Well selection method for shale gas reservoir horizontal well foam drainage process

Abstract

The invention discloses a well selection method for a shale gas reservoir horizontal well foam drainage process, and relates to the technical field of petroleum and natural gas engineering, and the well selection method comprises the following steps: S1, collecting daily production data, S2, analyzing a monthly production change coefficient, S3, determining a decline index, S4, calculating a potential index, and S5, determining a foam drainage process effect. According to the method, the well stage coefficient is used for reflecting the production stage of the target evaluation well, if the well stage coefficient is larger, the production of the target well is in the middle stage and also belongs to the most transformation potential stage, the mining effect of the target well is reflected through the daily production decline index, and if the daily production decline index is larger, the current mining effect of the well is worse. The foam drainage yield increasing potential index is introduced to judge whether a foam drainage process is suitable or not, if the foam drainage yield increasing potential index is larger, the well is more suitable for increasing the yield by using the foam drainage process, otherwise, the well is not suitable for increasing the yield by using the foam drainage process, so that the construction risk is reduced, and orderly production is ensured.

Description

Technical Field

[0001] This invention relates to the field of oil and gas engineering technology, specifically to a well selection method for horizontal well bubble drainage technology in shale gas reservoirs. Background Technology

[0002] A method for evaluating the production enhancement potential of foam drainage technology in horizontal wells of shale gas reservoirs quantifies the production enhancement potential of foam drainage technology on shale gas wells by fitting daily production data. In the mid-to-late stages of shale gas production, many long horizontal downdip shale gas wells commonly experience fluid accumulation in the wellbore, severely restricting the production capacity of shale gas wells. Currently, foam drainage gas production technology is one of the most effective and widely used new production enhancement technologies. By injecting a certain amount of foaming agent into the wellbore, the accumulated fluid in the wellbore comes into contact with the foaming agent, generating a large amount of low-density foam system. This foam system carries water from the bottom of the wellbore to the surface with the gas flow, achieving the goal of removing the accumulated fluid at the bottom of the well. However, implementing foam drainage... The timing of drainage gas production technology mainly relies on human experience, which carries high construction risks. Therefore, it is necessary to assess the current production potential of shale wells. In the invention patent application number 202010808286.1, a "comprehensive geological evaluation method for a single shale gas well" is disclosed, including: Step 1, calculating the tight sandstone gas resource quantity using the analogy method, volume method, and basin simulation method; Step 2, using the Fürth method to perform a weighted average of the resource quantities calculated by the analogy method, volume method, and basin simulation method to obtain the tight sandstone gas resource quantity; Step 3, conducting lateral sealing analysis of the fault in the single shale gas well; Step 4, conducting lateral sealing analysis of the fault in the single shale gas well.

[0003] The aforementioned existing technologies have solved the problem of the difficulty in assessing the resource volume in shale gas wells. However, when using them, due to the complex flow patterns of fluid in the wellbore after many years of production in candidate wells, the production of single wells varies significantly. Furthermore, the diffusion and stabilization capabilities of the injected reagents during fluid flow in the wellbore are difficult to quantitatively evaluate. Moreover, the method relies entirely on the experience of the mining personnel for evaluating the production potential, and the timing of implementing the foam drainage gas production process also depends on human experience, which continuously increases the risk of construction. Summary of the Invention

[0004] The purpose of this invention is to provide a well selection method for the bubble drainage process of horizontal wells in shale gas reservoirs, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a well selection method for horizontal well bubble drainage technology in shale gas reservoirs, comprising the following steps: S1. Collect daily production data: Obtain the daily production data curve of the target appraisal well; S2. Analyze the monthly production change coefficient: Calculate the monthly production change coefficient for the daily production data curve in the form of months. The monthly production change coefficient represents the degree of fluctuation in daily production within a month. S3. Determine the decline index: Fit the monthly production change coefficient to obtain the well stage coefficient, and then use the initial daily production data and the final daily production data to determine the daily production decline index. S4. Calculate the potential index: Combine the well stage coefficient and the daily production decline index to determine the potential index for increased production from foam drainage; S5. Clarify the effect of the foaming process: Analyze the effect of the foaming process on the target evaluation well based on the foaming production potential index.

[0006] Preferably, step S2 includes the following steps: S201. Construct multiple monthly production grids with 30 days as a month. The width of the monthly production grid is the number of days, which is assigned a value of 30. The height of the monthly production grid is the highest daily production data value, which is also assigned a value of 30. Use the monthly production grids to divide the daily production data curve.

[0007] Preferably, step S2 further includes the following step: S202. The portion of the daily production data curve with less than 30 days will not be divided using monthly production grids; the portion with less than 30 days will be directly deleted. S203. Calculate the fractal dimension of the monthly production grid using the coefficient analysis formula, and use this as the monthly production variation coefficient. The specific coefficient analysis formula is as follows:

[0008] in, Indicates the first The monthly production change coefficient corresponding to the monthly production grid. This represents 0.1 times the side length of the monthly production grid, with a value of 0.1. This indicates that the side length of the grid produced in the month is... At that time, the number of grids on the Nissan data curve was encountered. This represents 0.25 times the side length of the monthly production grid, and its value is 0.25. This indicates that the side length of the grid produced in the month is... At that time, the number of grids in the Nissan data curve was encountered.

[0009] Preferably, step S3 specifically includes the following steps: S301. Fit the results using all monthly production change coefficients to obtain the corresponding fitting function. Calculate the well stage coefficients based on the slope in the fitting function. S302. The daily production decline index is obtained by using the declining index analysis formula to calculate the daily production data of the initial tenth day and the latest daily production data at the end of the curve. The specific formula for the declining index analysis is as follows:

[0010] in, Indicates the declining production index, This represents the initial Nissan production data. This indicates the latest Nissan data.

[0011] Preferably, step S4 specifically includes the following steps: S401. The well stage coefficient and the daily production decline index are combined using the potential index analysis formula to determine the bubble discharge production increase potential index. S402. The effectiveness of the soaking and rinsing process is divided into four levels: very poor, poor, medium and good.

[0012] Preferably, step S5 specifically includes the following steps: S501. Well selection criteria are determined based on the production potential index of foaming and drainage. When the production potential index is between 0 and 0.25, the effect level of the current foaming and drainage process is judged to be extremely poor, indicating that the foaming and drainage process is not suitable. S502. When the production potential index is between 0.25 and 0.50, the effect level of the current foaming and bleaching process is judged to be poor, indicating that the application of the foaming and bleaching process is not significant.

[0013] Preferably, step S5 further includes the following steps: S503. When the production potential index is between 0.50 and 0.75, the effect level of the current foaming and bleaching process is judged to be medium, indicating that the effect of applying the foaming and bleaching process is average. S504. When the production potential index is between 0.75 and 1.0, the current foaming and bleaching process is judged to be of good quality, indicating that the application of the foaming and bleaching process has a significant effect.

[0014] Preferably, the fitting function in S301 is specifically: ;

[0015] in, This represents the monthly production change coefficient. Indicates the slope value. Represents the intercept value. Indicates parameters, This represents the well stage coefficient.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention obtains the daily production data curve of the target appraisal well, calculates the monthly production variation coefficient according to the monthly data curve, and uses the monthly production variation coefficient to clearly represent the fluctuation of daily production within a month, which facilitates subsequent analysis. At the same time, a well stage coefficient is used to reflect the production stage of the target appraisal well. If the well stage coefficient is larger, it indicates that the production of the target well is more in the middle stage and belongs to the stage with the greatest potential for improvement. The daily production decline index is used to reflect the exploitation effect of the target well. If the daily production decline index is larger, the current exploitation effect of the well is worse, and vice versa. The foam drainage production potential index is introduced to determine whether the foam drainage process is suitable. If the foam drainage production potential index is larger, it indicates that the well is more suitable for the foam drainage process to increase production, and vice versa. This reduces construction risks and ensures orderly production. Attached Figure Description

[0017] Figure 1 An overall method flowchart is provided for embodiments of the present invention; Figure 2 The target well daily gas production dynamic curve is provided for an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figures 1-2 This invention provides a technical solution: a well selection method for horizontal well foaming and drainage technology in shale gas reservoirs, comprising the following steps: S1. Collect daily production data: Obtain the daily production data curve of the target appraisal well; S2. Analyze the monthly production change coefficient: Calculate the monthly production change coefficient for the daily production data curve in the form of months. The monthly production change coefficient represents the degree of fluctuation in daily production within a month. S3. Determine the decline index: Fit the monthly production change coefficient to obtain the well stage coefficient, and then use the initial daily production data and the final daily production data to determine the daily production decline index. S4. Calculate the potential index: Combine the well stage coefficient and the daily production decline index to determine the potential index for increased production from foam drainage; S5. Clarify the effect of the foaming process: Analyze the effect of the foaming process on the target evaluation well based on the foaming production potential index.

[0020] S2 includes the following steps: S201. Construct multiple monthly production grids with 30 days as a month. The width of the monthly production grid is the number of days, which is assigned a value of 30. The height of the monthly production grid is the highest daily production data value, which is also assigned a value of 30. Use the monthly production grids to divide the daily production data curve. S2 also includes the following steps: S202. The portion of the daily production data curve with less than 30 days will not be divided using monthly production grids; the portion with less than 30 days will be directly deleted. S203. Calculate the fractal dimension of the monthly production grid using the coefficient analysis formula, and use this as the monthly production variation coefficient. The specific coefficient analysis formula is as follows:

[0021] in, Indicates the first The monthly production change coefficient corresponding to the monthly production grid. This represents 0.1 times the side length of the monthly production grid, with a value of 0.1. This indicates that the side length of the grid produced in the month is... At that time, the number of grids on the Nissan data curve was encountered. This represents 0.25 times the side length of the monthly production grid, and its value is 0.25. This indicates that the side length of the grid produced in the month is... At that time, the number of grids in the Nissan data curve were accessed; S3 specifically includes the following steps: S301. Fit all monthly production change coefficients to obtain the corresponding fitting function. Calculate the well stage coefficient based on the slope in the fitting function. The larger the well stage coefficient, the more the production of the target evaluation well is in the middle stage, and it is also the stage with the greatest potential for transformation. S302. Using the decline index analysis formula, the daily production data of the initial tenth day and the latest daily production data at the end of the curve are used to obtain the daily production decline index. The daily production decline index represents the well's production effectiveness. The larger the daily production decline index, the worse the well's current production effectiveness. The specific formula for the decline index analysis is as follows:

[0022] in, Indicates the declining production index, This represents the initial Nissan production data. This indicates the latest Nissan data; S4 specifically includes the following steps: S401. The well stage coefficient and daily production decline index are combined using the potential index analysis formula to determine the foam drainage production enhancement potential index. The larger the foam drainage production enhancement potential index, the more suitable the well is for increasing production using the foam drainage process, thus achieving the purpose of quantitative evaluation. The specific potential index analysis formula is as follows:

[0023] in, This indicates the potential for increased production of foam. This represents the maximum well stage coefficient of the block. Indicates the well stage coefficient. This represents the maximum daily production decline index of the block. This indicates the declining production index; S402. The effectiveness of the soaking and draining process is divided into four levels: very poor, poor, medium and good. S5 specifically includes the following steps: S501. Well selection criteria are determined based on the production potential index of foaming and drainage. When the production potential index is between 0 and 0.25, the effect level of the current foaming and drainage process is judged to be extremely poor, indicating that the foaming and drainage process is not suitable. S502. When the production potential index is between 0.25 and 0.50, the effect level of the current foaming and bleaching process is judged to be poor, indicating that the application of the foaming and bleaching process is not significant. S5 also includes the following steps: S503. When the production potential index is between 0.50 and 0.75, the effect level of the current foaming and bleaching process is judged to be medium, indicating that the effect of applying the foaming and bleaching process is average. S504. When the production potential index is between 0.75 and 1.0, the current foaming and bleaching process is judged to be of good quality, indicating that the application of the foaming and bleaching process is effective. The fitting function in S301 is as follows: ;

[0024] in, This represents the monthly production change coefficient. Indicates the slope value. Represents the intercept value. Indicates parameters, This represents the well stage coefficient.

[0025] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0026] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A well selection method for horizontal well bubble drainage technology in shale gas reservoirs, characterized in that, The method includes the following steps: S1. Collect daily production data: Obtain the daily production data curve of the target appraisal well; S2. Analyze the monthly production change coefficient: Calculate the monthly production change coefficient for the daily production data curve in the form of months. The monthly production change coefficient represents the degree of fluctuation in daily production within a month. S3. Determine the decline index: Fit the monthly production change coefficient to obtain the well stage coefficient, and then use the initial daily production data and the final daily production data to determine the daily production decline index. S4. Calculate the potential index: Combine the well stage coefficient and the daily production decline index to determine the potential index for increased production from foam drainage; S5. Clarify the effect of the foaming process: Analyze the effect of the foaming process on the target evaluation well based on the foaming production potential index.

2. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 1, characterized in that: S2 includes the following steps: S201. Construct multiple monthly production grids with 30 days as a month. The width of the monthly production grid is the number of days, which is assigned a value of 30. The height of the monthly production grid is the highest daily production data value, which is also assigned a value of 30. Use the monthly production grids to divide the daily production data curve.

3. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 2, characterized in that: S2 further includes the following steps: S202. The portion of the daily production data curve with less than 30 days will not be divided using monthly production grids; the portion with less than 30 days will be directly deleted. S203. Calculate the fractal dimension of the monthly production grid using the coefficient analysis formula, and use this as the monthly production variation coefficient. The specific coefficient analysis formula is as follows: in, Indicates the first The monthly production change coefficient corresponding to the monthly production grid. This represents 0.1 times the side length of the monthly production grid, with a value of 0.

1. This indicates that the side length of the grid produced in the month is... At that time, the number of grids on the Nissan data curve was encountered. This represents 0.25 times the side length of the monthly production grid, and its value is 0.

25. This indicates that the side length of the grid produced in the month is... At that time, the number of grids in the Nissan data curve was encountered.

4. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 1, characterized in that: S3 specifically includes the following steps: S301. Fit the results using all monthly production change coefficients to obtain the corresponding fitting function. Calculate the well stage coefficients based on the slope in the fitting function. S302. The daily production decline index is obtained by using the decline index analysis formula to calculate the daily production data of the initial tenth day and the latest daily production data at the end of the curve.

5. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 1, characterized in that: S4 specifically includes the following steps: S401. The well stage coefficient and the daily production decline index are combined using the potential index analysis formula to determine the bubble discharge production increase potential index. S402. The effectiveness of the soaking and rinsing process is divided into four levels: very poor, poor, medium and good.

6. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 1, characterized in that: S5 specifically includes the following steps: S501. Well selection criteria are determined based on the production potential index of foaming and drainage. When the production potential index is between 0 and 0.25, the effect level of the current foaming and drainage process is judged to be extremely poor, indicating that the foaming and drainage process is not suitable. S502. When the production potential index is between 0.25 and 0.50, the effect level of the current foaming and bleaching process is judged to be poor, indicating that the application of the foaming and bleaching process is not significant.

7. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 6, characterized in that: S5 further includes the following steps: S503. When the production potential index is between 0.50 and 0.75, the effect level of the current foaming and bleaching process is judged to be medium, indicating that the effect of applying the foaming and bleaching process is average. S504. When the production potential index is between 0.75 and 1.0, the current foaming and bleaching process is judged to be of good quality, indicating that the application of the foaming and bleaching process has a significant effect.

8. The well selection method for the horizontal well bubble discharge process in shale gas reservoirs according to claim 4, characterized in that: The fitting function in S301 is specifically as follows: in, This represents the monthly production change coefficient. Indicates the slope value. Represents the intercept value. Indicates parameters, This represents the well stage coefficient.

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