Method and system for judging super heavy oil steam drive conversion opportunity

Abstract

The embodiment of the invention provides a super heavy oil steam drive conversion opportunity judgment method and system, and belongs to the technical field of oil exploitation. The method comprises the following steps: classifying historical logging data and historical oil extraction data according to corresponding rotation drive opportunity judgment indexes to obtain a plurality of data sets; based on each data set, generating a judgment rule corresponding to the driving conversion opportunity judgment index item; acquiring acquisition state information in a current acquisition state in real time, and judging whether the current acquisition state information meets a driving conversion condition or not based on a judgment rule of each driving conversion opportunity judgment index item; and when the rotation driving condition is met, steam rotation driving is triggered and executed. According to the scheme, multiple key indexes are comprehensively considered, the limitation of a traditional single temperature judgment method is overcome, the accuracy and reliability of driving rotation opportunity judgment are remarkably improved, and the development effect of the super-heavy oil reservoir is optimized.

Description

Technical Field

[0001] This invention relates to the field of petroleum extraction technology, and more specifically to a method and system for determining the timing of vapor drive for extra-heavy oil. Background Technology

[0002] Extra-heavy oil reservoirs occupy an important position in heavy oil resources, and their development has a significant impact on the overall production of heavy oil resources. However, existing extra-heavy oil reservoir development technologies face many challenges, especially in the later stages of development. Currently, the main development methods for extra-heavy oil reservoirs are steam huff and puff and SAGD (steam-assisted gravity drainage). Among them, interlayered and thin-layer extra-heavy oil reservoirs, which are mainly developed using huff and puff, have generally entered the late stage of declining production, with recovery rates of only 25-30%, and recoverable reserves exceeding 90%. At this stage, the reservoirs generally face the problems of "high circulation, high water cut, high recovery rate, low oil production rate, and low oil-steam ratio," and urgently need to achieve stable production succession through technologies that improve recovery rates.

[0003] Existing methods for determining the timing of steam flooding in extra-heavy oil reservoirs primarily rely on temperature field monitoring, with the viscosity-temperature curve tangent method commonly used to determine the transition temperature limit. However, due to low coverage of temperature monitoring data and the fact that interpolation is typically performed using the highest reservoir temperature, the temperature field map cannot accurately reflect the vertical temperature distribution of the reservoir, resulting in low identification accuracy. Furthermore, the high viscosity of extra-heavy oil reservoirs means that even when the transition temperature is reached, there are still insufficiently heated dead oil zones, affecting the development effectiveness of steam flooding.

[0004] Therefore, existing technologies that rely solely on temperature fields to determine the timing of oil diversion have limitations. Insufficient temperature monitoring data leading to interpolation errors, and the inability to accurately reflect the recovery rate and formation pressure drop in local areas, all contribute to inaccurate judgments of diversion timing, thus affecting the development of extra-heavy oil reservoirs. These problems urgently need to be addressed through more comprehensive and precise technical means to improve the accuracy of diversion timing identification and development efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for determining the timing of vapor transfer for extra-heavy oil, so as to at least solve the problem of inaccurate timing determination of vapor transfer for extra-heavy oil in existing methods.

[0006] To achieve the above objectives, the first aspect of the present invention provides a method for determining the timing of steam drive conversion in extra-heavy oil. The method includes: collecting historical logging data and historical oil production data of a target reservoir area, and classifying the historical logging data and historical oil production data according to corresponding conversion timing determination indicators to obtain multiple datasets; generating determination rules for corresponding conversion timing determination indicators based on each dataset; collecting acquisition status information under the current acquisition state in real time, and determining whether the current acquisition status information meets the conversion conditions based on the determination rules for each conversion timing determination indicator; and triggering steam drive conversion when the conversion conditions are met.

[0007] Optionally, the switching timing determination index includes any combination of temperature, pressure, and viscosity indices; the step of classifying historical logging data and historical oil production data according to the corresponding switching timing determination index to obtain multiple datasets includes: performing data preprocessing on the historical logging data and historical oil production data; performing classification processing on the preprocessed data based on the K-means clustering algorithm to obtain the data classification results corresponding to each switching timing determination index, which serve as the dataset for the corresponding switching timing determination index.

[0008] Optionally, when the transition timing determination index is a temperature index, the corresponding determination rule generation process includes: fitting temperature and viscosity data curves based on the temperature index dataset; identifying slope abrupt change points in the temperature and viscosity data curves and using each slope abrupt change point as a candidate key temperature point; wherein, the slope abrupt change point is a point on the temperature and viscosity data curve where the proportional deviation between the front and back slopes is greater than a preset deviation proportional threshold; calculating the tangent slope of each candidate key temperature point, and determining the transition temperature limit value of the temperature index based on the magnitude relationship between the tangent slope and each candidate key temperature point; and generating determination rules under the temperature index based on the transition temperature limit value.

[0009] Optionally, the determination rule under the temperature index includes: if the current temperature value reaches the rotor temperature limit value, then the temperature trigger condition is determined to be met; otherwise, if the current temperature value does not reach the rotor temperature limit value, then the temperature trigger condition is determined to be met.

[0010] If the temperature exceeds the set limit, the temperature triggering condition is deemed not to be met.

[0011] Optionally, when the timing indicator for switching to displacement is a pressure indicator, the corresponding rule generation process includes: fitting the relationship between formation pressure and recovery degree based on the pressure indicator dataset; fitting the pressure field map of the target area based on the fitted relationship and the recovery degree of the current target area; recovering experimental data from indoor core displacement experiments performed to simulate crude oil seepage under formation conditions; determining the starting pressure limit value for extra-heavy oil based on the experimental data; and generating the judgment rule under the pressure indicator based on the starting pressure limit value and the pressure field map of the target area.

[0012] Optionally, fitting the relationship between formation pressure and recovery degree based on the pressure index dataset includes: performing outlier removal on the pressure index dataset to obtain a standard dataset of pressure index; constructing a coordinate system with formation pressure and recovery degree, and plotting a scatter plot based on the standard dataset of pressure index in the coordinate system; fitting a trend curve based on the scatter plot, and constructing a functional relationship between formation pressure and recovery degree based on the fitted trend curve, as the fitted relationship between formation pressure and recovery degree.

[0013] Optionally, the outlier removal process for the pressure index dataset to obtain a standard dataset for the pressure index includes: determining the change in extraction rate within each unit pressure drop based on the pressure index dataset; calculating the deviation between each change in extraction rate and the average value of the corresponding change in extraction rate based on the Z-Score algorithm; identifying change in extraction rate with a deviation greater than a preset deviation threshold as outlier values; identifying the data items in the pressure index dataset corresponding to the outlier values ​​as outliers, and performing outlier removal processing.

[0014] Optionally, after fitting the pressure field map of the target area based on the fitting relationship and the current production level of the target area, the method further includes: calculating the variation function value of each oil well based on the pressure index dataset and the distance information between each oil well; identifying outliers in the pressure field map of the target area based on the variation function value of each oil well; and correcting the pressure field map of the target area based on the outlier identification results to obtain a pressure field map that conforms to the smoothing coefficient of formation pressure elastic change in the target area.

[0015] Optionally, the recovery of experimental data from indoor core displacement experiments performed under simulated formation conditions includes: conducting indoor core displacement experiments sequentially on each crude oil sample determined based on the reservoir conditions of the target area using a pre-constructed indoor core displacement experimental setup to obtain all experimental data; wherein the indoor core displacement experimental setup includes: a fluid injection device for controlling the injection volume and pressure of the fluid; a physical simulation device for simulating the actual temperature and pressure environment of the formation; a data acquisition device for real-time acquisition of pressure and temperature during the experiment; and an oil-water metering device for measuring the fluid seepage velocity used to evaluate the crude oil displacement effect and the starting pressure.

[0016] Optionally, the indoor core displacement experiment is performed sequentially on each crude oil sample determined based on the reservoir conditions of the target area to obtain all experimental data, including: S1) sequentially performing filtration and dehydration treatment on all crude oil samples, filling them into each physical simulation device, and letting them stand for a first preset time; S2) adjusting the temperature of the physical simulation device corresponding to the current crude oil sample to reach a preset target temperature, and maintaining the preset target temperature for a second preset time; S3) displacing liquid to the inlet end of the core constructed based on the formation of the target area under preset ultra-low speed conditions, starting to record the pressure at the outlet end of the core when seepage begins, until the pressure value stabilizes, and obtaining a stable pressure value; S4) after letting the current core stand for a third preset time, modifying the displacement flow rate under preset ultra-low speed conditions, and repeating step S3) to obtain the latest stable pressure value; S5) repeating step S4) N times to obtain the stable pressure value of the current crude oil sample under each displacement flow rate; S6) changing the crude oil sample, and repeating steps S2)-S5) until obtaining the stable pressure value of all crude oil samples under each displacement flow rate.

[0017] Optionally, determining the starting pressure limit value of extra-heavy oil based on the experimental data includes: constructing a non-Darcy flow curve of extra-heavy oil corresponding to the target region based on the experimental data; identifying the starting point of seepage in the non-Darcy flow curve; and using the pressure value of the starting point of seepage as the determined starting pressure limit value of extra-heavy oil.

[0018] Optionally, a judgment rule for the pressure index is generated based on the starting pressure limit value and the pressure field map of the target area, including: using the determined starting pressure limit value as the judgment basis value, identifying areas in the pressure field map of the target area where the pressure value is greater than the judgment basis value; if the current area is in the identified area, the pressure triggering condition is determined to be met; if the current area is not in the identified area, the pressure triggering condition is determined to be unmet.

[0019] Optionally, when the viscosity index is used as the criterion for determining the timing of the shift, the corresponding rule generation process includes: fitting the relationship between injected steam volume and temperature, and fitting the relationship between temperature and formation crude oil viscosity, based on the viscosity index dataset; mapping the relationship between injected steam volume and formation crude oil viscosity based on the fitting relationship between injected steam volume and temperature, and the fitting relationship between temperature and formation crude oil viscosity; collecting pre-constructed one-dimensional physical model experimental results data based on small-scale numerical models; establishing the relationship between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on the one-dimensional physical model experimental results data; calculating the reservoir seepage factor and the starting viscosity threshold value at each location in the target area based on the relationship between different crude oil viscosities and different permeabilities and the starting viscosity threshold value; correcting the relationship between injected steam volume and formation crude oil viscosity based on the reservoir seepage factor in the target area; generating a viscosity field map of the target area based on the corrected relationship between injected steam volume and formation crude oil viscosity; and generating the determination rules under the viscosity index based on the viscosity field map of the target area and the starting viscosity threshold value at each location.

[0020] Optionally, the acquisition of pre-constructed one-dimensional physical model experimental results data based on small-scale numerical models, and the establishment of a relationship between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on the one-dimensional physical model experimental results data, includes: simulating the seepage process of crude oil under different crude oil viscosities and different permeabilities through one-dimensional physical model experiments; gradually increasing, such as the amount of injected steam, measuring the crude oil viscosity when the crude oil begins to flow, as the starting viscosity threshold value for the corresponding crude oil viscosity and corresponding permeability; iteratively adjusting the permeability and crude oil viscosity to obtain the starting viscosity threshold value for each crude oil viscosity and corresponding permeability; and constructing a relationship between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on each crude oil viscosity and corresponding permeability threshold value.

[0021] Optionally, the calculation rule for the seepage factor of the target area is as follows:

[0022]

[0023] Where φ is the seepage factor; m is the reservoir coefficient of the target area; k is the permeability of the target area; and μ is the current crude oil viscosity.

[0024] Optionally, the relationship between injected steam volume and formation crude oil viscosity is corrected based on the reservoir permeability factor of the target area, including: using the reservoir permeability factor of the target area as an adjustment factor between injected steam volume and formation crude oil viscosity; and adding factor variables to the relationship between injected steam volume and formation crude oil viscosity based on the adjustment factor to obtain the corrected relationship between injected steam volume and formation crude oil viscosity.

[0025] Optionally, a determination rule for the viscosity index is generated based on the viscosity field map of the target area and the starting viscosity limit value at each location, including: comparing the viscosity field map of the target area with the starting viscosity limit value at the corresponding location, and determining the location where the viscosity is greater than the starting viscosity limit value at the corresponding location as the trigger location; if the current location is a trigger location, the viscosity trigger condition is determined to be met; if the current location is not a trigger location, the viscosity trigger condition is determined to be unmet.

[0026] Optionally, the current acquisition status information is judged to meet the conversion conditions based on the judgment rules of each conversion timing judgment index item, including: judging whether the current temperature triggering condition is met based on the formation temperature information and temperature index judgment rules in the current acquisition status information; judging whether the current pressure triggering condition is met based on the acquisition location information and pressure index judgment rules in the current acquisition status information; judging whether the current viscosity triggering condition is met based on the acquisition location information and viscosity index judgment rules in the current acquisition status information; if the temperature triggering condition, pressure triggering condition, and viscosity triggering condition are all met, then the current acquisition status information is judged to meet the conversion conditions; otherwise, if at least one of the temperature triggering condition, pressure triggering condition, and viscosity triggering condition is not met, then the current acquisition status information is judged not to meet the conversion conditions.

[0027] A second aspect of the present invention provides a steam drive timing determination system for extra-heavy oil. The system includes: a data acquisition unit for acquiring historical logging data and historical oil production data of a target reservoir area, and classifying the historical logging data and historical oil production data according to corresponding steam drive timing determination indicators to obtain multiple datasets; a rule generation unit for generating determination rules for corresponding steam drive timing determination indicators based on each dataset; a determination unit for acquiring acquisition status information in real time under the current acquisition state, and determining whether the current acquisition status information meets the steam drive conditions based on the determination rules for each steam drive timing determination indicator; and an execution unit for triggering steam drive execution when the steam drive conditions are met.

[0028] On the other hand, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for determining the timing of steam transfer of extra-heavy oil.

[0029] Through the above technical solution, this invention collects historical logging data and historical oil production data from the target reservoir area, and classifies them according to conversion timing indicators (such as temperature, pressure, and viscosity) to form multiple datasets, thereby generating accurate conversion timing determination rules. Real-time acquisition of current oil production status information is used, and based on these determination rules, it is judged whether the current status meets the conversion conditions, ensuring that steam conversion operation is triggered under the most suitable conditions. This method overcomes the limitations of traditional single-temperature identification methods by comprehensively considering multiple key indicators, significantly improving the accuracy and reliability of conversion timing determination, and optimizing the development effect of extra-heavy reservoirs.

[0030] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0031] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0032] Figure 1 This is a flowchart of the steps of a method for determining the timing of vapor transfer of extra-heavy oil according to one embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of pressure test data provided in one embodiment of the present invention;

[0034] Figure 3 This is a diagram showing the relationship between the degree of extraction per unit pressure drop, provided by one embodiment of the present invention.

[0035] Figure 4 This is a recovery degree and formation pressure diagram provided by one embodiment of the present invention;

[0036] Figure 5 This is a pressure field diagram provided by one embodiment of the present invention;

[0037] Figure 6 This is a schematic diagram of local outliers provided in one embodiment of the present invention;

[0038] Figure 7 This is a schematic diagram of an indoor core displacement experimental apparatus provided in one embodiment of the present invention;

[0039] Figure 8 This is a schematic diagram of the non-Darcy flow curve of extra-heavy oil provided in one embodiment of the present invention;

[0040] Figure 9 This is a schematic diagram of the rotary drive region provided in one embodiment of the present invention;

[0041] Figure 10 This is a curve showing the relationship between the amount of injected steam and the temperature, provided in one embodiment of the present invention.

[0042] Figure 11 This is a viscosity-temperature curve of extra-heavy oil provided in one embodiment of the present invention;

[0043] Figure 12 This is a graph showing the relationship between the amount of injected steam and the viscosity, provided in one embodiment of the present invention.

[0044] Figure 13 This is a graph showing the relationship between different viscosities, different permeabilities, and starting viscosity, provided by one embodiment of the present invention.

[0045] Figure 14 This is a modified diagram showing the relationship between the injected steam quantity and the starting viscosity, provided by one embodiment of the present invention.

[0046] Figure 15 This is a viscosity field diagram provided in one embodiment of the present invention;

[0047] Figure 16 This is a system structure diagram of a vapor transfer timing determination system for extra-heavy oil provided in one embodiment of the present invention. Detailed Implementation

[0048] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0049] Figure 1 This is a flowchart of a method for determining the timing of vapor transfer for extra-heavy oil according to one embodiment of the present invention. Figure 1 As shown, this invention provides a method for determining the timing of extra-heavy oil steam drive, the method comprising:

[0050] Step S10: Collect historical logging data and historical oil production data for the target reservoir area, and classify the historical logging data and historical oil production data according to the corresponding conversion timing judgment indicators to obtain multiple...

[0051] A dataset.

[0052] Specifically, the process of classifying historical logging data and historical oil production data according to corresponding conversion timing indicators to obtain multiple datasets includes: performing data preprocessing on the historical logging data and historical oil production data; performing classification processing on the preprocessed data based on the K-means clustering algorithm to obtain the data classification results corresponding to each conversion timing indicator, which serve as the dataset for the corresponding conversion timing indicator.

[0053] In embodiments of the present invention, such as Figure 2This represents a type of pressure test data. Historical well logging data and historical oil production data of the target reservoir area are collected, and these data undergo detailed preprocessing, including data cleaning, missing value imputation, and data standardization. Preprocessed data is more consistent and complete, improving the accuracy of subsequent analysis. K-means clustering algorithm is applied to classify the preprocessed data. K-means clustering is an unsupervised learning algorithm that divides data points into several groups, minimizing the distance between data points within the same group in the feature space. In this method, key indicators for determining the transition timing, such as temperature, pressure, and viscosity, are selected as the feature dimensions for clustering. The K-means algorithm divides the data into several groups, each representing a typical transition timing scenario. In this way, hidden patterns and regularities in historical data can be effectively identified, generating multiple datasets, each corresponding to a specific transition timing rule.

[0054] Based on the present invention, cluster analysis of data allows for a comprehensive consideration of the influence of multiple key indicators, avoiding the limitations of traditional single-indicator identification methods. For example, traditional methods primarily rely on temperature changes to determine the timing of shifting to a different reservoir, but this approach ignores the influence of other important factors such as pressure and viscosity. By introducing multi-dimensional cluster analysis, the rationality of the shifting timing can be evaluated more comprehensively. The K-means clustering algorithm performs exceptionally well when processing large-scale data, quickly and effectively classifying data, thus making its application in actual reservoir management feasible and practical. Furthermore, by generating multiple datasets based on different judgment indicators, shifting strategies can be customized for different reservoir conditions, improving the flexibility and adaptability of the technology.

[0055] Step S20: Generate judgment rules for corresponding drive timing judgment indicators based on each dataset.

[0056] Specifically, when the transition timing determination index is a temperature index, the corresponding determination rule generation process includes: fitting temperature and viscosity data curves based on the temperature index dataset; identifying slope abrupt change points in the temperature and viscosity data curves and using each slope abrupt change point as a candidate key temperature point; wherein, the slope abrupt change point is a point on the temperature and viscosity data curve where the proportional deviation between the front and back slopes is greater than a preset deviation proportional threshold; calculating the tangent slope of each candidate key temperature point, and determining the transition temperature limit value of the temperature index based on the magnitude relationship between the tangent slope and each candidate key temperature point; and generating determination rules under the temperature index based on the transition temperature limit value.

[0057] Furthermore, the determination rules under the temperature index include: if the current temperature value reaches the drive temperature limit value, the temperature triggering condition is determined to be met; otherwise, if the current temperature value does not reach the drive temperature limit value, the temperature triggering condition is determined to be unmet.

[0058] In this embodiment of the invention, by fitting temperature and viscosity data curves, a curve reflecting how temperature changes affect the viscosity of crude oil in the reservoir can be obtained. On this curve, the relationship between temperature and viscosity typically exhibits a non-linear change, and within certain temperature ranges, the viscosity change can be very drastic. This drastic change is usually reflected in the slope of the curve, and the abrupt change in slope often signifies the critical state at which the crude oil in the reservoir transitions from relative stillness to the start of flow. Therefore, identifying the abrupt change in slope becomes an important basis for determining temperature triggering conditions.

[0059] Furthermore, to identify abrupt slope changes, the slope of the temperature-viscosity curve needs to be calculated. By setting a preset deviation threshold, points with significant slope changes are selected as candidate critical temperature points. Typically, the temperature values ​​corresponding to these abrupt slope changes can be considered potential transition temperature limits. However, to further improve the accuracy of the determination, the tangent slopes of these candidate critical temperature points also need to be calculated and their magnitudes compared. Finally, the temperature point with the most significant tangent slope is selected as the transition temperature limit value, and a determination rule based on this temperature index is generated.

[0060] Based on the present invention, through in-depth analysis of temperature and viscosity changes, the critical temperature point at which viscosity drops sharply in the reservoir can be captured, making the judgment of the timing of the transition more accurate. Compared with traditional methods that rely solely on temperature thresholds, this method not only considers the impact of temperature changes on viscosity but also further optimizes the timing judgment process by identifying slope abrupt change points and calculating tangent slopes. Furthermore, this method can dynamically adjust the judgment rules based on real-time temperature data, making the transition operation more flexible and adaptable to changes under different reservoir conditions, thereby improving reservoir development efficiency and recovery rate.

[0061] Furthermore, when the timing indicator for switching to displacement is a pressure indicator, the corresponding rule generation process includes: fitting the relationship between formation pressure and recovery degree based on the pressure indicator dataset; fitting the pressure field map of the target area based on the fitted relationship and the recovery degree of the current target area; recovering experimental data from indoor core displacement experiments performed under simulated formation conditions; determining the starting pressure limit value for extra-heavy oil based on the experimental data; and generating the judgment rule under the pressure indicator based on the starting pressure limit value and the pressure field map of the target area.

[0062] Furthermore, the process of fitting the relationship between formation pressure and recovery degree based on the pressure index dataset includes: performing outlier removal on the pressure index dataset to obtain a standard dataset of pressure indices; constructing a coordinate system using formation pressure and recovery degree, and plotting a scatter plot based on the standard dataset of pressure indices within the coordinate system; fitting a trend curve based on the scatter plot, and constructing a functional relationship between formation pressure and recovery degree based on the fitted trend curve, as the fitted relationship between formation pressure and recovery degree. Figure 3 This represents a correlation between the degree of extraction per unit pressure drop.

[0063] In this embodiment of the invention, the pressure index dataset is processed, particularly by removing outliers. This step ensures data reliability, making subsequent analysis more accurate. Outliers are often caused by measurement errors or extreme conditions; therefore, removing these data helps obtain a more representative standard dataset. A scatter plot is drawn on a coordinate system of formation pressure and recovery degree, visually illustrating the relationship between the two. By observing the distribution of the scatter plot, a preliminary judgment can be made as to how formation pressure changes with recovery degree. Finally, a trend curve is fitted based on the scatter plot. The trend curve fitting process uses statistical methods to find the curve that best represents the trend of the scatter plot data. This fitted curve quantifies the relationship between formation pressure and recovery degree, ultimately forming a mathematical function used to describe and predict formation pressure changes under different recovery degrees.

[0064] Based on the present invention, the variation of formation pressure with the degree of recovery can be accurately captured, providing strong theoretical support for reservoir development. Compared with traditional empirical estimation methods, the fitted functional relationship is more scientific and reliable, which helps to improve the accuracy of formation pressure prediction and thus optimize reservoir development strategies.

[0065] Furthermore, the outlier removal process for the pressure index dataset to obtain a standard dataset for the pressure index includes: determining the change in extraction rate within each unit pressure drop based on the pressure index dataset; calculating the deviation between each change in extraction rate and the average value of the corresponding change in extraction rate based on the Z-Score algorithm; identifying change in extraction rate with a deviation greater than a preset deviation threshold as outlier values; identifying the data items in the pressure index dataset corresponding to the outlier values ​​as outliers, and performing outlier removal processing.

[0066] In this embodiment of the invention, by analyzing the changes in extraction rate within each unit pressure drop, the dynamic relationship between pressure change and extraction rate can be captured. To ensure the reliability of this data, the Z-Score algorithm is used to evaluate the deviation of each extraction rate change value from its average value. The Z-Score algorithm is a statistical method that can standardize data and identify outliers that deviate from the normal range. Specifically, if the Z-Score of a certain extraction rate change value exceeds a preset deviation threshold, it means that the value does not conform to the overall trend and may be caused by measurement error, extreme conditions, or other abnormal factors. Once these abnormal changes are identified, their corresponding data items are marked as outliers. To ensure the accuracy of data analysis, these outliers are removed from the dataset, forming a cleaner and more reliable standard dataset of pressure indicators.

[0067] Furthermore, such as Figure 4 This represents a production level and formation pressure map. After fitting the pressure field map of the target area based on the fitting relationship and the production level of the current target area, the method further includes: calculating the variogram value of each oil well based on the pressure index dataset and the distance information between each oil well; identifying outliers in the pressure field map of the target area based on the variogram values ​​of each oil well; and correcting the pressure field map of the target area based on the outlier identification results to obtain a pressure field map that conforms to the smoothing coefficient of the elastic change of formation pressure in the target area. Figure 5 This represents a pressure field diagram.

[0068] In this embodiment of the invention, based on a dataset of pressure indicators and distance information between oil wells, the variogram value for each oil well is calculated. The variogram is a tool in geostatistics used to describe the variation of spatial variables with distance; it can quantify the correlation of pressure changes between oil wells. Within a target area, the variogram values ​​can reveal the regularity and anomalies of pressure changes. These variogram values ​​are then used to identify outliers in the initially generated pressure field map. Figure 6 This diagram illustrates local anomalies. If pressure changes in certain areas do not conform to expected spatial correlation (i.e., the variogram values ​​deviate significantly from the conventional pattern), these areas may contain anomalous pressure values. After identifying these anomalous areas, these anomalies are corrected based on the variogram and other geological information to make the pressure field map more consistent with the actual elastic variation characteristics of the formation. The corrected pressure field map can more accurately reflect the formation pressure changes in the target area and conforms to the smoothing coefficient of the elastic variation of formation pressure in the target area.

[0069] Based on the present invention, by identifying and correcting outliers in the preliminary pressure field map, the accuracy and reliability of the pressure field map are significantly improved. The corrected pressure field map can better reflect the actual pressure distribution within the reservoir, which helps to optimize development strategies and ensure reservoir management under appropriate pressure conditions. Furthermore, this method can avoid misjudgments caused by outliers, improving the overall efficiency and economic benefits of reservoir development.

[0070] Furthermore, the recovery of experimental data from indoor core displacement experiments conducted under simulated formation conditions includes: based on a pre-constructed indoor core displacement experimental setup, sequentially performing indoor core displacement experiments on each crude oil sample determined based on the reservoir conditions of the target area to obtain all experimental data; wherein, the indoor core displacement experimental setup includes: a fluid injection device for controlling the injection volume and pressure of the fluid; a physical simulation device for simulating the actual temperature and pressure environment of the formation; a data acquisition device for real-time acquisition of pressure and temperature during the experiment; and an oil-water metering device for measuring the fluid seepage velocity used to evaluate the crude oil displacement effect and the starting pressure. Figure 7 This is a schematic diagram of the structure of an indoor core displacement experimental apparatus provided in one embodiment.

[0071] Furthermore, the indoor core displacement experiments are sequentially performed on each crude oil sample determined based on the reservoir conditions of the target area to obtain all experimental data, including: S1) sequentially performing filtration and dehydration treatment on all crude oil samples, filling them into each physical simulation device, and letting them stand for a first preset time; S2) adjusting the temperature of the physical simulation device corresponding to the current crude oil sample to reach a preset target temperature, and maintaining the preset target temperature for a second preset time; S3) displacing liquid to the inlet end of the core constructed based on the formation of the target area under preset ultra-low speed conditions, starting to record the pressure at the outlet end of the core when seepage begins, until the pressure value stabilizes, and obtaining a stable pressure value; S4) after letting the current core stand for a third preset time, modifying the displacement flow rate under preset ultra-low speed conditions, and repeating step S3) to obtain the latest stable pressure value; S5) repeating step S4) N times to obtain the stable pressure value of the current crude oil sample under each displacement flow rate; S6) changing the crude oil sample and repeating steps S2)-S5) until obtaining the stable pressure value of all crude oil samples under each displacement flow rate.

[0072] Furthermore, determining the starting pressure limit value of extra-heavy oil based on the experimental data includes: constructing a non-Darcy flow curve of extra-heavy oil corresponding to the target region based on the experimental data; identifying the starting point of flow in the non-Darcy flow curve; and using the pressure value of the starting point of flow as the determined starting pressure limit value of extra-heavy oil.

[0073] Furthermore, based on the starting pressure limit value and the pressure field map of the target area, a judgment rule is generated under the pressure index, including: using the determined starting pressure limit value as the judgment basis value, identifying areas in the pressure field map of the target area where the pressure value is greater than the judgment basis value; if the current area is in the identified area, the pressure triggering condition is determined to be met; if the current area is not in the identified area, the pressure triggering condition is determined to be unmet.

[0074] In this embodiment of the invention, the non-Darcy flow curve is used to describe the nonlinear flow behavior of fluids in porous media, particularly under low-velocity or high-viscosity fluid conditions, such as extra-heavy oil. Using experimental data, a non-Darcy flow curve corresponding to the target region can be plotted, showing the pressure changes at the start of fluid flow. By analyzing the location of the flow initiation point on this curve, the starting pressure value for the initiation of seepage can be identified, i.e., the minimum pressure at which the fluid overcomes formation resistance and begins to seep. This pressure value is determined as the initiation pressure threshold for extra-heavy oil.

[0075] In one possible implementation, the fluid injection device mainly includes a high-precision displacement pump; the physical simulation device includes a constant temperature chamber, a core holder, and an intermediate crude oil container; the automatic data acquisition device includes pressure and temperature sensors, a computer, and data acquisition software. The experimental conditions are a 30cm long sand-filled pipe, manually filled with quartz sand. Core displacement experiments are used to study different physical properties and crude oil viscosities, determining the flow patterns under no-injection-rate conditions. The main experimental steps are as follows:

[0076] 1) First, filter the crude oil sample with a stainless steel sieve with an aperture of 0.045 mm (325 mesh) at 80°C, and then dehydrate it in a crude oil dehydrator at a constant temperature of 120°C for two hours. The water content should be less than 0.3% to be considered qualified.

[0077] 2) Load 1000mL of dehydrated oil sample into the crude oil intermediate container, connect the experimental apparatus according to the experimental flowchart, saturate the sand-filled tube with crude oil from different wells, and let it stand for 24 hours to fully age.

[0078] 3) Set the temperature of the constant temperature chamber to the experimental temperature. Once the temperature reaches the set value and stabilizes, maintain the temperature for two hours.

[0079] 4) Displace the liquid to the inlet end of the core under very low speed conditions, gradually build up the inlet pressure, and record the pressure when liquid appears at the outlet end of the core.

[0080] 5) Once the pressure data stabilizes, record the stable pressure.

[0081] 6) Allow the core to stand for 8 hours to age, then measure the starting pressure gradient using different displacement flow rates, repeating step 5).

[0082] 7) Change the crude oil product and repeat steps 3)-6).

[0083] The non-Darcy flow curve of extra-heavy oil is as follows: Figure 8 As shown. It is mainly divided into three stages:

[0084] First stage (OA segment): Point A is the actual starting pressure gradient of the reservoir, which is usually very small. When the pressure gradient is less than that at point A, the heavy oil does not flow and its flow rate is 0.

[0085] Second stage (AC segment): In this stage, the fluid flow velocity is relatively slow, and the rate of change of flow velocity increases with the increase of pressure gradient, and the seepage curve shows an "upward" trend.

[0086] The third stage (CE segment): When the fluid pressure gradient is greater than point C, the fluid velocity increases linearly with the pressure gradient. Point C is the critical point for the transition from nonlinear to linear flow, and the corresponding pressure gradient is called the critical pressure gradient. Point B is the intersection of the backward extension of the straight line segment CE and the coordinate axis, and its corresponding starting pressure gradient is the pseudo-starting pressure gradient. The purpose of this experiment is to use the velocity-pressure difference chart to fit the magnitude of point A, i.e., the starting pressure gradient.

[0087] Furthermore, such as Figure 9 This diagram illustrates a conversion zone. Based on a defined initiation pressure threshold and a pressure field map of the target area, judgment rules under pressure indicators can be generated. Specifically, the initiation pressure threshold is used as the baseline value, and areas with pressure values ​​exceeding this baseline value are identified in the pressure field map. These areas indicate that the formation pressure has reached the conditions for the extra-heavy oil to begin flowing. If the current area is within the identified high-pressure zone, it is determined that the area meets the pressure triggering conditions for conversion, and further reservoir development operations are suitable. If the current area has not reached the pressure condition, conversion operations are temporarily suspended.

[0088] Furthermore, when the timing indicator for switching to hydraulic fracturing is a viscosity index, the corresponding rule generation process includes: fitting the relationship between injected steam volume and temperature based on the viscosity index dataset, and fitting the relationship between temperature and formation crude oil viscosity; performing a mapping of the relationship between injected steam volume and formation crude oil viscosity based on the fitted relationship between injected steam volume and temperature, and the fitted relationship between temperature and formation crude oil viscosity; such as... Figure 10 This shows a curve illustrating the relationship between the amount of injected steam and temperature. Figure 11To correspond to the viscosity-temperature curve of extra-heavy oil, one-dimensional physical model experimental results data based on a pre-constructed small-scale numerical model were collected. Based on these results, the relationship between different crude oil viscosities and permeabilities and the threshold viscosity for initiation was established. Based on this relationship, the reservoir permeability factor and the threshold viscosity for initiation at various locations within the target area were calculated. The relationship between injected steam and formation crude oil viscosity was corrected based on the reservoir permeability factor. Figure 12 This represents the relationship between injected steam volume and viscosity. Based on the corrected relationship between injected steam volume and formation crude oil viscosity, a viscosity field map of the target area is generated; based on the viscosity field map of the target area and the starting viscosity threshold values ​​at each location, viscosity indices are generated.

[0089] Judgment rules.

[0090] Specifically, the acquisition of pre-constructed one-dimensional physical model experimental results data based on small-scale numerical models, and the establishment of relationships between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on the one-dimensional physical model experimental results data, includes: simulating the seepage process of crude oil under different crude oil viscosities and different permeabilities through one-dimensional physical model experiments; gradually increasing, for example, the amount of injected steam, and measuring the crude oil viscosity when the crude oil begins to flow, as the starting viscosity threshold value for the corresponding crude oil viscosity and corresponding permeability; iteratively adjusting the permeability and crude oil viscosity to obtain the starting viscosity threshold value for each crude oil viscosity and corresponding permeability; and constructing the relationship between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on each crude oil viscosity and corresponding starting viscosity threshold value. Figure 13 This diagram illustrates a comparison of the relationship between different viscosities, different permeabilities, and starting viscosity.

[0091] Furthermore, through one-dimensional physical model experiments, the seepage process under different crude oil viscosities and permeabilities can be simulated. During the experiment, by gradually increasing external driving forces such as the injection of steam, the starting viscosity of crude oil under different conditions is measured. When the crude oil begins to flow, the viscosity at this point is recorded as the starting viscosity threshold value for the corresponding permeability and crude oil viscosity. By iteratively adjusting the permeability and crude oil viscosity in the experiment, the starting viscosity threshold values ​​under different permeability conditions are systematically obtained. This iterative process allows the experiment to cover a wide range of reservoir conditions, ensuring that the obtained data is comprehensive and representative. After organizing all experimental results, a model is constructed to describe the relationship between different crude oil viscosities and permeabilities and the starting viscosity threshold values. This model can accurately describe how crude oil viscosity affects the conditions for starting flow at a specific permeability.

[0092] Based on the present invention, one-dimensional physical model experiments can accurately simulate the flow behavior of extra-heavy oil under different formation conditions, obtaining the starting viscosity threshold values ​​under different viscosity and permeability conditions. This experimental method not only provides a scientifically sound data foundation but also enables developers to construct a starting viscosity relationship model that comprehensively considers permeability and viscosity. This model can be directly applied to the formulation of reservoir development strategies, helping to optimize the timing of transition to hydraulic fracturing and improve reservoir recovery. Furthermore, this method can reduce resource waste caused by premature or delayed transition to hydraulic fracturing, lower development costs, and extend the oil recovery period.

[0093] The production life of the reservoir provides solid technical support for the development of extra-heavy oil reservoirs.

[0094] Furthermore, the calculation rule for the seepage factor of the target area is as follows:

[0095]

[0096] Where φ is the seepage factor; m is the reservoir coefficient of the target area; k is the permeability of the target area; and μ is the current crude oil viscosity.

[0097] Furthermore, the relationship between injected steam volume and formation crude oil viscosity is corrected based on the reservoir permeability factor of the target area, including: using the reservoir permeability factor of the target area as an adjustment factor between injected steam volume and formation crude oil viscosity; and adding factor variables to the relationship between injected steam volume and formation crude oil viscosity based on the adjustment factor to obtain the corrected relationship between injected steam volume and formation crude oil viscosity.

[0098] In this embodiment of the invention, the first step is to perform fitting analysis on the relationships between injected steam volume and temperature, and between temperature and formation crude oil viscosity. By processing the viscosity index dataset, curves showing the relationship between injected steam volume and temperature, and curves showing the relationship between temperature and formation crude oil viscosity, can be fitted respectively. The former reflects how formation temperature changes under different steam injection volume conditions; the latter shows how temperature changes affect the fluidity of crude oil, i.e., the trend of viscosity changes.

[0099] Furthermore, by mapping these two fitted relationships, a direct relationship between injected steam volume and formation crude oil viscosity can be established. This mapping provides a preliminary model capable of predicting viscosity variations in formation crude oil under different steam injection rates. However, the seepage conditions in actual oil reservoirs are often complex due to formation heterogeneity; therefore, relying solely on the preliminary mapping may not accurately reflect real reservoir conditions. To address this issue, the relationship needs to be corrected based on the reservoir seepage factor of the target area. Figure 14This figure illustrates the relationship between the corrected injected steam rate and the starting viscosity. The permeability factor, reflecting the ease of fluid flow in the formation, can be introduced as a modifier into the relationship between injected steam rate and formation crude oil viscosity. By adding this factor variable to adjust the impact of injected steam rate on formation crude oil viscosity, the reservoir's viscosity can be more accurately reflected.

[0100] Actual flow characteristics.

[0101] Based on the present invention, the modified model not only considers the fundamental physical relationships but also incorporates the flow characteristics of the formation, thus enabling better prediction of changes in crude oil viscosity under actual development conditions. This provides strong support for the formulation of steam-driven development strategies, helps optimize the amount of injected steam, improves recovery rates, reduces resource waste, and ultimately enhances the economic benefits and sustainability of reservoir development.

[0102] Furthermore, such as Figure 15 This paper presents a viscosity field map. Based on the viscosity field map of the target area and the starting viscosity threshold values ​​at each location, a determination rule for the viscosity index is generated, including: comparing the viscosity field map of the target area with the starting viscosity threshold values ​​at the corresponding locations, and determining the locations where the viscosity is greater than the starting viscosity threshold values ​​at the corresponding locations as trigger locations; if the current location is a trigger location, the viscosity trigger condition is determined to be met; if the current location is not a trigger location, the viscosity trigger condition is determined to be unmet.

[0103] In this embodiment of the invention, a viscosity field map of the target region is used, which illustrates the viscosity distribution of crude oil at different locations within the reservoir. Simultaneously, the starting viscosity threshold value for each location represents the minimum viscosity at which crude oil begins to flow. By comparing these two datasets, locations with viscosities exceeding the starting viscosity threshold value can be identified. These locations indicate that the crude oil viscosity within the reservoir has exceeded the critical value for flow, becoming potential "trigger locations." According to the judgment rules, if a location within the current reservoir falls under these trigger locations, it means that the viscosity conditions at that location are met, making steam drive operation suitable; conversely, if the viscosity at the current location is below the starting viscosity threshold value, steam drive operation is not recommended because the viscosity at this point is still insufficient to support effective crude oil flow.

[0104] Based on the present invention, this solution not only considers the actual viscosity distribution of the formation but also incorporates critical fluidity conditions, making the steam injection operation more scientific and rational. This technology can effectively reduce unnecessary steam injection operations, avoid resource waste, and maximize reservoir recovery and economic benefits, ensuring reservoir development under optimal conditions.

[0105] Step S30: Collect the current collection status information in real time, and determine whether the current collection status information meets the switching conditions based on the judgment rules of each switching timing indicator.

[0106] Specifically, based on the formation temperature information and temperature index determination rules in the current acquisition status information, it is determined whether the current temperature triggering condition is met; based on the acquisition location information and pressure index determination rules in the current acquisition status information, it is determined whether the current pressure triggering condition is met; based on the acquisition location information and viscosity index determination rules in the current acquisition status information, it is determined whether the current viscosity triggering condition is met; if the temperature triggering condition, pressure triggering condition, and viscosity triggering condition are all met, then the current acquisition status information is determined to meet the drive conversion condition; conversely, if at least one of the temperature triggering condition, pressure triggering condition, and viscosity triggering condition is not met, then the current acquisition status information is determined not to meet the drive conversion condition.

[0107] In this embodiment of the invention, formation temperature information is monitored in real time and compared with the judgment rules of temperature indicators to determine whether the current temperature meets the triggering conditions. If the temperature reaches a preset threshold value, it indicates that the temperature condition is met and meets the requirements for steam drive. Next, based on the collected location information, the pressure status of the current area is assessed in real time. The current pressure value is compared with the judgment rules of pressure indicators to determine whether the pressure triggering conditions are met. Finally, based on the real-time collected viscosity information, it is assessed whether the fluidity of the crude oil meets the requirements for steam drive, and the current viscosity condition is determined by comparing it with the judgment rules of viscosity indicators. If any one or more of the three indicators—temperature, pressure, and viscosity—meet their judgment rules simultaneously, it indicates that the current collected status information meets the steam drive conditions, and steam drive operation can be performed. Conversely, if any one indicator does not meet the triggering conditions, it indicates that the current conditions are not suitable for steam drive, and monitoring and waiting for changes in conditions are required.

[0108] Based on the present invention, by comprehensively analyzing real-time data from three key indicators—temperature, pressure, and viscosity—it is possible to more accurately assess whether a reservoir is in a suitable state for steam drive. Compared to traditional methods, this method has the advantages of real-time performance and comprehensiveness. It can make dynamic judgments based on real-time data, avoiding unnecessary operations or resource waste caused by misjudgments based on a single indicator. Simultaneously, this multi-indicator comprehensive evaluation method improves the accuracy of judgment, ensuring that steam drive operations are performed at the optimal time, thereby increasing recovery rates, extending reservoir production life, and maximizing development benefits.

[0109] Step S40: When the conditions for steam transfer are met, trigger the execution of steam transfer.

[0110] Specifically, when key indicators such as real-time monitored temperature, pressure, and viscosity all meet the preset steam injection criteria, the system immediately triggers the steam injection operation. This ensures that steam injection occurs at the most appropriate time, thereby optimizing steam utilization efficiency and reservoir production. By executing steam injection under optimal conditions, not only can crude oil recovery be maximized, but unnecessary resource waste and production delays can also be avoided, significantly improving the economic benefits and production stability of reservoir development.

[0111] Based on the present invention, this triggering mechanism ensures that steam-driven operations are performed at the optimal time, reduces unnecessary steam loss, and improves production efficiency and long-term reservoir stability.

[0112] Figure 3 This is a system structure diagram of a vapor transfer timing determination system for extra-heavy oil provided in one embodiment of the present invention. Figure 3 As shown, this invention provides a steam drive timing determination system for extra-heavy oil. The system includes: a data acquisition unit for acquiring historical logging data and historical oil production data of a target reservoir area, and classifying the historical logging data and historical oil production data according to corresponding steam drive timing determination indicators to obtain multiple datasets; wherein the steam drive timing determination indicators include temperature, pressure, and viscosity indicators; a rule generation unit for generating determination rules for corresponding steam drive timing determination indicators based on each dataset; a determination unit for acquiring acquisition status information in real time under the current acquisition state, and determining whether the current acquisition status information meets the steam drive conditions based on the determination rules for each steam drive timing determination indicator; and an execution unit for triggering steam drive execution when the steam drive conditions are met.

[0113] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described method for determining the timing of extra-heavy oil steam transfer.

[0114] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0115] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0116] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for determining the timing of vapor transfer for extra-heavy oil, characterized in that, The method includes: Historical logging data and historical oil production data of the target oil reservoir area were collected, and the historical logging data and historical oil production data were classified according to the corresponding drive timing judgment index to obtain multiple datasets; Judgment rules for corresponding drive timing indicators are generated based on each dataset; The system collects the current collection status information in real time and determines whether the current collection status information meets the conditions for switching to the drive based on the judgment rules of each drive switching timing indicator. When the conditions for steam transfer are met, steam transfer is triggered.

2. The method according to claim 1, characterized in that, The indicators for determining the timing of the drive include any combination of temperature, pressure, and viscosity indicators. The historical logging data and historical oil production data are classified according to the corresponding indicators for determining the timing of the shift, resulting in multiple datasets, including: Perform data preprocessing on the historical logging data and historical oil production data; The preprocessed data is classified using the K-means clustering algorithm to obtain the data classification results for each transition timing indicator, which serves as the dataset for that indicator.

3. The method according to claim 2, characterized in that, When the indicator for determining the timing of the drive transition is temperature, the corresponding rule generation process includes: Fitting temperature and viscosity data curves based on a dataset of temperature indices; Abrupt slope changes were identified in the temperature-viscosity data curves, and each abrupt slope change was selected as a candidate key temperature point; among them... The slope abrupt change point is the point on the temperature-viscosity data curve where the proportional deviation between the slope before and after the curve is greater than a preset deviation proportional threshold. Calculate the tangent slope of each candidate critical temperature point, and determine the drive temperature limit value of the temperature index based on the tangent slope and the relationship between each candidate critical temperature point. The determination rules for temperature indicators are generated based on the aforementioned drive temperature limit value.

4. The method according to claim 3, characterized in that, The determination rules under the temperature index include: If the current temperature value reaches the aforementioned drive temperature limit value, then the temperature triggering condition is determined to be met. Conversely, if the current temperature value does not reach the aforementioned drive temperature limit value, the temperature triggering condition is determined to be invalid.

5. The method according to claim 2, characterized in that, When the indicator for determining the timing of the drive shift is a pressure indicator, the corresponding rule generation process includes: Based on a dataset of pressure indices, the relationship between formation pressure and recovery degree is fitted. The pressure field map of the target area is fitted based on the fitting relationship and the current extraction level of the target area; Recover experimental data from indoor core displacement experiments conducted to simulate crude oil seepage under formation conditions; The starting pressure limit value for extra-heavy oil was determined based on the experimental data. The determination rules under the pressure index are generated based on the starting pressure limit value and the pressure field map of the target area.

6. The method according to claim 5, characterized in that, The dataset based on pressure indices is used to fit the relationship between formation pressure and recovery degree, including: Perform outlier removal on the stress metric dataset to obtain a standard dataset of stress metrics; A coordinate system is constructed based on formation pressure and production level, and a scatter plot is drawn in the coordinate system based on a standard dataset of pressure indices. Based on the scatter plot, a trend curve is fitted, and a functional relationship between formation pressure and recovery degree is constructed based on the fitted trend curve, which serves as the fitting relationship between formation pressure and recovery degree.

7. The method according to claim 6, characterized in that, The outlier removal process performed on the stress metric dataset to obtain a standard dataset of stress metrics includes: Based on the dataset of pressure indicators, determine the change in the degree of extraction within each unit pressure drop; The deviation between each change in extraction degree and the average change in the corresponding extraction degree is calculated based on the Z-Score algorithm. Changes in the sampling rate that deviate from the preset deviation threshold are considered abnormal changes. The data items in the dataset corresponding to the pressure indicators with abnormal changes are identified as outliers, and the outliers are removed.

8. The method according to claim 5, characterized in that, After fitting the pressure field map of the target area based on the fitting relationship and the current extraction level of the target area, the method further includes: Based on the pressure index dataset and the distance information between each oil well, the variation function value of each oil well is calculated. Outlier identification is performed on the pressure field map of the target area based on the variation function values ​​of each oil well. Based on the outlier identification results, the pressure field map of the target area is corrected to obtain a pressure field map that conforms to the smoothness coefficient of the elastic change of formation pressure in the target area.

9. The method according to claim 5, characterized in that, The experimental data recovered from the indoor core displacement experiment conducted under simulated formation conditions for crude oil seepage include: Based on a pre-constructed indoor core displacement experimental setup, indoor core displacement experiments were sequentially conducted on various crude oil samples determined based on the reservoir conditions of the target area, and all experimental data were obtained; among them, The indoor core displacement experimental apparatus includes: A fluid injection device used to control the injection volume and pressure of fluid; A physical simulation device used to simulate the temperature and pressure environment of actual geological formations; Data acquisition device, used to collect pressure and temperature during the experiment in real time; Oil-water metering device, used to measure the fluid seepage velocity used to evaluate the crude oil displacement effect and start-up pressure.

10. The method according to claim 9, characterized in that, The indoor core displacement experiments were sequentially conducted on each crude oil sample determined based on the reservoir conditions of the target area to obtain all experimental data, including: S1) Filter and dehydrate all crude oil samples sequentially, fill them into each physical simulation device, and let them stand for the first preset time. S2) Adjust the temperature of the physical simulation device corresponding to the current crude oil sample to reach the preset target temperature and maintain the preset target temperature for a second preset time; S3) Under preset ultra-low speed conditions, the liquid is displaced to the inlet end of the core constructed based on the strata of the target area, and the pressure at the outlet end of the core when seepage begins is recorded until the pressure value stabilizes and a stable pressure value is obtained. S4) After the current core has been left to stand for the third preset time, modify the displacement flow rate under the preset ultra-low speed condition, and repeat step S3) to obtain the latest stable pressure value. S5) Repeat step S4) N times to obtain the stable pressure value of the current crude oil sample under each displacement flow rate; S6) Change the crude oil sample and repeat steps S2)-S5) until stable pressure values ​​of all crude oil samples are obtained at each displacement flow rate.

11. The method according to claim 5, characterized in that, The determination of the starting pressure limit value of extra-heavy oil based on the experimental data includes: Based on the experimental data, non-Darcy flow curves of extra-heavy oil corresponding to the target region were constructed. The starting point of seepage is identified in the non-Darcy seepage curve, and the pressure value at the starting point of seepage is used as the determined threshold pressure for extra-heavy oil.

12. The method according to claim 5, characterized in that, Based on the starting pressure limit value and the pressure field map of the target area, a judgment rule is generated under the pressure index, including: Using the determined starting pressure limit value as the judgment basis value, the region with a pressure value greater than the judgment basis value is identified in the pressure field map of the target region. If the current area is within the identified area, the pressure triggering condition is determined to be met; If the current area is not within the identified area, the pressure triggering condition is determined to be invalid.

13. The method according to claim 2, characterized in that, When the viscosity index is used as the criterion for determining the timing of the drive transition, the corresponding rule generation process includes: Based on a dataset of viscosity indices, we fitted the relationship between injected steam volume and temperature, and the relationship between temperature and formation crude oil viscosity. The relationship between injected steam volume and formation crude oil viscosity is mapped based on the fitting relationship between injected steam volume and temperature, and the fitting relationship between temperature and formation crude oil viscosity. Collect pre-constructed one-dimensional physical model experimental results data based on small-scale numerical model construction, establish the relationship between different crude oil viscosities and different permeabilities and the starting viscosity limit value based on the one-dimensional physical model experimental results data, and calculate the reservoir seepage factor and the starting viscosity limit value at each location in the target area based on the relationship between different crude oil viscosities and different permeabilities and the starting viscosity limit value. Correction of the relationship between injected steam volume and formation crude oil viscosity based on reservoir seepage factor in the target area; Based on the corrected relationship between injected steam volume and formation crude oil viscosity, a viscosity field map of the target region is generated. The viscosity field map of the target area and the starting viscosity limit value at each location are used to generate the judgment rules for the viscosity index.

14. The method according to claim 13, characterized in that, The acquisition of pre-constructed one-dimensional physical model experimental results data based on small-scale numerical models, and the establishment of relationships between different crude oil viscosities and different permeabilities and the starting viscosity threshold value based on the one-dimensional physical model experimental results data, including: The seepage process of crude oil under different crude oil viscosities and permeabilities was simulated by one-dimensional physical model experiments. Gradually increase the amount of injected steam and measure the crude oil viscosity when it begins to flow, using this as the starting viscosity limit value for the corresponding crude oil viscosity and permeability. The permeability and crude oil viscosity were iteratively adjusted to obtain the viscosity of each crude oil and the corresponding starting viscosity limit value at each permeability. Based on the viscosity of each crude oil and the corresponding starting viscosity limit value at each permeability, the relationship between different crude oil viscosities and different permeabilities and the starting viscosity limit value is constructed.

15. The method according to claim 13, characterized in that, The calculation rule for the seepage factor of the target area is as follows: Where φ is the seepage factor; m is the reservoir coefficient of the target area; k represents the penetration rate of the target area; μ represents the current viscosity of the crude oil.

16. The method according to claim 13, characterized in that, Corrections to the relationship between injected steam rate and formation crude oil viscosity based on reservoir permeability factors in the target area include: The reservoir permeability factor in the target area is used as a regulating factor between the injected steam volume and the formation crude oil viscosity. By adding factor variables to the relationship between injected steam volume and formation crude oil viscosity based on the aforementioned adjustment factor, a corrected relationship between injected steam volume and formation crude oil viscosity is obtained.

17. The method according to claim 13, characterized in that, Based on the viscosity field map of the target region and the starting viscosity threshold values ​​at each location, the determination rules for viscosity indices are generated, including: By comparing the viscosity field map of the target area with the corresponding starting viscosity threshold value, the location where the viscosity is greater than the corresponding starting viscosity threshold value is determined as the trigger location; If the current position is a trigger position, then the viscosity trigger condition is determined to be met; If the current position is not a trigger position, then the viscosity trigger condition is determined to be invalid.

18. The method according to claim 2, characterized in that, Based on the judgment rules for each drive transition timing indicator, determine whether the currently collected status information meets the drive transition conditions, including: Based on the formation temperature information and temperature index determination rules in the current data collection status information, determine whether the current temperature triggering condition is met. Based on the collection location information and pressure index determination rules in the current collection status information, determine whether the current pressure triggering condition is met; Based on the acquisition location information and viscosity index determination rules in the current acquisition status information, determine whether the current viscosity trigger condition is met; If the temperature trigger condition, pressure trigger condition, and viscosity trigger condition are all met, then the current collected status information is determined to meet the driving conditions. Conversely, if at least one of the temperature trigger condition, pressure trigger condition, and viscosity trigger condition is not met, it is determined that the current collected status information does not meet the driving conditions.

19. A system for determining the timing of vapor transfer for extra-heavy oil, characterized in that, The system includes: The acquisition unit is used to collect historical logging data and historical oil production data of the target oil reservoir area, and classify the historical logging data and historical oil production data according to the corresponding drive timing judgment index to obtain multiple datasets; The rule generation unit is used to generate judgment rules for corresponding drive timing judgment indicators based on each dataset; The judgment unit is used to collect the collection status information under the current collection state in real time, and to determine whether the current collection status information meets the transfer conditions based on the judgment rules of each transfer timing judgment index item. The execution unit is used to trigger the steam transfer drive when the transfer drive conditions are met.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the method for determining the timing of steam transfer of extra-heavy oil as described in any one of claims 1-18.

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