellbore of gas wells at high-pressure conditions | |
| CN115045644B (en) | Method for rapidly predicting shale gas well fracturing fluid return displacement based on production data | |
| CN111271049B (en) | Method for identifying filling degree of sucker rod pumping well | |
| CN115977586B (en) | Novel method for evaluating productivity of offshore gas well | |
| CN204877437U (en) | Device based on non - oil pumping motor -pumped well liquid measure is measured on line to differential pressure method | |
| CN110633848A (en) | Prediction method and device for steady production time of coal-bed gas well | |
| CN111305806A (en) | Method and device for analyzing flow conductivity of self-supporting fracture | |
| CN212656816U (en) | Continuous measuring device for liquid production capacity of wellhead of oil pumping well | |
| CN111008775B (en) | Simplified calculation method for useful work based on different structures of mining field | |
| CN113464123A (en) | Rapid water finding method and tubular column for coiled tubing of high-pressure water outlet horizontal well | |
| CN109630100B (en) | Automatic coal seam permeability testing device and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |