Gas well productivity acquisition method, device, equipment, storage medium and program product

Abstract

The present application provides a method, device, equipment, storage medium, and program product for obtaining gas well productivity. The method includes: receiving an acquisition instruction and well test data of a target gas well; transforming the initial productivity equation of the target gas well to obtain a multivariate linear regression equation, wherein the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well, and its productivity coefficient is the coefficient to be solved in the multivariate linear regression equation; using multiple sets of measurement data in the well test data of the target gas well to solve the values ​​of the coefficients to be solved in the multivariate linear regression equation, and substituting the solved coefficient values ​​back into the initial productivity equation to obtain the productivity equation of the target gas well; and using the productivity equation to calculate and output the productivity of the target gas well. The present application obtains a productivity equation in which the dependent variable and the independent variable satisfy a linear correlation by transforming the initial productivity equation, thereby accurately obtaining the productivity of the target gas well using the productivity equation, thereby improving the accuracy of gas well productivity acquisition.

Description

Technical Field

[0001] The present application relates to the field of oil and gas mining and exploration technology, and in particular to a method, device, equipment, storage medium and program product for obtaining gas well productivity. Background Art

[0002] A gas well is a well drilled from the surface of a gas field into the gas formation for the purpose of extracting natural gas. Gas well productivity refers to the amount of gas produced at a given back pressure. Gas well productivity is a crucial basis for rationally allocating production to gas wells and evaluating the production capacity of a gas field. The reliability of the calculated results is directly related to the ability of the gas field to achieve stable production.

[0003] Under constant formation pressure conditions, testing a gas well's gas production at varying bottomhole flowing pressures (referred to as bottomhole flowing pressure or pseudo-bottomhole pressure) is called a gas well productivity test, also known as a backpressure test. Currently, a binomial productivity equation is established based on backpressure test data using pseudo-pressure productivity tests to determine the gas well's productivity. However, for gas wells whose gas production and pressure are unstable during backpressure testing, the productivity calculated using this pseudo-pressure binomial productivity equation is less accurate. Summary of the Invention

[0004] The present application provides a method, device, equipment, storage medium and program product for obtaining gas well productivity, which is used to solve the problem that the gas production and pressure in the existing backpressure testing process of gas wells are unstable, resulting in low accuracy of the gas well productivity obtained by the pseudo-pressure binomial productivity equation.

[0005] In a first aspect, the present application provides a method for obtaining gas well productivity, comprising:

[0006] receiving an acquisition instruction and the well test data of the target gas well, wherein the acquisition instruction is used to request acquisition of the production capacity of the target gas well;

[0007] Transforming the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation; the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficient in the initial productivity equation is the coefficient to be solved in the multivariate linear regression equation;

[0008] Using multiple sets of measurement data from the well test data of the target gas well, solving the coefficients to be solved in the multivariate linear regression equation, and substituting the solved coefficients into the initial productivity equation to obtain the productivity equation of the target gas well; each set of measurement data includes a well test flow rate value measured at a measurement point of the target gas well, and a pseudo-pressure value corresponding to the bottom hole flowing pressure value;

[0009] Calculating the productivity of the target gas well using the productivity equation of the target gas well;

[0010] The production capacity of the target gas well is output.

[0011] In a possible design, before transforming the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation, the method further includes:

[0012] The target gas well is determined to be a gas well with abnormal productivity acquisition, and the gas well with abnormal productivity acquisition is a gas well with unstable gas production and pressure during a backpressure well test.

[0013] In one possible design, the first preset relationship is the ratio of the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well, when the pseudo-pressure productivity well test is performed on the target gas well, to the well test flow rate value of the target gas well;

[0014] Determining that the target gas well is a gas well with abnormal productivity acquisition includes:

[0015] Using the well test data of the target gas well, obtaining the value of the first preset relationship;

[0016] Determining whether a first relationship curve formed by the value of the first preset relationship expression and the well test flow rate value in a rectangular coordinate system satisfies a linear relationship, or whether the slope of the first relationship curve is negative;

[0017] If the first relationship curve does not satisfy a linear relationship, or the slope of the first relationship curve is negative, it is determined that the target gas well is a gas well with abnormal productivity acquisition.

[0018] In one possible design, the second preset relationship is the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well when the pseudo-pressure productivity well test is performed on the target gas well;

[0019] Determining that the target gas well is a gas well with abnormal productivity acquisition includes:

[0020] Using the well test data of the target gas well, obtaining the value of the second preset relationship;

[0021] Determining whether the reciprocal of the slope of a second relationship curve formed by the value of the second preset relationship expression and the well test flow value in a logarithmic coordinate system is within a preset range;

[0022] If the inverse of the slope of the second relationship curve is not within the preset range, the target gas well is determined to be a gas well with abnormal productivity acquisition.

[0023] In one possible design, determining that the target gas well is a gas well with abnormal productivity acquisition includes:

[0024] Obtaining the reservoir thickness of the gas reservoir where the target gas well is located;

[0025] If the reservoir thickness is greater than or equal to a first preset threshold, the target gas well is determined to be a gas well with abnormal productivity acquisition.

[0026] In a second aspect, the present application provides a gas well productivity acquisition device, comprising:

[0027] A receiving module, configured to receive an acquisition instruction and the well testing data of the target gas well, wherein the acquisition instruction is used to request the production capacity of the target gas well;

[0028] A processing module is configured to transform the initial productivity equation of the target gas well to obtain a multiple linear regression equation corresponding to the initial productivity equation; solve the coefficients to be solved in the multiple linear regression equation using multiple sets of measurement data in the well test data of the target gas well, and substitute the solved coefficients into the initial productivity equation to obtain a first productivity equation for the target gas well; calculate the productivity of the target gas well using the productivity equation of the target gas well; wherein the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficients in the initial productivity equation are the coefficients to be solved in the multiple linear regression equation; each set of measurement data includes a well test flow value measured at a measurement point of the target gas well, and a bottom hole flowing pressure value;

[0029] The output module is used to output the production capacity of the target gas well.

[0030] In a third aspect, the present application provides an electronic device, comprising: a memory and a processor;

[0031] Memory is used to store computer programs;

[0032] The processor is used to implement the gas well productivity acquisition method in the first aspect and any possible design of the first aspect according to the computer program stored in the memory.

[0033] In a fourth aspect, the present application provides a readable storage medium, which stores execution instructions. When at least one processor of an electronic device executes the execution instructions, the electronic device executes the gas well productivity acquisition method in the first aspect and any possible design of the first aspect.

[0034] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which is executed by a processor to implement the gas well productivity acquisition method in the first aspect and any possible design of the first aspect.

[0035] The gas well productivity acquisition method, device, electronic device, medium and program product provided by the present application, by transforming the initial productivity equation of the target gas well into a multivariate linear regression equation, can utilize the characteristic that the dependent variable and the independent variable of the multivariate linear regression equation satisfy the linear correlation, use multiple groups of measurement data in the well test data of the target gas well, obtain the value that can make the productivity coefficient in the initial productivity equation satisfy the linear correlation, and introduce the value back into the initial productivity equation to obtain the productivity equation of the target gas well that satisfies the linear correlation. In this way, when using the productivity equation to obtain the productivity of the target gas well, even if the gas production and pressure are unstable during the back pressure test of the target gas well, the productivity of the target gas well can be accurately obtained, thereby improving the accuracy of obtaining the gas well productivity, thereby providing an accurate basis for gas field production allocation and ground engineering construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0037] Figure 1 Schematic diagram of binomial productivity curve of gas well 1 in an abnormally high-pressure gas reservoir;

[0038] Figure 2 Schematic diagram of binomial productivity curve of gas well 2 in another abnormally high-pressure gas reservoir;

[0039] Figure 3 A schematic flow chart of a method for obtaining gas well productivity provided in one embodiment of the present application;

[0040] Figure 4 A schematic diagram of the productivity of a sample gas well provided in one embodiment of the present application;

[0041] Figure 5 A schematic diagram of a productivity curve of a sample gas well provided in one embodiment of the present application;

[0042] Figure 6 The productivity curve is obtained by calculating the productivity of the sample gas well using the first productivity equation and the second productivity equation provided in one embodiment of the present application;

[0043] Figure 7 A schematic flow chart of a method for obtaining gas well productivity provided in another embodiment of the present application;

[0044] Figure 8A schematic structural diagram of a gas well productivity acquisition device provided in one embodiment of the present application;

[0045] Figure 9 A schematic diagram of the hardware structure of an electronic device provided in one embodiment of the present application.

[0046] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0048] In the prior art, based on the back pressure test data of the gas well, a binomial productivity equation is established using the pseudo-pressure productivity test to calculate the productivity of the gas well. The expression of the pseudo-pressure ψ of the gas well is shown in the following formula (1):

[0049]

[0050] Where ψ is the pseudo-pressure, μ is the viscosity of natural gas, P is the calculated pressure of the gas well, which can be the formation pressure or the flow pressure, Z is the natural gas deviation coefficient, and P0 is the original formation initial pressure of the gas well.

[0051] Based on the pseudo-pressure expression shown in formula (1) above, the expression of the binomial productivity equation established through the pseudo-pressure productivity test can be shown as the following formula (2):

[0052]

[0053] Among them, ψ R is the pseudo-pressure value of the formation pressure where the gas well is located, ψ wf is the pseudo-pressure value of the bottom hole flow pressure of the gas well, and A and B are both production capacity coefficients. g The test flow rate of the gas well is also called the gas production of the gas well (referred to as the gas well production), and the unit is 10 4 m 3 / d.

[0054] From the expression shown in the above formula (2), it can be seen that the expression of the absolute unobstructed flow rate of a single well is shown in the following formula (3):

[0055]

[0056] Among them, q AOF is the absolute open-flow capacity of a single well (also called the maximum theoretical production of a single well), ψ(Pr) is the pseudo-pressure corresponding to the formation pressure, and ψ(0.1) is the pseudo-pressure value corresponding to the atmospheric pressure.

[0057] At present, for gas wells in gas reservoirs with thick reservoir thickness, gas wells in abnormally high-pressure gas reservoirs, and gas wells in abnormally low-pressure gas reservoirs, gas production and pressure are unstable during the backpressure well test process. As a result, when performing binomial equation analysis or exponential analysis, the pseudo-pressure value of the formation pressure where the gas well is located, the pseudo-pressure value of the bottomhole flowing pressure of the gas well, and the test flow rate value of the gas well in the well test data do not satisfy the linear correlation. As a result, the coefficients of the binomial productivity equation established by the pseudo-pressure productivity well test do not satisfy the linear correlation value. Therefore, the accuracy of obtaining the productivity of the gas well using the binomial productivity equation is low.

[0058] It should be understood that the abnormally high pressure gas reservoir mentioned above has an original formation pressure coefficient greater than 1.2 or an original pressure gradient greater than 1.175 MPa / 100 m. The abnormally high pressure gas reservoir may also have characteristics other than the above characteristics, which are not limited in the embodiments of this application.

[0059] For example, Figure 1 Schematic diagram of the binomial productivity curve of gas well 1 in an abnormally high-pressure gas reservoir. Figure 2 Figure 2 is a schematic diagram of the binomial productivity curve of gas well 2 in another abnormally high-pressure gas reservoir. Figure 1 As shown, Figure 1 and Figure 2 The binomial productivity curves shown are all calculated using the binomial productivity equations corresponding to the respective gas wells. Figure 1 It can be seen that when the pseudo-pressure value of the formation pressure where the gas well is located, the pseudo-pressure value of the bottom hole flow pressure of the gas well, and the well test flow rate value of the gas well do not meet the linear correlation of the binomial equation analysis, the gas well production capacity cannot be obtained using the binomial production capacity equation, which causes the slope of the obtained binomial production capacity curve to be negative, making the accuracy of obtaining the gas well production capacity using the binomial production capacity equation low. Figure 2 It can be seen that when the pseudo-pressure value of the formation pressure where the gas well is located, the pseudo-pressure value of the bottom hole flowing pressure of the gas well, and the well test flow rate value of the gas well do not satisfy the linear correlation during exponential analysis, the binomial productivity curve formed by the productivity obtained by using the binomial productivity equation has poor linear correlation, resulting in low accuracy in obtaining the gas well productivity using the binomial productivity equation.

[0060] In summary, for gas wells with unstable gas production and pressure during the backpressure well test, the above-mentioned binomial productivity equation cannot be used to accurately obtain the gas well productivity.

[0061] To address the above issues, this application proposes a gas well productivity acquisition method, device, equipment, storage medium, and program product. These methods enable the gas well productivity equation to satisfy a linear correlation, allowing accurate calculation of the gas well productivity using this productivity equation. Even if gas production and pressure are unstable during the backpressure test, the accuracy of the gas well productivity is not affected, thus providing an accurate basis for gas field production allocation and surface engineering construction.

[0062] The method provided in this application can be applied to gas wells whose gas production and pressure are unstable during the backpressure test, as well as other gas wells, such as gas wells whose gas production and pressure are stable during the backpressure test. For ease of description in the subsequent embodiments, gas wells whose gas production and pressure are unstable during the backpressure test are referred to as gas wells with abnormal production capacity acquisition, and gas wells whose gas production and pressure are stable during the backpressure test are referred to as gas wells with normal production capacity acquisition.

[0063] The following specific embodiments are used to describe the technical solution of the present application in detail. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0064] In this application, an electronic device is used as the execution entity to execute the gas well productivity acquisition method of the following embodiments. Specifically, the execution entity can be a hardware device of the electronic device, or a software application implemented in the electronic device that implements the following embodiments, or a computer-readable storage medium installed with the software application that implements the following embodiments, or the code of the software application that implements the following embodiments.

[0065] Figure 3 This is a flow chart of a method for obtaining gas well productivity provided in one embodiment of the present application. Figure 3 As shown, with the electronic device as the execution subject, the method of this embodiment may include the following steps:

[0066] S301: Receive an acquisition instruction and well test data of a target gas well. The acquisition instruction is used to request to acquire the production capacity of the target gas well.

[0067] The well test data includes parameter values ​​for obtaining the productivity of the target gas well. The productivity of the target gas well obtained here may be, for example, a method for calculating productivity as shown in the prior art, for example, as shown in formula (2).

[0068] Taking formula (2) as an example, for example, the well test data includes the pseudo-pressure value corresponding to the formation pressure of the target gas well, the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well, and the well test flow rate value of the target gas well.

[0069] For example, the electronic device is provided with a user interface for receiving an acquisition instruction, and the user can input the acquisition instruction to the electronic device through the user interface. For example, the electronic device can send the acquisition instruction to the electronic device through a send key control of the user interface, or the user can use a voice acquisition control provided on the interface to input the acquisition instruction by voice.

[0070] S302. Transform the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation; the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficient in the initial productivity equation is the coefficient to be solved in the multivariate linear regression equation.

[0071] According to the above description, the initial productivity equation is the equation established by using the pseudo-pressure productivity well test for the target gas well, that is, the above-mentioned formula (2).

[0072] In some embodiments, the process of transforming the initial productivity equation of the target gas well into a multivariate linear regression equation is as follows:

[0073] Transform formula (2) to obtain the multivariate linear regression equation, as shown in formula (4):

[0074]

[0075] Among them, ψ R , A and B are the coefficients to be solved in the multiple linear regression equation.

[0076] In other embodiments, the initial productivity equation of the target gas well may be transformed according to the preset corresponding relationship to obtain a multivariate linear regression equation. The specific process is as follows:

[0077] The above preset corresponding relationship is y=ψ wf 、A0=ψ R , A1=-A, A2=-B, x1=q g 、 As an example, the preset corresponding relationship is brought into formula (4) to obtain the multivariate linear regression equation as shown in formula (5):

[0078] y=A0+A1x1+A2x2 (5)

[0079] Among them, A0, A1 and A2 are the coefficients to be solved in the multiple linear regression equation.

[0080] It should be noted that the symbols in the preset correspondence shown above are only exemplary. In some other embodiments, other symbols may be used as corresponding symbols in the preset correspondence, and this is not specifically limited in the embodiments of the present application.

[0081] From the above formula (4) and formula (5), we can see that there are two dependent variables in the multivariate linear regression equation, namely x1, x2, or q g 、 Therefore, the above multivariate linear regression equation can also be called a binary linear regression equation.

[0082] S303. Utilize multiple sets of measurement data from the well test data of the target gas well to solve the values ​​of the coefficients to be solved in the multivariate linear regression equation, and substitute the solved coefficient values ​​back into the initial productivity equation to obtain the productivity equation of the target gas well; each set of measurement data includes the well test flow value measured at a measurement point of the target gas well, and the pseudo-pressure value corresponding to the bottom hole flowing pressure value.

[0083] Taking formula (4) as an example, corresponding to the formula, the pseudo-pressure values ​​corresponding to multiple sets of well test flow values ​​and multiple sets of bottom hole flow pressures can be substituted into the multivariate linear regression equation shown in formula (4) to obtain ψ R , the values ​​of A1 and A2.

[0084] Alternatively, taking formula (5) as an example, corresponding to this formula, the pseudo-pressure values ​​corresponding to multiple sets of well test flow values ​​and multiple sets of bottom hole flow pressures can be substituted into y, x1, and x2 in the multivariate linear regression equation shown in formula (5) to calculate the values ​​of A0, A1, and A2.

[0085] Taking formula (5) as an example, the multivariate linear regression equation can be i =A0+A1x 1i +A2x 2i ; Where i represents the measurement data of group i, i = 1, 2, ..., N; then the original function y and the regression function y i The residual sum of squares Q is shown in formula (6):

[0086]

[0087] For formula (6), calculate the partial derivatives of A0, A1, and A2 respectively, and set the partial derivatives equal to zero, that is, as shown in formula (7), formula (8), and formula (9):

[0088]

[0089]

[0090]

[0091] From the above formula (5), we can get the following formula (10):

[0092]

[0093] in, represents the average pseudo-pressure corresponding to the bottom hole flowing pressure measured at the i measurement points of the target gas well, It represents the average value of the well test flow rate values ​​measured at the i measurement points of the target gas well. represents the average value of the square of the test flow rate obtained from the i measurement points of the target gas well. and As shown in formula (11), formula (12) and formula (13):

[0094]

[0095]

[0096]

[0097] Substituting A0 into formula (8) and formula (9), we can get the following formulas (14) and (15):

[0098] M 11 A1+M 12 A2=M 1y (14)

[0099] M 21 A1+M 22 A2=M 2y (15)

[0100] in:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] The above formula (12) is shown in Substituting the value of into formula (16), we get formula (22):

[0108]

[0109] The above formula (12) is shown in The value of is shown in the above formula (13) Substituting the values ​​of into formula (17) and formula (18), we can get formula (23) and formula (24):

[0110]

[0111]

[0112] The above formula (12) is shown in Substituting the value of into formula (19), we get formula (25):

[0113]

[0114] The above formula (11) shows The value of is shown in the above formula (12) Substituting the value of into formula (20), we get formula (26):

[0115]

[0116] The above formula (11) shows The value of is shown in the above formula (13) Substituting the value of into formula (21), we get formula (27):

[0117]

[0118] Solving formula (14) and formula (15) yields the following formulas (28) and (29):

[0119]

[0120]

[0121] Thus, the coefficients A0, A1, and A2 of the multiple linear regression equation are obtained.

[0122] Substituting the values ​​of coefficients A0, A1, and A2 back into the above formula (2), we can obtain the productivity equation of the target gas well, which is shown in the following formula (30):

[0123]

[0124] S304: Calculate the productivity of the target gas well using the productivity equation of the target gas well.

[0125] The method of using the productivity equation of the target gas well to calculate the productivity of the target gas well is similar to the method of using the binomial productivity equation to calculate the productivity of the target gas well in the prior art, and will not be described in detail.

[0126] S305: Output the production capacity of the target gas well.

[0127] The electronic device can display the production capacity of the target gas well through a user interface, and can also broadcast the production capacity of the target gas well through voice broadcasting.

[0128] The gas well productivity acquisition method provided in the present application, by transforming the initial productivity equation of the target gas well into a multivariate linear regression equation, can utilize the characteristic that the dependent variable and the independent variable of the multivariate linear regression equation satisfy the linear correlation, and use multiple groups of measurement data in the well test data of the target gas well to obtain the value that can make the productivity coefficient in the initial productivity equation satisfy the linear correlation, and then introduce the value back into the initial productivity equation to obtain the productivity equation of the target gas well that satisfies the linear correlation. In this way, when using the productivity equation to obtain the productivity of the target gas well, even if the gas production and pressure are unstable during the back pressure test of the target gas well, the productivity of the target gas well can be accurately obtained, thereby improving the accuracy of obtaining the gas well productivity, thereby providing an accurate basis for gas field production allocation and ground engineering construction.

[0129] When the above method is applied to a gas well with abnormal productivity, before transforming the initial productivity equation of the target gas well to obtain the multivariate linear regression equation corresponding to the initial productivity equation, the method further includes: determining that the target gas well is a gas well with abnormal productivity. That is, a gas well with unstable gas production and pressure during the backpressure well test.

[0130] For example, gas wells with abnormal production capacity have the following characteristics: thick gas reservoir thickness, high gas well production capacity, small gas well production pressure difference, and the pseudo-pressure value of the formation pressure of the gas well in the abnormally high-pressure gas reservoir, the pseudo-pressure value of the bottom hole flow pressure of the gas well, and the test flow rate value of the gas well do not satisfy the linear correlation during binomial equation or exponential analysis.

[0131] Based on the above characteristics, the following are some examples of gas wells that are identified as having abnormal productivity based on these characteristics:

[0132] Method 1: In the target gas well productivity analysis, binomial equation analysis can be used to determine whether the target gas well is a gas well with abnormal productivity acquisition.

[0133] First, the value of the first preset relationship is obtained using the well test data of the target gas well. The first preset relationship is the ratio of the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flow pressure of the target gas well when the pseudo-pressure production capacity well test is performed on the target gas well, to the well test flow rate value of the target gas well. That is, the first preset relationship is

[0134] Determining whether a first relationship curve formed by the value of the first preset relationship expression and the well test flow rate value in a rectangular coordinate system satisfies a linear relationship, or whether the slope of the first relationship curve is negative;

[0135] If the first relationship curve does not satisfy a linear relationship, or the slope of the first relationship curve is negative, it means that the pseudo-pressure value of the formation pressure where the target gas well is located, the pseudo-pressure value of the bottom hole flowing pressure of the target gas well, and the well test flow rate value of the target gas well do not satisfy the linear correlation of the binomial equation analysis, and the target gas well is determined to be a gas well with abnormal productivity acquisition.

[0136] If the first relationship curve satisfies a linear relationship, or the slope of the first relationship curve is positive, it means that the pseudo-pressure value of the formation pressure where the target gas well is located, the pseudo-pressure value of the bottom hole flowing pressure of the target gas well, and the well test flow rate value of the target gas well satisfy the linear correlation of the binomial equation analysis, then the target gas well is determined to be a gas well with normal production capacity acquisition, and at this time, the existing production capacity acquisition method can be used for processing.

[0137] For example, the slope of the first relationship curve of gas well 3 is -2, and gas well 3 is determined to be a gas well with abnormal productivity acquisition.

[0138] Alternatively, the slope of the first relationship curve of gas well 4 is 2, and gas well 4 is determined to be a gas well with normal production capacity.

[0139] Method 2: In the target gas well productivity analysis, an exponential analysis can be used to determine whether the target gas well is a gas well with abnormal productivity. The exponential analysis can be expressed as: logq~log(ψ R -ψ wf ).

[0140] First, the value of the second preset relationship is obtained using the well test data of the target gas well. The second preset relationship is the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flow pressure of the target gas well when the pseudo-pressure production capacity well test is performed on the target gas well; that is, the second preset relationship is ψ R -ψ wf .

[0141] Determining whether the reciprocal of the slope of a second relationship curve formed by the value of the second preset relationship expression and the well test flow value in a logarithmic coordinate system is within a preset range;

[0142] If the inverse of the slope of the second relationship curve is not within the preset range, it means that the pseudo-pressure value of the formation pressure where the target gas well is located, the pseudo-pressure value of the bottom hole flowing pressure of the target gas well, and the well test flow rate value of the target gas well do not satisfy the linear correlation during exponential analysis, and the target gas well is determined to be a gas well with abnormal production capacity acquisition.

[0143] If the inverse of the slope of the second relationship curve is within the preset range, it means that the pseudo-pressure value of the formation pressure where the target gas well is located, the pseudo-pressure value of the bottom hole flowing pressure of the gas well, and the well test flow rate value of the gas well meet the linear correlation during exponential analysis, and the target gas well is determined to be a gas well with normal production capacity acquisition.

[0144] For example, the slope of the second relationship curve of gas well 5 is 3, the inverse of the slope is 1 / 3, and the preset range is [1 / 2, 1]. It is determined that the inverse of the slope of the second relationship curve of gas well 5 is not within the preset range, that is, gas well 5 is determined to be a gas well with abnormal production capacity acquisition.

[0145] Alternatively, the slope of the second relationship curve of gas well 6 is 2, the inverse of the slope is 1 / 2, and the preset range is [1 / 2, 1]. It is determined that the inverse of the slope of the second relationship curve of gas well 6 is within the preset range, that is, gas well 6 is determined to be a gas well with normal production capacity.

[0146] Method 3: Use the reservoir thickness of the gas reservoir where the target gas well is located to determine whether the target gas well is a gas well with abnormal productivity.

[0147] For example, the reservoir thickness of the gas reservoir where the target gas well is located can be obtained from well test data. A judgment can then be made based on the reservoir thickness. For example, if the reservoir thickness is greater than or equal to a first preset threshold, the target gas well is determined to have abnormal productivity; if the reservoir thickness is less than the first preset threshold, the target gas well is determined to have normal productivity.

[0148] In some examples, the first preset threshold may be any thickness value between 300 and 400 m. In other examples, the first preset threshold may also be less than 300 m or greater than 400 m. The specific value of the first preset threshold is not limited in the embodiments of the present application.

[0149] For example, the first preset threshold is 250m, and the target gas well is gas well 7. The storage thickness under the gas reservoir of gas well 7 is obtained and judged. If the storage thickness is greater than or equal to 250m, it means that the storage thickness of the gas reservoir where gas well 7 is located is thick, and gas well 7 is determined to be a gas well with abnormal production capacity acquisition. Otherwise, gas well 7 is a gas well with normal production capacity acquisition.

[0150] Although the above three methods provide some ways to determine whether the target gas well is a gas well with abnormal production capacity acquisition, it should be understood that other characteristic information that can characterize abnormal production capacity acquisition can also be used to determine whether the target gas well is a gas well with abnormal production capacity acquisition. In addition, they will not be listed one by one.

[0151] This application uses actual data from sample gas wells to verify the reliability of the gas well productivity equation provided by the above method, as follows:

[0152] Based on the actual production obtained by performing a back pressure test on a sample gas well for a preset production time using multiple test flow values, the production capacity coefficient in the initial production capacity equation is determined by using the existing pseudo-pressure to obtain a first production capacity equation for the sample gas well, as shown in the above formula (2), and a second production capacity equation is obtained using the gas well production capacity acquisition method of the present application, as shown in the above formula (30);

[0153] The first productivity equation and the second productivity equation are used to calculate the first productivity and the second productivity of the sample gas well respectively;

[0154] If the error between the first productivity and the second productivity is less than or equal to the preset error threshold, it is determined that the verification of the second productivity equation is passed, indicating that the reliability of the gas well productivity equation obtained by the above method is high.

[0155] For example, Figure 4 A schematic diagram of the productivity of a sample gas well provided in one embodiment of the present application is shown in FIG. Figure 4 As shown in the figure, the actual test data of sample gas well B is used as an example for explanation. When the sample gas well B is tested for productivity, the back pressure method stable well test adopts the following four working systems for production, namely: 100×10 4 m 3 / d, 150×10 4 m 3 / d, 200×10 4 m 3 / d, 250×10 4 m 3 Each test regime lasted 12 hours. The pseudo-pressure and production data for sample gas well B during the backpressure test are detailed in Table 1.

[0156] Table 1

[0157]

[0158] Under the condition of stable production at each well test flow pressure value of sample gas well B, the coefficients of the initial productivity equation are determined by pseudo-pressure to obtain the first productivity equation of sample gas well B. The second productivity equation of sample gas well B is determined by multivariate linear regression. Specifically, as shown in Table 2, the first productivity equation is ψ R -ψ wf =1.29E16q+2.75E13q 2 , and the second energy production equation is: ψ R -ψ wf =1.23E16q+2.94E13q 2 .

[0159] Table 2

[0160]

[0161] Figure 5 A schematic diagram of the productivity curve of a sample gas well provided in an embodiment of the present application is shown in FIG. Figure 5 As shown in the figure, it can be seen that the binomial productivity curve obtained based on the first productivity equation has a good linear correlation and a positive slope. In other words, the first productivity equation can accurately obtain the productivity of sample gas well B.

[0162] Figure 6 The productivity curve is obtained by calculating the productivity of the sample gas well using the first productivity equation and the second productivity equation provided in an embodiment of the present application, such as Figure 6 As shown in the figure, by comparing the binomial productivity curve of the first productivity equation with the productivity curve of the second productivity equation, it can be seen that the productivity of the sample gas well calculated by the first productivity equation is 1693.87×10 4 m 3 / d, the productivity of the sample gas well calculated by the second productivity equation is 1653.31×10 4 m 3 / d, the error between the first and second production capacities is 2.39%. Assuming the preset error threshold is 10%, if the error between the first and second production capacities is less than 10%, the second production capacities equation is considered to have passed verification. This means that the accuracy and reliability of the second production capacities equation have been verified.

[0163] The above verification shows that the productivity equation obtained by the method of the present application is highly accurate, and thus the productivity of a gas well can be accurately obtained using the productivity equation.

[0164] The following is a complete example to illustrate the gas well productivity acquisition method provided by this application:

[0165] Figure 7 A flow chart of a method for obtaining gas well productivity provided in another embodiment of the present application is shown in FIG. Figure 7 As shown, the method includes:

[0166] S701, receiving an acquisition instruction and well testing data of a target gas well.

[0167] S702: Determine whether the target gas well is a gas well with abnormal productivity based on the well test data. If yes, execute S703; if not, execute S706.

[0168] S703: transform the initial production capacity equation according to the preset corresponding relationship to obtain a multiple linear regression equation.

[0169] S704: Obtain the values ​​of the coefficients to be solved in the multivariate linear regression equation based on the multiple sets of measurement data in the well test data, substitute the solved coefficient values ​​back into the initial productivity equation, and obtain the productivity equation of the target gas well.

[0170] S705 , using the productivity equation of the target gas well to obtain the productivity of the target gas well.

[0171] After executing S705, execute S707.

[0172] S706: Obtain the productivity of the target gas well using the initial productivity equation.

[0173] After S706 is executed, S707 is also executed.

[0174] S707: Output the production capacity of the target gas well.

[0175] The gas well productivity acquisition method provided in the present application, by transforming the initial productivity equation of the target gas well into a multivariate linear regression equation, can utilize the characteristic that the dependent variable and the independent variable of the multivariate linear regression equation satisfy the linear correlation, and use multiple groups of measurement data in the well test data of the target gas well to obtain the value that can make the productivity coefficient in the initial productivity equation satisfy the linear correlation, and then introduce the value back into the initial productivity equation to obtain the productivity equation of the target gas well that satisfies the linear correlation. In this way, when using the productivity equation to obtain the productivity of the target gas well, even if the gas production and pressure of the target gas well are unstable during the backpressure test, the productivity of the target gas well can be accurately obtained, thereby improving the accuracy of obtaining the gas well productivity, thereby providing an accurate basis for gas field production allocation and ground engineering construction.

[0176] Figure 8 A schematic diagram of the structure of a gas well productivity acquisition device provided in one embodiment of the present application is shown in FIG. Figure 8 As shown, the gas well productivity acquisition device 80 of this embodiment is used to implement the operations corresponding to the electronic device in any of the above method embodiments. The gas well productivity acquisition device 80 of this embodiment includes: a receiving module 81, a processing module 82, and an output module 83. Optionally, in some embodiments, the gas well productivity acquisition device 80 may further include a determination module 84.

[0177] The receiving module 81 is used to receive an acquisition instruction and well test data of a target gas well, wherein the acquisition instruction is used to request to obtain the production capacity of the target gas well;

[0178] Processing module 82 is used to transform the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation; use multiple sets of measurement data from the well test data of the target gas well to solve the values ​​of the coefficients to be solved in the multivariate linear regression equation, and substitute the solved coefficients into the initial productivity equation to obtain a first productivity equation for the target gas well; calculate the productivity of the target gas well using the productivity equation of the target gas well; wherein the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficients in the initial productivity equation are the coefficients to be solved in the multivariate linear regression equation; each set of measurement data includes a well test flow value measured at a measurement point of the target gas well and a bottom hole flowing pressure value;

[0179] The output module 83 is used to output the production capacity of the target gas well.

[0180] Optionally, the determination module 84 is used to determine that the target gas well is a gas well with abnormal production capacity acquisition before the processing module 82 transforms the initial production capacity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial production capacity equation. The gas well with abnormal production capacity acquisition is a gas well with unstable gas production and pressure during the backpressure test.

[0181] Optionally, the first preset relationship is the ratio of the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flow pressure of the target gas well, to the test flow rate value of the target gas well when the pseudo-pressure production capacity test is adopted for the target gas well; the determination module 84 is specifically used to obtain the value of the first preset relationship using the test data of the target gas well; determine whether the first relationship curve formed by the value of the first preset relationship and the test flow rate value in the rectangular coordinate system satisfies a linear relationship, or whether the slope of the first relationship curve is negative; if the first relationship curve does not satisfy the linear relationship, or the slope of the first relationship curve is negative, the target gas well is determined to be a gas well with abnormal production capacity acquisition.

[0182] Optionally, the second preset relationship is the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flow pressure of the target gas well when a pseudo-pressure productivity test is performed on the target gas well; the determination module 84 is specifically used to use the well test data of the target gas well to obtain the value of the second preset relationship; determine whether the reciprocal of the slope of the second relationship curve formed by the value of the second preset relationship and the well test flow value in the logarithmic coordinate system is within a preset range; if the reciprocal of the slope of the second relationship curve is not within the preset range, the target gas well is determined to be a gas well with abnormal productivity acquisition.

[0183] Optionally, the determination module 84 is specifically configured to obtain a reservoir thickness of a gas reservoir where the target gas well is located; if the reservoir thickness is greater than or equal to a first preset threshold, the target gas well is determined to be a gas well with abnormal productivity.

[0184] The gas well productivity acquisition device 80 provided in the embodiment of the present application can execute the above method embodiment. Its specific implementation principles and technical effects can be found in the above method embodiment, and this embodiment will not be repeated here.

[0185] Figure 9 This is a schematic diagram of the hardware structure of an electronic device provided in one embodiment of the present application. Figure 9 As shown, the electronic device 90 is used to implement the operations corresponding to the electronic device in any of the above method embodiments. The electronic device 90 of this embodiment may include: a processor 91 and a memory 92; wherein,

[0186] The memory 92 is a memory for storing processor executable instructions.

[0187] The processor 91 is configured to implement the gas well productivity acquisition method in the above embodiment according to the executable instructions stored in the memory. For details, please refer to the relevant description in the above method embodiment.

[0188] Optionally, the memory 92 may be independent or integrated with the processor 91 .

[0189] When the memory 92 is independently provided, the electronic device 90 further includes a bus 93 for connecting the memory 92 and the processor 91 .

[0190] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided in the various embodiments described above.

[0191] Among them, the computer-readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, a computer-readable storage medium is coupled to a processor so that the processor can read information from the computer-readable storage medium and write information to the computer-readable storage medium. Of course, the computer-readable storage medium can also be an integral part of the processor. The processor and the computer-readable storage medium can be located in an application-specific integrated circuit (ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the computer-readable storage medium can also exist in a communication device as discrete components.

[0192] Specifically, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random-access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0193] The present application also provides a computer program product, comprising a computer program stored in a computer-readable storage medium. At least one processor of a device can read the computer program / instructions from the computer-readable storage medium, and at least one processor executes the computer program to cause the device to implement the methods provided in the various embodiments described above.

[0194] An embodiment of the present application also provides a chip, which includes a memory and a processor, the memory is used to store computer programs, and the processor is used to call and run computer programs from the memory, so that a device equipped with the chip executes the methods in various possible implementation modes as described above.

[0195] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0196] The modules may be physically separate, for example, installed in different locations on a single device, or installed on different devices, or distributed across multiple network units, or distributed across multiple processors. The modules may also be integrated, for example, installed in the same device, or integrated into a set of codes. The modules may exist in the form of hardware, or in the form of software, or may be implemented in the form of software plus hardware. The present application may select some or all of the modules according to actual needs to achieve the purpose of the present embodiment.

[0197] When each module is implemented as an integrated module in the form of a software function module, it can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to perform some steps of the methods of various embodiments of the present application.

[0198] It should be understood that, although the various steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they may be performed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times, and their execution order is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of sub-steps or stages of other steps.

[0199] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the aforementioned embodiments, those skilled in the art will appreciate that they may modify the technical solutions described in the aforementioned embodiments or replace some or all of the technical features therein with equivalents. However, such modifications or replacements do not deviate from the essence of the corresponding technical solutions within the scope of the various embodiments of this application.

Claims

1. A method for obtaining gas well productivity, characterized in that: The method comprises: receiving an acquisition instruction and well test data of a target gas well, wherein the acquisition instruction is used to request acquisition of the production capacity of the target gas well; The initial productivity equation of the target gas well is transformed to obtain a multiple linear regression equation corresponding to the initial productivity equation; the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficient in the initial productivity equation is the coefficient to be solved in the multiple linear regression equation; the initial productivity equation is: Among them, ψ R is the pseudo-pressure value of the formation pressure of the target gas well, ψ wf is the pseudo-pressure value of the bottom hole flowing pressure of the target gas well, q g is the well test flow rate value of the target gas well, A and B are the productivity coefficients of the initial productivity equation; The initial productivity equation of the target gas well is transformed to obtain the multivariate linear regression equation corresponding to the initial productivity equation: Using multiple sets of measurement data from the target gas well test data, the coefficient ψ to be solved in the multivariate linear regression equation is solved. R , the values ​​of A, B, and the coefficient ψ R , the values ​​of A and B are substituted back into the initial productivity equation to obtain the productivity equation of the target gas well; each set of measurement data includes a well test flow value measured at a measurement point of the target gas well, and a pseudo-pressure value corresponding to the bottom hole flowing pressure value; Calculating the productivity of the target gas well using the productivity equation of the target gas well; outputting the production capacity of the target gas well; Before transforming the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation, the method further includes: Determining that the target gas well is a gas well with abnormal productivity acquisition, wherein the gas well with abnormal productivity acquisition is a gas well with unstable gas production and pressure during a backpressure well test; The first preset relationship is the ratio of the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well, to the well test flow rate value of the target gas well, when the pseudo-pressure productivity well test is performed on the target gas well; Determining that the target gas well is a gas well with abnormal productivity acquisition includes: Using the well test data of the target gas well, obtaining the value of the first preset relationship; Determining whether a first relationship curve formed by the value of the first preset relationship expression and the well test flow rate value in a rectangular coordinate system satisfies a linear relationship, or whether the slope of the first relationship curve is negative; If the first relationship curve does not satisfy a linear relationship, or the slope of the first relationship curve is negative, it is determined that the target gas well is a gas well with abnormal productivity acquisition.

2. The method according to claim 1, characterized in that The second preset relationship is the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well when the pseudo-pressure productivity well test is performed on the target gas well; Determining that the target gas well is a gas well with abnormal productivity acquisition includes: Using the well test data of the target gas well, obtaining the value of the second preset relationship; Determining whether the reciprocal of the slope of a second relationship curve formed by the value of the second preset relationship expression and the well test flow value in a logarithmic coordinate system is within a preset range; If the inverse of the slope of the second relationship curve is not within the preset range, the target gas well is determined to be a gas well with abnormal productivity acquisition.

3. The method according to claim 1, characterized in that Determining that the target gas well is a gas well with abnormal productivity acquisition includes: Obtaining the reservoir thickness of the gas reservoir where the target gas well is located; If the reservoir thickness is greater than or equal to a first preset threshold, the target gas well is determined to be a gas well with abnormal productivity.

4. A gas well productivity acquisition device, characterized in that: The device comprises: A receiving module, configured to receive an acquisition instruction and well test data of a target gas well, wherein the acquisition instruction is used to request acquisition of the production capacity of the target gas well; The processing module is used to transform the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation; the initial productivity equation is: Among them, the ψ R is the pseudo pressure value of the formation pressure of the target gas well, the ψ wf is the pseudo-pressure value of the bottom hole flowing pressure of the target gas well, q g is the well test flow rate value of the target gas well, A and B are the productivity coefficients of the initial productivity equation; The initial productivity equation of the target gas well is transformed to obtain the multivariate linear regression equation corresponding to the initial productivity equation: Using multiple sets of measurement data from the target gas well test data, solve the coefficients to be solved in the multivariate linear regression equation. R , A, B values, and the coefficient ψ R , the values ​​of A and B are substituted back into the initial productivity equation to obtain the first productivity equation of the target gas well; the productivity of the target gas well is calculated using the productivity equation of the target gas well; wherein the initial productivity equation is an equation established by using a pseudo-pressure productivity well test for the target gas well; the productivity coefficient in the initial productivity equation is the coefficient to be solved in the multivariate linear regression equation; each set of measurement data includes a well test flow value measured at a measurement point of the target gas well, and a bottom hole flowing pressure value; An output module, configured to output the production capacity of the target gas well; a determination module, configured to determine that the target gas well is a gas well with abnormal productivity before the processing module transforms the initial productivity equation of the target gas well to obtain a multivariate linear regression equation corresponding to the initial productivity equation; The first preset relationship is the ratio of the difference between the pseudo-pressure value corresponding to the formation pressure of the target gas well and the pseudo-pressure value corresponding to the bottom hole flowing pressure of the target gas well, to the well test flow rate value of the target gas well, when the pseudo-pressure productivity well test is performed on the target gas well; Identify the module, specifically for: Using the well test data of the target gas well, obtaining the value of the first preset relationship; Determining whether a first relationship curve formed by the value of the first preset relationship expression and the well test flow rate value in a rectangular coordinate system satisfies a linear relationship, or whether the slope of the first relationship curve is negative; If the first relationship curve does not satisfy a linear relationship, or the slope of the first relationship curve is negative, it is determined that the target gas well is a gas well with abnormal productivity acquisition.

5. An electronic device, characterized in that: The device includes: a memory and a processor; The memory is used to store computer programs; the processor is used to implement the gas well productivity acquisition method according to any one of claims 1 to 3 according to the computer programs stored in the memory.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, is used to implement the gas well productivity acquisition method according to any one of claims 1 to 3.

7. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, the gas well productivity acquisition method according to any one of claims 1 to 3 is implemented.

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