New well real-time tracking and advanced early warning method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a new well real-time tracking and advanced early warning method and device, equipment and a storage medium. The method comprises the steps of obtaining data of a target development unit over the years; according to the number of new monthly commissioning wells, the commissioning time rate of the current month, the initial yield of the newly commissioning wells and the monthly comprehensive decline rate of the target development unit over the years, fitting the average initial yield of the newly commissioning wells and the average monthly comprehensive decline rate of the target development unit; and constructing a new well real-time tracking and advanced early warning model by using the average initial yield of the newly commissioned well and the average monthly comprehensive decline rate. According to the technical scheme, the annual yield of the new well can be predicted in real time, early warning is timely performed, production operation is timely optimized, and completion of the annual yield target is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of oil and gas field development, and particularly to a method, device, electronic device and storage medium for real-time tracking and early warning of new wells. Background Art

[0002] The operation of oilfield production is the core of oilfield development work. Each oilfield branch company aims at the annual production allocation target and organizes the implementation. The annual production composition is divided into three parts: natural production, new well production and measure production. Due to the influence of reservoir endowment, development mode, production operation, etc., the new well production has great randomness and large prediction uncertainty, which has always been a difficult point in oilfield production allocation and production operation.

[0003] Historically, there have been mainly two traditional methods for predicting new well production: The first is a prediction model established based on statistical theory with development time as a variable. This method converts different distribution laws in mathematical statistics into production prediction models. There are currently more than a dozen of them, such as the Weng's cyclic model, etc. The core is to apply the least squares method to solve the relevant parameters of the model and solve the new well production according to time extrapolation. However, this method cannot reflect the workload, cannot reflect the production operation arrangement, and is easy to be disconnected from the development work, resulting in large errors. The second is to calculate the new well production in the next year according to the annual production effect of new wells. According to the annual effect law of new wells in previous years and combining the workload of newly drilled wells, the new well production in the deployment year is calculated. This method does not consider the monthly operation arrangement of the workload and cannot optimize and predict the annual production according to the current monthly production operation. Summary of the Invention

[0004] In view of this, the present application provides a method, device, electronic device and storage medium for real-time tracking and early warning of new wells, which can predict the annual production of new wells in real time according to the workload, operation rhythm and production effect implemented monthly for new wells, give early warnings, organize and optimize production operation and oilfield development work in time, and ensure the smooth completion of the annual production target. Therefore, a method for real-time tracking and early warning of new wells in oilfields is studied and proposed.

[0005] In a first aspect, an embodiment of the present application provides a method for real-time tracking and early warning of new wells, including:

[0006] Obtaining historical data of a target development unit;

[0007] Fitting the average initial production of newly drilled wells and the average monthly comprehensive decline rate of the target development unit according to the number of newly drilled wells put into production per month, the production rate at the time of production in the current month, the initial production of newly drilled wells and the monthly comprehensive decline rate in the target development unit over the years;

[0008] Constructing a real-time tracking and early warning model for new wells by using the average initial production of newly drilled wells and the average monthly comprehensive decline rate.

[0009] In a possible implementation, the annual data includes the number of newly put into production wells per month in past years of the target development unit, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate.

[0010] In a possible implementation, fitting the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit according to the number of newly put into production wells per month in past years of the target development unit, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate includes:

[0011] S2.1: Select the maximum value Q0max and the minimum value Q0min of the initial production of newly put into production wells in past years of the target development unit, and perform the following calculations:

[0012]

[0013] where N is the number of copies of the initial production of newly put into production wells;

[0014] S2.2: Set the first variable K, K = 1;

[0015] S2.3: Calculate the predicted value Q′0 of the initial production of newly put into production wells:

[0016] Q′0 = Q0min + n·K

[0017] S2.4: Select the maximum value D , j实际 ,

[0018] , , K,L ,

[0017] , 月 , ,

[0016] , , 月 , , , , , , j , 月 ,

[0023] , , 月 ,

[0022] , , 月 ,

[0021] , , ,

[0020] ,

[0026] ,

[0019] ,

[0025] ,

[0024] max and the minimum value D 月 min, and perform the following calculations:

[0018]

[0019] where M is the number of copies of the monthly comprehensive decline rate;

[0020] S2.5: Set the second variable L, L = 1;

[0021] S2.6: Calculate the predicted value D′ of the monthly comprehensive decline rate 月 :

[0022] D′ 月 = D <000000​​​​​​​​​​​​​​​​​​​​

[0027]

[0028]

[0029] Among them, i represents the production start month, i = 1, 2, 3,..., 12; j represents the production month after production start, j = i,..., 12; Q' i,j represents the predicted monthly production of the wells put into production in month i in month j; S0 represents the production time rate in the first month of the newly put into production wells; S j represents the number of production days in a month, and S2, S3... S 12 correspond to the natural monthly calendar days of February, March... December respectively; N i represents the number of newly put into production wells in a month; Q'0 represents the predicted value of the initial production of the newly put into production wells; D' 月 represents the predicted value of the monthly comprehensive decline rate;

[0030] S2.8: Set L = L + 1. If L < M, repeat steps S2.6 - S2.7; if L ≥ M, go to step S2.9.

[0031] S2.9: Set K = K + 1. If K < N, repeat steps S2.3 - S2.8; if K ≥ N, go to step S2.10.

[0032] S2.10: Obtain the sequence of the error ε K,L and select the minimum error min[ε K,L , and record the first variable K corresponding to min[ε K,L as K min , and record the second variable L corresponding to it as L min , then:

[0033] Q0 = Q0min + n·K min

[0034] D 月 = D 月 min + m·L min

[0035] The Q0 represents the average initial production of the newly put into production wells, and D 月 represents the average monthly comprehensive decline rate.

[0036] In a possible implementation manner, the building of the real-time tracking and early warning model for new wells by using the average initial production of the newly put into production wells and the average monthly comprehensive decline rate includes:

[0037] Using the average initial production Q0 of the newly put into production wells and the average monthly comprehensive decline rate D 月 to perform real-time tracking on the new wells;

[0038] According to the tracking results of real-time tracking of new wells, the annual production of new wells is predicted. If the production target set at the beginning of the year cannot be achieved, a warning is issued.

[0039] In a possible implementation, the real-time tracking is to predict the total monthly production of the target development unit in real time, and its calculation formula is as follows:

[0040]

[0041] Among them, Q j represents the total monthly production of the target development unit in the j-th month; Q i,j represents the monthly production of the well put into production in the i-th month in the j-th month; i represents the production month, i = 1, 2, 3,..., 12; j represents the production month after production, j = i,..., 12.

[0042] In a possible implementation, the calculation formula of Q i,j is as follows:

[0043]

[0044] Among them, S0 represents the production time rate in the first month of the newly put into production well; S j represents the number of production days in a month, and S2, S3... S 12 correspond to the natural calendar days of February, March... December respectively; N i represents the number of newly put into production wells in a month; Q0 represents the initial production of the average newly put into production well; D 月 represents the average monthly comprehensive decline rate.

[0045] In a second aspect, an embodiment of the present application provides a new well real-time tracking and early warning device, including:

[0046] A data acquisition module, configured to acquire the number of newly put into production wells per month, the production time rate in the current month, the initial production of the newly put into production well, and the monthly comprehensive decline rate of the target development unit over the years;

[0047] A data fitting module, configured to fit the initial production of the average newly put into production well and the average monthly comprehensive decline rate of the target development unit according to the number of newly put into production wells per month, the production time rate in the current month, the initial production of the newly put into production well, and the monthly comprehensive decline rate of the target development unit over the years;

[0048] A new well implementation tracking and early warning module, configured to perform real-time tracking on new wells by using the initial production of the average newly put into production well and the average monthly comprehensive decline rate, and predict the annual production of new wells. If the production target set at the beginning of the year cannot be achieved, a warning is issued.

[0049] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0050] Processor;

[0051] Memory;

[0052] And a computer program, where the computer program is stored in the memory, and the computer program includes instructions that, when executed by the processor, cause the electronic device to execute the method described in any one of the first aspects.

[0053] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, it controls the device where the computer-readable storage medium is located to execute the method described in any one of the first aspects.

[0054] The method of the present application combines the monthly production workload and production effect, can realize real-time prediction of the annual output on a monthly basis, and give early warnings; the comprehensive application results of various methods and iterative algorithms are mutually verified with the actual effects, reducing system errors and improving the accuracy and rationality of new well prediction; real-time prediction of the annual output and early warning ensure the smooth completion of the output task; it can optimize the subsequent monthly production workload and ensure the completion of the annual output target.

[0055] The present application can be further popularized and applied in three aspects: one is the management of oil production plants by each oilfield branch company to ensure the completion of the output targets of all levels of units; the second is that it can be extended to the allocation and tracking warning of measure production, ensuring the rationality of measure allocation and the completion of the target; the third is that it can be extended and applied to the allocation and tracking warning of the production of conventional natural gas and unconventional oil and gas. Description of the Drawings

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0057] Figure 1 It is a schematic flowchart of a method for real-time tracking and early warning of new wells provided by an embodiment of the present application;

[0058] Figure 2 It is a flowchart of iterative fitting calculation provided by an embodiment of the present application;

[0059] Figure 3 It is a structural block diagram of a device for real-time tracking and early warning of new wells provided by an embodiment of the present application;

[0060] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0061] To better understand the technical solutions of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0062] It should be clear that the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application.

[0063] The terms used in the embodiments of this application are only for the purpose of describing specific embodiments, and are not intended to limit this application. The singular forms "a", "the" and "said" used in the embodiments of this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0064] It should be understood that the term " / or" used herein is only a relationship describing associated objects, indicating that three relationships may exist. For example, a / or b may represent: a exists alone, a and b exist simultaneously, and b exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0065] See Figure 1 , which is a schematic flowchart of a real-time tracking and early warning method for new wells provided by the embodiments of this application. As Figure 1 shown, it mainly includes the following steps.

[0066] Step S1: Obtain the monthly number of newly put into production wells, the current month's production rate at the time of production, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years.

[0067] Step S2: Fit the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit according to the monthly number of newly put into production wells, the current month's production rate at the time of production, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years.

[0068] See Figure 2 , which is an iterative fitting calculation flowchart provided by the embodiments of this application. As Figure 2 shown, step S2 specifically includes:

[0069] S2.1: Select the maximum value Q0max and the minimum value Q0min of the initial production of newly put into production wells of the target development unit over the years, and perform the following calculations:

[0070]

[0071] where N is the number of copies of the initial production of newly put into production wells;

[0072] S2.2: Set the first variable K, where K = 1;

[0073] S2.3: Calculate the predicted initial production value Q′0 of the newly put - into - production well:

[0074] Q′0 = Q0min + n·K

[0075] S2.4: Select the maximum value D 月 max and the minimum value D 月 min of the monthly comprehensive decline rates of the target development unit over the years, and perform the following calculations:

[0076]

[0077] Among them, M is the number of copies of the monthly comprehensive decline rate;

[0078] S2.5: Set the second variable L, where L = 1;

[0079] S2.6: Calculate the predicted value D′ of the monthly comprehensive decline rate 月 :

[0080] D′ 月 = D 月 min + m·L

[0081] S2.7: Calculate the error:

[0082] ε K,L = |Q′ j - Q j实际 |

[0083] Among them,

[0084]

[0085]

[0086]

[0087] Among them, i represents the production month, i = 1, 2, 3,..., 12; j represents the production month after production, j = i,..., 12; Q′ i,j represents the predicted monthly production of the well put into production in the i - th month in the j - th month, with the unit of ton; S0 represents the production time rate in the first month of the newly put - into - production well, which is determined according to the statistical rules of the newly put - into - production wells of each oilfield company or plate (oilfield) over the years, with the unit of day; S j represents the monthly production days, with the unit of day. After the second month of the new well's production, it produces at full time rate, which is determined according to the natural monthly calendar. S2, S3... S 12 correspond to the natural monthly calendar days of February, March... December respectively; N iRepresents the number of newly put into production wells per month, with the unit of well; Q′0 represents the predicted value of the initial production of the newly put into production wells, with the unit of ton / day; D′ 月 Represents the predicted value of the monthly comprehensive decline rate, with the unit of %.

[0088] S2.8: Set L = L + 1. If L < M, repeat steps S2.6 - S2.7; if L ≥ M, go to step S2.9.

[0089] S2.9: Set K = K + 1. If K < N, repeat steps S2.3 - S2.8; if K ≥ N, go to step S2.10.

[0090] S2.10: Obtain the sequence regarding the error ε K,L and select the minimum error min[ε K,L , and denote the first variable K corresponding to min[ε K,L as K min , and denote the second variable L corresponding to it as L min , then:

[0091] Q0 = Q0min + n·K min

[0092] D 月 = D 月 min + m·L min

[0093] The said Q0 represents the average initial production of newly put into production wells, and D 月 represents the average monthly comprehensive decline rate.

[0094] Step S3: Construct a real-time tracking and early warning model for new wells by using the average initial production of newly put into production wells and the average monthly comprehensive decline rate.

[0095] S3.1: Conduct real-time tracking of new wells by using the average initial production Q0 of newly put into production wells and the average monthly comprehensive decline rate D 月 Assume that the decline law of newly put into production wells per month in a certain branch company or plate (oilfield) is the same and conforms to exponential decline, that is, the monthly comprehensive decline rate is a constant. Assume that the initial production of newly put into production wells per month is the same. Then, the monthly production of newly put into production wells per month, the number of newly put into production wells per month, the average initial production of newly put into production wells, the monthly production time rate, and the average monthly comprehensive decline rate can establish the following relational expression:

[0096] where, i represents the production month, i = 1, 2, 3,..., 12; j represents the production month after production, j = i,..., 12; Q

[0097]

[0098] i,j ​Denote the monthly production volume (unit: "ton") of the wells put into production in the i-th month in the j-th month; S0 represents the production rate in the first month of the newly put into production wells, which is determined according to the statistical rules of the newly put into production wells in each oilfield branch company or plate (oilfield) over the years (unit: "day"); S j Denote the number of monthly production days (unit: "day"). After the second month of the newly put into production wells, they all produce at the full production rate, which is determined according to the natural monthly calendar. S2, S3... S 12 Correspond to the natural monthly calendar days of February, March... December respectively; N i Denote the number of newly put into production wells per month (unit: "well"); Q0 represents the initial production volume of the average newly put into production wells (unit: "ton / day"), which is determined according to the statistical rules of the newly put into production wells in each oilfield branch company over the years; D 月 Denote the average monthly comprehensive decline rate (unit: "%").

[0099] In this embodiment, taking the newly put into production wells in January as an example, the production volume of each month is respectively expressed as:

[0100] Production volume in January: Q 1,1 = S0 × N1 × Q0

[0101] Production volume in February: Q 1,2 = S2 × N1 × Q0

[0102] Production volume in March: Q 1,3 = S3 × N1 × Q(0) × (1 - D 月 )

[0103] Production volume in April: Q 1,4 = S4 × N1 × Q(0) × (1 - D 月 ) × (1 - D 月 ) = S4 × N1 × Q(0) × (1 - D 月 ) 2

[0104] ......

[0105] Production volume in December: Q 1,12 = S 12 × N1 × Q(0) × (1 - D 月 ) 10

[0106] In this embodiment, taking the newly put into production wells in March as an example, the production volume of each month is respectively expressed as:

[0107] Production volume in March: Q 3,3 = S0 × N3 × Q0

[0108] Production volume in April: Q 3,4 = S4 × N3 × Q0

[0109] Production volume in May: Q3,5 = S5 × N3 × Q0 × (1 - D 月 )

[0110] Output in June: Q 3,6 = S6 × N3 × Q0 × (1 - D 月 ) × (1 - D 月 ) = S6 × N3 × Q0 × (1 - D 月 ) 2

[0111] ……

[0112] Output in December: Q 3,12 = S 12 × N3 × Q0 × (1 - D 月 ) 8

[0113] In a certain month, add up the outputs of the newly drilled wells put into production in different months in that month, then the total output of that month can be obtained, which can be expressed monthly as:

[0114] Output in January: Q1 = Q 1,1

[0115] Output in February: Q2 = Q 1,2 + Q 2,2

[0116] Output in March: Q3 = Q 1,3 + Q 2,3 + Q 3,3

[0117] ……

[0118] Output in December: Q 12 = Q 1,12 + Q 2,12 +,..., + Q 12,12

[0119] Then the total output Q of the j-th month j can be expressed by the following relational expression:

[0120]

[0121] where Q i,j represents the monthly output (unit: "ton") of the wells put into production in the i-th month in the j-th month.

[0122] S3.2: According to the tracking results of real-time tracking of newly drilled wells, predict the annual output of newly drilled wells. If the output target deployed at the beginning of the year cannot be completed, give an early warning.

[0123] The model consists of four key parameters: the number of newly put into production wells, the initial production of newly put into production wells, the production rate of newly drilled wells, and the monthly comprehensive decline rate of newly drilled wells. In this embodiment, first, according to the actual data of the first 7 months, the average initial production of newly put into production wells and the average monthly comprehensive decline rate are calculated as 5.1 tons and 0.025 respectively through fitting and iterative calculation. Then, the production in August - December is further calculated, and the annual production of newly drilled wells is predicted to be 913,700 tons, which cannot meet the production target of 945,900 tons deployed at the beginning of the year, so a warning is issued. Therefore, the operation rhythm needs to be accelerated in August - December, with early production and ensuring the production rate, so as to ensure the realization of the annual production target. The real - time tracking and early warning model for newly drilled wells is as follows:

[0124]

[0125] The technical solution of this application can not only track the current production of newly drilled wells in real - time, but also predict the annual production of newly drilled wells in this development unit at any time according to the model. Comparing with the production deployed at the beginning of the year, if there is a large error, timely warning feedback is given and operation optimization suggestions are put forward.

[0126] Compared with the traditional measurement method for newly drilled wells, this application has the following prominent advantages: combining the monthly production workload and production effect, it can realize monthly real - time prediction of annual production and early warning; the comprehensive application results of various methods and iterative algorithms are mutually verified with the actual effect, reducing the systematic error and improving the accuracy and rationality of the prediction of newly drilled wells; real - time prediction of annual production and early warning to ensure the smooth completion of the production task; it can optimize the subsequent monthly production workload to ensure the completion of the annual production target. After nearly three years of implementation and application, 12 optimization suggestions are put forward, the operation efficiency of newly drilled wells is increased by 10%, and the completion rate of the annual deployed production task is 100%. Calculated at an oil price of $64 per barrel, the annual economic benefit is increased by more than 40 million yuan. This application can be further popularized and applied to the production allocation and tracking warning of measure production, ensuring the rationality of measure production allocation and the completion of the target, and can also be popularized and applied to the production allocation and tracking warning of conventional natural gas and unconventional oil and gas.

[0127] Corresponding to the above - mentioned embodiment, this application also provides a real - time tracking and early warning device for newly drilled wells.

[0128] See Figure 3 For the structural block diagram of a real - time tracking and early warning device for newly drilled wells provided by the embodiment of this application. As Figure 3 shown, it mainly includes the following modules.

[0129] The data acquisition module 301 is used to acquire the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years;

[0130] The data fitting module 302 is configured to fit the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit according to the number of newly put into production wells per month in previous years, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit.

[0131] The new well implementation tracking and early warning module 303 is configured to use the average initial production of newly put into production wells and the average monthly comprehensive decline rate to track new wells in real time, predict the annual production of new wells, and give an early warning if the production target deployed at the beginning of the year cannot be completed.

[0132] It should be noted that the specific content involved in the embodiments of the present application can be referred to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0133] Corresponding to the above embodiments, the embodiments of the present application also provide an electronic device.

[0134] See Figure 4 , which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 4 shown, the electronic device 400 may include: a processor 401, a memory 402, and a communication unit 403. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiments of the present application. It can be a bus structure, a star structure, and may also include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0135] Among them, the communication unit 403 is configured to establish a communication channel so that the electronic device can communicate with other devices.

[0136] The processor 401 is the control center of the electronic device, connecting various parts of the entire electronic device through various interfaces and lines, and executing various functions and / or processing data of the electronic device by running or executing software programs and / or modules stored in the memory 402, and calling data stored in the memory. The processor may be composed of an integrated circuit (IC). For example, it may be composed of a single packaged IC, or may be composed of connecting multiple packaged ICs with the same or different functions. For example, the processor 401 may only include a central processing unit (CPU). In the embodiment of the present application, the CPU may be a single operation core or may include multiple operation cores.

[0137] A memory 402 for storing execution instructions of a processor 401. The memory 402 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 memory, flash memory, a magnetic disk, or an optical disc.

[0138] When the execution instructions in the memory 402 are executed by the processor 401, the electronic device 400 is enabled to execute some or all of the steps in the above method embodiments.

[0139] Corresponding to the above embodiments, an embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium can store a program. When the program runs, it can control a device where the computer-readable storage medium is located to execute some or all of the steps in the above method embodiments. Specifically, the computer-readable storage medium can be a magnetic disk, an optical disc, a read-only memory (ROM), a random access memory (RAM), or the like.

[0140] Corresponding to the above embodiments, an embodiment of the present application further provides a computer program product. The computer program product includes executable instructions. When the executable instructions are executed on a computer, the computer is enabled to execute some or all of the steps in the above method embodiments.

[0141] In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent the cases of A existing alone, A and B existing simultaneously, and B existing alone. Here, A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one of the following" and its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0142] Those of ordinary skill in the art can realize that the various units and algorithm steps described in the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0143] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0144] In several embodiments provided in this application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0145] The above is only the specific implementation manner of this application. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all such changes or substitutions should be covered by the protection scope of this application. The protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A real-time tracking and early warning method for new wells, characterized in that, Including: Obtain the historical data of the target development unit; According to the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years, fit the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit; Use the average initial production of newly put into production wells and the average monthly comprehensive decline rate to construct a real-time tracking and early warning model for new wells.

2. The method according to claim 1, wherein The historical data includes the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years.

3. The method according to claim 1, wherein The fitting of the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit according to the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years includes: S2.1: Select the maximum value Q0max and the minimum value Q0min of the initial production of newly put into production wells of the target development unit over the years, and perform the following calculations: Where N is the number of copies of the initial production of newly put into production wells; S2.2: Set the first variable K, K = 1; S2.3: Calculate the predicted value Q′0 of the initial production of newly put into production wells: Q′0 = Q0min + n·K S2.4: Select the maximum value D 月 max and the minimum value D 月 min of the monthly comprehensive decline rates of the target development unit over the years, and perform the following calculations: Where M is the number of copies of the monthly comprehensive decline rate; S2.5: Set the second variable L, L = 1; S2.6: Calculate the predicted value D' of the monthly comprehensive decline rate 月 : D′ 月 = D 月 min + m·L S2.7: Calculate the error: ε K,L = |Q' j - Q j实际 | Where Among them, i represents the production start month, where i = 1, 2, 3,..., 12; j represents the production month after start-up, where j = i,..., 12; Q' i,j represents the predicted monthly production of the wells started in month i in month j; S0 represents the production time rate in the first month of the newly started wells; S j represents the number of production days in a month, and S2, S3... S 12 correspond to the natural calendar days of February, March... December respectively; N i represents the number of newly started wells in a month; Q'0 represents the predicted initial production value of the newly started wells; D' 月 represents the predicted monthly comprehensive decline rate; S2.8: Set L = L + 1. If L < M, repeat steps S2.6 - S2.7; if L ≥ M, go to step S2.9; S2.9: Set K = K + 1. If K < N, repeat steps S2.3 - S2.8; if K ≥ N, go to step S2.10; S2.10: Obtain the sequence regarding the error ε K,L , select the minimum error min[S K,L among them, and denote the first variable K corresponding to min[ε K,L as K min , and denote the second variable L corresponding to it as L min , then: Q0 = Q0min + n·K min D 月 = D 月 min + m·L min The Q0 represents the initial production of the average newly put into production wells, and D 月 represents the average monthly comprehensive decline rate.

4. The method according to claim 1, wherein The construction of a real-time tracking and early warning model for new wells using the average initial production of newly put into production wells and the average monthly comprehensive decline rate includes: Using the initial production Q0 of the average newly put into production wells and the average monthly comprehensive decline rate D 月 Carry out real-time tracking of new wells; According to the tracking results of real-time tracking of new wells, predict the annual production of new wells. If the production target deployed at the beginning of the year cannot be completed, an early warning is issued.

5. The method according to claim 4, characterized in that The real-time tracking is to predict the total monthly production of the target development unit in real time, and its calculation formula is as follows: Among them, Q j represents the total output of the target development unit in month j; Q i,j represents the monthly output of the wells put into production in month i in month j; i represents the production month, i = 1, 2, 3,..., 12; j represents the production month after production, j = i,..., 12.

6. The method according to claim 5, wherein Q i,j The calculation formula is as follows: Among them, S0 represents the production time rate in the first month of the newly put into production wells; S j represents the number of production days in a month, and S2, S3... S 12 correspond to the natural monthly calendar days of February, March... December respectively; N i represents the number of newly put into production wells in a month; Q0 represents the initial output of the average newly put into production wells; D 月 represents the average monthly comprehensive decline rate.

7. A real-time tracking and early warning device for new wells, characterized in that, Including: A data acquisition module for obtaining the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years; A data fitting module for fitting the average initial production of newly put into production wells and the average monthly comprehensive decline rate of the target development unit according to the number of newly put into production wells per month, the production rate at the time of production in the current month, the initial production of newly put into production wells, and the monthly comprehensive decline rate of the target development unit over the years; A new well implementation tracking and early warning module for using the average initial production of newly put into production wells and the average monthly comprehensive decline rate to perform real-time tracking of new wells, predicting the annual production of new wells, and issuing an early warning if the production target deployed at the beginning of the year cannot be completed.

8. An electronic device, characterized in that, Including: A processor; A memory; And a computer program, where the computer program is stored in the memory, and the computer program includes instructions. When the instructions are executed by the processor, the electronic device executes the method described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program runs, it controls the device where the computer-readable storage medium is located to execute the method according to any one of claims 1 to 6.

Images