Wellbore fluid accumulation early warning method and apparatus

Abstract

The application discloses a kind of wellbore liquid accumulation early warning method and device, belong to oil and gas field exploitation technical field.It includes: real-time acquisition gas well production data, and constructs dynamic data flow;Real-time calculation core dynamic parameter based on the dynamic data flow;Using historical flow pressure / static pressure test data, establish the empirical quantitative relationship between casing pressure difference and the height of net liquid column in wellbore;Using multiphase pipe flow software to establish steady flow model, with gas production, wellhead oil pressure and water-gas ratio as core variable to simulate, generate multi-factor early warning mechanism map;Based on the dynamic data flow, core dynamic parameter, the height of net liquid column in wellbore and multi-factor early warning mechanism map carry out multi-level dynamic early warning of wellbore liquid accumulation.The application realizes liquid accumulation quantitative identification and dynamic risk classification by fusing real-time dynamic monitoring data, casing pressure difference quantitative analysis, multiphase pipe flow steady-state simulation for gas well wellbore liquid accumulation intelligent identification, quantitative evaluation and risk early warning.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method and device for early warning of fluid accumulation in wellbores. Background Technology

[0002] Wellbore fluid accumulation is one of the core bottlenecks restricting the efficient development of gas fields, especially tight sandstone gas fields. Fluid accumulation leads to increased additional pressure loss in the wellbore, decreased gas production, reduced production rate, and in severe cases, water flooding and shutdown of the gas well. Currently used methods for identifying fluid accumulation in the field have the following limitations:

[0003] The empirical threshold method relies on a fixed oil-casing pressure difference (e.g., ΔP>2 MPa) or the critical fluid carrying capacity formula for judgment. It fails to consider the changes in production dynamics, tubing structure, and fluid properties throughout the entire life cycle of the gas well, resulting in poor adaptability and high false alarm and false alarm rates.

[0004] Single-point testing reliance: It relies on irregular flow pressure tests for "post-event diagnosis", which cannot achieve "real-time monitoring" and "early warning" of the liquid accumulation process, and the testing cost is high and the coverage is limited.

[0005] Model simplification: Existing early warning models are mostly based on single theoretical formulas (such as the Turner model) or static charts, failing to effectively couple the complex physical processes of multiphase flow in wellbore (such as flow pattern transformation, liquid holdup changes, pressure drop gradients, etc.) with real-time production data, resulting in insufficient prediction accuracy. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a wellbore fluid accumulation early warning method and device, which realizes quantitative identification of fluid accumulation and dynamic risk classification.

[0007] The technical solution provided by this invention is as follows:

[0008] A wellbore fluid accumulation early warning method, the method comprising:

[0009] S1: Acquire gas well production data in real time and construct a dynamic data stream;

[0010] The dynamic data stream includes time series, wellhead oil pressure, casing pressure, gas production, water production, and temperature.

[0011] S2: Calculate the core dynamic parameters in real time based on the dynamic data stream;

[0012] The core dynamic parameters include the oil-casing pressure difference and the water-vapor ratio;

[0013] S3: Utilize historical flowing pressure / static pressure test data to establish an empirical quantitative relationship between the oil casing pressure difference and the height of the net fluid column in the wellbore;

[0014] S4: Use multiphase pipeline flow software to establish a steady-state flow model, and use gas production, wellhead oil pressure and water-gas ratio as core variables to simulate and generate a multi-factor early warning mechanism map;

[0015] Among them, the core indicators of the multi-factor early warning mechanism map include theoretical oil-casing pressure difference, critical fluid carrying flow rate, and critical erosion flow rate;

[0016] S5: Based on the dynamic data stream, core dynamic parameters, the height of the clean fluid column in the wellbore, and the multi-factor early warning mechanism map, perform multi-level dynamic early warning of fluid accumulation in the wellbore.

[0017] Furthermore, S1 includes:

[0018] S11: Real-time acquisition of gas well production data through a data acquisition and monitoring control system;

[0019] S12: Based on the aforementioned production data, construct a data structure including time series T and wellhead oil pressure. , sleeve pressure Gas production Water production and temperature The dynamic data stream D(t) is included.

[0020] Where t represents the time series T contains;

[0021] S13: Perform data cleaning on the dynamic data stream D(t), including removing outliers, filling in missing values, and smoothing filtering.

[0022] Furthermore, the oil-casing pressure differential Compared to water vapor The calculation formula is as follows:

[0023]

[0024] .

[0025] Furthermore, the oil-casing pressure difference ∆P(t) is related to the height of the net fluid column in the wellbore. The empirical quantitative relationship is as follows:

[0026]

[0027] Where k is the proportionality coefficient obtained by regression from historical flow pressure / static pressure test data.

[0028] Furthermore, S4 includes:

[0029] S41: Based on the wellbore structure, tubing parameters and fluid PVT properties of the gas well, a steady-state flow model is established using multiphase pipe flow software;

[0030] S42: The steady-state flow model is corrected and fitted using historical flow pressure / static pressure test data;

[0031] S43: Based on the aforementioned steady-state flow model, with gas production... Wellhead oil pressure Compared to water vapor Using these as core variables, orthogonal experiments or sensitivity analyses are conducted to generate core indicators, including theoretical oil-casing pressure differential. Critical liquid carrying flow rate and critical erosion flow rate A map of multi-factor early warning mechanisms.

[0032] Furthermore, the critical liquid carrying flow rate The calculation formula is as follows:

[0033]

[0034] Where A is the empirical coefficient. For gas-liquid interfacial tension, and These are the liquid phase density and the gas phase density, respectively.

[0035] Furthermore, S5 includes:

[0036] S51: When the height of the net fluid column in the wellbore... Reaching the middle of the gas layer, and producing gas... If the gas production threshold is lower than the set threshold, it is considered a serious liquid accumulation and a level one warning is issued.

[0037] S52: When the oil jacket pressure difference The set time is higher than the theoretical oil-sleeve pressure difference. The upper limit of the reasonable range, or gas production. Less than the critical liquid carrying flow rate Or the height of the net fluid column in the wellbore. If the set safety threshold is exceeded, it is determined that liquid accumulation has formed and is affecting production, and a level two warning is issued;

[0038] S53: When the oil jacket pressure difference Higher than the theoretical oil-casing pressure difference The lower limit of the reasonable range and an upward trend, or gas production Less than and close to the critical liquid carrying capacity If the situation is as described, a risk of fluid accumulation is identified, and a Level 3 warning is issued.

[0039] A wellbore fluid accumulation early warning device, the device comprising:

[0040] The data acquisition module is used to acquire gas well production data in real time and build a dynamic data stream;

[0041] The dynamic data stream includes time series, wellhead oil pressure, casing pressure, gas production, water production, and temperature.

[0042] The core dynamic parameter calculation module is used to calculate the core dynamic parameters in real time based on the dynamic data stream;

[0043] The core dynamic parameters include the oil-casing pressure difference and the water-vapor ratio;

[0044] The net fluid column height calculation module is used to establish an empirical quantitative relationship between the oil casing pressure difference and the net fluid column height in the wellbore using historical flowing pressure / static pressure test data;

[0045] The mechanism diagram construction module is used to establish a steady-state flow model using multiphase pipeline flow software, with gas production, wellhead oil pressure and water-gas ratio as core variables for simulation, and generate a multi-factor early warning mechanism diagram.

[0046] Among them, the core indicators of the multi-factor early warning mechanism map include theoretical oil-casing pressure difference, critical fluid carrying flow rate, and critical erosion flow rate;

[0047] The multi-level dynamic early warning module is used to provide multi-level dynamic early warning of wellbore fluid accumulation based on the dynamic data stream, core dynamic parameters, the height of the clean fluid column in the wellbore, and the multi-factor early warning mechanism diagram.

[0048] Furthermore, the data acquisition module includes:

[0049] The data access unit is used to collect gas well production data in real time through the data acquisition and monitoring control system.

[0050] The dynamic data stream construction unit is used to construct a data stream based on the production data, including time series T and wellhead oil pressure. , sleeve pressure Gas production Water production and temperature The dynamic data stream D(t) is included.

[0051] Where t represents the time series T contains;

[0052] The data cleaning unit is used to perform data cleaning on the dynamic data stream D(t), including removing outliers, filling in missing values, and smoothing filtering.

[0053] Furthermore, the oil-casing pressure differential Compared to water vapor The calculation formula is as follows:

[0054]

[0055] .

[0056] Furthermore, the oil-casing pressure difference ∆P(t) is related to the height of the net fluid column in the wellbore. The empirical quantitative relationship is as follows:

[0057]

[0058] Where k is the proportionality coefficient obtained by regression from historical flow pressure / static pressure test data.

[0059] Furthermore, the mechanism diagram construction module includes:

[0060] The model building unit is used to establish a steady-state flow model based on the wellbore structure, tubing parameters, and fluid PVT properties of the gas well using multiphase pipe flow software.

[0061] The model calibration unit is used to calibrate and fit the steady-state flow model using historical flow pressure / static pressure test data;

[0062] The mechanism diagram generation unit is used to generate gas production based on the steady-state flow model. Wellhead oil pressure Compared to water vapor Using these as core variables, orthogonal experiments or sensitivity analyses are conducted to generate core indicators, including theoretical oil-casing pressure differential. Critical liquid carrying flow rate and critical erosion flow rate A map of multi-factor early warning mechanisms.

[0063] Furthermore, the critical liquid carrying flow rate The calculation formula is as follows:

[0064]

[0065] Where A is the empirical coefficient. For gas-liquid interfacial tension, and These are the liquid phase density and the gas phase density, respectively.

[0066] Furthermore, the multi-level dynamic early warning module includes:

[0067] The first-level early warning unit is used when the height of the net fluid column in the wellbore is... Reaching the middle of the gas layer, and producing gas... If the gas production threshold is lower than the set threshold, it is considered a serious liquid accumulation and a level one warning is issued.

[0068] The secondary early warning unit is used when the oil-casing pressure difference... The set time is higher than the theoretical oil-sleeve pressure difference. The upper limit of the reasonable range, or gas production. Less than the critical liquid carrying flow rate Or the height of the net fluid column in the wellbore. If the set safety threshold is exceeded, it is determined that liquid accumulation has formed and is affecting production, and a level two warning is issued;

[0069] The three-level early warning unit is used when the oil-casing pressure difference... Higher than the theoretical oil-casing pressure difference The lower limit of the reasonable range and an upward trend, or gas production Less than and close to the critical liquid carrying capacity If the situation is as described, a risk of fluid accumulation is identified, and a Level 3 warning is issued.

[0070] The present invention has the following beneficial effects:

[0071] This invention aims to solve the problems of lagging wellbore fluid accumulation identification, low early warning accuracy, and inability to quantitatively evaluate the degree of fluid accumulation and dynamic risk level in existing technologies. By combining multi-source information fusion and mechanism simulation, it provides a method for intelligent identification, quantitative evaluation, and risk early warning of gas wellbore fluid accumulation that integrates real-time dynamic monitoring data, quantitative analysis of oil-casing pressure difference, and steady-state simulation of multiphase pipeline flow. This method is a real-time, accurate, highly adaptable, and mechanism-supported intelligent early warning method that realizes quantitative identification of fluid accumulation and dynamic risk classification. Attached Figure Description

[0072] Figure 1 This is a flowchart of the wellbore fluid accumulation early warning method of the present invention;

[0073] Figure 2 This is an example of a mechanism diagram obtained through multiphase pipe flow simulation;

[0074] Figure 3 for Example of a calibration curve;

[0075] Figure 4 This is a schematic diagram of the wellbore liquid accumulation early warning device of the present invention. Detailed Implementation

[0076] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0077] This invention provides a wellbore fluid accumulation early warning method, which is a quantitative identification and graded early warning method for wellbore fluid accumulation based on dynamic monitoring and multiphase pipe flow coupling, such as... Figure 1 As shown, the method includes:

[0078] S1: Acquire gas well production data in real time and build a dynamic data stream.

[0079] This step is used for real-time data stream construction and preprocessing. One possible implementation method includes:

[0080] S11: Real-time acquisition of gas well production data through a Supervisory Control and Data Acquisition (SCADA) system.

[0081] Specifically, by deploying data interfaces, data from systems such as SCADA and daily production reports can be accessed in real time.

[0082] S12: Based on production data, construct a data structure including time series T and wellhead oil pressure. , sleeve pressure Gas production Water production and temperature The dynamic data flow D(t) is included.

[0083] Where t represents the time span contained in the time series T.

[0084] S13: Perform data cleaning on the dynamic data stream D(t), including removing outliers, filling in missing values, and smoothing filtering.

[0085] For example, it automatically marks and repairs abnormal data such as "output is zero and oil pressure is non-zero" and "pressure exceeds range".

[0086] S2: Calculate the core dynamic parameters in real time based on the dynamic data stream.

[0087] Among them, the core dynamic parameters include the oil-casing pressure differential. Compared to water vapor The specific calculation formula is as follows:

[0088]

[0089]

[0090] S3: Using historical flowing / static pressure test data, establish the relationship between the oil-casing pressure difference ∆P(t) and the net fluid column height in the wellbore for this well or this block. The empirical quantitative relationship.

[0091] This empirical quantitative relationship can be obtained through data fitting, and its form can be:

[0092]

[0093] Where k is a proportionality coefficient obtained by regression of historical flowing pressure / static pressure test data, and its physical meaning is related to the average fluid density in the wellbore.

[0094] This invention establishes and continuously updates The calibration model achieved online real-time conversion from pressure difference to liquid accumulation height, a key engineering parameter, thus enabling real-time quantitative description of liquid accumulation height. The final established... Calibration curve (discrete test data points and fitted curve) as shown Figure 3 As shown.

[0095] S4: Establish a steady-state flow model using multiphase pipeline flow software, and simulate the process with gas production, wellhead oil pressure, and water-gas ratio as core variables to generate a multi-factor early warning mechanism map.

[0096] This step is used for high-fidelity multiphase pipe flow steady-state simulation and mechanism diagram construction. In one example, it includes:

[0097] S41: Based on the accurate wellbore structure, tubing parameters, and fluid PVT properties of a single gas well, a steady-state flow model is established using multiphase pipe flow software.

[0098] S42: The steady-state flow model is calibrated and fitted using historical flow pressure / static pressure test data to ensure model accuracy.

[0099] Specifically, a "digital profile" can be established for each well, recording static data such as completion tubing, fluid properties, gas testing results, and historical tests. Initial flow pressure test data is used to initialize and calibrate the multiphase pipe flow model.

[0100] S43: Based on the aforementioned steady-state flow model, with gas production... Wellhead oil pressure Compared to water vapor Using these as the core variables, orthogonal experiments or sensitivity analyses were conducted to calculate the theoretical oil-casing pressure differential under different combinations in batches. Critical liquid carrying flow rate and critical erosion flow rate This forms a multi-factor early warning mechanism map covering the working area of ​​gas wells.

[0101] The multiphase pipe flow simulation engine can use PipeSim, OLGA, Prosper, or a self-developed numerical solver.

[0102] Critical liquid carrying flow rate An improved Turner model can be used for calculation, and the formula is as follows:

[0103]

[0104] Where A is the empirical coefficient. For gas-liquid interfacial tension, and These are the liquid phase density and gas phase density, respectively. The empirical coefficient A, liquid phase density, and gas phase density parameters are corrected according to the actual fluid properties and pipe diameter of this well.

[0105] Critical liquid carrying flow rate The calculation can also use LiMin model, Coleman model, etc. to replace Turner model.

[0106] The final multiphase pipe flow simulation mechanism diagram is shown in the example below. Figure 2 As shown.

[0107] S5: Multi-level dynamic early warning of wellbore fluid accumulation based on dynamic data stream, core dynamic parameters, wellbore clean fluid column height, and multi-factor early warning mechanism map.

[0108] This step utilizes multi-source information fusion for intelligent early warning, constructing a system that integrates real-time data (dynamic data streams, core dynamic parameters) and the net fluid column height within the wellbore. A specific example of a rule engine for quantitative models and mechanistic diagrams is as follows:

[0109] S51: When the height of the net fluid column in the wellbore... Reaching the middle of the gas layer, and producing gas... When the gas production falls below the set production threshold (a sharp drop or zero in gas production), production dynamics indicate that the wellbore may be filled; this indicates a severe liquid accumulation stage, triggering a Level 1 warning, i.e., a severe liquid accumulation warning. At this point, the gas well faces the risk of water flooding and production shutdown, and it is recommended to immediately implement forced drainage measures.

[0110] S52: When the oil jacket pressure difference The set time is higher than the theoretical oil-sleeve pressure difference. The upper limit of the reasonable range, or gas production. Less than the critical liquid carrying flow rate Or the height of the net fluid column in the wellbore. When the flow exceeds the set safety threshold (e.g., 10% of the well depth), it is determined that fluid accumulation has formed and is affecting production (i.e., the fluid accumulation development stage), and a secondary warning, namely the critical fluid-carrying warning, is issued. At this time, it is recommended to arrange a flow pressure test for verification and prepare measures such as foam drainage.

[0111] In practice, a rules engine can compare the dynamic data stream D(t) with the mechanistic diagram every second. For example, reading the current... and Interpolate from the mechanism diagram to obtain the current state Reasonable range and .

[0112] This invention employs a dynamic threshold technology based on mechanistic diagrams, abandoning fixed thresholds and using dynamic mechanistic diagrams generated based on multiphase flow simulations as the early warning benchmark, thus making the early warning threshold (i.e., the threshold under the current state) more flexible and less restrictive. Reasonable range and The adaptability is greatly improved by dynamically changing the working point of the gas well.

[0113] S53: When the oil jacket pressure difference Higher than the theoretical oil-casing pressure difference The lower limit of the reasonable range and an upward trend, or gas production Less than and close to the critical liquid carrying capacity If the situation is detected at this point, it is determined that there is a risk of fluid accumulation (i.e., the initial stage of fluid accumulation), and a three-level early warning is issued, namely, an early trend warning. At this time, it is recommended to optimize the work system and monitor the situation closely.

[0114] The above is an example of a three-level early warning system. Of course, the early warning levels can be expanded to more levels based on on-site management needs.

[0115] The following three specific examples illustrate the above three levels of warnings:

[0116] Example 1 (Severe fluid accumulation warning):

[0117] Taking a selected example well in the A and B well areas of the Y gas field as an example, the system monitored its... The pressure continued to climb from 5 MPa and stabilized above 8.5 MPa. The flow rate dropped from 0.2 million cubic meters per day to near zero. Real-time queries of the multiphase pipe flow diagram are available. Down, The reasonable range should be 1.5-3.0 MPa. The measured values ​​deviate significantly. This needs to be addressed through model calibration. The estimated fluid accumulation height has reached 1968m. The rule engine has determined it to be a Level 1 warning, outputting the conclusion: "Severe fluid accumulation, wellbore nearly full, forced drainage measures recommended immediately."

[0118] Example 2 (Critical Liquid Carrying Warning):

[0119] Taking another selected example well in the A and B well areas of the Y gas field as an example, the system monitored its... It fluctuates around 35,000 cubic meters per day. It is 4.0 MPa. It is 1.8 MPa but showing a slow upward trend. The current status can be obtained from the chart. The daily gas production is 38,000 cubic meters. The real-time gas production has fallen below the critical liquid-carrying flow rate. The system has triggered a level-two warning: "Insufficient liquid-carrying capacity, production has fallen below the critical liquid-carrying flow rate, and there is a risk of further liquid accumulation. It is recommended to increase the production or prepare for auxiliary liquid drainage."

[0120] Example 3 (Early Trend Warning):

[0121] Take a well in the middle stage of production as an example. The pressure rose rapidly from 1.2 MPa to 2.5 MPa within 24 hours, but the absolute value remained within the common threshold. Based on the multiphase pipe flow diagram, the system determined that this pressure rise rate far exceeded the simulated normal pressure drop rate. Meanwhile, the trend prediction model showed… The pressure will continue to rise. The system triggered a Level 3 early warning: "The oil-casing pressure differential is rising rapidly, deviating from the normal production trend. It is recommended to closely monitor and verify the changes in the water-air ratio," thus achieving early intervention.

[0122] After completing multi-level dynamic early warning, the diagnostic report and action recommendations can be output in conjunction, specifically:

[0123] The system automatically generates early warning reports, which include: the current risk level of liquid accumulation, the estimated height of liquid accumulation, the degree of deviation from the reasonable range of simulation, and the analysis of the main causes (such as insufficient gas production, sudden increase in water-gas ratio, etc.). It also outputs suggested measures, such as "optimize production adjustment", "suggest foam drainage", "arrange flow pressure test verification" or "prepare for stimulating liquid drainage".

[0124] This invention can also perform feedback learning: after each flow pressure test, the actual liquid accumulation is inverted using the new test data and compared with the warning records to evaluate the accuracy of the warning and fine-tune the calibration model parameter k or the warning threshold, thereby realizing the system's self-learning.

[0125] This invention aims to solve the problems of lagging wellbore fluid accumulation identification, low early warning accuracy, and inability to quantitatively evaluate the degree of fluid accumulation and dynamic risk level in existing technologies. By combining multi-source information fusion and mechanism simulation, it provides a method for intelligent identification, quantitative evaluation, and risk early warning of gas wellbore fluid accumulation that integrates real-time dynamic monitoring data, quantitative analysis of oil-casing pressure difference, and steady-state simulation of multiphase pipeline flow. This method is a real-time, accurate, highly adaptable, and mechanism-supported intelligent early warning method that realizes quantitative identification of fluid accumulation and dynamic risk classification.

[0126] The specific beneficial effects are as follows:

[0127] 1. The “Monitoring-Simulation-Rules” Tripartite Coupling Architecture: This architecture deeply couples real-time monitoring data, high-fidelity mechanism simulation, and an interpretable business rule engine at the methodological level, forming a solution that combines physical accuracy, real-time performance, and engineering practicality. It enables a mechanistic and quantitative description of the liquid accumulation process and provides a strong scientific basis for early warning.

[0128] 2. Dynamic quantitative identification: By calibrating with historical test data, the oil-casing pressure difference can be converted into an estimated liquid accumulation height in real time, realizing the dynamic quantification of the liquid accumulation degree, rather than a simple qualitative judgment.

[0129] 3. Full life cycle adaptive: The constructed mechanism diagram and early warning threshold can be adaptively adjusted according to the dynamic characteristics of different production stages of gas wells (stable production period, declining production period), which has wide applicability.

[0130] 4. Precise risk classification: The establishment of a three-level early warning mechanism can clearly distinguish between the initial, development and severe stages of liquid accumulation, providing precise guidance for taking differentiated measures on site and improving control efficiency.

[0131] 5. Proactive early warning: Based on simulation and trend analysis, the potential risk of insufficient liquid carrying capacity can be identified before the gas well production declines significantly, realizing the transformation from "post-event handling" to "pre-event early warning".

[0132] 6. Solid Theoretical Foundation: The wellbore casing pressure difference is essentially the difference between the annular air column pressure and the gas-liquid mixed-phase flow pressure within the tubing. Its value directly reflects the total frictional resistance and static pressure loss of the multiphase flow within the tubing and is highly correlated with the liquid holdup. Steady-state simulation of multiphase pipe flow is a mature numerical method for solving the mass, momentum, and energy conservation equations, capable of reproducing this physical process with high accuracy. Therefore, the simulated theoretical casing pressure difference... The measured oil jacket pressure difference By comparison, the deviation can be directly attributed to the additional flow resistance that the model did not consider—i.e., liquid accumulation—thus making the quantitative identification theoretically valid and reliable.

[0133] The beneficial effects of the present invention are demonstrated below with specific empirical results:

[0134] Application in wells A and B of the Y gas field shows that:

[0135] For example well 1 (severe fluid accumulation), the system issued a level one warning before the oil-casing pressure difference was continuously >8MPa and the gas production returned to zero. The estimated fluid accumulation height was 1981m, which is consistent with the trend of the subsequent flowing pressure test results (fluid accumulation depth 1226m vertical depth).

[0136] For example well 2 (moderate fluid accumulation), the system fluctuates more in the range of ∆P(t) between 2-4 MPa. near An orange alert is issued at times, indicating "critical liquid carrying capacity," with an advance warning period of more than 15 days.

[0137] The overall accuracy of early warnings has increased to 92%, the false alarm rate has decreased by about 60%, and the average early warning lead time has reached 7 days, which has bought valuable time for the implementation of measures.

[0138] This invention also provides a wellbore liquid accumulation early warning device, such as... Figure 4 As shown, the device includes:

[0139] Data acquisition module 1 is used to acquire gas well production data in real time and construct a dynamic data stream.

[0140] The dynamic data stream includes time series, wellhead oil pressure, casing pressure, gas production, water production, and temperature.

[0141] The core dynamic parameter calculation module 2 is used to calculate the core dynamic parameters in real time based on the dynamic data stream.

[0142] The core dynamic parameters include the oil-casing pressure difference and the water-vapor ratio.

[0143] The net fluid column height calculation module 3 is used to establish an empirical quantitative relationship between the oil casing pressure difference and the net fluid column height in the wellbore using historical flowing pressure / static pressure test data.

[0144] Mechanism diagram construction module 4 is used to establish a steady-state flow model using multiphase pipeline flow software, and to simulate the gas production, wellhead oil pressure and water-gas ratio as core variables to generate a multi-factor early warning mechanism diagram.

[0145] The core indicators of the multi-factor early warning mechanism map include theoretical oil-casing pressure difference, critical fluid carrying flow rate, and critical erosion flow rate.

[0146] The multi-level dynamic early warning module 5 is used to perform multi-level dynamic early warning of wellbore fluid accumulation based on the dynamic data stream, core dynamic parameters, the height of the clean fluid column in the wellbore, and the multi-factor early warning mechanism map.

[0147] In one example, the data acquisition module includes:

[0148] The data access unit is used to collect gas well production data in real time through the data acquisition and monitoring control system.

[0149] The dynamic data stream construction unit is used to construct a data stream based on the production data, including time series T and wellhead oil pressure. , sleeve pressure Gas production Water production and temperature The dynamic data flow D(t) is included.

[0150] Where t represents the time span contained in the time series T.

[0151] The data cleaning unit is used to perform data cleaning on the dynamic data stream D(t), including removing outliers, filling in missing values, and smoothing filtering.

[0152] Specifically, the oil-casing pressure difference Compared to water vapor The calculation formula is as follows:

[0153]

[0154] .

[0155] Correspondingly, the oil-casing pressure difference ∆P(t) is related to the height of the net fluid column in the wellbore. The empirical quantitative relationship is as follows:

[0156]

[0157] Where k is the proportionality coefficient obtained by regression from historical flow pressure / static pressure test data.

[0158] As an improvement to this embodiment of the invention, the mechanism diagram construction module includes:

[0159] The model building unit is used to establish a steady-state flow model based on the wellbore structure, tubing parameters, and fluid PVT properties using multiphase pipe flow software.

[0160] The model calibration unit is used to calibrate and fit the steady-state flow model using historical flow pressure / static pressure test data.

[0161] The mechanism diagram generation unit is used to generate gas production based on the steady-state flow model. Wellhead oil pressure Compared to water vapor Using these as core variables, orthogonal experiments or sensitivity analyses are conducted to generate core indicators, including theoretical oil-casing pressure differential. Critical liquid carrying flow rate and critical erosion flow rate A map of multi-factor early warning mechanisms.

[0162] The aforementioned critical liquid carrying flow rate The calculation formula is as follows:

[0163]

[0164] Where A is the empirical coefficient. For gas-liquid interfacial tension, and These are the liquid phase density and the gas phase density, respectively.

[0165] The multi-level dynamic early warning module in this invention includes:

[0166] The first-level early warning unit is used when the height of the net fluid column in the wellbore is... Reaching the middle of the gas layer, and producing gas... If the gas production threshold is lower than the set threshold, it is considered a serious liquid accumulation and a level one warning is issued.

[0167] The secondary early warning unit is used when the oil-casing pressure difference... The set time is higher than the theoretical oil-sleeve pressure difference. The upper limit of the reasonable range, or gas production. Less than the critical liquid carrying flow rate Or the height of the net fluid column in the wellbore. If the set safety threshold is exceeded, it is determined that liquid accumulation has formed and is affecting production, and a level two warning is issued.

[0168] The three-level early warning unit is used when the oil-casing pressure difference... Higher than the theoretical oil-casing pressure difference The lower limit of the reasonable range and an upward trend, or gas production Less than and close to the critical liquid carrying capacity If the situation is as described, a risk of fluid accumulation is identified, and a Level 3 warning is issued.

[0169] The apparatus provided in this embodiment of the invention operates on the same principle and produces the same technical effects as the aforementioned method embodiments. For the sake of brevity, any parts not mentioned in the apparatus embodiments can be referred to the corresponding content in the aforementioned method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the apparatus and units described above can all be referred to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0170] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention.

Claims

1. A method for early warning of fluid accumulation in wellbore, characterized in that, The method includes: S1: Acquire gas well production data in real time and construct a dynamic data stream; The dynamic data stream includes time series, wellhead oil pressure, casing pressure, gas production, water production, and temperature. S2: Calculate the core dynamic parameters in real time based on the dynamic data stream; The core dynamic parameters include the oil-casing pressure difference and the water-vapor ratio; S3: Utilize historical flowing pressure / static pressure test data to establish an empirical quantitative relationship between the oil casing pressure difference and the height of the net fluid column in the wellbore; S4: Use multiphase pipeline flow software to establish a steady-state flow model, and use gas production, wellhead oil pressure and water-gas ratio as core variables to simulate and generate a multi-factor early warning mechanism map; Among them, the core indicators of the multi-factor early warning mechanism map include theoretical oil-casing pressure difference, critical fluid carrying flow rate, and critical erosion flow rate; S5: Based on the dynamic data stream, core dynamic parameters, the height of the clean fluid column in the wellbore, and the multi-factor early warning mechanism map, perform multi-level dynamic early warning of fluid accumulation in the wellbore.

2. The wellbore fluid accumulation early warning method according to claim 1, characterized in that, S1 includes: S11: Real-time acquisition of gas well production data through a data acquisition and monitoring control system; S12: Based on the aforementioned production data, construct a data structure including time series T and wellhead oil pressure. , sleeve pressure Gas production Water production and temperature The dynamic data stream D(t) includes the data stream. Where t represents the time span contained in the time series T; S13: Perform data cleaning on the dynamic data stream D(t), including removing outliers, filling in missing values, and smoothing filtering.

3. The wellbore fluid accumulation early warning method according to claim 2, characterized in that, The oil jacket pressure difference Compared to water vapor The calculation formula is as follows: 。 4. The wellbore fluid accumulation early warning method according to claim 3, characterized in that, The oil-casing pressure difference ∆P(t) and the net fluid column height in the wellbore are related. The empirical quantitative relationship is as follows: Where k is the proportionality coefficient obtained by regression from historical flow pressure / static pressure test data.

5. The wellbore fluid accumulation early warning method according to claim 4, characterized in that, S4 includes: S41: Based on the wellbore structure, tubing parameters and fluid PVT properties of the gas well, a steady-state flow model is established using multiphase pipe flow software; S42: The steady-state flow model is corrected and fitted using historical flow pressure / static pressure test data; S43: Based on the aforementioned steady-state flow model, with gas production... Wellhead oil pressure Compared to water vapor Using these as core variables, orthogonal experiments or sensitivity analyses are conducted to generate core indicators, including theoretical oil-casing pressure differential. Critical liquid carrying flow rate and critical erosion flow rate A map of multi-factor early warning mechanisms.

6. The wellbore fluid accumulation early warning method according to claim 5, characterized in that, The critical liquid carrying flow rate The calculation formula is as follows: Where A is the empirical coefficient. For gas-liquid interfacial tension, and These are the liquid phase density and the gas phase density, respectively.

7. The wellbore fluid accumulation early warning method according to claim 6, characterized in that, S5 includes: S51: When the height of the net fluid column in the wellbore... Reaching the middle of the gas layer, and producing gas... If the gas production threshold is lower than the set threshold, it is considered a serious liquid accumulation and a level one warning is issued. S52: When the oil jacket pressure difference The set time is higher than the theoretical oil-sleeve pressure difference. The upper limit of the reasonable range, or gas production. Less than the critical liquid carrying flow rate Or the height of the net fluid column in the wellbore If the set safety threshold is exceeded, it is determined that liquid accumulation has formed and is affecting production, and a level two warning is issued; S53: When the oil jacket pressure difference Higher than the theoretical oil-casing pressure difference The lower limit of the reasonable range and an upward trend, or gas production Less than and close to the critical liquid carrying capacity If the situation is as described, a risk of fluid accumulation is identified, and a Level 3 warning is issued.

8. A wellbore liquid accumulation early warning device, characterized in that, The device includes: The data acquisition module is used to acquire gas well production data in real time and build a dynamic data stream; The dynamic data stream includes time series, wellhead oil pressure, casing pressure, gas production, water production, and temperature. The core dynamic parameter calculation module is used to calculate the core dynamic parameters in real time based on the dynamic data stream; The core dynamic parameters include the oil-casing pressure difference and the water-vapor ratio; The net fluid column height calculation module is used to establish an empirical quantitative relationship between the oil casing pressure difference and the net fluid column height in the wellbore using historical flowing pressure / static pressure test data; The mechanism diagram construction module is used to establish a steady-state flow model using multiphase pipeline flow software, with gas production, wellhead oil pressure and water-gas ratio as core variables for simulation, and generate a multi-factor early warning mechanism diagram. Among them, the core indicators of the multi-factor early warning mechanism map include theoretical oil-casing pressure difference, critical fluid carrying flow rate, and critical erosion flow rate; The multi-level dynamic early warning module is used to provide multi-level dynamic early warning of wellbore fluid accumulation based on the dynamic data stream, core dynamic parameters, the height of the clean fluid column in the wellbore, and the multi-factor early warning mechanism diagram.

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