CN109271747B - Fitting method for determining oil well yield and wellhead back pressure of oil well with diameter of 38mm - Google Patents
Fitting method for determining oil well yield and wellhead back pressure of oil well with diameter of 38mm Download PDFInfo
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Abstract
The invention relates to the technical field of oil extraction in the petroleum industry, in particular to a fitting method and a fitting device for determining the yield of an oil well with the diameter of an oil well being 38mm and the back pressure of a wellhead, and a determining method and a determining device for the back pressure of the wellhead. The fitting method comprises the steps of setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure, wherein a regression constant and a regression coefficient of the regression equation are to be determined; obtaining a regression constant and a regression coefficient of a regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir; and establishing a fitting model between the oil well yield and the wellhead back pressure. The fitting method comprises the steps of setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure according to the relation between the oil well yield and the wellhead back pressure, collecting the oil well yield value and the wellhead back pressure value of the oil reservoir with the same oil-containing structure, obtaining a regression coefficient and a regression constant of the regression equation, obtaining a fitting model between the oil well yield and the wellhead back pressure, and conveniently analyzing and managing the oil well.
Description
Technical Field
The invention relates to the technical field of oil extraction in the petroleum industry, in particular to a fitting method and a fitting device for determining the yield of an oil well with the diameter of an oil well being 38mm and the back pressure of a wellhead, and a determining method and a determining device for the back pressure of the wellhead.
Background
In the oil production process of an oil well, a certain back pressure can be generated at the wellhead of the oil well, the yield of the oil well can be influenced by the rise of the wellhead back pressure, and according to GB 50350-2005 oil and gas gathering and transportation design specifications, when the oil well is designed, the allowable back pressure of the oil well is as follows: when the mechanical oil production well of the low-yield oil field uses a pipeline for gathering and transportation, the well head back pressure can be 1.0-2.5 MPa.
The oil has high viscosity and high wax content, and the wax in the oil is separated out and attached to the pipe wall of an oil pipeline, so that the flowing of the oil is hindered, the back pressure is increased, and the oil recovery yield of an oil well is reduced. Therefore, in the field oil production process, the yield of the oil well is ensured, and meanwhile, the wellhead back pressure is ensured not to exceed the maximum allowable value of the design specification, so that the problem to be solved by technical personnel is urgently solved.
At present, in the oil extraction process, the oil well yield and the wellhead back pressure need to be measured respectively, the operation is complex, and in addition, the wellhead back pressure value is constantly changed in the flowing process of oil, so that technical personnel can not give consideration to the determination of the oil well yield and the wellhead back pressure at the same time.
Disclosure of Invention
In view of this, the embodiment of the present invention provides a fitting method for determining the yield of an oil well with an oil well diameter of 38mm and the back pressure of a wellhead, so as to ensure that the back pressure of the wellhead is within an allowable range of a design specification while ensuring the yield of the oil well.
Specifically, the embodiment of the invention comprises the following technical scheme:
a fitting method for determining the production of an oil well with a 38mm diameter of an oil well and the back pressure of a wellhead, the fitting method comprising:
setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure, wherein the regression constant and the regression coefficient of the regression equation are to be determined;
obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir;
and establishing a fitting model between the oil well yield and the wellhead back pressure.
Optionally, the fitting method further comprises:
checking the reasonableness of the regression equation prior to said establishing a fitted model between the well production and wellhead back pressure.
Optionally, said checking the reasonableness of said regression equation comprises:
checking a correlation coefficient of the regression equation;
checking the significance of the regression coefficients;
checking the significance of the regression equation;
and when the correlation coefficient, the significance of the regression coefficient and the significance of the regression equation are tested, the regression equation has rationality, otherwise, the samples are reselected to establish the regression equation.
Optionally, wherein said checking the correlation coefficients of said regression equation comprises:
calculating a correlation coefficient of the regression equation;
and judging whether the correlation coefficient is larger than a first critical value or not, and when the correlation coefficient is larger than the first critical value, the correlation coefficient of the regression equation passes the test.
Optionally, wherein said verifying the significance of said regression coefficients comprises:
calculating a first parameter of the regression equation;
and judging whether the first parameter of the regression equation is larger than a second critical value, and when the first parameter of the regression equation is larger than the second critical value, the first parameter of the regression equation passes the test, and the regression coefficient has significance.
Optionally, wherein said testing the significance of said regression equation comprises:
calculating a second parameter of the regression equation;
and judging whether the second parameter of the regression equation is larger than a third critical value, and when the second parameter of the regression equation is larger than the third critical value, checking the second parameter of the regression equation to establish the significance of the regression equation.
A method for determining a wellhead back pressure of an oil well pump with a diameter of 38mm, comprising the following steps:
adopting a fitting method for determining the oil well yield and the wellhead back pressure to establish a fitting model between the oil well yield and the wellhead back pressure;
and substituting the oil well yield value of the target oil well into the fitting model to obtain the wellhead back pressure of the target oil well, wherein the sample oil well with the fitting model and the target oil well are in the same oil-containing structure oil deposit.
A fitting apparatus for determining production from a 38mm diameter well and wellhead back pressure, said fitting apparatus comprising:
the setting module is used for setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure, wherein the regression constant and the regression coefficient of the regression equation are to be determined;
the first acquisition module is used for obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir;
and the model establishing module is used for establishing a fitting model between the oil well yield and the wellhead back pressure.
Optionally, the fitting device further comprises:
a verification module for verifying the reasonableness of the regression equation prior to said establishing a model of fit between the well production and the wellhead back pressure.
Optionally, the inspection module comprises:
the first checking unit is used for checking the correlation coefficient of the regression equation;
a second checking unit for checking the significance of the regression coefficient;
a third checking unit for checking the significance of the regression equation;
and when the correlation coefficient, the significance of the regression coefficient and the significance of the regression equation are tested, the regression equation has rationality, otherwise, the samples are reselected to establish the regression equation.
Optionally, the first inspection unit includes:
the first calculation unit is used for calculating a correlation coefficient of the regression equation;
and the first judgment unit is used for judging whether the correlation coefficient is larger than a first critical value or not, and when the correlation coefficient is larger than the first critical value, the correlation coefficient of the regression equation passes the test.
Optionally, the second inspection unit comprises:
the second calculation unit is used for calculating a first parameter of the regression equation;
and the second judging unit is used for judging whether the first parameter of the regression equation is larger than the second critical value or not, and when the first parameter of the regression equation is larger than the second critical value, the first parameter of the regression equation passes the test, and the regression coefficient has significance.
Optionally, the third inspection unit includes:
the third calculation unit is used for calculating a second parameter of the regression equation;
and the third judging unit is used for judging whether the second parameter of the regression equation is larger than the third critical value or not, and when the second parameter of the regression equation is larger than the third critical value, the second parameter of the regression equation passes the test, so that the significance of the regression equation is established.
An apparatus for determining a return pressure of a 38mm diameter well head of a pump, said apparatus comprising:
the fitting module is used for establishing a fitting model between the oil well yield and the wellhead back pressure by adopting a fitting device for determining the oil well yield and the wellhead back pressure;
and the determining module is used for substituting the oil well yield value of the target oil well into the model establishing module to obtain the wellhead back pressure of the target oil well, wherein the sample oil well for establishing the fitting model and the target oil well are in the same oil-containing structure oil reservoir.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
the fitting method determines the regression constant and the regression coefficient of the regression equation according to the relation between the natural logarithm of the oil well yield and the wellhead back pressure and the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir, so that a fitting model between the oil well yield and the wellhead back pressure is obtained, and the oil wells are conveniently analyzed and managed through the oil well yield and the wellhead back pressure. When using this fitting model, can obtain corresponding well head back pressure value with this fitting model of the oil well output value substitution of target oil well, and then judge whether the well head back pressure of this target oil well exceeds the highest admissible value of design standard, if the well head back pressure exceeds the highest admissible value, then the accessible reduces the viscosity of oil, and then reduces the well head back pressure for this well head back pressure value satisfies the well head back pressure scope of design standard. The fitting model of the oil well yield about the well head back pressure can be used for rapidly and directly obtaining the corresponding well head back pressure when the oil well yield is determined, the oil well yield is ensured, viscosity reduction treatment can be carried out on an oil well of which the well head back pressure exceeds the maximum allowable value of the design specification after the corresponding well head back pressure is obtained through calculation, the purpose that technical personnel can simultaneously consider the oil well yield and the well head back pressure is achieved, time is saved, and influence on oil extraction of the oil well due to the fact that the well head back pressure exceeds the maximum allowable value of the design specification can not be timely known.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below.
FIG. 1 is a flow chart of a fitting method for determining the production rate of an oil well with a diameter of 38mm and the back pressure of a wellhead according to an embodiment of the present invention;
FIG. 2 is a flowchart of one implementation of checking the rationality of the regression equation provided in an embodiment of the present invention;
FIG. 3 is a flowchart illustrating the testing of the correlation coefficients of the regression equation according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for verifying the significance of the regression coefficients of the regression equation according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for verifying the significance of a regression equation according to an embodiment of the present invention;
FIG. 6 is a flow chart of a method for determining a back pressure of a 38mm diameter well head of an oil well pump according to an embodiment of the present invention;
FIG. 7 is a block diagram of a fitting apparatus for determining the yield of an oil well with a diameter of 38mm and the back pressure of a wellhead according to a second embodiment of the present invention;
FIG. 8 is a block diagram of a verification module according to a second embodiment of the present invention;
FIG. 9 is a block diagram of a first verification unit according to a second embodiment of the present invention;
FIG. 10 is a block diagram of a second verification unit according to a second embodiment of the present invention;
FIG. 11 is a block diagram of a third verification unit according to a second embodiment of the present invention;
fig. 12 is a block diagram of a device for determining a wellhead back pressure of an oil well pump with a diameter of 38mm according to a second embodiment of the present invention.
Detailed Description
In order to make the technical solutions and advantages of the present invention clearer, the following will describe embodiments of the present invention in further detail with reference to the accompanying drawings.
The embodiment of the invention provides a fitting method for determining the yield of an oil well with the diameter of an oil well being 38mm and the back pressure of a wellhead, and referring to fig. 1, the fitting method for determining the yield of the oil well with the diameter of the oil well being 38mm and the back pressure of the wellhead comprises the following steps:
and step S1, setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure, wherein the regression constant and the regression coefficient of the regression equation are to be determined.
In the application, in the actual oil production process on site, the oil well yield and the wellhead back pressure of the same oil-containing structure oil deposit of a large number of samples are obtained, and the nonlinear relation between the oil well yield and the wellhead back pressure is obtained. The oil wells with the same oil-containing structure oil reservoirs refer to the oil wells with the same oil-containing oil reservoir structure, and the effectiveness of collected data of oil well yield and wellhead back pressure is guaranteed.
For example, in the embodiment of the present application, data of the well production rate and the corresponding wellhead back pressure of a plurality of wells of a large number of reservoirs with the same oil-bearing structure are collected, it is known that the well production rate and the corresponding wellhead back pressure have a nonlinear relationship, and the first formula Y-e is obtaineda+bxWherein, in the above formula: y-oil well yield, m3D; x is the oil well mouth back pressure, MPa; a-a regression constant; b-regression coefficient; e-natural constant, take 2.718281828.
Taking the natural base logarithm of the two sides of the first formula, a regression equation between the natural logarithm of the oil well production and the wellhead back pressure can be obtained, namely the second formula LnY is a + bx, wherein the regression constant and the regression coefficient in the regression equation are to be determined.
And step S2, obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil deposit.
In the application, the actual values of the yield of a plurality of oil wells with the same diameter of the oil pump being 38mm and the same oil-bearing structure and oil reservoir and the actual values of the corresponding wellhead back pressure are collected, and the regression coefficient b and the regression constant a of the fitting model of the oil well yield and the wellhead back pressure are obtained through the collected data, so that the regression equation of the oil well yield relative to the wellhead back pressure is obtained.
For example, in the present embodiment, Q is LnY for the convenience of calculation of the regression constant a and the regression coefficient b. Taking an oil well with the diameter of the oil pump being 38mm as an example, the actual values of the yield and the wellhead back pressure of 30 oil wells of oil reservoirs with the same oil-containing structure are collected and are shown in table 1.
TABLE 1
According to the yield value and the wellhead back pressure value of the oil wells of the 30 oil-bearing structure oil reservoirs, a regression coefficient b and a regression constant a can be calculated:
the regression equation Q is obtained 2.4256+0.0267 x.
And step S4, establishing a fitting model between the oil well yield and the wellhead back pressure.
In this application, obtain this regression equation after, can learn the relation between oil well output and the well head back pressure, conveniently manage the oil well through the output and the well head back pressure of oil well.
In the first embodiment of the present application, referring to fig. 1, in order to ensure the reasonableness of the regression equation between the natural logarithm of the oil well production and the wellhead back pressure, after step S2 and before step S4, the fitting method may further include:
step S3, the regression equation is checked for plausibility.
In the application, the correlation coefficient R, the first parameter T and the second parameter F of the regression equation need to be checked respectively, and when the degree of freedom n-2(n is the number of samples 30) and the significance level a is 0.05, and the correlation coefficient R, the first parameter T and the second parameter F of the regression equation are all larger than the corresponding critical values, the regression equation of the oil well yield with respect to the wellhead back pressure is established, otherwise, sample data needs to be selected again to establish the regression equation.
In one implementation of the first embodiment, for example, referring to fig. 2, checking the reasonableness of the regression equation may include:
in step S31, the correlation coefficient of the regression equation is checked.
For example, referring to fig. 3, in this step, verifying the correlation coefficients of the regression equation may include:
step 311, calculating the correlation coefficient of the regression equation,
step S312, determining whether the correlation coefficient of the regression equation is greater than a first threshold, when the correlation coefficient is greater than the first threshold, it indicates that the correlation coefficient passes the verification, otherwise, reselecting data to establish the regression equation.
In this embodiment, as can be seen from the correlation coefficient threshold value table described in the book "modern consulting method and practice" published by the chinese plan publisher in the first edition of 4 months in 2003, when the degree of freedom n-2(n is the number of samples) and the significance level a is 0.05, the threshold value of the correlation coefficient is 0.361, and the correlation coefficient R of the regression equation is 0.5787, which is greater than the threshold value, and indicates that the correlation coefficient R passes the test, and that the linear relationship between x and Q is established. Of course, the present application is not limited thereto, and in other embodiments, the number of samples may be changed or compared with the corresponding threshold value at other significant levels to determine whether the correlation coefficient passes the test.
In step S32, the regression coefficients of the regression equation are checked for significance.
For example, referring to fig. 4, in this step, verifying the significance of the regression coefficients may include:
step 321, calculating a first coefficient of the regression equation,
step S322, determining whether the first parameter T of the regression equation is greater than a second critical value, when the first parameter T of the regression equation is greater than the second critical value, it indicates that the first parameter T of the regression equation passes the test, and the regression coefficient has significance, otherwise, reselecting the sample to establish the regression equation.
In this embodiment, according to the distribution table of T (a/2, n-2) described in the book "modern consulting method and practice" published by the chinese plan publisher in the first edition of 4/2003, it can be seen that, when the degree of freedom n-2(n is the number of samples) and the significance level a is 0.05, the critical value of the first parameter T is 2.0484, the first parameter T of the regression equation is 2.7591, which is greater than the critical value, which indicates that the first parameter T passes the test, the linear assumption of x and Q is reasonable, and the regression coefficient of the regression equation has significance. Of course, the present application is not limited thereto, and in other embodiments, the number of samples may be changed or compared with the corresponding threshold value at other significance levels to determine whether the regression coefficient of the regression equation has significance.
Step S33, the regression equation is checked for significance.
For example, referring to fig. 5, in this step, verifying the significance of the regression equation may include:
step S331, calculating a second parameter F of the regression equation,
step S332, determining whether the second parameter F of the regression equation is greater than a third threshold, and when the second parameter F of the regression equation is greater than the third threshold, the second parameter F of the regression equation passes the test, so that the regression equation has significance.
In this embodiment, from the F distribution table of the significance F test of the regression equation described in the book "modern consulting method and practice" first edition, 4.2003, published by the chinese plan publisher, it can be seen that, when the degree of freedom n-2(n is the number of samples) and the significance level a is 0.05, the critical value of the second parameter F is 4.20, and the second parameter F of the regression equation is 4.46, which is greater than the critical value, indicating that the second parameter F passes the test, and that the linear assumption of x and Q is reasonable, the regression equation has significance. Of course, the present application is not limited thereto, and in other embodiments, the number of samples may be changed or compared with the corresponding threshold value at other significance levels to determine whether the regression equation has significance.
For the step of checking the rationality of the regression equation in the first embodiment of the present application, the present application is not limited to this, and the correlation coefficient, the significance of the regression coefficient, and the significance of the regression equation are checked, and in the checking of the rationality of the regression equation, the order of the step of checking the correlation coefficient, the significance of the regression coefficient, and the significance of the regression equation is not limited, and in other implementations of the first embodiment of the present application, the correlation coefficient, the significance of the regression coefficient, and the significance of the regression equation may also be checked in different orders.
Referring to fig. 6, in an embodiment of the present application, there is further provided a method for determining a wellhead back pressure of an oil well pump with a diameter of 38mm, including:
step S1, adopting the fitting method for determining the oil well yield and the wellhead back pressure of the oil well pump diameter of 38mm to establish a fitting model between the oil well yield and the wellhead back pressure,
and step S2, substituting the oil well yield value of the target oil well into the fitting model to obtain the wellhead back pressure of the target oil well.
Wherein the sample oil well and the target oil well which establish the fitting model are in the same oil-containing structure oil deposit. For example, when a design well determines well production and measures production during oil recovery, the production value of the target well can be substituted into the fitting model to obtain the wellhead back pressure of the target well.
For example, in one implementation of the first embodiment, the daily oil production is required to be 15m when designing the well development3And d, calculating to obtain a corresponding wellhead back pressure value of 1.06MPa by applying the regression equation, referring to GB 50350-2005 oil and gas gathering and transportation design specification, locating in a wellhead back pressure allowable range, and ensuring that the wellhead back pressure does not exceed the highest allowable value of the design specification while ensuring the oil well yield. Certainly, the present application is not limited to this, in other implementation manners of this embodiment, if the wellhead back pressure corresponding to the oil well production is greater than the maximum allowable value of the design specification, then viscosity reduction processing may be performed on the oil through chemical viscosity reduction or other reasonable manners, so that the wellhead back pressure value is within the allowable range of the design specification, and it is ensured that the wellhead back pressure does not exceed the maximum allowable value of the design specification while the oil well production is not reduced.
The second embodiment of the present invention provides a fitting apparatus for determining the yield of an oil well with a diameter of 38mm of an oil well and the back pressure of a wellhead, referring to fig. 7, the fitting apparatus includes:
the setting module 1 is used for setting a regression equation between the natural logarithm of the oil well yield and the wellhead back pressure, wherein the regression constant and the regression coefficient of the regression equation are to be determined;
the acquisition module 2 is used for obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir;
and the model establishing module 4 is used for establishing a fitting model between the oil well yield and the wellhead back pressure.
In the second embodiment of the present application, referring to fig. 7, in order to ensure the reasonability of the regression equation between the natural logarithm of the oil well production and the wellhead back pressure, before the obtaining module 2 and the model building module 4, the fitting device may further include:
and the checking module 3 is used for checking the reasonableness of the regression equation.
In the application, the correlation coefficient R, the first parameter T and the second parameter F of the regression equation need to be checked respectively, and when the degree of freedom n-2(n is the number of samples 30) and the significance level a is 0.05, and the correlation coefficient R, the first parameter T and the second parameter F of the regression equation are all larger than the corresponding critical values, the regression equation of the oil well yield with respect to the wellhead back pressure is established, otherwise, sample data needs to be selected again to establish the regression equation.
In an implementation manner of the second embodiment, for example, referring to fig. 8, the inspection module 3 may include:
a first checking unit 31 for checking the correlation coefficient of the regression equation.
Wherein, for example, referring to fig. 9, the first checking unit may comprise:
a first calculation unit 311 for calculating a correlation coefficient of the regression equation;
the first determining unit 312 is configured to determine whether a correlation coefficient of the regression equation is greater than a first threshold, and when the correlation coefficient is greater than the first threshold, the correlation coefficient is verified, otherwise, data is reselected to establish the regression equation.
A second checking unit 32 for checking the significance of the regression coefficient;
wherein, for example, referring to fig. 10, the second checking unit may comprise:
a second calculating unit 321, configured to calculate a first parameter of the regression equation;
the second determining unit 322 is configured to determine whether the first parameter of the regression equation is greater than a second adjacent value, when the first parameter of the regression equation is greater than the second threshold, it indicates that the first parameter of the regression equation passes the test, the regression coefficient has significance, otherwise, the sample is reselected to establish the sample equation.
A third checking unit 33 for checking the significance of the regression equation.
Wherein, for example, referring to fig. 11, the third inspection unit may comprise:
a third calculation unit 331 for calculating a second parameter of the regression equation;
a third determining unit 332, configured to determine whether the second parameter of the regression equation is greater than a third threshold, and when the second parameter of the regression equation is greater than the third threshold, the second parameter of the regression equation passes the test, and the regression equation has significance.
In the second embodiment of the present application, the sequence of the first inspection unit 31, the second inspection unit 32, and the third inspection unit 33 is performed in parallel in the inspection module 3, and is not limited thereto, and in the second embodiment of the present application, the first inspection unit 31, the second inspection unit 32, and the third inspection unit 33 may be performed in a different sequence.
The second embodiment further provides a device for determining the wellhead back pressure of the oil well pump with the diameter of 38mm, referring to fig. 12, the device includes:
a fitting module for establishing a fitting model between the oil well production and the wellhead back pressure by using the fitting device for determining the oil well production and the wellhead back pressure of the oil well pump with the diameter of 38mm as claimed in any one of claims 8 to 13;
and the determining module is used for substituting the oil well yield value of the target oil well into the fitting model to obtain the wellhead back pressure of the target oil well, wherein the sample oil well with the fitting model established and the target oil well are in the same oil-bearing structure oil reservoir.
The fitting apparatus of the second embodiment corresponds to the method of the first embodiment, and all modules performing functions thereof can find corresponding steps in the embodiment, so that the method for describing the first embodiment is also applicable to the second embodiment, and details and effects of the second embodiment are not described for the sake of brevity.
Those skilled in the art will appreciate that all or part of the steps and modules for implementing the above embodiments may be implemented by hardware, or may be implemented by relevant hardware instructed by programs. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.
The above description is only exemplary of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (14)
1. A fitting method for determining the production of an oil well with a diameter of 38mm of an oil well and the back pressure of a wellhead, which is characterized by comprising the following steps:
acquiring a plurality of groups of oil well yields and corresponding wellhead back pressure data of a plurality of sample oil wells of the same oil-bearing structure oil reservoir;
setting a regression equation between a natural logarithm of the well production and the wellhead back pressure when it is determined that there is a non-linear relationship between the well production and the wellhead back pressure based on the plurality of sets of well production and corresponding wellhead back pressure data;
obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of sample oil wells of the same oil-bearing structure oil reservoir;
and establishing a fitting model between the oil well yield and the wellhead back pressure.
2. The fitting method for determining the yield of an oil well with a 38mm diameter of an oil well and the back pressure of a wellhead as claimed in claim 1, wherein the fitting method further comprises:
checking the reasonableness of the regression equation prior to said establishing a fitted model between the well production and the wellhead back pressure.
3. The method of claim 2, wherein said testing said regression equation for plausibility comprises:
checking the correlation coefficient of the regression equation;
checking the significance of the regression coefficients;
checking the significance of the regression equation;
and when the correlation coefficient, the significance of the regression coefficient and the significance of the regression equation are tested, the regression equation has rationality, otherwise, the samples are reselected to establish the regression equation.
4. The method of claim 3, wherein said verifying the correlation coefficients of said regression equation comprises:
calculating a correlation coefficient of the regression equation;
and judging whether the correlation coefficient is larger than a first critical value or not, and when the correlation coefficient is larger than the first critical value, the correlation coefficient of the regression equation passes the test.
5. The method of claim 3, wherein said testing the significance of said regression coefficients comprises:
calculating a first parameter of the regression equation;
and judging whether the first parameter of the regression equation is larger than a second critical value or not, and when the first parameter T of the regression equation is larger than the second critical value, the first parameter of the regression equation passes the test, and the regression coefficient has significance.
6. The method of claim 3, wherein said verifying the significance of said regression equation comprises:
calculating a second parameter of the regression equation;
and judging whether the second parameter of the regression equation is larger than a third critical value, and when the second parameter of the regression equation is larger than the third critical value, the second parameter of the regression equation passes the test, so that the significance of the regression equation is established.
7. A method of determining wellhead back pressure, the method comprising:
establishing a fitting model between the oil well production and the wellhead back pressure by using the fitting method for determining the oil well production and the wellhead back pressure of the oil well with the oil well pump diameter of 38mm in any one of claims 1 to 6;
and substituting the oil well yield value of the target oil well into the fitting model to obtain the wellhead back pressure of the target oil well, wherein the sample oil well of which the fitting model is established and the target oil well are in the same oil-containing structure oil reservoir.
8. A fitting apparatus for determining the production of a 38mm diameter oil well and the back pressure at the wellhead, the fitting apparatus comprising:
the acquisition module is used for acquiring the output of a plurality of groups of oil wells of a plurality of sample oil wells of the same oil-bearing structure oil reservoir and corresponding wellhead back pressure data;
a setting module for setting a regression equation between a natural logarithm of the well production and a wellhead back pressure when a non-linear relationship between the well production and the wellhead back pressure is determined based on the plurality of sets of well production and corresponding wellhead back pressure data;
the acquisition module is used for obtaining a regression constant and a regression coefficient of the regression equation according to the oil well yield value and the wellhead back pressure value of a plurality of oil wells of the same oil-bearing structure oil reservoir;
and the model building module is used for building a fitting model between the oil well yield and the wellhead back pressure.
9. The fitting apparatus for determining the yield of a 38mm diameter oil well and the back pressure at the wellhead as claimed in claim 8, wherein the fitting apparatus further comprises:
a verification module for verifying the reasonableness of the regression equation prior to said establishing a model of fit between the well production and the wellhead back pressure.
10. The fitting device for determining the yield of an oil well with a diameter of 38mm of an oil well as the back pressure of a wellhead as claimed in claim 9, wherein the inspection module comprises:
the first checking unit is used for checking the correlation coefficient of the regression equation;
a second checking unit for checking the significance of the regression coefficient;
a third checking unit for checking the significance of the regression equation;
and when the correlation coefficient, the significance of the regression coefficient and the significance of the regression equation are tested, the regression equation has rationality, otherwise, the samples are reselected to establish the regression equation.
11. The fitting device for determining the yield of an oil well with a 38mm diameter of an oil well and the back pressure of a wellhead as claimed in claim 10, wherein the first inspection unit comprises:
the first calculation unit is used for calculating a correlation coefficient of the regression equation;
and the first judgment unit is used for judging whether the correlation coefficient is larger than a first critical value or not, and when the correlation coefficient is larger than the first critical value, the correlation coefficient of the regression equation passes the test.
12. The fitting device for determining the yield of an oil well with a 38mm diameter of an oil well and the back pressure of a wellhead as claimed in claim 10, wherein the second inspection unit comprises:
the second calculation unit is used for calculating a first parameter of the regression equation;
and the second judging unit is used for judging whether the first parameter of the regression equation is larger than a second critical value or not, and when the first parameter of the regression equation is larger than the second critical value, the first parameter of the regression equation passes the test, and the regression coefficient has significance.
13. The fitting device for determining the yield of an oil well with a 38mm diameter of an oil well and the back pressure of a wellhead as claimed in claim 10, wherein the third inspection unit comprises:
the third calculation unit is used for calculating a second parameter of the regression equation;
and the third judging unit is used for judging whether the second parameter of the regression equation is larger than a third critical value or not, and when the second parameter of the regression equation is larger than the third critical value, the second parameter of the regression equation passes the test, so that the significance of the regression equation is established.
14. A wellhead back pressure determination device, comprising:
a fitting module for establishing a fitting model between the oil well production and the wellhead back pressure by using the fitting device for determining the oil well production and the wellhead back pressure of the oil well pump with the diameter of 38mm as claimed in any one of claims 8 to 13;
and the determining module is used for substituting the oil well yield value of the target oil well into the fitting model to obtain the wellhead back pressure of the target oil well, wherein the sample oil well with the fitting model established and the target oil well are in the same oil-bearing structure oil reservoir.
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