Method for predicting oil production of oil well
By normalizing the historical oil production and time of individual wells in the study area, a hyperbolic decline model was constructed, which solved the problem of insufficient prediction accuracy of the block decline model and achieved more accurate oil well production prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-12
- Publication Date
- 2026-04-14
AI Technical Summary
In existing technologies, the prediction accuracy of single-well oil production using block decline models is poor. This is mainly because the different production times of multiple oil wells lead to differences between the fitted decline model and the actual oil production decline pattern.
By normalizing the historical oil production per unit time and production time of single wells adjacent to the target well in the study area, a normalized correspondence between oil production and time is constructed, a hyperbolic decline model is determined, the influence of time and oil production data in the non-decline stage is eliminated, and the model fitting accuracy is improved.
It achieves a more accurate reflection of the decline in oil production from oil wells, improves the prediction accuracy of the hyperbolic decline model, and ensures that the prediction results are more consistent with the actual production changes of a single well.
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Abstract
Description
Technical Field
[0001] This invention relates to a method for predicting oil production from oil wells, belonging to the field of oilfield development technology. Background Technology
[0002] The oilfield development process includes the early drilling phase, the mid-term construction phase, and the late production reduction phase. The early drilling phase involves drilling to obtain industrial oil and gas flow; the mid-term construction phase involves development and construction to achieve a certain scale of oil and gas production capacity; and the late production reduction phase is the process of gradually decreasing oil and gas production capacity. The change in oil well production includes the construction phase with increasing production, the stable production phase with stable production, and the declining production phase.
[0003] Analyzing the production decline pattern during the production decline stage of oil wells has the following important significance: (1) predicting the production capacity of new wells or adjustment wells, providing a basis for the design of production capacity construction and adjustment plans; (2) guiding the implementation of measures to delay production decline, so as to achieve the goal of stable production, high production and rational development of oil wells; (3) predicting dynamic changes in production, providing a basis for the prediction and calibration of recoverable reserves and recovery rate, and also providing a basis for the economic evaluation of oil wells.
[0004] Currently, the decline pattern of oil well production is mainly characterized by the Arps decline model. The Arps decline model includes decline rates and decline indices related to the spatial distribution of oil wells, seepage characteristics, development methods, the completeness of the well network system, and production management. Therefore, determining the decline rate and decline index is crucial for accurately evaluating the decline pattern of oil well production. Existing technologies primarily use decline models for blocks with similar reservoir properties, similar crude oil viscosity, and similar well networks and development methods to predict the production capacity of new wells and adjustment wells. For example, Chinese patent document CN109784705B discloses a method for predicting oil production. This method includes the following steps: determining at least one production decline stage based on M historical unit oil production values and Arps standard charts; determining the hyperbolic decline index for each production decline stage using a stepwise approximation method; determining the initial decline rate for each production decline stage using linear regression analysis based on the hyperbolic decline index; determining the Arps hyperbolic decline model for each production decline stage based on the initial unit oil production value, hyperbolic decline index, and initial decline rate; and predicting oil production based on the Arps hyperbolic decline model for each production decline stage.
[0005] However, due to the different commissioning times of multiple wells within a block—sometimes a year apart, sometimes several years apart—the production of wells commissioned earlier begins to decline before the production of wells commissioned later begins, and these wells have not yet entered the decline phase. Therefore, when determining the decline model for new or adjustment wells based on the overall oil production of the block, the method actually uses time and production data from non-decline phases because the decline phases of multiple wells at the same production stage differ. Furthermore, the production of each individual well at different decline phases is uniformly labeled as the production of a fixed decline phase within the block. The actual oil production data used for the block is from multiple wells at different decline phases, leading to a discrepancy between the fitted decline model and the actual decline pattern of production of individual wells within the block. This results in poor prediction accuracy of the fitted hyperbolic decline model used to predict the production of new and adjustment wells. Summary of the Invention
[0006] The purpose of this invention is to provide a method for predicting oil production in oil wells, which can solve the problem of poor prediction accuracy when using the block decline model to predict the oil production of a single well.
[0007] To achieve the above objectives, the technical solution adopted by the oil well production prediction method of the present invention is as follows:
[0008] A method for predicting oil well production includes the following steps:
[0009] (1) Based on the historical oil production per unit time of each adjacent single well in the same block as the target well to be evaluated in the study area, the historical oil production per unit time and production time of each single well during the production decline stage are normalized to obtain the normalized oil production and normalized time of each single well.
[0010] The formula for calculating normalized oil production is as follows:
[0011]
[0012] In the formula, q (T) N represents the normalized oil production of a single well at a production time of T. p(T) This represents the oil production per unit time of a single well during production time T. This represents the maximum oil production per unit time of a single well during the production decline phase.
[0013] The normalization time is calculated from the initial time of the single-well production decline phase;
[0014] (2) Construct the correspondence between the normalized oil production and normalized time of each single well, and determine the production decline model for predicting the target wells in the study area;
[0015] (3) Based on the production decline model, predict the oil production of the target well.
[0016] The oil well production prediction method of this invention normalizes the historical unit time oil production and production time of single wells adjacent to the target well in the study area, and uses the normalized oil production and time to fit and determine the hyperbolic decline model. This can eliminate the influence of using time and oil production data in the non-decline stage on the fitted model, more objectively reflect the oil production decline law of oil wells in the study area, and effectively improve the prediction accuracy of the fitted hyperbolic decline model.
[0017] Preferably, the normalized time is an integer not less than 0.
[0018] Preferably, the formula for calculating the normalized time is as follows:
[0019] t = T - T0
[0020] In the formula, t is the normalized time, T is the production time, and T0 is the start time of the production decline stage of each single well.
[0021] Preferably, the normalized production and normalized time of each individual well are fitted according to a hyperbolic decline model to determine the decline index and decline rate in the hyperbolic decline model, thereby obtaining a production decline model for predicting the target wells in the study area.
[0022] Preferably, the expression for the hyperbolic decreasing model is as follows:
[0023]
[0024] In the formula, q is the normalized oil production, d is the decline rate, n is the decline exponent, and t is the normalization time.
[0025] Preferably, the method for predicting the oil production of the target well is as follows: normalize the production time of the target well to obtain the normalized time of the target well, substitute the normalized time into the hyperbolic decline model of the target well in the study area to obtain the normalized oil production, and calculate the product of the normalized oil production and the maximum oil production per unit time of the target well during the production decline stage to obtain the oil production per unit time of the target well.
[0026] Preferably, the number of individual wells is not less than three.
[0027] Preferably, the target well is a new well or an adjustment well. Attached Figure Description
[0028] Figure 1 This is a flowchart illustrating the oil well production prediction method according to an embodiment of the present invention.
[0029] Figure 2 This is a schematic diagram of the fitting curve corresponding to the hyperbolic decline model of the oil wells in the study area in this embodiment of the invention;
[0030] Figure 3 This is a schematic diagram of the fitting curve corresponding to the hyperbolic decline model of the oil wells in the study area in the comparative example of this invention.
[0031] Figure 4 This is a schematic diagram showing the annual oil production of well Y10-5 predicted by the methods of the present invention and comparative examples, as well as the actual annual oil production curves from 2019 to 2023.
[0032] Figure 5 This is a schematic diagram showing the comparison results of the fitting curves corresponding to the hyperbolic decline model of the oil wells in the study area in the embodiments and comparative examples of the present invention. Detailed Implementation
[0033] The oil well production prediction method of this invention is an improved invention. This invention addresses the problems of using non-decreasing phase time and production data in the decline model for new or adjustment wells based on the overall oil production of a block, and the inability to effectively reflect the actual decline pattern of individual well production by uniformly labeling the production of individual wells in different decline phases as the production of a fixed decline phase in the block. This invention normalizes the historical unit-time production and production time of all individual wells in the study area, thereby ensuring that the data used when fitting the hyperbolic decline model are all production data of individual wells in the same decline phase. This truly and objectively reflects the oil production decline pattern and improves the prediction accuracy of the fitted hyperbolic decline model.
[0034] The technical solution of the present invention will be further described below with reference to specific embodiments.
[0035] Example
[0036] The oil well production prediction method in this embodiment takes an active edge-water reservoir as the study area, such as... Figure 1 As shown, the specific steps include:
[0037] (1) Based on the historical oil production per unit time of each adjacent well in the same block as the target well in the study area, the production decline stage of each adjacent well is determined. The historical oil production per unit time and the production time corresponding to the production decline stage of each adjacent well are normalized to obtain the normalized oil production q of the well. (i)(T) and normalized time t; where normalized oil production q (i)(T) The calculation formula is as follows:
[0038]
[0039] In the formula, q (i)(T) N represents the normalized oil production of the i-th well at production time T; p(i)(T) N represents the oil production per unit time of the i-th well at production time T;p(i)(T0) The maximum oil production per unit time of the i-th well during the production decline phase is equal to the initial oil production per unit time of the i-th well during the production decline phase.
[0040] The normalized time t is calculated from the initial time of the single-well production decline phase, and the formula for calculating the normalized time t is as follows:
[0041] t = T - T0
[0042] In the formula, t is the normalized time, T is the production time, and T0 is the start time of the declining production stage of each adjacent single well. The normalized time t is an integer greater than or equal to 0.
[0043] In this embodiment, there are a total of 4 wells in the study area. We will now take 3 adjacent wells in the same block as the target well as the well to be evaluated as examples for detailed explanation. The 3 wells are Y10-2, Y10, and Y10-4. The historical annual oil production of the 3 wells is shown in Table 1. According to Table 1, well Y10-2 was put into production in July 2014. It produced for less than a year in 2014, with the highest annual oil production in 2015. The overall trend of annual oil production from 2015 to 2022 is a decreasing trend. Therefore, 2015-2022 is the production decline phase of well Y10-2. 2015 is the initial time of this production decline phase. At this time, the normalized time t = 0. The initial annual oil production of well Y10-2 during the production decline phase is the annual oil production in 2015, which is equal to 0.10189 × 10⁻⁶. 4 Based on the initial annual oil production and the annual oil production from 2015 to 2022, the normalized time and normalized annual oil production for 2015 to 2022 can be calculated using the above formula.
[0044] Well Y10 was put into production in December 2013. The overall trend of annual oil production from 2015 to 2022 was a decreasing trend. Therefore, 2015-2022 is the production decline phase of Well Y10, with 2015 being the initial time of this phase. At this point, the normalized time t = 0. The initial annual oil production of Well Y10 during the production decline phase is the annual oil production in 2015, which equals 0.15692 × 10⁻⁶. 4 Based on the initial annual oil production and the annual oil production from 2015 to 2022, the normalized time and normalized annual oil production for 2015 to 2022 can be calculated using the above formula.
[0045] Well Y10-4 was put into production in July 2014. The overall trend of annual oil production from 2017 to 2022 was a decreasing trend. Therefore, 2017-2022 represents the declining production phase of Well Y10-4, with 2017 being the initial year of this phase. At this point, the normalized time t = 0. The initial annual oil production of Well Y10-4 during this declining phase is the annual oil production in 2017, which equals 0.09689 × 10⁻⁶. 4 Based on the initial annual oil production and the annual oil production from 2017 to 2022, the normalized time and normalized annual oil production for 2017 to 2022 can be calculated using the above formula.
[0046] The historical annual oil production, normalized time (t), and normalized annual oil production of the three single wells are summarized in Table 1.
[0047] Table 1. Historical annual oil production, normalized time (t), and normalized annual oil production of three individual wells.
[0048]
[0049]
[0050] (2) Construct the normalized oil production q of each adjacent single well in the same block as the target well in the study area obtained in step (1). (i)(T) By establishing the correspondence between the normalized time t and the decline exponent n and decline rate d in the hyperbolic decline model, a production decline model for predicting the production decline of target wells in the study area is obtained.
[0051] In this embodiment, taking the three single wells Y10-2, Y10, and Y10-4 in step (1) as examples, the method for determining the production decline model for predicting the target wells in the study area is described in detail. The specific method for determining the oil production decline model for predicting the target wells in the study area in this embodiment is as follows:
[0052] Plot the normalized time t on the x-axis and the normalized annual oil production q on the y-axis. (i)(T) Using the vertical axis, the normalized time t and normalized annual oil production q of the three individual wells Y10-2, Y10, and Y10-4 obtained in step (1) are plotted. (i)(T) The data points are plotted as scatter points on a coordinate graph to obtain a scatter plot. The scatter plot data is then fitted using a hyperbolic decline model to determine the decline exponent n and decline rate d in the model, resulting in the following... Figure 2 ( Figure 2 The decreasing curve shown by the vertical axis (dimensionalless annual oil production representing normalized annual oil production) is the production decline model used to predict the target well's production decline in the study area.
[0053] The expression for the hyperbolic decreasing model is as follows:
[0054]
[0055] In the formula, q is the normalized annual oil production, d is the decline rate, n is the decline exponent, and t is the normalization time.
[0056] The fitting relationship obtained by fitting according to the hyperbolic decreasing model in this embodiment is as follows:
[0057]
[0058] The fitting results show that in this embodiment, the decreasing exponent n = 1.871 and the decreasing rate d = 0.3984.
[0059] In other embodiments, the normalized oil production q of one, two, or three or more wells adjacent to the target well can also be used. (i)(T) By establishing the correspondence between the normalized time t and the decline rate d, the decline exponent n and decline rate d in the hyperbolic decline model of the target well in the study area are determined, thus obtaining the production decline model for predicting the target well's production decline in the study area. The more single wells used, the higher the prediction accuracy.
[0060] To verify the accuracy of the hyperbolic decline model for the target well in the study area, the normalized annual oil production of adjacent single wells in the same block as the target well in the study area was calculated according to the determined hyperbolic decline model. The calculation results and the actual normalized annual oil production of the three single wells are summarized in Table 2.
[0061] Table 2. Actual normalized annual oil production and normalized annual oil production calculated according to the established hyperbolic decline model for three individual wells.
[0062] Normalized time t y10-2 well Y10 well y10-4 well Calculation results 0 1 1 1 1.00000 1 0.68516 0.95543 0.54263 0.74253 2 0.53343 0.88311 0.47404 0.61400 3 0.51589 0.70057 0.41608 0.53382 4 0.46265 0.61932 0.34435 0.47784 5 0.42701 0.50175 0.32574 0.43596 6 0.40002 0.40036 - 0.40314 7 0.38306 0.39412 - 0.37655
[0063] Table 2 shows that the correlation coefficient between the normalized annual oil production calculated according to the determined hyperbolic decline model and the actual normalized annual oil production of well y10-2 is 0.989, the correlation coefficient with the actual normalized annual oil production of well y10 is 0.906, and the correlation coefficient with the actual normalized annual oil production of well y10-4 is 0.975. These results indicate that the calculation results of the determined hyperbolic decline model have a high correlation with the actual normalized annual oil production of the three individual wells, conform to actual production, and can meet the prediction accuracy requirements for the target well's oil production.
[0064] (3) The production time of the target well in the study area is normalized. Using the hyperbolic decline model of the target well in the study area determined in step (2), the oil production per unit time of the target well in the study area is predicted. In this embodiment, the production time of the target well in the study area is normalized to obtain the normalized time of the target well. The normalized time is substituted into the hyperbolic decline model of the target well in the study area to obtain the normalized oil production. The product of the normalized oil production and the maximum oil production per unit time of the target well in the production decline stage is calculated to obtain the oil production per unit time of the target well.
[0065] Comparative Example
[0066] The method for predicting oil production from wells in this comparative example, using the same active edge-water reservoir as in the examples, as the study area, specifically includes the following steps:
[0067] (1) Based on the sum of the historical oil production per unit time of all single wells in the study area, the historical oil production per unit time data of the study area are determined.
[0068] In this comparative example, three single wells, Y10-2, Y10, and Y10-4, are used as examples. The historical oil production per unit time of the three single wells is summed to obtain the historical oil production per unit time data of the study area.
[0069] (2) Based on the historical oil production per unit time in the study area, the historical oil production per unit time and production time in the study area during the production decline phase are normalized to obtain the normalized oil production q. (T) and normalized time t; where normalized oil production q (T) The calculation formula is as follows:
[0070]
[0071] In the formula, q (T) N represents the normalized oil production in the study area at production time T; p(T) N represents the oil production per unit time in the study area at production time T. p(T0) The maximum oil production per unit time in the study area during the production decline phase is equal to the initial oil production per unit time in the study area during the production decline phase.
[0072] The formula for calculating the normalized time t is as follows:
[0073] t = T - T0
[0074] In the formula, t is the normalized time, T is the production time, and T0 is the initial unit time of the declining output stage in the study area.
[0075] In this comparative example, the historical annual oil production, normalized time t, and normalized annual oil production q of the study area are included.(T) As shown in Table 3.
[0076] Table 3 Historical annual oil production, normalization time, and normalized annual oil production for the study area.
[0077] Production time T Normalized Time Annual oil production Normalized annual oil production (Year) - <![CDATA[(10 4 t)]]> - 2013 - 0.00148 - 2014 - 0.22292 - 2015 0 0.38729 1.00000 2016 1 0.25311 0.65355 2017 2 0.289827 0.74836 2018 3 0.21508 0.55535 2019 4 0.19026 0.49126 2020 5 0.16256 0.41975 2021 6 0.13695 0.35362 2022 7 0.13244 0.34197
[0078] (3) Based on the normalized annual oil production q of the study area obtained in step (2) (T) By establishing the correspondence between the normalized time t and the decline exponent n and decline rate d in the hyperbolic decline model, the hyperbolic decline model of the oil wells in the study area is obtained.
[0079] In this comparative example, normalized time t is used as the horizontal axis, and normalized annual oil production q is used as the horizontal axis. (T) Using the normalized time t and normalized annual oil production q of the study area obtained in step (2) as the ordinate, (T) The points are plotted as scatter points on a coordinate graph to obtain a scatter plot. The scatter points are then fitted using a hyperbolic decline model to determine the decline exponent n and decline rate d in the model, resulting in the following... Figure 3 ( Figure 3 The decreasing curve shown by the dimensionless annual oil production (representing normalized annual oil production) on the ordinate is the hyperbolic decreasing model of the oil wells in the study area.
[0080] The fitting relationship based on the hyperbolic decreasing model is as follows:
[0081]
[0082] The fitting results show that in this comparative example, the decline exponent n = 1.1844, the decline rate d = 0.2965, and the hyperbolic decline model of the study area is the above-mentioned fitted relationship. In this comparative example, the correlation coefficient when fitting the relationship is 0.959, indicating that the normalized annual oil production q of the study area... (T) There is a good correlation between the normalized time t and the fitted relationship.
[0083] To verify the accuracy of the hyperbolic decline model for the wells in the study area, the normalized annual oil production of individual wells in the study area was calculated according to the determined hyperbolic decline model. The calculation results and the actual normalized annual oil production of the three individual wells are summarized in Table 4.
[0084] Table 4. Actual normalized annual oil production and normalized annual oil production calculated according to the established hyperbolic decline model for three single wells.
[0085] Normalized time t y10-2 well Y10 well y10-4 well Calculation results 0 1 1 1 1.000 1 0.68516 0.95543 0.54263 0.776 2 0.53343 0.88311 0.47404 0.638 3 0.51589 0.70057 0.41608 0.545 4 0.46265 0.61932 0.34435 0.477 5 0.42701 0.50175 0.32574 0.425 6 0.40002 0.40036 - 0.384 7 0.38306 0.39412 - 0.351
[0086] Table 4 shows that the correlation coefficient between the normalized annual oil production calculated according to the determined hyperbolic decline model and the actual normalized annual oil production of well Y10-2 is 0.976, the correlation coefficient with the actual normalized annual oil production of well Y10 is 0.9348, and the correlation coefficient with the actual normalized annual oil production of well Y10-4 is 0.9566. These results indicate that the calculation results of the determined hyperbolic decline model in the study area have a high correlation with the actual normalized annual oil production of the three individual wells. Except for well Y10, where the effect of single-well normalization is slightly worse, single-well normalization of well Y10-2 is more consistent with actual production, with a correlation coefficient reaching 0.989, indicating improved accuracy. Similarly, single-well normalization of well Y10-4 is more consistent with actual production, with a correlation coefficient reaching 0.975, also indicating improved accuracy. This meets the prediction accuracy requirements for the target wells' oil production. The single-well normalized decline model better reflects the decline pattern of most wells.
[0087] (4) Based on the production decline model obtained in step (3), the oil production of the target well is predicted.
[0088] To further verify the accuracy of the prediction methods in the examples and comparative examples, well Y10-5 in the block containing the target well within the study area was selected for verification. Well Y10-5 was put into production at the beginning of 2019 and is currently in a declining production phase. Specifically, the oil production of the target well in this declining phase was predicted according to the methods in the examples and comparative examples, and the predicted results were compared with the actual oil production. The results are shown in Table 5. The annual oil production of well Y10-5 predicted using the methods in the examples and comparative examples, as well as the actual annual oil production from 2019 to 2023, are also listed in Table 5. Figure 4 middle.
[0089] Table 5 shows the predicted and actual oil production data of the target wells using different methods.
[0090]
[0091]
[0092] From Table 5, Figure 4 It can be seen that the actual annual oil production of well Y10-5 from 2019 to 2023 is more consistent with the decline model of the example. The annual oil production decline is faster in the early stage. In contrast, the predicted value of the block decline model in the comparative example is too large and the error between the actual annual oil production is too large. Therefore, the prediction of the single-well normalized decline model in the example is more consistent with the actual production of new wells / adjustment wells, and the prediction results are reliable and accurate.
[0093] The hyperbolic decreasing model determined by the examples and comparative examples is presented graphically. Figure 5 ( Figure 5 The vertical axis represents dimensionless annual oil production (normalized annual oil production). (From...) Figure 5It can be seen that in the hyperbolic decline model determined by the comparative and examples, the oil production shows a rapid initial decline followed by a slower decline. This is because each new well has a stable annual oil production in the initial stage due to high formation pressure. As production time increases, formation pressure decreases, and the annual oil production begins to decline. However, due to the different initial production times of each well, the start time of the decline stage for each well also differs, resulting in a difference between the start time of the decline stage for the block and the start time of the decline stage for each individual well. When fitting the hyperbolic decline model with the overall oil production of the block, the actual time and oil production data of the non-decline stage are used, which differs from the actual oil production decline pattern of each well within the block, leading to poor prediction accuracy of the fitted hyperbolic decline model.
[0094] In this invention, the production time and oil production of each individual well are normalized. When fitting the hyperbolic decline model, the time and oil production data of all individual wells in the decline stage are used, which can truly and objectively reflect the decline law of oil production in the study area and effectively improve the prediction accuracy of the fitted hyperbolic decline model.
Claims
1. A method for predicting oil well production, characterized in that, Includes the following steps: (1) Based on the historical oil production per unit time of each adjacent single well in the same block as the target well to be evaluated in the study area, the historical oil production per unit time and production time of each single well during the production decline stage are normalized to obtain the normalized oil production and normalized time of each single well. The formula for calculating normalized oil production is as follows: In the formula, q(T) is the normalized oil production of a single well at a production time of T; N p (T) represents the oil production per unit time of a single well at a production time of T; This represents the maximum oil production per unit time of a single well during the production decline phase. The normalization time is calculated from the initial time of the single-well production decline phase; (2) Construct the correspondence between the normalized oil production and normalized time of each single well, and determine the production decline model for predicting the target wells in the study area; (3) Based on the production decline model, predict the oil production of the target well.
2. The method for predicting oil well production as described in claim 1, characterized in that, The normalized time is an integer not less than 0.
3. The method for predicting oil well production as described in claim 1 or 2, characterized in that, The formula for calculating normalized time is as follows: t = T - T0 In the formula, t is the normalized time, T is the production time, and T0 is the start time of the production decline stage of each single well.
4. The method for predicting oil well production as described in claim 1, characterized in that, The normalized production and normalized time of each well are fitted according to the hyperbolic decline model to determine the decline index and decline rate in the hyperbolic decline model, thus obtaining a production decline model for predicting the target wells in the study area.
5. The method for predicting oil well production as described in claim 4, characterized in that, The expression for the hyperbolic decreasing model is as follows: In the formula, q is the normalized oil production, d is the decline rate, n is the decline exponent, and t is the normalization time.
6. The method for predicting oil well production as described in claim 1, characterized in that, The method for predicting the oil production of the target well is as follows: Normalize the production time of the target well to obtain the normalized time of the target well. Substitute the normalized time into the hyperbolic decline model of the target well in the study area to obtain the normalized oil production. Calculate the product of the normalized oil production and the maximum oil production per unit time of the target well during the production decline stage to obtain the oil production per unit time of the target well.
7. The method for predicting oil well production as described in claim 1, characterized in that, The number of individual wells shall not be less than three.
8. The method for predicting oil well production as described in claim 1, characterized in that, The target well is either a new well or an adjustment well.
Citation Information
Patent Citations
Methods, apparatus and storage media for predicting oil production
CN109784705B