Tubing number calculation method based on string acceleration during string tripping process

Abstract

The present application belongs to the technical field of oil well downhole operation detection. The provided method for calculating the number of tubing in the process of tubing tripping based on the acceleration of the tubing string is characterized in that: the acceleration data in the process of tripping down and tripping up is recorded by a tubing string intelligent monitoring device, the effective data section in the tripping down section is identified through the acceleration waveform characteristics, the acceleration data is denoised, then the characteristic section and the characteristic point are calculated, and finally the number of the tubing string is calculated according to the number of the characteristic points. The present application uses the Z-axis acceleration data corresponding to the process of tubing tripping, realizes the correspondence between the data collected by the tubing string intelligent monitoring device and the action of installing the tubing string under the wellhead by the operation team. The present application has the advantages of simple operation, high automation, reduced production cost, reduced education cost of training personnel, reduced learning cost of users, and prevention of data falsification.

Description

Technical Field

[0001] This invention relates to a method for calculating the number of tubing strings during the running-in and running-out process based on tubing string acceleration, belonging to the field of downhole operation detection technology for oil wells. Background Technology

[0002] As oilfield development enters its mid-to-late stages, both new well development and maintenance of existing wells become crucial for increasing production. Therefore, monitoring and management of downhole operations and their quality are of paramount importance. Downhole operations involve taking appropriate technical measures to maintain oil and water wells, restoring them to normal operation or enhancing their productivity.

[0003] The technical capabilities and skills of the construction teams working in underground mines vary greatly. Most of the operational parameters are still manually tested and recorded, resulting in a large workload, low level of automation, and inability to intuitively reflect the quality of the work. It is necessary to digitally manage the operational parameters and monitor the operational quality online in order to effectively control the production costs and improve the overall economic benefits.

[0004] Running the tubing string is the most routine and largest-scale procedure in downhole operations, but it is also the procedure where accidents and safety hazards frequently occur. However, in current technology, the downhole environment is complex, the actions of running the tubing string are varied, and counting is difficult. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method for calculating the number of tubing pipes during the tubing string raising and lowering process based on tubing string acceleration. This method offers high counting accuracy and minimal error, resolving issues related to omissions in manual recording, data tampering, and falsified data.

[0006] The present invention is achieved through the following technical solutions.

[0007] The present invention provides a method for calculating the number of tubing strings during the running-out and tripping process based on tubing string acceleration. This method records acceleration data during the running-out and tripping processes using an intelligent tubing string monitoring device. It identifies effective data segments in the running-out interval based on acceleration waveform characteristics, denoises the acceleration data, calculates characteristic intervals and characteristic points, and then calculates the number of tubing strings based on the number of characteristic points. Specifically, the method is as follows: Step 1: Process the Z-axis acceleration by adding 1 to the Z-axis acceleration data to obtain the engineering Z-axis acceleration, generate the acceleration waveform, read the acceleration waveform, and filter out the valid data segments of the Z-axis acceleration data in the downhole and uphole intervals. Step 2: Calculate the mean acceleration of all data points in the valid data segment, and then calculate the difference between each point and the mean to perform noise reduction. Step 3: Identify the downhole interval of each tubing string based on the acceleration curve: On the acceleration curve, define a period of drastic acceleration change and a period of stable acceleration as a characteristic interval; define the start and end points of the drastic acceleration change period as characteristic points, and each characteristic interval corresponds to the complete downhole placement of one tubing string. Step 4: Calculate all valid feature points in the downhole section using the feature point formula. The valid feature points correspond to the valid feature intervals of the downhole section, which is the number of tubing strings used in this downhole process.

[0008] The calculation process of the characteristic point formula is as follows: First, calculate the point of abrupt acceleration change A. n A n =i|a i a i+1 <1 (1); In the formula a Let i be the acceleration, and i be the acceleration sampling time. A This refers to the moment of rapid acceleration and change. When the accelerations of adjacent points are positive and negative, a i a i+1 <1, that is, when the acceleration changes drastically, the time i at the measurement point is denoted as the acceleration change point A. n Once all points of abrupt acceleration changes are obtained, the characteristic points are then calculated using the following formula: Start m =A n |(A n -A n-1 )>T / 3 (2); Stop m-1 =A n-1 |(A n -A n-1 )> T / 3 (3); Start m Stop is the starting point of drastic acceleration changes within the characteristic interval. m-1 This represents the endpoint of the drastic acceleration change within the characteristic interval. m The count value is the characteristic interval, where T is the length of the characteristic interval (default length is 450). The time interval A between adjacent points of abrupt acceleration change is... n -A n-1 When the value is greater than T / 3, the point of An at this time is regarded as the starting point of the drastic change in acceleration in the current characteristic interval. m The corresponding A n-1 The point is considered as the end point of the drastic acceleration change in the previous characteristic interval m-1 (stop). m-1 Iterate through all An to obtain all feature points Start. mand stop m Next, calculate the adaptive feature interval value according to the following formula: T real =( (Start m -Start m-1 ) / (m-1)+ (Stop m -Stop m-1 ) / (m-1)) / 2 (4); T real The characteristic interval value of the current well-running process is given. Then, this value is substituted into the above formulas (2) and (3) as T and the calculation is performed again to obtain the characteristic point that is suitable for the current well-running process.

[0009] In step 2, the difference within the range of 0.1g is considered noise.

[0010] In step 3, the number of feature intervals is half the number of feature points.

[0011] The beneficial effects of the present invention are as follows: The present invention has the following characteristics: This invention uses Z-axis acceleration data to correspond to the tubing string installation process, thus realizing the correspondence between the work team's tubing string installation actions below the wellhead and the data collected by the tubing string intelligent monitoring device.

[0012] This invention uses Z-axis acceleration data as the basis for calculation, which simplifies the calculation process, increases efficiency, and facilitates intelligent monitoring during the well process.

[0013] The present invention employs multiple noise reduction methods in the calculation process to shield against sudden acceleration changes during the well-running process and the influence of excessive acceleration noise in the early stage of well-running, which leads to unclear waveform characteristics, resulting in accurate calculation results.

[0014] This invention has the advantages of simple operation, high degree of automation, reduced production costs, reduced training costs for personnel, reduced learning costs for users, and prevention of data fraud.

[0015] This invention can detect the time taken for the work team to lower the tubing string by observing the length of a characteristic interval. If the length is too short, it indicates that the work team is prioritizing speed over quality, effectively supervising the quality of the work. Furthermore, the acceleration curve of the entire well-lowering process can be viewed at any time. If an operational accident occurs, such as the tubing string falling into the well, there will be a corresponding abnormal reaction on the acceleration curve, which can be provided to professionals for analysis and effectively prevent the work team from concealing operational accidents. Attached Figure Description

[0016] Figure 1This is a schematic diagram illustrating the principle and flow of the present invention.

[0017] Figure 2 This is a data display graph collected by the intelligent monitoring device for tubular columns.

[0018] Figure 3 yes Figure 2 Enlarged schematic diagram of the waveform.

[0019] Figure 4 This is the waveform after noise reduction in step 2.

[0020] Figure 5 This is a schematic diagram of the feature intervals and feature points in step 3.

[0021] Figure 6 This is a schematic diagram showing the results of the calculation of the number of tubular columns.

[0022] Figure 7 This is a schematic diagram showing the calculation results of the number of tubing strings in a certain oilfield in the example. Detailed Implementation

[0023] The technical solution of the present invention is further described below, but the scope of protection is not limited to what is described. Example 1

[0024] A method for calculating the number of tubing strings during the running-out and tripping process based on tubing string acceleration is proposed. This method uses an intelligent tubing string monitoring device to record acceleration data during the running-out and tripping processes. Effective data segments within the running-out interval are identified through acceleration waveform characteristics. The acceleration data is then denoised, and characteristic intervals and points are calculated. The number of tubing strings is then calculated based on the number of characteristic points. While existing intelligent tubing string monitoring devices can be used, they collect a wide variety of data, including acceleration, flow rate, temperature, and pressure. Calculating and analyzing all of this data would be extremely complex and could even lead to system crashes due to the sheer volume of data. Therefore, a simplified calculation method is needed to ensure accurate results.

[0025] The specific calculation method is as follows: Step 1: Process the Z-axis acceleration by adding 1 to the Z-axis acceleration data to obtain the engineering Z-axis acceleration. Generate an acceleration waveform, read the waveform, and filter out the valid data segments of the Z-axis acceleration data between the wellhead and wellhead tripping intervals. The intelligent monitoring device for the tubing string is cylindrical, and the axis perpendicular to the cylindrical surface is defined as the Z-axis. Before being lowered into the well, the instrument is placed in a horizontal position at the wellhead awaiting lowering, therefore there is no acceleration in the Z-axis direction, the Z-axis acceleration is 0, and the value presented in the processed engineering data is 1. During lowering into the well, the instrument is mounted on the casing, and there is a negative 1g acceleration in the Z-axis direction, and the value presented in the processed engineering data is 0.

[0026] Step 2: Calculate the mean acceleration of all data points in the valid data segment, then calculate the difference between each point and the mean to perform noise reduction. Based on the analysis of the operation, generally speaking, the difference within the range of 0.1g is considered noise, where g represents the acceleration due to gravity, and the unit is m / s². 2 .

[0027] Step 3: Identify the downhole interval for each tubing string based on the acceleration curve: On the acceleration curve, define a period of drastic acceleration fluctuation and a period of stable acceleration as a characteristic interval; define the start and end points of the drastic acceleration fluctuation period as characteristic points; each characteristic interval corresponds to the complete placement of one tubing string, specifically as follows: During the tubing string placement process, the work team will continuously add tubing strings at the wellhead. During the addition of tubing strings, the Z-axis acceleration will fluctuate, which is considered the tubing string placement operation time. After the tubing string is added, the downhole operation continues. At this time, the tubing string is relatively stable, and the Z-axis acceleration basically does not fluctuate, which is considered the waiting time for adding tubing strings. The above process is defined as a characteristic interval, indicating that one tubing string has been completely placed. To facilitate calculation, characteristic points are introduced based on the characteristic intervals to represent the start and end points of the tubing string placement operation, which facilitates data collection and calculation. Therefore, it can be seen that the number of characteristic intervals is half the number of characteristic points.

[0028] Step 4: Calculate all valid feature points in the downhole section using the feature point formula. The valid feature points correspond to the valid feature intervals of the downhole section, which is the number of tubing strings used in this downhole process.

[0029] It uses only Z-axis acceleration data for calculations to monitor the number of tubing pipes during downhole operations, simplifying the calculation process and reducing the amount of data, thus increasing efficiency.

[0030] The calculation process of the characteristic point formula is as follows: First, calculate the point of abrupt acceleration change A. n A n =i|a i a i+1 <1 (1); In the formula a Let i be the acceleration, and i be the acceleration sampling time. A This refers to the moment of rapid acceleration and change. When the accelerations of adjacent points are positive and negative, a i a i+1 <1, that is, when the acceleration changes drastically, the time i at the measurement point is denoted as the acceleration change point A. n Once all points of abrupt acceleration changes are obtained, the characteristic points are then calculated using the following formula: Start m =A n |(A n-A n-1 )>T / 3 (2); Stop m-1 =A n-1 |(A n -A n-1 )> T / 3 (3); Start m Stop is the starting point of drastic acceleration changes within the characteristic interval. m-1 This represents the endpoint of the drastic acceleration change within the characteristic interval. m The count value is the characteristic interval, where T is the length of the characteristic interval (default length is 450). The time interval A between adjacent points of abrupt acceleration change is... n -A n-1 When the value is greater than T / 3, the point of An at this time is regarded as the starting point of the drastic change in acceleration in the current characteristic interval. m The corresponding A n-1 The point is considered as the end point of the drastic acceleration change in the previous characteristic interval m-1 (stop). m-1 Iterate through all An to obtain all feature points Start. m and stop m Next, calculate the adaptive feature interval value according to the following formula: T real =( (Start m -Start m-1 ) / (m-1)+ (Stop m -Stop m-1 ) / (m-1)) / 2 (4); T real The characteristic interval value of the current well-running process is given. Then, this value is substituted into the above formulas (2) and (3) as T and the calculation is performed again to obtain the characteristic point that is suitable for the current well-running process.

[0031] In the specific implementation process, data from one well in Jilin Oilfield and two wells in Daqing Oilfield were used for verification. The intelligent tubing monitoring device was lowered into the well along with the tubing string, and the instrument was retrieved after the well-running operation was completed. Then, the instrument was connected to the software, and the acceleration data stored in the instrument was read through the software interface. After reading the data, simply clicking the "Calculate Tubing Quantity" button automatically identifies and calculates the number of tubing strings used during the current well-running process. The Z-axis acceleration data waveform of a certain well is shown below. Figure 2 and 3 As shown, the image after denoising is as follows. Figure 4 As shown, the feature intervals and feature points are as follows: Figure 5 As shown, the final number of tubing columns is as follows: Figure 6As shown, the calculation results for each well are as follows: Figure 7 As shown in Table 1, the statistical comparison of the results is presented.

[0032]

[0033] The calculation results show that the algorithm maintains an accuracy rate of over 99%, with an average accuracy of 99.1%, achieving a very high level of accuracy. Furthermore, the software design fully integrates the algorithm's logical operations into the software itself, making it easy to operate and greatly simplifying the learning curve. Even operators without relevant technical knowledge can use it. The process requires no additional parameter settings or waveform adjustments by the user. The algorithm only needs to read and process a single data point (acceleration Z-axis data) to obtain the result, avoiding the uncertainties introduced by multi-parameter data. Moreover, this software is a finished product, having undergone testing and verification before being delivered to the customer.

[0034] Meanwhile, to address abnormal well-running situations, such as repeated tubing tripping, the software interface includes settings for the characteristic interval length and the start and end points of the well-running process. When operators detect abnormal waveforms or significant discrepancies in the calculated tubing count, they can manually set the parameters for calculation. The parameter settings can be determined by observing the acceleration waveform.

Claims

1. A method for calculating the number of tubing pipes during the tubing string raising and lowering process based on tubing string acceleration, characterized in that: Acceleration data during the well run-in and well trip-out processes are recorded using an intelligent tubing monitoring device. Valid data segments in the well run-in interval are identified based on acceleration waveform characteristics. The acceleration data is then denoised, and characteristic intervals and points are calculated. Finally, the number of tubing segments is calculated based on the number of characteristic points, as detailed below: Step 1: Process the Z-axis acceleration by adding 1 to the Z-axis acceleration data to obtain the engineering Z-axis acceleration, generate the acceleration waveform, read the acceleration waveform, and filter out the valid data segments of the Z-axis acceleration data in the downhole and uphole intervals. Step 2: Calculate the mean acceleration of all data points in the valid data segment, and then calculate the difference between each point and the mean to perform noise reduction. Step 3: Identify the downhole interval of each tubing string based on the acceleration curve: On the acceleration curve, define a period of drastic acceleration change and a period of stable acceleration as a characteristic interval; define the start and end points of the drastic acceleration change period as characteristic points, and each characteristic interval corresponds to the complete downhole placement of one tubing string. Step 4: Calculate all valid feature points in the downhole section using the feature point formula. The valid feature points correspond to the valid feature intervals of the downhole section, which is the number of tubing strings used in this downhole process.

2. The method for calculating the number of tubing lines during the tubing string raising and lowering process based on tubing string acceleration as described in claim 1, characterized in that: The calculation process of the characteristic point formula is as follows: First, calculate the point of abrupt acceleration change A. n A n =i|a i a i+1 <1 (1); In the formula a Let i be the acceleration, and i be the acceleration sampling time. A This refers to the moment of rapid acceleration and change. When the accelerations of adjacent points are positive and negative, a i a i+1 <1, that is, when the acceleration changes drastically, the time i at the measurement point is denoted as the acceleration change point A. n Once all points of abrupt acceleration changes are obtained, the characteristic points are then calculated using the following formula: Start m =A n |(A n -A n-1 )>T / 3 (2); Stop m-1 =A n-1 |(A n -A n-1 )> T / 3 (3); In the formula Start m Stop is the starting point of the characteristic interval. m-1 The end point of the characteristic interval, m The count value is the characteristic interval, where T is the length of the characteristic interval (default length is 450). The time interval A between adjacent points of abrupt acceleration change is... n -A n-1 When the value is greater than T / 3, the point of An at this time is regarded as the starting point of the current feature interval. m The corresponding A n-1 The point is considered as the end point (stop) of the previous characteristic interval m-1. m-1 Iterate through all An to obtain all feature points Start. m and stop m Next, calculate the adaptive feature interval value according to the following formula: T real =( (Start m -Start m-1 ) / (m-1)+ (Stop m -Stop m-1 ) / (m-1)) / 2 (4) ; T real The characteristic interval value of the current well-running process is given. Then, this value is substituted into the above formulas (2) and (3) as T and the calculation is performed again to obtain the characteristic point that is suitable for the current well-running process.

3. The method for calculating the number of tubing lines during the tubing string raising and lowering process based on tubing string acceleration as described in claim 1, characterized in that: In step 2, the difference within the range of 0.1g is considered noise.

4. The method for calculating the number of tubing units during the tubing string tripping process based on tubing string acceleration as described in claim 1, characterized in that: In step 3, the number of feature intervals is half the number of feature points.

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