Plunger gas lift abnormal working condition identification method based on single parameter analysis

Abstract

The invention belongs to the technical field of oil and gas field drainage gas recovery, and particularly discloses a plunger gas lift abnormal working condition recognition method based on single parameter analysis. According to the method, production data related to the plunger gas lift system are obtained, abnormal working condition recognition is conducted on a single parameter through a trend algorithm according to the obtained production data related to the plunger gas lift system, and an abnormal working condition result is output; real-time data acquisition is carried out on a plurality of single parameters of a long-term operation form or a fault of a well, trend algorithm calculation is carried out on the data, a corresponding abnormal working condition result is obtained, and the problems that when plunger gas lift fault data are identified, the identification efficiency is too low, and the accuracy is poor are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas field drainage and gas production, and in particular relates to a method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis. Background Art

[0002] Plunger gas lift is an efficient drainage and gas production technology. It places a plunger tool in the wellbore to form a mechanical isolation, reduce liquid slippage and gas up-streaming, and use the energy of the gas well itself to push the plunger to reciprocate in the wellbore to discharge the accumulated liquid. It has the advantages of wide application range, high degree of automation, high input-output ratio, and green environmental protection. It is suitable for the development of tight gas fields with a large area, many wells, and few people. With the promotion of technology, application problems have gradually emerged, mainly manifested in the high degree of dependence on manual labor, the aging of well site supporting equipment, and the inevitable erosion and blockage of foreign objects in the well, which leads to control valve damage, sensor failure, network disconnection and other problems, which need to be solved after manual identification, and the annual analysis workload is more than 200,000 times.

[0003] The identification of plunger gas lift operation faults is usually based on human experience. With the help of big data analysis and artificial intelligence technology, trend analysis is performed on production data related to the plunger gas lift system, such as "switch well status", "plunger status", "casing pressure", "oil pressure" and its structural indicators. Fault identification through analysis of production data based on human experience is prone to inaccurate identification and low identification efficiency. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis, so as to solve the problem of low recognition efficiency and poor accuracy when identifying plunger gas lift fault data.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides a method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis, comprising:

[0007] Obtain production data related to the plunger gas lift system;

[0008] Based on the production data related to the plunger gas lift system, the abnormal operating conditions of single parameters are identified through trend algorithms;

[0009] Output abnormal operating conditions results.

[0010] Furthermore, the acquisition of production data related to the plunger gas lift system includes:

[0011] Obtain switch well status data, plunger status data, oil pressure data, casing pressure data and oil-casing pressure difference data.

[0012] Furthermore, the abnormal operating condition identification is performed on a single parameter, and the identification objects include: switch well status, plunger status, oil pressure status, casing pressure status and oil-casing pressure difference.

[0013] Furthermore, the trend algorithm includes: trend index calculation, 3σ extreme value identification, constant value identification and parameter overall rising and falling trend determination function.

[0014] Furthermore, the trend index is calculated as:

[0015]

[0016] Among them, f m (x,y) is the trend index, x is the oil pressure and casing pressure, y is the time, and n is a natural number;

[0017] The 3σ extreme value is identified as:

[0018]

[0019]

[0020]

[0021] Among them, p min is the minimum pressure, p max is the maximum pressure, δ is a fixed value, f l (x) is the calculated outlier point, 1 is beyond the normal range, and 0 is the normal range;

[0022] The constant value is identified as:

[0023]

[0024] Among them, x max is the maximum value of oil pressure and casing pressure, x min is the minimum value of oil pressure and casing pressure, j is the discrimination threshold, y s1 is the constant value identification result, 1 means the oil pressure difference or casing pressure difference is constant, 2 means the maximum and minimum oil pressure difference or casing pressure difference is less than j;

[0025] The overall upward and downward trend determination function of the parameter is:

[0026]

[0027]

[0028] Among them, x s is the slope of oil pressure and casing pressure, y s2is the judgment result of the overall rising and falling trend of the parameter, 0 is normal, 1 is abnormal rising, 2 is abnormal falling, and a is the judgment threshold.

[0029] Furthermore, the well switching status includes: well switching is normal, well switching data is missing, and well switching time is too short;

[0030] Normal well opening and closing means that the well opening and closing cycle is normal;

[0031] Missing switch well data means that the switch well has no status data;

[0032] The well opening and closing time is too short, which means the well opening time is less than 10 minutes.

[0033] Furthermore, the plunger status includes: the plunger is normal, the plunger is at the bottom of the well for a long time, the plunger is at the wellhead for a long time, and the plunger does not match the switch well;

[0034] Normal plunger means the plunger is operating normally;

[0035] The plunger is at the bottom of the well for a long time, indicating that the plunger has not arrived;

[0036] The plunger is at the wellhead for a long time, which means the plunger is always in the arrival state;

[0037] The mismatch between the plunger and the well switch means that the plunger lifting process does not match. When the well is opened, the plunger does not show the arrival status, and when the well is closed, the plunger is not at the bottom of the well.

[0038] Furthermore, the oil pressure status includes: normal oil pressure status, oil pressure communication failure, abnormal constant oil pressure, approximately constant oil pressure, abnormal increase in oil pressure, abnormal decrease in oil pressure, and oil pressure exceeding a normal range;

[0039] Normal oil pressure status means that the oil pressure status is consistent with the normal operation of the plunger;

[0040] Oil pressure communication failure refers to oil pressure failure caused by communication problems;

[0041] Abnormal constant value of oil pressure means that the oil pressure is a constant value;

[0042] The approximate constant value of oil pressure means that the segmented constant value is less than 0.7;

[0043] Abnormal increase in oil pressure means that the slope of the oil pressure cycle mean increases by more than 0.07;

[0044] Abnormal oil pressure drop means that the slope of the oil pressure cycle mean drops by more than 0.05;

[0045] Oil pressure exceeding the normal range means that the oil pressure exceeds the normal oil pressure range of the gas well, and the 3σ extreme value is identified as 1.

[0046] Furthermore, the casing pressure status includes: normal casing pressure status, casing pressure communication failure, abnormal constant casing pressure, approximately constant casing pressure, abnormal increase in casing pressure, abnormal decrease in casing pressure, and exceeding the normal range;

[0047] Normal casing pressure state means that the casing pressure state conforms to the normal operation state of the plunger;

[0048] Casing pressure communication failure refers to casing pressure failure caused by communication problems;

[0049] Abnormal constant value of casing pressure means that the casing pressure is a constant value;

[0050] The casing pressure approximate constant value means that the segmented constant value is less than 0.7;

[0051] Abnormal increase in casing pressure means that the slope of the casing pressure cycle mean value increases by more than 0.07;

[0052] Abnormal increase in casing pressure means that the slope of the mean of the casing pressure cycle decreases by more than 0.05;

[0053] Casing pressure exceeding the normal range means that the casing pressure exceeds the normal casing pressure range of the gas well, and the 3σ extreme value is identified as 1.

[0054] Further, the oil-casing pressure difference includes: normal oil-casing pressure difference, abnormally misplaced oil-casing pressure difference, excessive oil-casing pressure difference and excessive oil-casing pressure difference;

[0055] Normal oil-casing pressure difference means that the oil-casing pressure is less than 3MPa;

[0056] The oil-casing pressure difference is often misaligned when the oil-casing pressure difference is negative;

[0057] Too large oil-casing pressure difference means that the oil-casing pressure difference is greater than 3MPa and less than or equal to 5MPa;

[0058] An excessively large oil-casing pressure difference means that the oil-casing pressure difference is greater than 5MPa.

[0059] The present invention has at least the following beneficial effects:

[0060] The present invention obtains production data related to the plunger gas lift system, identifies abnormal operating conditions of single parameters through a trend algorithm based on the acquired production data related to the plunger gas lift system, and outputs abnormal operating condition results; real-time data collection is performed on the long-term operating form of a well or several single parameters of the fault, and the trend algorithm is calculated on the data to obtain corresponding abnormal operating condition results, thereby solving the problems of low recognition efficiency and poor accuracy when identifying plunger gas lift fault data. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 It is a flow chart of a method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis of the present invention;

[0063] Figure 2 It is a schematic diagram of the production curve of insufficient energy recovery of the plunger gas lift gas well of the present invention;

[0064] Figure 3 It is a schematic diagram of the production curve of the plunger gas lift liquid-filled and water-flooded well of the present invention;

[0065] Figure 4 It is a schematic diagram of the production curve of the pressure increase of the gathering and transportation pipeline of the plunger gas lift well of the present invention;

[0066] Figure 5 It is a schematic diagram of the production curve error of the plunger gas lift well process of the present invention;

[0067] Figure 6 It is a schematic diagram of the production curve of the plunger gas lift well of the present invention when the plunger is stuck or the sensor fails;

[0068] Figure 7 It is a schematic diagram of the abnormal production curve of plunger gas lift well data of the present invention. DETAILED DESCRIPTION

[0069] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0070] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0071] like Figure 1 As shown in the figure, after analyzing a large number of fault cases, especially after a detailed analysis of the fault diagnosis chart, it can be found that the long-term operation pattern of the plunger gas lift well is related to the long-term trend of a single parameter when the changes in a single cycle are not considered, and it is a combination of the trend patterns of several single parameters. Single parameter anomaly identification focuses on anomaly identification of the long-term trend (ten cycles) of a single parameter.

[0072] A method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis, comprising:

[0073] S1: Obtain production data related to the plunger gas lift system;

[0074] Obtain real-time switch well status data, plunger status data, oil pressure data, casing pressure data and oil-casing pressure difference data;

[0075] S2: Based on the obtained production data related to the plunger gas lift system, the abnormal working condition of the single parameter is identified through the trend algorithm, and the abnormal working condition results are output;

[0076] Abnormal working conditions are identified for single parameters, including: switch well status, plunger status, oil pressure status, casing pressure status and oil-casing pressure difference.

[0077] As a further improvement of this scheme, the long-term operation form or fault of a well is a combination of the trend forms of several single parameters; the calculation of the slope and extreme value of the long period is the main means, and the real-time collected data is used as the research object to perform a trend algorithm, including: trend index calculation, 3σ extreme value identification, constant value identification and parameter overall rising and falling trend determination function; the long-term trend of the five single parameters of the switch well status, plunger status, oil pressure, casing pressure, and oil-casing pressure difference within the period is judged, and the identification results are applied in combination according to business characteristics.

[0078] As a further improvement of this solution, the specific formula of the trend algorithm is as follows:

[0079] (1) The trend index is calculated as:

[0080]

[0081] Among them, f m (x,y) is the trend index, x is the oil pressure, casing pressure and other values, y is the time, and n is a natural number.

[0082] (2) 3σ extreme value identification is:

[0083]

[0084]

[0085]

[0086] Among them, p min is the minimum pressure, p max is the maximum pressure, δ is a fixed value, 0.67, f l (x) is the calculated outlier point, 1 means it is beyond the normal range, and 0 means it is within the normal range.

[0087] (3) Constant value identification is:

[0088]

[0089] Among them, x max is the maximum value of oil pressure and casing pressure, x min is the minimum value of oil pressure and casing pressure, j is the judgment threshold (set value), y s1 is the constant value identification result, 1 means the oil pressure difference or casing pressure difference is constant, 2 means the maximum and minimum oil pressure difference or casing pressure difference is less than j.

[0090] (4) The overall upward and downward trend determination function of the parameter is:

[0091]

[0092]

[0093] Among them, x s is the slope of oil pressure, casing pressure, etc., y s2 It is the judgment result of the overall rising and falling trend of the parameter, 0 is normal, 1 is abnormal rising, 2 is abnormal falling, and a is the judgment threshold (set value).

[0094] Apply the trend algorithm to the five single parameters of the well opening and closing state, plunger state, oil pressure state, casing pressure state, and oil-casing pressure difference, and finally obtain the 25 identifiable conditions in all single parameter abnormality identification, including:

[0095] There are three types of well switching status: normal well switching, missing well switching data, and too short well switching time;

[0096] Normal well switching means that the well switching cycle is normal; missing well switching data means that the well switching has no status data; too short well switching time means that the well opening time is less than 10 minutes.

[0097] There are four types of plunger states: plunger is normal, plunger is at the bottom of the well for a long time, plunger is at the wellhead for a long time, and plunger does not match the switch well;

[0098] The plunger is normal means that the plunger is in normal operating condition; the plunger is at the bottom of the well for a long time, which means that the plunger has not arrived; the plunger is at the wellhead for a long time, which means that the plunger has always been in the arrival state; the plunger does not match the switch well, which means that the plunger lifting process does not match; the plunger does not show the arrival state when the well is opened; the plunger is not at the bottom of the well when the well is closed.

[0099] There are 7 types of oil pressure status: normal oil pressure status, oil pressure communication failure, abnormal constant oil pressure, approximately constant oil pressure, abnormal oil pressure increase, abnormal oil pressure decrease and oil pressure exceeding the normal range;

[0100] Normal oil pressure status means that the oil pressure status conforms to the normal operation status of the plunger; oil pressure communication failure refers to oil pressure failure caused by communication problems; abnormal constant value of oil pressure means that the oil pressure is a constant value; approximate constant value of oil pressure means that the segmented constant value is less than 0.7; abnormal increase in oil pressure means that the slope mean of the oil pressure cycle mean increases by more than 0.07; abnormal decrease in oil pressure means that the slope mean of the oil pressure cycle mean decreases by more than 0.05; oil pressure exceeds the normal range means that the oil pressure exceeds the normal oil pressure range of the gas well, and the 3σ extreme value is identified as 1.

[0101] There are 7 types of casing pressure status: normal casing pressure status, casing pressure communication failure, abnormal casing pressure constant value, casing pressure approximately constant value, abnormal casing pressure rise, abnormal casing pressure drop, and exceeding the normal range;

[0102] To further explain, normal casing pressure status means that the casing pressure status conforms to the normal operation status of the plunger; casing pressure communication failure refers to a casing pressure failure caused by a communication problem; abnormal constant value of casing pressure means that the casing pressure is a constant value; approximate constant value of casing pressure means that the segmented constant value is less than 0.7; abnormal increase in casing pressure means that the slope mean of the casing pressure cycle mean increases by more than 0.07; abnormal increase in casing pressure means that the slope mean of the casing pressure cycle mean decreases by more than 0.05; casing pressure exceeds the normal range means that the casing pressure exceeds the normal casing pressure range of the gas well, and the 3σ extreme value is identified as 1.

[0103] There are four types of oil-casing pressure differential: normal oil-casing pressure differential, abnormally misplaced oil-casing pressure differential, excessive oil-casing pressure differential, and extremely large oil-casing pressure differential.

[0104] To further explain, normal oil-casing pressure difference means that the oil-casing pressure is less than 3MPa; abnormal oil-casing pressure difference means that the oil-casing pressure difference is negative; excessive oil-casing pressure difference means that the oil-casing pressure difference is greater than 3MPa and less than or equal to 5MPa; excessive oil-casing pressure difference means that the oil-casing pressure difference is greater than 5MPa.

[0105] Example 1

[0106] Insufficient energy recovery: Figure 2 As shown in the figure, the long-term performance of the plunger fault well with insufficient energy recovery is as follows: the casing pressure state rises, the oil pressure state is stable, the gas well is opened normally, the plunger state has not been reached, and the switch well state is basically normal. Here, only the long-term overall form of a single parameter is considered, that is, whether it rises, falls or is stable in the long term. The change law within the plunger gas lift drainage cycle (the three trends of rising, continuous flow, and recovery in a single cycle, and the rationality of the form) is not considered.

[0107] Example 2

[0108] Effusion and flooding: Figure 3 As shown in the figure, the failure of plunger gas lift liquid accumulation and water flooding in the well is specifically manifested in the long term as follows: the casing pressure continues to rise, the oil pressure is stable, and the plunger state has not been reached. The well can be opened and closed normally for a period of time at the beginning, but the gas well is flooded and shut down in the later stage.

[0109] In terms of the long-term performance of a single parameter, effusion and flooding are the same as insufficient energy recovery, that is, the casing pressure rises and the oil pressure is stable. The difference lies in the changing rules within the cycle (whether the three-segment morphology within the cycle conforms to the business characteristics) and other multi-parameter factors such as oil-casing pressure difference and load coefficient. This part will be analyzed in the multi-parameter anomaly identification.

[0110] Example 3

[0111] Gathering pipeline pressure rises: Figure 4 As shown, the failure of the gathering and transportation pipeline pressure increase is specifically manifested in the long term as follows in terms of a single parameter: the casing pressure continues to rise, the oil pressure rises, the plunger state has never reached the target, and the well switching state performs normal well switching operations.

[0112] Example 4

[0113] Process error: Figure 5 As shown in the diagram of the production curve of the plunger gas lift process error, the curve has been unstable for a long time, that is, there is no fixed pattern for the changes in the casing pressure state and the oil pressure state, the plunger state has not been reached, and the switching well state performs normal switching well operations.

[0114] Example 5

[0115] The plunger is stuck or the arrival sensor is faulty: Figure 6 As shown, for wells where the casing pressure and oil pressure are stable and normal for a long time due to the stuck plunger or sensor failure, the change pattern within the cycle is in line with the business characteristics. Some wells even have normal drainage. For wells where the plunger is stuck and has not arrived for a long time, the plunger status is "not arrived" for a long time, and the well switching status performs normal well switching operations.

[0116] Example 6

[0117] Data anomaly: such as Figure 7 As shown in the figure, in the actual production environment, in addition to some classic fault types, there are a large number of data abnormality faults in the plunger data abnormal well. The casing pressure state is a constant value of 5MPa for a long time, which may be a sensor failure, resulting in constant data. The plunger state has not arrived for a long time, which may be a long-term failure or data error. It is necessary to identify the data missing in the switch well state. In certain time periods, the data of the switch well is empty and may not be returned.

[0118] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis, characterized in that: include: Obtain production data related to the plunger gas lift system; Based on the production data related to the plunger gas lift system, the abnormal operating conditions of single parameters are identified through trend algorithms; Output abnormal operating conditions results.

2. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 1 is characterized in that: The acquisition of production data related to the plunger gas lift system includes: Obtain switch well status data, plunger status data, oil pressure data, casing pressure data and oil-casing pressure difference data.

3. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 1, characterized in that: The abnormal working condition identification is performed on a single parameter, and the identification objects include: the switch well status, the plunger status, the oil pressure status, the casing pressure status and the oil-casing pressure difference.

4. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 3 is characterized in that: The trend algorithm includes: trend index calculation, 3σ extreme value identification, constant value identification and parameter overall rising and falling trend determination function.

5. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 4 is characterized in that: The trend index is calculated as: Among them, f m (x,y) is the trend index, x is the oil pressure and casing pressure, y is the time, and n is a natural number; The 3σ extreme value is identified as: Among them, p min is the minimum pressure, p max is the maximum pressure, δ is a fixed value, f l (x) is the calculated outlier point, 1 is beyond the normal range, and 0 is the normal range; The constant value is identified as: Among them, x max is the maximum value of oil pressure and casing pressure, x min is the minimum value of oil pressure and casing pressure, j is the discrimination threshold, y s1 is the constant value identification result, 1 means the oil pressure difference or casing pressure difference is constant, 2 means the maximum and minimum oil pressure difference or casing pressure difference is less than j; The overall upward and downward trend determination function of the parameter is: Among them, x s is the slope of oil pressure and casing pressure, y s2 is the judgment result of the overall rising and falling trend of the parameter, 0 is normal, 1 is abnormal rising, 2 is abnormal falling, and a is the judgment threshold.

6. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 5, characterized in that: The switch well status includes: the switch well is normal, the switch well data is missing, and the switch well time is too short; Normal well opening and closing means that the well opening and closing cycle is normal; Missing switch well data means that the switch well has no status data; The well opening and closing time is too short, which means the well opening time is less than 10 minutes.

7. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 5, characterized in that: The plunger status includes: the plunger is normal, the plunger is at the bottom of the well for a long time, the plunger is at the wellhead for a long time, and the plunger does not match the switch well; Normal plunger means the plunger is operating normally; The plunger is at the bottom of the well for a long time, indicating that the plunger has not arrived; The plunger is at the wellhead for a long time, which means the plunger is always in the arrival state; The mismatch between the plunger and the well switch means that the plunger lifting process does not match. When the well is opened, the plunger does not show the arrival status, and when the well is closed, the plunger is not at the bottom of the well.

8. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 5, characterized in that: The oil pressure status includes: normal oil pressure status, oil pressure communication failure, abnormal constant oil pressure, approximately constant oil pressure, abnormal increase in oil pressure, abnormal decrease in oil pressure, and oil pressure exceeding the normal range; Normal oil pressure status means that the oil pressure status is consistent with the normal operation of the plunger; Oil pressure communication failure refers to oil pressure failure caused by communication problems; Abnormal constant value of oil pressure means that the oil pressure is a constant value; The approximate constant value of oil pressure means that the segmented constant value is less than 0.7; Abnormal increase in oil pressure means that the slope of the oil pressure cycle mean increases by more than 0.07; Abnormal oil pressure drop means that the slope of the oil pressure cycle mean drops by more than 0.05; Oil pressure exceeding the normal range means that the oil pressure exceeds the normal oil pressure range of the gas well, and the 3σ extreme value is identified as 1.

9. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 5, characterized in that: The casing pressure status includes: normal casing pressure status, casing pressure communication failure, abnormal constant casing pressure, approximately constant casing pressure, abnormal casing pressure rise, abnormal casing pressure drop and exceeding the normal range; Normal casing pressure state means that the casing pressure state conforms to the normal operation state of the plunger; Casing pressure communication failure refers to casing pressure failure caused by communication problems; Abnormal constant value of casing pressure means that the casing pressure is a constant value; The casing pressure approximate constant value means that the segmented constant value is less than 0.7; Abnormal increase in casing pressure means that the slope of the casing pressure cycle mean value increases by more than 0.07; Abnormal increase in casing pressure means that the slope of the mean of the casing pressure cycle decreases by more than 0.05; Casing pressure exceeding the normal range means that the casing pressure exceeds the normal casing pressure range of the gas well, and the 3σ extreme value is identified as 1.

10. The method for identifying abnormal working conditions of plunger gas lift based on single parameter analysis according to claim 5, characterized in that: The oil casing pressure difference includes: normal oil casing pressure difference, abnormal oil casing pressure difference, excessive oil casing pressure difference and super large oil casing pressure difference; Normal oil-casing pressure difference means that the oil-casing pressure is less than 3MPa; The oil-casing pressure difference is often misaligned when the oil-casing pressure difference is negative; Too large oil-casing pressure difference means that the oil-casing pressure difference is greater than 3MPa and less than or equal to 5MPa; An excessively large oil-casing pressure difference means that the oil-casing pressure difference is greater than 5MPa.

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