Gas well intelligent gas lifting control system and method based on dynamic time slice and adaptive scheduling

Abstract

This invention discloses an intelligent gas lift control system and method for gas wells based on dynamic time slices and adaptive scheduling. The system includes a data acquisition device, a control device, and an actuator. The data acquisition device collects gas well casing pressure, oil pressure, and flow rate data and sends them to the control device. The control device scores the current gas injection time slice based on a preset drainage efficiency evaluation function, generates a scheduling strategy based on the scoring results, and outputs a control signal to the actuator. The actuator controls the opening and closing of the electrically controlled gas lift valve and the duration of its opening based on this signal. This invention constructs a closed-loop mechanism for data acquisition, logical judgment, and action execution, achieving adaptive dynamic expansion and contraction of gas lift resources without changing the on-site gas source discharge rate, thereby effectively improving drainage efficiency and reducing ineffective gas injection consumption.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas extraction technology, and specifically relates to an intelligent gas lift control system and method for gas wells based on dynamic time slices and adaptive scheduling. Background Technology

[0002] Gas lift is an effective means of removing accumulated liquid in gas wells. However, in actual production, due to the complex slippage effect and wellbore storage effect of the gas-liquid two-phase flow in the wellbore, the changes in oil-casing pressure difference and production rate monitored on the surface often lag significantly behind the actual liquid accumulation state downhole, making it difficult to accurately determine the optimal start-up and shutdown time of the gas lift on site.

[0003] Existing airlift control methods have the following significant drawbacks when dealing with data lag and dynamic resource allocation: The first type is timed control, such as patent CN111472733B ("An Intelligent Intermittent Drainage Gas Production System and Its Control Method"), which relies on preset fixed start and stop times, ignoring the dynamic liquid production capacity of the gas well, and is very likely to cause ineffective gas injection or insufficient liquid drainage.

[0004] The second category is single-well pressure threshold closed-loop control, such as patent CN110318715B ("A plunger-assisted intermittent gas lift fluid drainage and gas production control system and control method"). Due to data lag, when the pressure differential reaches the target, there is often severe fluid accumulation downhole, and when the pressure differential recovers, ineffective gas blowing has already occurred for a long time, lacking an advance prediction and cutoff mechanism for the gas injection duration.

[0005] The third type focuses on passive flow stabilization, such as patent ZL200410073493.8 ("A separator and a self-lift method for eliminating severe slugging flow"). It uses liquid level signals for passive adjustment, but lacks a low-cost "cold start test" mechanism. If severe gas channeling occurs downhole, the trial and error cost of blindly injecting gas for a long time is extremely high.

[0006] The fourth category focuses on global gas volume allocation, such as patent CN113153281A ("An Optimization Model for Realizing Cooperative Production of Oil and Gas Wells on Offshore Platforms"). Its complex mathematical model has a large amount of computation and slow solution, and can only output macroscopic long-cycle production allocation schemes. It cannot meet the needs of on-site high-frequency dynamic scheduling of limited gas lift resources at the minute level.

[0007] In conclusion, existing technologies cannot overcome the blind spots caused by data lag, and resource allocation is rigid, which has significant shortcomings and urgently needs to be optimized and resolved. Summary of the Invention

[0008] To address the problems of lagging ground monitoring data, inaccurate gas lift initiation judgment, lack of dynamic adjustment mechanism in the gas injection process, and low resource utilization in existing gas lift control technologies, this invention proposes an intelligent gas lift control system and method for gas wells based on dynamic time slices and adaptive scheduling. By managing the gas lift process in a time slice manner and combining it with real-time performance evaluation, the system achieves adaptive optimization of gas lift resources, thereby improving drainage efficiency and reducing ineffective gas injection consumption.

[0009] One aspect of the present invention proposes a smart gas lift control system for gas wells based on dynamic time slices and adaptive scheduling, comprising: Gas injection pipeline, the gas injection pipeline is used to connect the high-pressure gas source to the gas well casing or oil tubing annulus; An actuator, which is disposed on the gas injection pipeline, includes an electrically controlled gas lift valve for controlling the opening or closing of the gas injection channel; The data acquisition device is used to collect pressure and flow parameter data during the operation of the gas well, namely, pressure gauges and flow meters deployed at the wellhead; The control device is electrically connected to the data acquisition device and the actuator deployed on the gas lift pipeline valve, and is used to receive data, perform logical operations and output control signals.

[0010] The control device includes: The data receiving module, an industrial-grade router deployed in the field control cabinet, is wired to the flow meter and pressure gauge of the gas sampling tree and is used to receive casing pressure, tubing pressure and flow data collected by the data acquisition device. The computation and processing module, deployed on a remote computing server, is used to score the current gas injection time slice based on a preset liquid discharge efficiency evaluation function, and generate the scheduling strategy for the next time slice based on the scoring results, serving as the decision unit for the gas lift valve opening and closing. The control output module is used to output control signals to the actuator according to the scheduling strategy, so as to control the opening or closing of the electro-pneumatic lift valve and the opening duration.

[0011] A further improvement of the present invention is that the control device is an industrial control equipment, preferably a programmable logic controller, a remote terminal unit, or an industrial control computer, and the arithmetic processing module is executed by a processor using the time slice scheduling algorithm.

[0012] A further improvement of the present invention is that the data acquisition device includes a casing pressure sensor, a tubing pressure sensor, and a flow meter, which are directly connected to the gas production tree.

[0013] A further improvement of the present invention is that the data acquisition device and the control device transmit data via an industrial communication protocol, preferably the Modbus protocol.

[0014] A further improvement of the present invention is that the control output module outputs a switching control signal to the electrically controlled air lift valve through a digital output interface, thereby realizing the control of the electrically controlled air lift valve.

[0015] A further improvement of the present invention is that the system further includes a network communication module and a remote server. The network communication module is connected to the control device via wireless communication to realize data interaction between field data and the remote system. The remote server includes a protocol parsing server and a back-end control system to realize data processing, storage and remote monitoring functions.

[0016] According to another aspect of the present invention, a smart gas lift control method for gas wells based on dynamic time slices and adaptive scheduling is also proposed, implemented using the aforementioned smart gas lift control system for gas wells, comprising: When the gas well is in normal production, the data acquisition device continuously collects the pressure and flow data of the gas well. When the control device determines that the gas lift start-up conditions are met, it sends an start command to the actuator and allocates an initial probe time slice for trial gas injection. After the probe time slice has run out, the control device calculates a comprehensive score of the drainage efficiency within that time slice based on the collected data. Based on the comprehensive score of drainage efficiency, the control device generates a scheduling strategy for the next time slot and controls the actuator to perform the corresponding gas injection operation through the control output module; In subsequent operation, the performance evaluation and time slice scheduling steps are repeated to achieve dynamic adjustment of the airlift process; When the overall performance score of drainage is lower than the preset threshold, the control device outputs a shutdown command, closes the electrically controlled air lift valve, and ends the current air lift process.

[0017] A further improvement of the present invention is that the time slices are scheduled according to the comprehensive score of drainage efficiency as follows: When the overall score of drainage efficiency is greater than or equal to the excellent threshold, the next time segment will be increased by multiples according to the preset expansion coefficient. When the overall score of drainage efficiency is between the passing threshold and the excellent threshold, the next time slice will decrease according to the preset decay coefficient. When the overall drainage efficiency score is lower than the passing threshold, shutdown control is executed.

[0018] The scoring formula is as follows:

[0019] in, Q represents the rate of decrease in the differential pressure between the oil casing and the casing, used to characterize the trend of decreasing fluid level in the downhole annulus;liquid (t) represents the instantaneous liquid production on the ground; T represents the duration of the current time slice; w1 and w2 are the weighting coefficients set by the system.

[0020] A further improvement of the present invention is that an anti-vibration mechanism is set in the gas lift start-up determination process. The trend of oil-casing pressure difference change is judged by multiple consecutive sampling cycles. Only when the pressure difference continues to increase and exceeds a preset threshold is it determined that the gas lift start-up condition is met, so as to avoid false triggering.

[0021] Compared with the prior art, the advantages of the present invention are as follows: This invention achieves adaptive matching between air lift resource input and drainage effect by dividing the air lift process into multiple dynamically adjustable time slice units and expanding or attenuating the time slices based on real-time performance evaluation results. By introducing a probe time slice mechanism, a trial can be conducted at a lower cost in the early stages of gas lift startup, effectively reducing the waste of resources caused by blind gas injection. By constructing a closed-loop control system of "data acquisition - logical judgment - execution control", the real-time performance and stability of air lift control are improved. Without changing the on-site hardware displacement and gas source conditions, the performance of the gas lift process can be improved simply by optimizing the control strategy, which has good engineering application value and promotion prospects. Attached Figure Description

[0022] Figure 1 The figure shown is a schematic diagram of the intelligent gas lift control system for gas wells according to the present invention.

[0023] Figure 2 The diagram shown is a flowchart of the main steps of the intelligent gas lift control method for gas wells of the present invention. Figure 3 The figure shows the core scheduling logic flowchart of the air lift time adaptive scaling based on probe time slice and performance score of the present invention. Figure 4 The image shown is a picture of the actual field equipment of this invention; Figure 5 Photos of industrial router equipment; Figure 6 Photos of well sites using the system; Figure 7 Photos of the control circuit boards placed on site; Figure 8 Photos of air-lift motor equipment; Figure 9 A flowchart of the entire system; Explanation of reference numerals in the attached diagram: 1—Gas well; 2—Data acquisition device; 3—Industrial-grade router; 4—Kepserver server; 5—Back-end control system; 6—Electrically controlled gas lift valve; 7—Wired connection; 8—Network communication module; 9—Cloud server; 10—Gas lift unit. Detailed Implementation

[0024] To make the technical solution and beneficial effects of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. These embodiments are used to illustrate the present invention, and not to limit the scope of protection of the present invention.

[0025] In one embodiment, such as Figure 1 As shown, the present invention provides an intelligent gas lift control system for gas wells based on dynamic time slices and adaptive scheduling, including a gas well 1, a data acquisition device 2, a control device, a control device (electrically controlled gas lift valve 6), and a communication module.

[0026] The gas well 1 includes a casing and an oil pipe installed inside the casing. An annulus structure is formed between the oil pipe and the casing. High-pressure gas enters the annulus through the gas injection line to achieve gas lift.

[0027] The data acquisition device 2 includes a casing pressure sensor, a tubing pressure sensor, and a flow meter, which are used to collect casing pressure, oil pressure, and flow data in real time.

[0028] In this embodiment, the data acquisition device collects data at a fixed sampling period and sends the data to the control device via the Modbus communication protocol.

[0029] The control device is preferably a PLC, which includes a data receiving module, a processing module, and a control output module.

[0030] The actuator includes an electrically controlled air lift valve 6, which is installed on the air injection line and is used to control the on / off of the high-pressure air source.

[0031] In this embodiment, the control device sends a switching signal to the electronically controlled air lift valve through a digital output interface to control its opening or closing.

[0032] Combination Figures 1 to 4 The specific implementation steps of the present invention will be described in detail below. The initial probe time slice T0 = 15 minutes, the time slice expansion coefficient k = 2, the attenuation coefficient m = 0.5, and the preset passing performance threshold S are set below. pass =40, Excellent performance threshold S excellent =80 is used as a data reference for a specific embodiment.

[0033] In one specific implementation, the air lift control process of the present invention operates according to the following steps: Step 1, Initial Production Status: (e.g.) Figure 1 As shown, after the system is powered on, the electrically controlled gas lift valve 6 in the field sensing and execution layer is in the closed state, and the gas well 1 is in the natural production state; the data acquisition device 2 (pressure sensor / flow meter) continuously collects casing pressure, oil pressure and flow data, and periodically sends them to the back-end control system 5 of the remote server through the wired connection 7 and the network communication module 8.

[0034] Step 2, Determine the start-up conditions: such as Figure 2 and Figure 3 As shown in the initial logic, after receiving the data, the back-end control system 5 calculates the oil-casing pressure difference and its changing trend. To avoid false triggering due to data fluctuations, an anti-jitter mechanism is adopted. Only when the oil-casing pressure difference continues to increase and exceeds the preset threshold (e.g., 4.5MPa) within multiple consecutive sampling cycles (e.g., 3 consecutive cycles) is it determined that there is liquid accumulation in the well, which meets the gas lift start-up conditions. At this time, the control system outputs an opening signal to the electronically controlled gas lift valve 6 to start the gas lift process and allocates an initial probe time slice T0 (15 minutes).

[0035] Step 3: Probe time slice operation: (e.g.) Figure 4 As shown in the "cold start" stage, during the probe time slice T0, the electrically controlled gas lift valve 6 remains open, and the high-pressure gas provided by the gas lift unit 10 enters the wellbore annulus to lift the liquid in the well. During this time slice, the data acquisition device 2 continuously collects pressure and flow data and sends it to the back-end control system 5 in real time.

[0036] Step 4: End of Time Slot and Data Calculation: When time slot T0 (15 minutes) ends, the control system processes the data from that time slot and calls a preset function to calculate the comprehensive drainage efficiency score S(t). This score is calculated by weighting the parameters of the oil-jacket pressure difference change rate and flow rate change. Assuming that the pressure difference decreased significantly and the flow rate increased during this stage, the weighted calculation yields the air lift effect evaluation value S(T_0) = 85 for that time slot.

[0037] Step 5: Generate scheduling strategy: The control system based on... Figure 3 The core logic of the algorithm compares the score S(t) with a preset threshold and generates the scheduling strategy for the next time slice. When S(t) ≥ S excellent (As in this example, 85 ≥ 80) indicates that the air-lift effect is good and triggers. Figure 4 The "multiplicative surge" in the text refers to extending the next time slice length by a multiple of k. When S(t) is between the passing and excellent thresholds (i.e., 40 ≤ S(t) < 80), it indicates that the air-lift efficiency is decaying, triggering... Figure 4 The "smooth fading" in the text refers to shortening the time slice by the attenuation coefficient m; When S(t) pass When S(t) < 40, it indicates that the air lift effect is poor or air leakage has occurred, and the control system determines that the current air lift process is invalid.

[0038] Step 6: Execute control signal: According to the scheduling strategy generated in Step 5, the control system sends a control signal to the electro-pneumatic lift valve 6: if the air lift continues, the valve remains open and the timing is set according to the new time slice length; if the air lift stops, a shut-off signal is output to close the electro-pneumatic lift valve 6.

[0039] Step 7, Dynamic scaling loop: (e.g.) Figure 4 As shown on the timeline, if the airlift continues, the system enters the next time slice and repeats steps three through six. Based on the data from this embodiment: since the probe period S(T0) = 85 ≥ 80, expansion (T1) is executed, allocating the next time slice T1 = 15 × 2 = 30 minutes. If the score S(T1) = 60 after T1 ends, satisfying 40 ≤ S(T1) < 80, then phasing out (T3) is executed, allocating the next time slice T2 = 30 × 0.5 = 15 minutes, achieving a soft landing. During operation, each time slice undergoes independent evaluation and scheduling, achieving dynamic optimization control.

[0040] Step 8: Shut down the machine: (e.g.) Figure 3 "Ending the air lift process" and Figure 4 As shown in “T4”, when the scores of consecutive time slices are all below the threshold (e.g., the score is 25 after the slope reduction period ends) or the preset limit time is reached, the control system outputs a forced cutoff signal, the electric gas lift valve 6 is closed, and the gas well returns to the natural production state; the system continues to enter the data monitoring stage, waiting for the next start-up conditions to be met.

[0041] In one embodiment, such as Figure 1 As shown, the industrial-grade router 3 at the field edge can upload operating data to the cloud server 9 and cloud database through wireless network pass-through, realizing remote monitoring of data and parameter adjustment, but without affecting the independent operation of the Kepserver server 4 and the basic logic of the back-end control system 5.

[0042] Through the above implementation methods, the present invention achieves fully automated control of the gas lift process, forming a complete closed loop from data acquisition, status judgment, scheduling decision-making to execution control, enabling the gas lift process to be dynamically adjusted according to actual working conditions, improving liquid discharge efficiency and reducing energy consumption.​

Claims

1. A gas well intelligent gas lift control system based on dynamic time slices and adaptive scheduling, characterized in that, include: The downhole portion includes a casing and a tubing disposed within the casing, with an annular structure formed between the tubing and the casing; The surface section includes a gas production tree installed at the wellhead, a gas injection pipeline connected to the gas production tree, and an actuator installed on the gas injection pipeline.

2. The system according to claim 1, characterized in that, The control device includes: a data receiving module for receiving data collected by the data acquisition device; a calculation and processing module for calculating the gas injection process based on a preset liquid drainage efficiency evaluation function and generating a time slice scheduling strategy; and a control output module for outputting control signals to the actuator according to the scheduling strategy.

3. The system according to claim 2, characterized in that, The control output module outputs a switching control signal to the electrically controlled air lift valve through a relay output or digital output interface.

4. The system according to claim 1, characterized in that, The control device is an industrial control equipment, selected from one or more of a programmable logic controller, a remote terminal unit, or an industrial control computer.

5. The system according to claim 1, characterized in that, The data acquisition device includes a casing pressure sensor, a tubing pressure sensor, and a flow meter.

6. The system according to claim 1, characterized in that, The data acquisition device and the control device transmit data via an industrial communication protocol, namely the Modbus protocol.

7. The system according to claim 1, characterized in that, The system also includes a communication module and a remote server. The communication module is used to enable data interaction between field data and the remote system.

8. The system according to claim 2, characterized in that, The computational processing module is pre-set with: probe time slice initial value, excellent drainage efficiency threshold, qualified drainage efficiency threshold, time slice expansion coefficient, and time slice decay coefficient.

9. A method for intelligent gas lift control of gas wells based on dynamic time slices and adaptive scheduling, characterized in that, The gas well intelligent gas lift control system according to any one of claims 1 to 8 is used, comprising: When the gas well is in production, collect casing pressure, tubing pressure and flow rate data; When the gas lift start-up conditions are met, the control device sends an start signal to the actuator to open the electronically controlled gas lift valve and allocates an initial probe time slot for trial gas injection. After the current time slice ends, a comprehensive score for the drainage efficiency of that time slice is calculated based on the collected data; The next time slice scheduling strategy is generated based on the comprehensive score of the drainage efficiency, and the electronically controlled air lift valve is controlled to perform the corresponding opening or closing operation. Repeat the above process to achieve dynamic scheduling and control of the air lift process; When the overall performance score of drainage is lower than the preset threshold, the electronically controlled air lift valve is closed, ending the air lift process.

10. The intelligent gas lift control method for gas wells according to claim 9, characterized in that, The comprehensive drainage efficiency score is calculated by weighting the oil-casing pressure difference change rate and flow rate data. Based on the calculated comprehensive drainage efficiency score, the following scheduling strategy is executed: when the comprehensive drainage efficiency score is greater than or equal to the excellent threshold, the next time slice is increased by the expansion coefficient; when the comprehensive drainage efficiency score is between the passing threshold and the excellent threshold, the next time slice is decreased by the decay coefficient; when the comprehensive drainage efficiency score is lower than the passing threshold, shutdown control is executed.

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