Method and device for evaluating final extraction information of coal-bed gas well
By acquiring time-series gas production data from coalbed methane wells, determining and solving the functional relationship, the problem of inaccurate assessment of the final production information of coalbed methane wells in existing technologies is solved, achieving accurate assessment under various well conditions and having wide applicability.
Patent Information
- Application Number
- CN202411293440.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-14
- Publication Date
- 2026-03-17
AI Technical Summary
Existing decline models cannot effectively assess the final recovery information of coalbed methane wells, especially when the gas production curve is irregular and fluctuates greatly, making it impossible to accurately assess the final recovery level.
By acquiring time-series gas production data of the target coalbed methane well, the functional relationship between cumulative production time and cumulative gas production is determined. The relationship is then transformed to obtain a linear relationship, and the unknown constant is solved by linear regression fitting, thereby calculating the final production information.
It can accurately assess the final production information of coalbed methane wells even when the gas production curve is irregular and fluctuates greatly. It is applicable to various well conditions, including the production increase stage, the production stabilization stage, and the production decline stage, thus improving the accuracy and applicability of the assessment.
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Figure CN121681990A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of coalbed methane extraction technology, and in particular to a method and apparatus for evaluating the final production information of a coalbed methane well. Background Technology
[0002] In coalbed methane development, it is necessary to assess the final production information of coalbed methane wells, such as the final cumulative gas production or the final recovery level. Currently, in the fields of oilfield development and coalbed methane development, the assessment of production information (such as the final recovery level) is mostly based on decline models (such as the Arps decline model, the Joshi decline model, etc.).
[0003] However, the decline model is applicable to the production decline phase, but not to the production increase or stabilization phase. Furthermore, for coalbed methane wells, the actual production curve is sometimes irregular and fluctuates significantly. The current decline model is only suitable for wells with relatively smooth and monotonic daily production curves, and cannot be applied to wells with large fluctuations in their daily production curves. Summary of the Invention
[0004] To address or at least partially address the aforementioned technical problems, embodiments of this disclosure provide a method and apparatus for evaluating the final production information of coalbed methane wells.
[0005] In a first aspect, embodiments of this disclosure provide a method for evaluating coalbed methane well production information. The method includes: acquiring time-series gas production data of a target coalbed methane well; determining a first functional relationship between cumulative production time and cumulative gas production based on the time-series gas production data; wherein the first functional relationship contains an unknown constant to be solved; transforming the first functional relationship to obtain a second functional relationship conforming to a linear relationship; wherein in the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is a variable related to both the cumulative production time and the cumulative gas production; using the independent variable and the dependent variable as the horizontal and vertical coordinates of target data points respectively, performing linear regression fitting on the target data points to obtain the fitting slope and fitting intercept values in the second functional relationship and calculating the unknown constant; substituting the calculated unknown constant into the first functional relationship for calculation to obtain the evaluated production information of the target coalbed methane well.
[0006] In some embodiments, the aforementioned assessed production information is one of the following: the final cumulative gas production of the target coalbed methane well and the final recovery level of the target coalbed methane well. In some embodiments, substituting the calculated unknown constant into the first functional relationship to obtain the assessed production information of the target coalbed methane well includes: substituting the calculated unknown constant into the first functional relationship, such that the unknown constant in the first functional relationship is represented by the fitted slope value and the fitted intercept value, to obtain a relationship between the cumulative gas production and the cumulative production time; and taking the limit of the relationship to obtain the final cumulative gas production of the target coalbed methane well. Alternatively, in other embodiments, the calculated unknown constant is substituted into the first functional relationship to calculate the evaluation and production information of the target coalbed methane well. This includes: substituting the calculated unknown constant into the first functional relationship, such that the unknown constant in the first functional relationship is represented by the fitted slope value and the fitted intercept value, to obtain the relationship between the cumulative gas production and the cumulative production time; taking the limit of the relationship to obtain the final cumulative gas production of the target coalbed methane well; and calculating the ratio of the final cumulative gas production to the geological reserves of the target coalbed methane well, wherein the ratio is used as the final production level of the target coalbed methane well.
[0007] In some embodiments, the gas production in the above-mentioned time-series gas production data is the actual gas production obtained by sequentially counting the production time starting from the initial gas production time, and the corresponding time-series statistical period is one of the following: day or month.
[0008] In some embodiments, determining the first functional relationship between cumulative production time and cumulative gas production based on the aforementioned time-series gas production data includes: calculating the cumulative production time and its corresponding cumulative gas production according to the production time; based on a first correlation, using variables related to the cumulative production time as the abscissa of the data points, and based on a second correlation, using variables related to the cumulative gas production as the ordinate of the data points, to draw one or more scatter plots; at least one of the variables corresponding to the abscissa and ordinate differs among the scatter plots; selecting a target scatter plot from the aforementioned one or more scatter plots; the distribution trend curve corresponding to each scatter point in the target scatter plot is a smooth curve and the value of the ordinate tends to stabilize as the value of the abscissa increases; and determining the functional relationship corresponding to the target scatter plot as the first functional relationship.
[0009] In some embodiments, the first functional relationship described above is:
[0010]
[0011] Where N represents the cumulative gas production; lg represents the logarithm to base 10, which is a commonly used logarithm; Nm and t m t represents the unknown constant to be solved; t represents the cumulative production time.
[0012] In some embodiments, the second functional relationship described above is:
[0013]
[0014] In the second functional relationship mentioned above, the slope corresponding to the independent variable of cumulative production time is... Intercept is The dependent variable is the ratio of the cumulative production time to the logarithm of the cumulative gas production.
[0015] Secondly, embodiments of this disclosure provide an evaluation device for coalbed methane well production information. The device includes: a data acquisition module, a first function determination module, a second function determination module, a linear regression processing module, and an evaluation module. The data acquisition module is used to acquire time-series gas production data of a target coalbed methane well. The first function determination module is used to determine a first functional relationship between cumulative production time and cumulative gas production based on the time-series gas production data; wherein, the first functional relationship contains an unknown constant to be solved. The second function determination module is used to transform the first functional relationship to obtain a second functional relationship that conforms to a linear relationship. In the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is a variable related to both the cumulative production time and the cumulative gas production. The linear regression processing module is used to use the independent variable and the dependent variable as the horizontal and vertical coordinates of the target data points, respectively, to perform linear regression fitting on the target data points, obtain the fitting slope and fitting intercept values in the second functional relationship, and calculate the unknown constant. The aforementioned evaluation module is used to substitute the calculated unknown constants into the aforementioned first functional relationship to perform calculations and obtain the evaluation and production information of the aforementioned target coalbed methane well.
[0016] In some embodiments, the first functional relationship in the above-described apparatus is:
[0017]
[0018] Where N represents the cumulative gas production; lg represents the logarithm to base 10, which is a commonly used logarithm; N m and t m represents the unknown constant to be solved; t represents the cumulative production time;
[0019] The second functional relationship mentioned above is:
[0020]
[0021] In the second functional relationship mentioned above, the slope corresponding to the independent variable of cumulative production time is... Intercept is The dependent variable is the ratio of the cumulative production time to the logarithm of the cumulative gas production.
[0022] Thirdly, embodiments of this disclosure provide an electronic device. The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus; the memory stores computer programs; and the processor, when executing the program stored in the memory, implements the aforementioned method for evaluating the final production information of coalbed methane wells.
[0023] Fourthly, embodiments of this disclosure provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for evaluating the final production information of a coalbed methane well.
[0024] The technical solutions provided in the embodiments of this disclosure have at least some or all of the following advantages:
[0025] Based on the time-series gas production data of the target coalbed methane well, a first functional relationship between cumulative production time and cumulative gas production is determined. This first functional relationship contains unknown constants to be solved. It is derived from the distribution trend curve of variables related to cumulative production time (as the x-axis) and variables related to cumulative gas production (as the y-axis). This distribution trend curve is smooth, and the y-axis value tends to stabilize as the x-axis value increases. Therefore, the first functional relationship obtained here can characterize the inherent correlation between cumulative gas production and cumulative production time. By transforming the first functional relationship, a second functional relationship conforming to a linear relationship is obtained. In this second functional relationship, the independent variable is the cumulative production time, and the dependent variable is a variable related to both the cumulative production time and the cumulative gas production. By using the aforementioned independent and dependent variables as the horizontal and vertical coordinates of the target data points respectively, linear regression fitting is performed on the target data points to obtain the fitting slope and fitting intercept values in the second functional relationship and to calculate the aforementioned unknown constants. The calculated unknown constants are then substituted into the first functional relationship for calculation to obtain the evaluation production information of the target coalbed methane well. The evaluation method for the final production information of coalbed methane wells provided in this embodiment can effectively evaluate production information in the face of single wells with irregular and fluctuating gas production curves, and / or when the single well is in the production increase stage or the stable production stage, filling the gap in related technologies for the difficulty in evaluating such situations. It is also applicable to various well conditions such as smooth gas production curves or production decline stages, and has wide applicability, thereby enabling effective evaluation of final production information in the face of various production stages and production curve types. Attached Figure Description
[0026] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.
[0027] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.
[0028] Figure 1 A flowchart illustrating a method for evaluating the final production information of a coalbed methane well according to an embodiment of the present disclosure is shown schematically.
[0029] Figure 2 A schematic diagram of the gas production curve of time-series gas production data of a target coalbed methane well according to an embodiment of the present disclosure is shown.
[0030] Figure 3 A detailed implementation flowchart of step S120 according to an embodiment of the present disclosure is illustrated schematically;
[0031] Figure 4 A schematic diagram of the distribution trend curve of a target scatter plot according to an embodiment of the present disclosure is shown.
[0032] Figure 5 A schematic diagram of the linear fitting curve corresponding to the second functional relationship obtained after linear regression fitting according to an embodiment of the present disclosure is shown.
[0033] Figure 6 A structural block diagram of an apparatus for evaluating the final production information of a coalbed methane well according to an embodiment of the present disclosure is shown schematically.
[0034] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation
[0035] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.
[0036] The first exemplary embodiment of this disclosure provides a method for evaluating the final production information of a coalbed methane well. The evaluation method of this embodiment can be performed by an electronic device with computing capabilities.
[0037] The gas production of a coalbed methane well depends on geological conditions and development technology. For a specific coalbed methane well, given its geological conditions, well type, and stimulation technology, its gas production capacity is already determined and reflected in the preliminary production data. Therefore, the final production information of each single well can be evaluated based on the preliminary production data, which is an important part of production testing. It should be noted that the evaluation method provided in this disclosure is a final production information evaluation conducted after the target coalbed methane well has been developed and some time-series gas production data is available, given that the stimulation technology and geological conditions are determined. Accurate evaluation is possible only if the geological conditions, well type, and stimulation technology are determined, and the reservoir state does not undergo significant further disturbance or secondary stimulation, such as not drilling new wells near the predicted target coalbed methane well, not changing the stimulation technology, or not conducting secondary well development based on previous development.
[0038] Furthermore, through extensive verification using field production data, it has been found that the cumulative production time and cumulative gas production of coalbed methane wells under various well conditions satisfy certain functional relationships (e.g., the first functional relationship described in the embodiments of this disclosure), and after transformation, a linear functional relationship can be obtained (e.g., the second functional relationship described in the embodiments of this disclosure). This serves as an empirical formula with good applicability in the field. Since a linear relationship exists, only a portion of the data needs to be obtained to calculate the fitting slope and fitting intercept values, which can then be used to assess or predict the entire life cycle of coalbed methane wells.
[0039] Figure 1 A flowchart illustrating a method for evaluating the final production information of a coalbed methane well according to an embodiment of the present disclosure is shown schematically.
[0040] Reference Figure 1 As shown, the method for evaluating the final production information of coalbed methane wells provided in the embodiments of this disclosure includes the following steps: S110, S120, S130, S140 and S150.
[0041] In step S110, time-series gas production data of the target coalbed methane well is obtained.
[0042] The evaluation method provided in the embodiments of this disclosure can effectively solve the problem in related technologies that it is impossible to evaluate the final production information (e.g., the degree of final production) of single wells with irregular and highly fluctuating gas production curves, or that the evaluation accuracy is poor. It can also be widely applied to various well conditions, such as at least one of the following: irregular gas production curve, highly fluctuating gas production curve, smooth gas production curve, well in the production increase stage, well in the stable production stage, well in the production decline stage, etc. It can perform personalized evaluation of the final production information of a single well based on the known gas production data of various well conditions.
[0043] In some embodiments, the magnitude of gas production fluctuations is determined by one or more of the following methods:
[0044] If the difference span of peak-valley differences exceeds the first set value (different values are selected based on the cumulative production time of the gas production curve; the shorter the cumulative production time, the smaller the corresponding preset number), it indicates that the fluctuation is large. For example, if there are 8 peak-valley differences and the difference span of these 8 peak-valley differences (selecting the 8 peak-valley differences and taking the maximum value of the difference results) exceeds the first set value, it is considered that the fluctuation is large.
[0045] If the difference between the peak-to-valley difference of the overall gas production and the peak-to-valley difference of the gas production within a time period exceeds the second set value, it indicates that the fluctuation is large. By dividing the gas production curve into time periods according to the time sequence, each time period contains at least one peak and at least one trough. The difference between the peak and trough within the time period is calculated, and the difference between the maximum peak and minimum trough of the overall gas production is also calculated. The difference between the two peak-to-valley differences is calculated. If this difference exceeds the second set value, it is considered that the fluctuation is large.
[0046] If the standard deviation of the gas production curve is greater than the third set value, it is considered to have large fluctuations.
[0047] In some embodiments, the gas production in the above time-series gas production data is the actual gas production obtained by sequentially counting the production time starting from the initial gas production time. The corresponding time-series statistical period is one of the following: day or month, and the corresponding gas production curve can be a daily gas production curve or a monthly gas production curve.
[0048] Figure 2 A schematic diagram of the gas production curve of time-series gas production data of a target coalbed methane well according to an embodiment of the present disclosure is shown.
[0049] Taking a coalbed methane well (referred to as well X1) as an example, well X1 went into production in September 2008 and has been producing for more than 5,600 days. The corresponding gas production curve is as follows: Figure 2 As shown, from Figure 2 As can be seen, the gas production curve of well X1 is a daily production curve, and the overall curve is irregular and fluctuates greatly.
[0050] Applying the conventional Arps decreasing method to this daily production curve fails to achieve the expected accurate fit, resulting in inaccurate assessments of the final harvest information (e.g., the degree of final harvest).
[0051] In view of this, an evaluation method including steps S110 to S150 is provided. It can effectively evaluate the production information of single wells with irregular and fluctuating gas production curves, and / or single wells in the production increase or stable production stage. It fills the gap in related technologies for evaluating such situations. Moreover, the evaluation method is also applicable to various well conditions such as smooth gas production curves or production decline stage, and has wide applicability.
[0052] In step S120, based on the aforementioned time-series gas production data, a first functional relationship between the cumulative production time and the cumulative gas production is determined; wherein, the aforementioned first functional relationship contains an unknown constant to be solved.
[0053] Figure 3 A detailed implementation flowchart of step S120 according to an embodiment of the present disclosure is shown schematically.
[0054] Reference Figure 3 As shown, in step S120 above, the first functional relationship between cumulative production time and cumulative gas production is determined based on the above time-series gas production data, including the following steps: S310, S320, S330 and S340.
[0055] In step S310, the cumulative production time and its corresponding cumulative gas production are calculated based on the cumulative production time.
[0056] For example, if the time-series statistical period for gas production data is days, then the corresponding production time is days. The cumulative production time can be accumulated by days, weeks, or months, etc. Taking the accumulation by days as an example, the cumulative gas production corresponding to the cumulative production time can be: the cumulative gas production within 1 day of production, the cumulative gas production within 2 days (the sum of the gas production on the 1st and 2nd days of production), the cumulative gas production within 3 days (the sum of the gas production from the 1st to the 3rd day of production), and so on, which can yield the cumulative gas production over more than 5600 days.
[0057] In step S320, based on the first correlation, the variable related to the cumulative production time is used as the horizontal axis of the data point, and based on the second correlation, the variable related to the cumulative gas production is used as the vertical axis of the data point, and one or more scatter plots are drawn; wherein at least one of the variables corresponding to the horizontal and vertical axes of each scatter plot is different.
[0058] In some embodiments, the first correlation may use the cumulative production time itself as the x-axis, or the reciprocal or logarithm of the cumulative production time as the x-axis; in the second correlation, the reciprocal, derivative, or natural logarithm of the cumulative gas production may be used as the y-axis. The first and second correlations can be adjusted and tested according to the actual distribution of data points.
[0059] If a scatter plot, after fitting the distribution trend of each scatter point, meets the following conditions: it produces a smooth curve and the value of the ordinate tends to stabilize as the value of the horizontal axis increases, then this scatter plot can be identified as the target scatter plot. If the distribution trend curve of one or more scatter plots does not meet the above conditions, then the first correlation and the second correlation need to be adjusted to obtain a new scatter plot until the target scatter plot that meets the above conditions is obtained.
[0060] In step S330, a target scatter plot is selected from one or more of the above scatter plots; the distribution trend curve corresponding to each scatter point in the target scatter plot is a smooth curve and the value of the vertical axis tends to be stable as the value of the horizontal axis increases.
[0061] Figure 4 A schematic diagram of the distribution trend curve of a target scatter plot according to an embodiment of the present disclosure is shown.
[0062] For example, by processing time-series gas production data according to steps S310 to S330, a target scatter plot that meets the set conditions is obtained. The distribution trend curve of this target scatter plot is as follows: Figure 4 As shown, the curve is smooth overall, and the value of the vertical axis tends to stabilize as the value of the horizontal axis increases.
[0063] In step S340, the functional relationship corresponding to the above target scatter plot is determined as the first functional relationship.
[0064] Reference Figure 4 As shown in the above target scatter plot, the horizontal axis represents the cumulative production time t, and the vertical axis represents the common logarithm of the cumulative gas production lg(N).
[0065] In some embodiments, the first functional relationship described above is:
[0066]
[0067] Where N represents the cumulative gas production; lg represents the logarithm to base 10, which is a commonly used logarithm; N m and t m t represents the unknown constant to be solved; t represents the cumulative production time.
[0068] In step S130, the first functional relationship is transformed to obtain a second functional relationship that conforms to a linear relationship; wherein, in the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is a variable that is related to both the cumulative production time and the cumulative gas production.
[0069] In some embodiments, by transforming the first functional relation corresponding to formula (1), the second functional relation is obtained as follows:
[0070]
[0071] In the second functional relationship mentioned above, the slope corresponding to the independent variable of cumulative production time t is... Intercept is The dependent variable is the ratio of the cumulative production time to the logarithm of the cumulative gas production.
[0072] In step S140, the above independent variables and the above dependent variables are respectively used as the horizontal and vertical coordinates of the target data points, and linear regression fitting is performed on the above target data points to obtain the fitting slope value and fitting intercept value in the above second function relationship and to solve the above unknown constant.
[0073] Figure 5 A schematic diagram of the linear fitting curve corresponding to the second functional relationship obtained after linear regression fitting according to an embodiment of the present disclosure is shown.
[0074] By using the independent variable (e.g., cumulative production time t) in the second functional relationship as the x-axis of the target data point and the dependent variable (the ratio of the cumulative production time to the logarithm of the cumulative gas production, t / lg(N)) as the y-axis of the target data point, a linear regression fitting of the target data point can be performed to obtain the fitting slope value k and the fitting intercept value b in the second functional relationship. In some embodiments, the fitting slope value k and the fitting intercept value b are required to be accurate to at least four decimal places. For example, refer to... Figure 5 As shown, the correlation coefficient R of the linear fit 2 The value reached 0.9999; in the linear fitting curve corresponding to the second function relationship obtained after linear regression fitting, the fitting slope value k = 0.1419 and the fitting intercept value b = 13.7920.
[0075] In embodiments of this disclosure, the unknown constant can also be calculated based on the relationship between the fitted slope value and the fitted intercept value and the unknown constant to be solved.
[0076] For example, the fitted slope value k satisfies the following expression:
[0077]
[0078] The fitted intercept value b satisfies the following expression:
[0079]
[0080] The unknown constant N to be solved can be obtained from the known fitting slope value. m and t m The calculation relationship is shown in the following formula:
[0081]
[0082] In step S150, the calculated unknown constant is substituted into the first functional relationship mentioned above for calculation to obtain the evaluation and production information of the target coalbed methane well.
[0083] In some embodiments, the above-mentioned assessment of production information is one of the following: the final cumulative gas production of the target coalbed methane well, and the final production level of the target coalbed methane well.
[0084] In some embodiments, when the assessed production information is the final cumulative gas production, in step S150, the calculated unknown constant is substituted into the first functional relationship for calculation to obtain the assessed production information of the coalbed methane well, including:
[0085] Substitute the calculated unknown constants into the first functional relationship above, so that the unknown constants in the first functional relationship above are represented by the above-mentioned fitting slope value and the above-mentioned fitting intercept value, and obtain the relationship between the cumulative gas production and the cumulative production time.
[0086] By applying the limit to the above-mentioned relationship, the final cumulative gas production of the target coalbed methane well is obtained.
[0087] For example, substituting the unknown constants calculated according to formulas (5) and (6) into the first functional relationship in the example of formula (1), we get the following result: lg(N)=7.0472t / (97.1952+t), which, after conversion, gives the relationship between the cumulative gas production and the cumulative production time: N=10 7.0472t / (97.1952+t) .
[0088] Next, the above relationship is subjected to a time limit operation, yielding the final cumulative gas production of the target coalbed methane well as: 10 Nm =11148497.7 square meters.
[0089] In other embodiments, when the assessed production information is the final production level, in step S150, the calculated unknown constant is substituted into the first functional relationship for calculation to obtain the assessed production information of the coalbed methane well, including:
[0090] Substitute the calculated unknown constants into the first functional relationship above, so that the unknown constants in the first functional relationship above are represented by the above-mentioned fitting slope value and the above-mentioned fitting intercept value, and obtain the relationship between the cumulative gas production and the cumulative production time.
[0091] By applying the limit to the above-mentioned relationship, the final cumulative gas production of the target coalbed methane well is obtained.
[0092] Calculate the ratio of the final cumulative gas production to the geological reserves of the target coalbed methane well. This ratio is used as the final recovery rate of the target coalbed methane well.
[0093] Compared to the previous embodiment, this embodiment adds a step of calculating a ratio. In this embodiment, the geological reserves of a coalbed methane well are calculated based on the well-controlled area and resource abundance. Specifically, the product of resource abundance and well-controlled area is used as the geological reserve calculation result. As an example, the well-controlled area of well X1 is 0.085 square kilometers, and its resource abundance is 168 million cubic meters per square kilometer, resulting in a calculated geological reserve of 14.28 million cubic meters. The ratio between the final cumulative gas production of 11.1485 million cubic meters (rounded) and the geological reserve of 14.28 million cubic meters is calculated, yielding a final recovery rate of 78.07% for the well.
[0094] In the coalbed methane well final production information evaluation method provided in the embodiments of steps S110 to S150, the final production information can be effectively evaluated for various production stages and production curve types. By determining the first functional relationship between cumulative production time and cumulative gas production based on the time-series gas production data of the target coalbed methane well, an unknown constant to be solved is obtained. This first functional relationship is based on the distribution trend curve between variables related to cumulative production time (as the abscissa) and variables related to cumulative gas production (as the ordinate). This distribution trend curve is a smooth curve, and the ordinate value tends to stabilize as the abscissa value increases. Therefore, the first functional relationship obtained can characterize the inherent correlation between cumulative gas production and cumulative production time. By transforming the first functional relationship, a second functional relationship conforming to a linear relationship is obtained. In the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is... The variables related to the aforementioned cumulative production time and cumulative gas production are used. By taking the aforementioned independent variables and dependent variables as the horizontal and vertical coordinates of the target data points respectively, linear regression fitting is performed on the target data points to obtain the fitting slope and fitting intercept values in the aforementioned second functional relationship and to calculate the aforementioned unknown constants. The calculated unknown constants are substituted into the aforementioned first functional relationship for calculation to obtain the evaluation and production information of the aforementioned target coalbed methane well. The evaluation method provided by this embodiment can effectively evaluate the final production information of a single well with irregular and fluctuating gas production curves, and / or when the aforementioned single well is in the production increase stage or the production stabilization stage, filling the gap in related technologies for evaluating the aforementioned situations. It is also applicable to various well conditions such as smooth gas production curves or production decline stages, and has wide applicability.
[0095] A second exemplary embodiment of this disclosure provides an apparatus for evaluating final production information of a coalbed methane well. This apparatus can effectively evaluate final production information across various production stages and production curve types.
[0096] Figure 6A structural block diagram of an apparatus for evaluating the final production information of a coalbed methane well according to an embodiment of the present disclosure is shown schematically.
[0097] Reference Figure 6 As shown, the coalbed methane well final production information evaluation device 600 provided in this embodiment includes: a data acquisition module 610, a first function determination module 620, a second function determination module 630, a linear regression processing module 640, and an evaluation module 650.
[0098] The aforementioned data acquisition module 610 is used to acquire time-series gas production data of the target coalbed methane well.
[0099] The evaluation device provided in the embodiments of this disclosure can effectively solve the problem in related technologies that it is impossible to evaluate the final production information (e.g., the degree of final production) of single wells with irregular and highly fluctuating gas production curves. It can also be widely applied to various well conditions, such as at least one of the following: irregular gas production curve, highly fluctuating gas production curve, smooth gas production curve, well in the production increase stage, well in the stable production stage, well in the production decline stage, etc. It can perform personalized evaluation of the final production information based on the known gas production data of a single well under various well conditions.
[0100] The first function determination module 620 is used to determine the first functional relationship between the cumulative production time and the cumulative gas production based on the time-series gas production data; wherein, there are unknown constants to be solved in the first functional relationship.
[0101] In some embodiments, the gas production in the above-mentioned time-series gas production data is the actual gas production obtained by sequentially counting the production time starting from the initial gas production time, and the corresponding time-series statistical period is one of the following: day or month.
[0102] Based on the aforementioned time-series gas production data, a first functional relationship between cumulative production time and cumulative gas production is determined, including: calculating the cumulative production time and its corresponding cumulative gas production according to the production time; based on the first correlation, using variables related to the cumulative production time as the abscissa of the data points, and based on the second correlation, using variables related to the cumulative gas production as the ordinate of the data points, to draw one or more scatter plots; wherein at least one of the variables corresponding to the abscissa and ordinate differs among the scatter plots; selecting a target scatter plot from the above one or more scatter plots; the distribution trend curve corresponding to each scatter point in the target scatter plot is a smooth curve and the value of the ordinate tends to stabilize as the value of the abscissa increases; and determining the functional relationship corresponding to the target scatter plot as the first functional relationship.
[0103] In some embodiments, the first functional relationship in the above-described apparatus is:
[0104]
[0105] Where N represents the cumulative gas production; lg represents the logarithm to base 10, which is a commonly used logarithm; N m and t m t represents the unknown constant to be solved; t represents the cumulative production time.
[0106] The second function determination module 630 is used to transform the first functional relationship to obtain a second functional relationship that conforms to a linear relationship. In the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is a variable that is related to both the cumulative production time and the cumulative gas production.
[0107] In some embodiments, the second functional relationship described above is:
[0108]
[0109] In the second functional relationship mentioned above, the slope corresponding to the independent variable of cumulative production time is... Intercept is The dependent variable is the ratio of the cumulative production time to the logarithm of the cumulative gas production.
[0110] The linear regression processing module 640 is used to take the independent variable and the dependent variable as the horizontal and vertical coordinates of the target data points, respectively, and perform linear regression fitting processing on the target data points to obtain the fitting slope value and fitting intercept value in the second function relationship and solve for the unknown constant.
[0111] The aforementioned evaluation module 650 is used to calculate the unknown constants and substitute them into the aforementioned first functional relationship to obtain the evaluation and production information of the aforementioned target coalbed methane well.
[0112] In some embodiments, the above-mentioned assessment of production information is one of the following: the final cumulative gas production of the target coalbed methane well, and the final production level of the target coalbed methane well.
[0113] In some embodiments, substituting the calculated unknown constants into the first functional relationship to calculate and obtain the evaluation production information of the coalbed methane well includes: substituting the calculated unknown constants into the first functional relationship, such that the unknown constants in the first functional relationship are represented by the fitted slope value and the fitted intercept value, to obtain the relationship between the cumulative gas production and the cumulative production time; and taking the limit of the relationship to obtain the final cumulative gas production of the target coalbed methane well.
[0114] Alternatively, in other embodiments, the calculated unknown constant is substituted into the first functional relationship to calculate the evaluation and production information of the coalbed methane well. This includes: substituting the calculated unknown constant into the first functional relationship, such that the unknown constant in the first functional relationship is represented by the fitted slope value and the fitted intercept value, to obtain the relationship between the cumulative gas production and the cumulative production time; taking the limit of the relationship to obtain the final cumulative gas production of the target coalbed methane well; and calculating the ratio of the final cumulative gas production to the geological reserves of the target coalbed methane well, wherein the ratio is used as the final production level of the target coalbed methane well.
[0115] Further details included in this embodiment can be found in the relevant description of the first embodiment, and will not be repeated here.
[0116] The evaluation device provided in this embodiment can effectively evaluate the final production information for various production stages and production curve types. By using the time-series gas production data of the target coalbed methane well, a first functional relationship between cumulative production time and cumulative gas production is determined. This first functional relationship contains an unknown constant to be solved. The first functional relationship is obtained based on the distribution trend curve between variables related to cumulative production time (as the abscissa) and variables related to cumulative gas production (as the ordinate). This distribution trend curve is a smooth curve, and the ordinate value tends to stabilize as the abscissa value increases. Therefore, the first functional relationship obtained can characterize the inherent correlation between cumulative gas production and cumulative production time. By transforming the first functional relationship, a second functional relationship conforming to a linear relationship is obtained. In the second functional relationship, the independent variable is the cumulative production time, and the dependent variable is... The variables are related to the aforementioned cumulative production time and cumulative gas production. By using the aforementioned independent and dependent variables as the horizontal and vertical coordinates of the target data points respectively, a linear regression fitting is performed on the target data points to obtain the fitting slope and fitting intercept values in the aforementioned second functional relationship, and the aforementioned unknown constants are calculated. The calculated unknown constants are substituted into the aforementioned first functional relationship for calculation to obtain the evaluation and production information of the aforementioned coalbed methane well. In the face of single wells with irregular and fluctuating gas production curves, and / or when the aforementioned single well is in the production increase stage or the production stabilization stage, effective final production information evaluation can be performed, filling the gap in related technologies for the difficulty in evaluating the aforementioned situations. At the same time, it can also evaluate the final production information for various well conditions such as smooth gas production curves or those in the production decline stage, with wide applicability.
[0117] Any number of the functional modules included in the aforementioned evaluation apparatus can be combined into one module, or any one of the modules can be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules can be combined with at least a portion of the functionality of other modules and implemented in one module. At least one of the functional modules included in the evaluation apparatus can be at least partially implemented as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the functional modules included in the evaluation apparatus can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.
[0118] A third exemplary embodiment of this disclosure provides an electronic device.
[0119] Figure 7 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown.
[0120] Reference Figure 7 As shown, the electronic device 700 provided in this embodiment includes a processor 701, a communication interface 702, a memory 703, and a communication bus 704. The processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704. The memory 703 is used to store computer programs. When the processor 701 executes the program stored in the memory, it implements the above-mentioned method for evaluating the final production information of coalbed methane wells.
[0121] A fourth exemplary embodiment of this disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for evaluating the final production information of a coalbed methane well.
[0122] The computer-readable storage medium may be included in the device or apparatus described in the above embodiments; or it may exist independently and not assembled into the device or apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.
[0123] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0124] It should be noted that, in this document, relational terms such as "first" and "second" are used merely 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 a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0125] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.
Claims
1. A method of assessing information on final recovery of coal bed gas wells, characterized in that, The method comprises the following steps: obtaining time-series gas production data of a target coalbed methane well; determining a first function relationship between cumulative production time and cumulative gas production based on the time-series gas production data, wherein the first function relationship contains an unknown constant to be solved; transforming and converting the first function relationship to obtain a second function relationship conforming to a linear relationship, wherein in the second function relationship, the independent variable is the cumulative production time, and the dependent variable is a variable related to both the cumulative production time and the cumulative gas production; regarding the independent variable and the dependent variable as horizontal and vertical coordinates of a target data point respectively, performing linear regression fitting of the target data point to obtain a fitting slope value and a fitting intercept value in the second function relationship and solve the unknown constant; substituting the solved unknown constant into the first function relationship to obtain evaluation production information of the target coalbed methane well.
2. The evaluation method according to claim 1, characterized in that The evaluation production information is one of the following information: final cumulative gas production of the target coalbed methane well, final recovery degree of the target coalbed methane well; wherein substituting the solved unknown constant into the first function relationship to obtain evaluation production information of the coalbed methane well comprises: substituting the solved unknown constant into the first function relationship, so that the unknown constant in the first function relationship is represented by the fitting slope value and the fitting intercept value, to obtain a relationship between cumulative gas production and cumulative production time; performing limit processing on the relationship to obtain the final cumulative gas production of the target coalbed methane well; or substituting the solved unknown constant into the first function relationship, so that the unknown constant in the first function relationship is represented by the fitting slope value and the fitting intercept value, to obtain a relationship between cumulative gas production and cumulative production time; performing limit processing on the relationship to obtain the final cumulative gas production of the target coalbed methane well; calculating a ratio of the final cumulative gas production to the geological reserves of the target coalbed methane well, and the ratio is taken as the final recovery degree of the target coalbed methane well.
3. The method of claim 1, wherein, The gas production in the time-series gas production data is the real gas production obtained by sequentially counting according to production time from the initial gas production time, and the corresponding time-series counting period is one of the following: day, month.
4. The method of claim 1, wherein, The method for determining the first function relationship between cumulative production time and cumulative gas production based on the time-series gas production data comprises: cumulatively calculating the cumulative production time and the corresponding cumulative gas production according to production time; based on a first correlation relationship, taking a variable related to the cumulative production time as the horizontal coordinate of a data point, and based on a second correlation relationship, taking a variable related to the cumulative gas production as the vertical coordinate of the data point, to draw one or more scatter plots; at least one of the variables corresponding to the horizontal and vertical coordinates of each scatter plot is different; selecting a target scatter plot from the one or more scatter plots; the distribution trend curve of each scatter point in the target scatter plot is a smooth curve and the value of the vertical coordinate tends to be stable as the value of the horizontal coordinate increases. The function relationship corresponding to the target scatter plot is determined as a first function relationship.
5. The method according to any one of claims 1-4, characterized in that, The first function relationship is: Wherein, N represents the cumulative gas production; lg represents the logarithm operation with 10 as the base, which is the common logarithm; N m and t m represents the unknown constant to be solved; t represents the cumulative production time.
6. The method of claim 5, wherein, The second function relationship is: In the second function relationship, the slope corresponding to the independent variable of cumulative production time is The intercept is The dependent variable is the ratio of the cumulative production time to the common logarithm of the cumulative gas production 7. An apparatus for evaluating production information of a coalbed methane well, characterized by comprising: a coalbed methane well production information evaluation device according to any one of claims 1 to 6. The first function relationship is: The data acquisition module is configured to acquire time-series gas production data of a target coalbed methane well. The first function determination module is configured to determine a first function relationship between cumulative production time and cumulative gas production based on the time-series gas production data, wherein the first function relationship includes an unknown constant to be solved. The second function determination module is configured to perform deformation conversion processing on the first function relationship to obtain a second function relationship conforming to a linear relationship, wherein the independent variable of the second function relationship is the cumulative production time, and the dependent variable is a variable related to both the cumulative production time and the cumulative gas production. The linear regression processing module is configured to perform linear regression fitting of the target data points by taking the independent variable and the dependent variable as the horizontal and vertical coordinates of the target data points, respectively, to obtain a fitting slope value and a fitting intercept value in the second function relationship and solve the unknown constant. The evaluation module is configured to calculate the unknown constant by substituting the solved unknown constant into the first function relationship.
8. The apparatus of claim 7, wherein The first function relationship is: Wherein, N represents the cumulative gas production; lg represents the logarithm operation with 10 as the base, which is the common logarithm; N m and t m represents the unknown constant to be solved; t represents the cumulative production time; The second function relationship is: In the second function relationship, the slope corresponding to the independent variable of cumulative production time is The intercept is The dependent variable is the ratio of the cumulative production time to the common logarithm of the cumulative gas production 9. An electronic device, comprising: The apparatus includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus. The memory is configured to store a computer program. The processor is configured to execute the program stored in the memory to implement the method of any one of claims 1-6.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the method of any one of claims 1-6.