A method and system for verifying the productivity of a single shale gas well

Abstract

The present invention belongs to the technical field of shale gas well capacity assessment, and in particular relates to a method and system for assessing the capacity of a single shale gas well. The method first obtains actual production data of a single shale gas well within a preset time period; then, based on the acquired production data, the actual production rate is calculated, and the number of shut-in days and the preset production rates for each stage are extracted from the production data using a preset semantic recognition model; then, the calculated actual production rate is compared with the preset production rates for each stage, and the number of shut-in days is compared with the preset shut-in days to generate comparison data; finally, a shale gas well capacity assessment model corresponding to each stage is constructed based on the production rates for each stage, and the comparison data and production data are used as input data for the shale gas well capacity assessment model to output the shale gas well capacity value. The present invention can solve the problem in the prior art of inaccurate assessment results caused by incomplete consideration of shale gas well capacity assessment factors.

Description

Technical Field

[0001] The present invention belongs to the technical field of shale gas well productivity verification, and in particular relates to a method and system for verifying the productivity of a single shale gas well. Background Art

[0002] Shale gas is an unconventional natural gas found in organic-rich shale formations, primarily composed of methane. Its unique properties and enormous potential make it an important component of the modern energy system. The development and utilization of shale gas not only enriches global energy supply but also promotes the diversification of the energy structure, and has far-reaching significance for ensuring energy security, promoting economic development, and protecting the environment.

[0003] Shale gas well capacity assessment is a crucial step in shale gas development projects. It directly determines the project's economic feasibility and the formulation of development strategies. Therefore, accurate capacity estimation can help decision makers optimize resource allocation, support investment decisions, manage assets, and plan production strategies.

[0004] There are many existing methods for estimating shale gas well productivity, including empirical formulas, geological modeling, and fluid dynamics analysis. However, the following key issues remain:

[0005] 1. Limitations of production data processing: Existing methods primarily focus on calculating total or average production, while ignoring the actual impact of production rate and shut-in time on productivity. The production rate reflects the actual production efficiency of a gas well, while shut-in time is constrained by multiple factors, both of which have a significant impact on the accuracy of production capacity assessment.

[0006] 2. Shale gas wells may experience temporary shutdowns during their operating cycles, possibly due to maintenance, technology upgrades, or in response to changes in market conditions. Therefore, the length of time a shale gas well is shut down directly affects its ability to resume production and long-term productivity, a factor that is often overlooked in existing technologies.

[0007] In summary, developing a new shale gas well productivity estimation method that can carefully consider the impact of production rate, shut-in time, and shut-in days on productivity is of great significance for improving estimation accuracy and optimizing development decisions. Summary of the Invention

[0008] The technical problem solved by the present invention is to provide a shale gas single well productivity assessment method and system to solve the problem in the prior art of inaccurate assessment results caused by incomplete consideration of shale gas well productivity assessment factors.

[0009] The basic solution provided by the present invention is a method for assessing the productivity of a single shale gas well, comprising:

[0010] S1: Obtain the actual production data of a single shale gas well within a preset time period;

[0011] S2: Calculate the actual production time rate based on the acquired production data, and extract the shut-in days and preset production time rates for each stage from the production data through a preset semantic recognition model;

[0012] S3: Compare the calculated actual production time rate with the preset production time rate for each stage, and compare the shut-in days with the preset shut-in days to generate comparison data;

[0013] S4: Construct a shale gas well productivity assessment model corresponding to each stage based on the production time rate of each stage, use the comparison data and production data as input data of the shale gas well productivity assessment model, and output the shale gas well productivity value.

[0014] Furthermore, the production data in S1 includes production time, daily gas production and remarks information.

[0015] Furthermore, the production time rates of each stage preset in S2 are specifically:

[0016] Obtain single well production time data, calendar day data and establish a standard knowledge base;

[0017] After preprocessing and calculation of the acquired data, screening and analysis are performed based on the standard knowledge base to generate production time rates at each stage that characterize the productivity of shale gas wells.

[0018] Further, the S2 includes:

[0019] S2-1: Calculate the actual production time rate based on the production data within the preset time period. The calculation formula is:

[0020]

[0021] S2-2: Build a semantic recognition model, input the remark information in the production data into the semantic recognition model, and output the numerical value of the number of days the well is shut in.

[0022] Further, the S4 includes:

[0023] S4-1: Construct multiple shale gas well capacity assessment models based on the characteristics of the production time rate at each stage, obtain historical production data of the shale gas well, and generate training samples and validation samples based on the characteristics of the production time rate at each stage. Train the staged shale gas well capacity assessment model using the training samples. After training, validate the staged shale gas well capacity assessment model using the validation samples until a fully trained staged shale gas well capacity assessment model is obtained.

[0024] S4-2: Input the comparison data and production data into the trained stage shale gas well productivity assessment model, determine the correlation between the actual production time rate in the comparison data and the preset production time rate in each stage, and determine the correlation between the shut-in days and the preset shut-in days, and calculate the shale gas well productivity value based on the correlation results.

[0025] Furthermore, the operating steps of the shale gas well productivity verification model in the above stage are as follows:

[0026] Determine the corresponding stage information of the actual production time rate in the received comparison data among the preset production time rates of each stage;

[0027] Determine the marking information of the shut-in days in the production data and the preset shut-in days;

[0028] Matching the corresponding stage shale gas well productivity verification model according to the corresponding stage information and marking information, and inputting the production data into the corresponding stage shale gas well productivity verification model;

[0029] The shale gas well productivity value is calculated based on the preset productivity verification days of the matched stage shale gas well productivity verification model and the daily gas production in the production data.

[0030] A shale gas single well productivity verification system, applied to the above-mentioned shale gas single well productivity verification method, comprises:

[0031] Data acquisition module: used to obtain the actual production data of a single shale gas well within a preset time period;

[0032] Production time rate calculation module: used to calculate the actual production time rate based on the acquired production data;

[0033] Semantic recognition module: used to identify shut-in days in production data using a preset semantic recognition model;

[0034] Data comparison module: The production time rate of each stage is preset, which is used to compare the calculated actual production time rate with the preset production time rate of each stage, and compare the shut-in days with the preset shut-in days to generate comparison data;

[0035] Capacity verification module: Build a shale gas well capacity verification model corresponding to each stage based on the production time rate of each stage, use the comparison data and production data as input data of the shale gas well capacity verification model, and output the shale gas well capacity value.

[0036] The principle and advantage of the present invention are: in this application, for the production capacity verification of a single shale gas well, its production data in a preset time period is first obtained, including production time, daily gas production and remark information. The production time and daily gas production can be used to calculate the production time rate of the single shale gas well, and the remark information can obtain the number of days the shale gas well is shut in. The obtained production time rate is compared with the preset production time rate of each stage, and then the relationship between the shut-in days and the preset shut-in days is compared, and the data is imported into the shale gas well production capacity verification model of each stage to obtain the shale gas well production capacity value corresponding to the production time rate at different stages.

[0037] Therefore, this application can comprehensively understand the production status and potential production capacity of a single shale gas well based on the production time rate and shut-in days of the single shale gas well, and at the same time use different calculation methods to verify the production capacity based on the characteristics of the production time rate at different stages, so as to provide more accurate production capacity information based on the different production conditions of the shale gas well. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flowchart of an embodiment of the present invention;

[0039] Figure 2 is an execution flow chart of an embodiment of the present invention;

[0040] Figure 3 This is a functional block diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following is further described in detail through specific implementation methods:

[0042] The embodiment is basically as shown in the attached Figure 1 A method for determining the productivity of a single shale gas well is shown in FIG. 1 , comprising:

[0043] S1: Obtain the actual production data of a single shale gas well within a preset time period; in this embodiment, the obtained production data includes production time, daily gas production and remark information. The preset time period is selected according to actual conditions. This application sets it to 30 days. Specifically, first obtain the actual production time, daily gas production and remark information of a single shale gas well within 30 days as production data. Among them, the remark information in this application includes normal operation, pressure recovery, well shut-in, well opening, etc., so as to obtain the operating status information of the single shale gas well.

[0044] S2: Calculate the actual production time rate based on the acquired production data, and extract the shut-in days and the preset production time rates for each stage from the production data through a preset semantic recognition model; S2 includes:

[0045] S2-1: Calculate the actual production time rate based on the production data within the preset time period. The calculation formula is:

[0046]

[0047] S2-2: Build a semantic recognition model, input the remark information in the production data into the semantic recognition model, and output the numerical value of the number of days the well is shut in.

[0048] Specifically, by calculating the actual production time rate, the production efficiency of the target shale gas well during the production time can be obtained. The production efficiency of the target shale gas well actively affects the production capacity of the shale gas well on the one hand, and is passively affected by the number of days of well closure on the other hand. Therefore, the number of days of well closure is obtained through a preset semantic recognition model. In this embodiment, the production data of the acquired shale gas well includes remark information, and the remark information contains the operating status information of the target shale gas well during the production time. Therefore, it is only necessary to perform text recognition and classification on the remark information through the semantic recognition model to obtain the remark representing the well closure status in the target shale gas well, such as the remark "well closure, pressure recovery", etc., and then determine the well closure days based on the duration of the well closure status in the remark information. The preset semantic recognition model in this application adopts the Transformer model.

[0049] After calculating the actual production time rate and shut-in days, the production time rate for each stage is preset. The implementation process is as follows:

[0050] Acquire single-well production time data and calendar day data and establish a standard knowledge base. The acquired data can effectively characterize the business strategies, production guidelines, production standards, and other systems of the company to which the shale gas single well belongs. The established standard knowledge base is established in accordance with some existing national standards for shale gas well production and enterprise-customized production standards, and can serve as the basis for dividing the production time rates of each stage of the company in accordance with actual conditions.

[0051] Then, the acquired single well production time data and calendar day data are preprocessed, including data cleaning, data unification, data conversion and other operations, so that the acquired data remains consistent and facilitates subsequent calculations;

[0052] When calculating the data obtained above, the performance data of different time periods in the obtained data are divided, and the performance data of the above enterprises are evaluated according to the scoring standards and weight ratios formulated by experts. After the evaluation is completed, the production time rate range corresponding to the enterprise in different production stages is obtained.

[0053] S3: Compare the calculated actual production time rate with the preset production time rate for each stage, and compare the well-shut-in days with the preset well-shut-in days to generate comparison data; in the comparison process of this embodiment, after the actual production time rate is calculated, it is compared with the preset production time rate for each stage to obtain the stage production time rate corresponding to the actual production time rate. Similarly, the relevant well-days are also preset for the production time rate for each stage. The actual well-shut-in days identified in the production data are compared with the preset well-shut-in days in the corresponding stage production time rate, so that accurate comparison data can be obtained.

[0054] S4: Construct a shale gas well productivity assessment model corresponding to each stage based on the production time rate of each stage, use the comparison data and production data as input data of the shale gas well productivity assessment model, and output the shale gas well productivity value. S4 includes:

[0055] S4-1: Construct multiple shale gas well capacity assessment models based on the characteristics of the production time rate at each stage, obtain historical production data of the shale gas well, and generate training samples and validation samples based on the characteristics of the production time rate at each stage. Train the staged shale gas well capacity assessment model using the training samples. After training, validate the staged shale gas well capacity assessment model using the validation samples until a fully trained staged shale gas well capacity assessment model is obtained.

[0056] S4-2: Input the comparison data and production data into the trained stage shale gas well productivity assessment model, determine the correlation between the actual production time rate in the comparison data and the preset production time rate in each stage, and determine the correlation between the shut-in days and the preset shut-in days, and calculate the shale gas well productivity value based on the correlation results.

[0057] In this application, in order to better calculate the production capacity value corresponding to the production time rate at each stage, a shale gas well production capacity verification model for each stage is constructed. By calling historical production data, the accuracy of the shale gas well production capacity verification model for each stage is trained. After the training is completed, the production data and comparison data are input into the shale gas well production capacity verification model for each stage, and the corresponding calculation is performed to obtain the production capacity value of a single shale gas well. To better reflect the solution of this application, an example is shown below:

[0058] Define the actual production time rate as ρ, the number of shut-in days as τ, and the production time as 30 days. Then, the steps for determining the production capacity of shale gas wells according to the preset production time rates at each stage are as follows: Figure 2 As shown, specifically:

[0059] When ρ = 100%, the production time rate of this stage is the production time rate of the first stage, in which the number of shut-in days is 0, which corresponds to the one-stage shale gas well capacity verification model. The one-stage shale gas well capacity verification model calculates the capacity verification of the target shale gas well by calculating the average daily gas production within 5 days as the capacity value.

[0060] When 95%≤ρ<100%, the production time rate of this stage is divided into the second stage production time rate in this application, which corresponds to the second stage shale gas well capacity verification model. At this time, it is necessary to consider the impact of the number of days of well closure on the capacity verification. Therefore, the second stage shale gas well capacity verification model calculates the average daily gas production within 15 days as the capacity value.

[0061] When 70%≤ρ<95%, the production time rate of this stage is divided into the third stage production time rate in this application, which corresponds to the three-stage shale gas well capacity verification model. At this time, it is necessary to perform the corresponding capacity calculation based on the comparison data of the number of days of well closure. Specifically, when τ<3, the average daily gas production within 30 days is calculated as the capacity value; when τ≥3, the daily gas production after removing the number of days of well closure is calculated as the capacity value.

[0062] When 50%≤ρ<70%, the production time rate of this stage is divided into the fourth stage production time rate in this application, which corresponds to the four-stage shale gas well capacity verification model. At this time, it is also necessary to calculate the capacity based on the comparison data of the number of days of well closure. Specifically, when τ<4, the average daily gas production within 30 days is calculated as the capacity value. Conversely, when τ≥4, the average daily gas production after removing the number of days of well closure is calculated as the capacity value.

[0063] When 20%≤ρ<50%, the production time rate of this stage is divided into the fifth stage production time rate in this application, which corresponds to the five-stage shale gas well capacity verification model. At this time, it is also necessary to calculate the capacity based on the comparison data of the number of days of well closure. Specifically, when τ<6, the average daily gas production within 30 days is calculated as the capacity value. Conversely, when τ≥6, the average daily gas production after removing the number of days of well closure is calculated as the capacity value.

[0064] When ρ<20%, the production time rate of this stage is divided into the sixth stage production time rate in this application, which corresponds to the six-stage shale gas well capacity verification model. At this time, it is also necessary to calculate the capacity based on the comparison data of the number of days of well closure. Specifically, when τ<22, the average daily gas production within 30 days is calculated as the capacity value. Conversely, when τ≥22, the average daily gas production after removing the number of days of well closure is calculated as the capacity value.

[0065] Therefore, the method for determining the production capacity of a single shale gas well provided in this application can comprehensively understand the production status and potential production capacity of a single shale gas well based on the production time rate and shut-in days of the single shale gas well. At the same time, different calculation methods are used to determine the production capacity based on the characteristics of the production time rate at different stages, thereby providing more accurate production capacity information based on the different production conditions of the shale gas well.

[0066] like Figure 3 As shown, in another embodiment of this embodiment, a shale gas single well productivity verification system is further included, which is applied to the above-mentioned shale gas single well productivity verification method, including:

[0067] Data acquisition module: used to obtain the actual production data of a single shale gas well within a preset time period;

[0068] Production time rate calculation module: used to calculate the actual production time rate based on the acquired production data;

[0069] Semantic recognition module: used to identify shut-in days in production data using a preset semantic recognition model;

[0070] Data comparison module: The production time rate of each stage is preset, which is used to compare the calculated actual production time rate with the preset production time rate of each stage, and compare the shut-in days with the preset shut-in days to generate comparison data;

[0071] Capacity verification module: Build a shale gas well capacity verification model corresponding to each stage based on the production time rate of each stage, use the comparison data and production data as input data of the shale gas well capacity verification model, and output the shale gas well capacity value.

[0072] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme are not described in detail here. Ordinary technicians in the field are aware of all common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the field can improve and implement this scheme in combination with their own abilities under the inspiration given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for assessing the productivity of a single shale gas well, characterized by: include: S1: Obtain the actual production data of a single shale gas well within a preset time period; S2: Calculate the actual production time rate based on the acquired production data, and extract the shut-in days and preset production time rates for each stage from the production data through a preset semantic recognition model; S3: Compare the calculated actual production time rate with the preset production time rate for each stage, and compare the shut-in days with the preset shut-in days to generate comparative data; S4: Constructing a shale gas well productivity assessment model corresponding to each stage based on the production time rate of each stage, using the comparison data and production data as input data for the shale gas well productivity assessment model, and outputting the shale gas well productivity value; The S4 includes: S4-1: Construct multiple shale gas well capacity assessment models based on the characteristics of the production time rate at each stage, obtain historical production data of the shale gas well, and generate training samples and validation samples based on the characteristics of the production time rate at each stage. Train the staged shale gas well capacity assessment model using the training samples. After training, validate the staged shale gas well capacity assessment model using the validation samples until a fully trained staged shale gas well capacity assessment model is obtained. S4-2: Input the comparison data and production data into the trained stage shale gas well productivity assessment model, determine the correlation between the actual production time rate in the comparison data and the preset production time rate in each stage, and determine the correlation between the shut-in days and the preset shut-in days, and calculate the shale gas well productivity value based on the correlation results.

2. The method for assessing the productivity of a single shale gas well according to claim 1, wherein: The production data in S1 includes production time, daily gas production and remarks.

3. The method for assessing the productivity of a single shale gas well according to claim 2, wherein: The preset production time rates of each stage in S2 are specifically: Obtain single well production time data, calendar day data and establish a standard knowledge base; After preprocessing and calculation of the acquired data, screening and analysis are performed based on the standard knowledge base to generate production time rates at each stage that characterize the productivity of shale gas wells.

4. The method for assessing the productivity of a single shale gas well according to claim 3, wherein: The S2 includes: S2-1: Calculate the actual production time rate based on the production data within the preset time period. The calculation formula is: S2-2: Build a semantic recognition model, input the remark information in the production data into the semantic recognition model, and output the numerical value of the number of days the well is shut in.

5. The method for assessing the productivity of a single shale gas well according to claim 4, wherein: The operating steps of the shale gas well productivity verification model in this stage are as follows: Determine the corresponding stage information of the actual production time rate in the received comparison data among the preset production time rates of each stage; Determine the marking information of the shut-in days in the production data and the preset shut-in days; Matching the corresponding stage shale gas well productivity verification model according to the corresponding stage information and marking information, and inputting the production data into the corresponding stage shale gas well productivity verification model; The shale gas well productivity value is calculated based on the preset productivity verification days of the matched stage shale gas well productivity verification model and the daily gas production in the production data.

6. A shale gas single well productivity verification system, applied to a shale gas single well productivity verification method as described in any one of claims 1 to 5 above, characterized in that: include: Data acquisition module: used to obtain the actual production data of a single shale gas well within a preset time period; Production time rate calculation module: used to calculate the actual production time rate based on the acquired production data; Semantic recognition module: used to identify shut-in days in production data using a preset semantic recognition model; Data comparison module: The production time rate of each stage is preset, which is used to compare the calculated actual production time rate with the preset production time rate of each stage, and compare the shut-in days with the preset shut-in days to generate comparison data; Capacity verification module: Build a shale gas well capacity verification model corresponding to each stage based on the production time rate of each stage, use the comparison data and production data as input data of the shale gas well capacity verification model, and output the shale gas well capacity value.

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