Method and device for calculating the viscosity of a mud filtrate

Abstract

The application discloses a mud filtrate viscosity calculation method and device, and relates to the field of exploration. The method comprises the following steps: acquiring mud filtrate viscosities of mud filtrate samples of various mud filtrate types under different temperatures and different pressures, establishing mud filtrate viscosity charts corresponding to the various mud filtrate types according to the mud filtrate viscosities, determining influence laws of the temperature and the pressure on the mud filtrate viscosities according to the mud filtrate viscosity charts, and respectively constructing corresponding mud filtrate viscosity calculation models for each mud filtrate type according to the influence laws; acquiring a mud filtrate type of a well to be calculated, a current downhole temperature and a current downhole pressure, substituting the current downhole temperature and the current downhole pressure into the mud filtrate viscosity calculation model matched with the mud filtrate type, and calculating the mud filtrate viscosity of the well to be calculated, so that real-time and accurate calculation of the mud filtrate viscosity under high temperature and high pressure conditions is realized, and the interpretation accuracy of the formation mobility and the permeability is improved.

Description

Technical Field

[0001] This application relates to the field of exploration, specifically to a method and apparatus for calculating the viscosity of mud filtrate. Background Technology

[0002] In oil and gas exploration and development, the viscosity of drilling mud filtrate is a crucial parameter affecting formation mobility interpretation and production prediction. Formation mobility is defined as the ratio of effective permeability to fluid viscosity, and this parameter plays a vital role in assessing reservoir permeability and formulating development plans. Currently, formation mobility is typically obtained through downhole testing methods such as wireline logging or testing while drilling, and in data interpretation, the viscosity of drilling mud filtrate is usually taken as a fixed value (e.g., 0.9 cP). However, the viscosity of drilling mud filtrate is not a constant value; it varies with factors such as temperature and pressure. Continuing to use a fixed viscosity value for interpretation will result in significant deviations in the inverted formation mobility and permeability, affecting the accuracy of reservoir evaluation. Furthermore, existing viscosity measurement methods (such as the rotation method, free-fall method, and capillary method) all have varying degrees of limitations when measuring low-viscosity drilling mud filtrate under high temperature and high pressure. Therefore, there is an urgent need for a method that can accurately predict the viscosity of drilling mud filtrate to improve the accuracy of formation mobility and permeability interpretation. Summary of the Invention

[0003] In view of the above problems, this application is made in order to provide a method and apparatus for calculating the viscosity of mud filtrate that overcomes or at least partially solves the above problems.

[0004] According to one aspect of the embodiments of this application, a method for calculating the viscosity of mud filtrate is provided, the method comprising: The viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions was obtained. Mud filtrate viscosity charts were established for each mud filtrate type based on the mud filtrate viscosity. The influence of temperature and pressure on mud filtrate viscosity was determined based on the mud filtrate viscosity charts. Based on the influence, a corresponding mud filtrate viscosity calculation model was constructed for each mud filtrate type. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable. Obtain the mud filtrate type, current downhole temperature, and current downhole pressure of the well to be calculated. Substitute the current downhole temperature and current downhole pressure into the mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculate the mud filtrate viscosity of the well to be calculated.

[0005] Furthermore, the mud filtrate viscosity chart includes at least one of the following plotting methods: plotting multiple mud filtrate viscosity-temperature variation curves under different pressure conditions in the same coordinate system with temperature as the abscissa and mud filtrate viscosity as the ordinate; and / or plotting multiple mud filtrate viscosity-pressure variation curves under different temperature conditions in the same coordinate system with pressure as the abscissa and mud filtrate viscosity as the ordinate.

[0006] Furthermore, based on the mud filtrate viscosity chart, the influence of temperature and pressure on the mud filtrate viscosity was determined, including: Based on the comparison of the viscosity-temperature change curves of mud filtrate under the same pressure conditions, the influence law of temperature on mud filtrate viscosity is determined as follows: under constant pressure conditions, the viscosity of mud filtrate decreases as the temperature increases. Based on the comparison of the viscosity-pressure change curves of mud filtrate under the same temperature conditions, the influence law of pressure on mud filtrate viscosity is determined as follows: under constant temperature conditions, the viscosity of mud filtrate increases with increasing pressure.

[0007] Furthermore, based on the influencing factors, a corresponding mud filtrate viscosity calculation model is constructed for each type of mud filtrate, including: Based on the influence law, an initial mathematical model was constructed. The initial mathematical model uses temperature as the variable and the viscosity of mud filtrate as the dependent variable, and includes multiple model parameters that correspond to pressure. Under each pressure condition, the initial mathematical model was fitted using the viscosity of the mud filtrate at different temperatures to obtain the model parameter values ​​under each pressure condition; Using the model parameter values ​​obtained by fitting under various pressure conditions, a functional relationship between each model parameter and pressure is established; Substituting the functional relationship between each model parameter and pressure into the initial mathematical model, we obtain the mud filtrate viscosity calculation model.

[0008] Furthermore, the initial mathematical model is as follows:

[0009] Where η is viscosity, T is temperature, a, b and k are model parameters, a and b are related to pressure, and k is a fixed value related to the type of mud filtrate.

[0010] Furthermore, if the mud filtrate type is water-based mud filtrate, then the relationship between model parameters a and b and pressure is:

[0011] If the mud filtrate type is oil-based mud filtrate, then the relationship between model parameters a and b and pressure is:

[0012] Where P represents pressure.

[0013] According to another aspect of the embodiments of this application, a mud filtrate viscosity calculation device is provided, the device comprising: The chart creation module is suitable for obtaining the viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions, and creating mud filtrate viscosity charts corresponding to each mud filtrate type based on the mud filtrate viscosity. The model building module is suitable for determining the influence of temperature and pressure on the viscosity of mud filtrate based on the mud filtrate viscosity chart. Based on the influence, a corresponding mud filtrate viscosity calculation model is built for each type of mud filtrate. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable. The calculation module is suitable for obtaining the mud filtrate type, current downhole temperature, and current downhole pressure of the well to be calculated. It then substitutes the current downhole temperature and current downhole pressure into a mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculates the mud filtrate viscosity of the well to be calculated.

[0014] According to another aspect of the embodiments of this application, a computing device is provided, including: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described mud filtrate viscosity calculation method.

[0015] According to another aspect of the embodiments of this application, a computer storage medium is provided, which stores at least one executable instruction that causes a processor to perform an operation corresponding to the above-described mud filtrate viscosity calculation method.

[0016] According to another aspect of this application, a computer program product is provided, including at least one executable instruction that causes a processor to perform operations corresponding to the above-described mud filtrate viscosity calculation method.

[0017] The technical solution provided in this application enables real-time and accurate calculation of drilling mud filtrate viscosity under high temperature and pressure conditions downhole, effectively improving the interpretation accuracy of formation mobility and permeability, reducing the uncertainty of reservoir evaluation, and optimizing drilling fluid performance, thus providing technical support for the efficient development of oil and gas reservoirs. Drilling mud is widely used in drilling unconventional reservoirs such as shale oil and gas and tight sandstone. This application provides key parameter support for the interpretation of pressure mobility in these complex reservoirs, contributing to the efficient development of unconventional oil and gas resources.

[0018] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating a method for calculating the viscosity of mud filtrate according to an embodiment of this application is shown; Figures 2-5 This is a schematic diagram of a mud filtrate viscosity chart. Figure 6 A structural block diagram of a mud filtrate viscosity calculation device according to an embodiment of this application is shown; Figure 7 A schematic diagram of the structure of a computing device according to an embodiment of this application is shown. Detailed Implementation

[0020] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0021] Figure 1 A schematic flowchart of a method for calculating the viscosity of mud filtrate according to an embodiment of this application is shown, as follows: Figure 1 As shown, the method includes the following steps: Step S101: Obtain the viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions. Establish mud filtrate viscosity charts for each mud filtrate type based on the mud filtrate viscosity charts. Determine the influence of temperature and pressure on mud filtrate viscosity based on the mud filtrate viscosity charts. Based on the influence, construct corresponding mud filtrate viscosity calculation models for each mud filtrate type. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable.

[0022] Specifically, mud filtrate samples of various types were obtained. Mud filtrate type refers to the classification system of liquid phase filtrate precipitated under drilling mud filtration loss, based on the mud base fluid system. It can generally be divided into two categories: water-based mud filtrate formed using an aqueous base fluid and oil-based mud filtrate formed using an oil base fluid. In this embodiment, mud filtrate samples were mainly obtained from two different wells, designated BY6-XX and HZ19-XX, respectively. The mud filtrate sample from BY6-XX was of the water-based type, while the mud filtrate sample from HZ19-XX was of the oil-based type.

[0023] Then, under multiple temperature and pressure conditions, the viscosity values ​​of mud filtrate samples for each type of mud filtrate were determined using a viscosity measuring device. The experimental temperatures covered a wide range from room temperature to high temperature, for example, 25°C, 50°C, 75°C, 100°C, 125°C, 150°C, and 175°C. The experimental pressures covered a wide range from atmospheric pressure to high pressure, for example, atmospheric pressure, 2000 psi, 4000 psi, 6000 psi, 8000 psi, and 10000 psi.

[0024] Viscometers capable of stable operation under high temperature and high pressure conditions are preferred for viscosity measurement. For example, an oscillating high-temperature and high-pressure online viscometer can be used. This type of viscometer measures viscosity based on the oscillation principle, generating oscillations in the fluid through a sensor and measuring changes in oscillation damping or frequency to calculate the fluid viscosity. This viscometer has a range of 0–10 mPa·s and an accuracy of 0.001 mPa·s. During measurement, the temperature of the mud filtrate sample is first stabilized to a set value. Then, the sample is injected into the viscometer sample cell using a pressure pump. The system pressure is adjusted using a back pressure valve to meet experimental requirements, and the viscosity value is recorded. Measurements are repeated multiple times (e.g., three times) under each temperature and pressure condition, and the arithmetic mean of all measurements is taken as the effective mud filtrate viscosity under that temperature and pressure condition.

[0025] The viscosity values ​​of two mud filtrate samples were measured at 25~175℃ and atmospheric pressure~10000 psi, as shown in Table 1.

[0026] Table 1: Measurement data of mud filtrate viscosity under different temperature and pressure conditions

[0027] Based on the mud filtrate viscosity measured under various temperature and pressure conditions, a mud filtrate viscosity chart corresponding to each mud filtrate type was plotted, as follows: Figures 2-5 As shown, where, Figure 2 This is a graph showing the change in mud filtrate viscosity as a function of pressure in well BY6-XX. Figure 3This is a graph showing the viscosity of the mud filtrate from well HZ19-XX as a function of pressure. Figure 4 This is a graph showing the viscosity of the mud filtrate from well BY6-XX as a function of temperature. Figure 5 This is a graph showing the viscosity of mud filtrate from well HZ19-XX as a function of temperature. Mud filtrate viscosity charts are graphical representations of temperature and pressure as variables, with viscosity as the response value. They are used to visually demonstrate how mud filtrate viscosity changes with temperature and pressure.

[0028] In one optional embodiment of this application, the mud filtrate viscosity chart includes at least one of the following plotting methods: plotting multiple mud filtrate viscosity-temperature variation curves under different pressure conditions on the same coordinate system, with temperature as the abscissa and mud filtrate viscosity as the ordinate, such as... Figure 4 and Figure 5 As shown, this method allows for a direct comparison of the viscosity variation trend of the same type of mud filtrate under different pressure conditions with temperature; and / or, by plotting pressure as the abscissa and mud filtrate viscosity as the ordinate on the same coordinate system, multiple viscosity-pressure variation curves of mud filtrate under different temperature conditions can be drawn, such as... Figure 2 and Figure 3 As shown, this method allows for a direct comparison of the viscosity variation trend of the same type of mud filtrate under different temperature conditions with pressure.

[0029] After establishing a mud filtrate viscosity chart, the influence of temperature and pressure on the mud filtrate viscosity can be determined based on the chart. Specifically, by comparing and analyzing different curves in the mud filtrate viscosity chart, the individual effects of temperature and pressure on the mud filtrate viscosity, as well as the extent of those effects, can be determined.

[0030] On the one hand, by comparing the viscosity-temperature change curves of mud filtrate under the same pressure conditions, the influence of temperature on the viscosity of mud filtrate can be determined. Figure 4 and Figure 5 As shown in the mud filtrate viscosity chart, under constant pressure, the mud filtrate viscosity decreases with increasing temperature. That is, as the temperature increases, the mud filtrate viscosity of mud filtrate samples of all mud filtrate types shows a significant decreasing trend, indicating that temperature has a dominant influence on mud filtrate viscosity.

[0031] On the other hand, by comparing the viscosity-pressure change curves of mud filtrate under the same temperature conditions, the influence of pressure on mud filtrate viscosity can be determined. Figure 2 and Figure 3As shown in the mud filtrate viscosity chart, under constant temperature conditions, the mud filtrate viscosity increases with increasing pressure. That is, as the pressure increases, the mud filtrate viscosity of mud filtrate samples of each mud filtrate type shows a slight upward trend, indicating that pressure has a slight positive regulatory effect on mud filtrate viscosity, but its influence is much smaller than that of temperature.

[0032] Among these factors, temperature has a dominant effect on the viscosity of the mud filtrate, with increased temperature leading to a significant decrease in viscosity; pressure has a secondary positive regulatory effect on the viscosity of the mud filtrate, with increased pressure leading to a slight increase in viscosity. Figures 2-5 As shown in the mud filtrate viscosity chart, although the viscosity values ​​of different types of mud filtrate are different, the overall trend of mud filtrate viscosity changes with temperature and pressure is basically the same.

[0033] After determining the influence of temperature and pressure on the viscosity of mud filtrate, a corresponding mud filtrate viscosity calculation model can be constructed for each type of mud filtrate based on the determined influence law. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as the dependent variable, used to quantitatively describe the change of mud filtrate viscosity with temperature and pressure. Different mud filtrate viscosity calculation models are constructed for different types of mud filtrate.

[0034] In one optional embodiment of this application, the corresponding mud filtrate viscosity calculation model can be constructed using the following method: Based on the influence law, an initial mathematical model was constructed. The initial mathematical model uses temperature as the variable and the viscosity of mud filtrate as the dependent variable, and includes multiple model parameters that correspond to pressure. Under each pressure condition, the initial mathematical model was fitted using the viscosity of the mud filtrate at different temperatures to obtain the model parameter values ​​under each pressure condition; Using the model parameter values ​​obtained by fitting under various pressure conditions, a functional relationship between each model parameter and pressure is established; Substituting the functional relationship between each model parameter and pressure into the initial mathematical model, we obtain the mud filtrate viscosity calculation model.

[0035] Specifically, based on the viscosity chart of mud filtrate, which shows that temperature has a dominant influence on viscosity and that viscosity decreases significantly with increasing temperature, an initial mathematical model is constructed. This initial mathematical model uses temperature as the independent variable and viscosity as the dependent variable, and includes multiple model parameters. These model parameters have a corresponding relationship with pressure, meaning that the values ​​of the model parameters differ under different pressure conditions.

[0036] For example, by expressing the viscosity η of the mud filtrate as an exponential function of temperature T, the following initial mathematical model can be constructed:

[0037] Where η is viscosity, T is temperature, a, b, and k are model parameters. a and b are related to pressure, and k is a fixed value related to the type of mud filtrate, which can be determined by fitting experimental data under different pressure conditions. A negative value for parameter k indicates that the viscosity of the mud filtrate decreases with increasing temperature.

[0038] Then, under each pressure condition, the initial mathematical model is fitted using multiple sets of experimental data on temperature and slurry viscosity measured under that pressure condition to obtain the model parameter values ​​for each pressure condition. The fitting can be performed using a nonlinear regression method, with the goal of minimizing the sum of squared residuals. For example, for multiple sets of temperature and slurry viscosity data measured under a certain constant pressure condition, the goal is to minimize the sum of the squared differences between the measured and calculated slurry viscosity values ​​at each data point. The model parameters are repeatedly adjusted and solved using an iterative optimization algorithm until the preset convergence condition is met, thereby obtaining the optimal model parameters a, b, and k under that pressure condition.

[0039] Taking the mud filtrate from well BY6-XX as an example, the viscosity-temperature curves (temperature points: 25℃, 50℃, 75℃, 100℃, 125℃, 150℃, 175℃) measured under pressure conditions of normal pressure, 2000psi, 4000psi, 6000psi, 8000psi, and 10000psi were subjected to nonlinear regression fitting using the method described above, and the values ​​of the model parameters a, b, and k under each pressure were obtained, as shown in Table 2.

[0040] Table 2: Model parameters for BY6-XX mud filtrate samples under different pressures

[0041] Similarly, taking the mud filtrate from well HZ19-XX as an example, following the same method, the viscosity-temperature curves (temperature points: 25℃, 50℃, 75℃, 100℃, 125℃, 150℃, 175℃) measured under pressures of normal pressure, 2000psi, 4000psi, 6000psi, 8000psi, and 10000psi were subjected to nonlinear regression fitting to obtain the values ​​of model parameters a, b, and k under each pressure, as shown in Table 3.

[0042] Table 3: Model parameters for HZ19-XX mud filtrate samples under different pressures

[0043] Next, using the model parameter values ​​fitted under various pressure conditions, a functional relationship between each model parameter and pressure is established. That is, the parameter values ​​fitted under each pressure are used as discrete data points, and regression analysis is performed with pressure as the independent variable and the parameter values ​​as the dependent variable to obtain a continuous functional expression of the model parameters changing with pressure.

[0044] For the mud filtrate sample from well BY6-XX: The fitted values ​​of 'a' at each pressure in Table 2 were correlated with the corresponding pressure P. The results show that parameter 'a' and pressure P have a good linear correlation. Using the minimum sum of squared residuals as the objective function, a univariate linear regression method was used to fit the data, yielding the linear relationship between 'a' and pressure P:

[0045] Using the same univariate linear regression method, regression calculations were performed on the parameter b fitted under each pressure to obtain the linear relationship between parameter b and pressure P:

[0046] Where P represents pressure, measured in psi.

[0047] For the model parameter k, the numerical fluctuation range of this parameter under different pressure conditions is -0.0179 to -0.0178, and the numerical variation is very small. Therefore, its arithmetic mean is taken as the fixed constant for this type of mud filtrate. For the mud filtrate of BY6-XX well, the value of parameter k is -0.01783.

[0048] For the mud filtrate sample from well HZ19-XX: The fitted values ​​of 'a' at each pressure in Table 3 were correlated with the corresponding pressure P. The results show that parameter 'a' and pressure P have a good linear correlation. Using the minimum sum of squared residuals as the objective function, a univariate linear regression method was used to fit the data, yielding the linear relationship between 'a' and pressure P:

[0049] Using the same univariate linear regression method, regression calculations were performed on the parameter b fitted under each pressure to obtain the linear relationship between parameter b and pressure P:

[0050] Where P represents pressure, measured in psi.

[0051] For the model parameter k, the numerical fluctuation range of this parameter under different pressure conditions is -0.0192 to -0.0191, and the numerical change is very slight. Therefore, its arithmetic mean is taken as the fixed constant for this type of mud filtrate. For the mud filtrate of well HZ19-XX, the value of parameter k is -0.01918.

[0052] Finally, by substituting the established functional relationships between the model parameters and pressure into the initial mathematical model, a complete mud filtrate viscosity calculation model can be obtained. This mud filtrate viscosity calculation model uses temperature T and pressure P as input variables and mud filtrate viscosity η as the output result, in the form η=f(temperature T, pressure P), thus realizing the quantitative calculation of the change of mud filtrate viscosity with temperature and pressure.

[0053] Using the above methods, a corresponding mud filtrate viscosity calculation model can be constructed for each type of mud filtrate, forming a model library for multiple mud filtrate types. In practical applications, only the type of mud filtrate in the well to be calculated needs to be determined, and the corresponding mud filtrate viscosity calculation model can be called. Combined with downhole measured temperature and pressure data, the mud filtrate viscosity under the current temperature and pressure conditions can be calculated quickly and accurately.

[0054] In this embodiment, the mud filtrate viscosity calculation model based on temperature-pressure relationship can be integrated into the pressure flow interpretation process of the cable formation testing instrument to realize real-time calculation of mud filtrate viscosity under downhole high temperature and high pressure conditions.

[0055] To verify the accuracy of the constructed mud filtrate viscosity calculation model, the experimental temperature and pressure under each temperature and pressure condition in Table 1 were substituted into the above model to calculate the corresponding mud filtrate viscosity values, and compared with the experimentally measured values, as shown in Tables 4 and 5.

[0056] Table 4 shows the calculated viscosity of the mud filtrate.

[0057] Table 5 shows the relative deviations between calculated and experimental values.

[0058] For the mud filtrate samples from well BY6-XX: The experimental temperatures and pressures under 42 sets of conditions, ranging from 25℃ to 175℃ and from atmospheric pressure to 10000psi, were substituted into the corresponding mud filtrate viscosity calculation model to obtain the calculated mud filtrate viscosity values, which were then compared with the experimentally measured values. The results show that the maximum relative deviation between the calculated and experimental mud filtrate viscosity values ​​from well BY6-XX was 0.86%, the minimum was 0, and the average relative deviation was 0.26%.

[0059] For the mud filtrate samples from well HZ19-XX: The experimental temperatures and pressures under 42 sets of conditions, ranging from 25℃ to 175℃ and from atmospheric pressure to 10000psi, were substituted into the corresponding mud filtrate viscosity calculation model to obtain the calculated mud filtrate viscosity values, which were then compared with the experimentally measured values. The results show that the maximum relative deviation between the calculated and experimental mud filtrate viscosity values ​​from well HZ19-XX was 0.81%, the minimum was 0, and the average relative deviation was 0.26%.

[0060] Based on the above verification results, under a total of 84 temperature and pressure conditions for the two types of mud filtrate, the maximum relative deviation between the calculated and experimental values ​​did not exceed 0.86%, and the average relative deviation was 0.26%. This fully demonstrates that the mud filtrate viscosity calculation model constructed in this invention has high reliability and high prediction accuracy. It can be reliably used for accurate prediction of downhole mud filtrate viscosity, which helps to improve the interpretation accuracy of formation mobility and permeability. It has important application value for drilling fluid performance optimization and efficient oil and gas reservoir development.

[0061] Step S102: Obtain the mud filtrate type, current downhole temperature, and current downhole pressure of the well to be calculated. Substitute the current downhole temperature and current downhole pressure into the mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculate the mud filtrate viscosity of the well to be calculated.

[0062] Obtain the mud filtrate type of the well to be calculated, wherein the mud filtrate type of the well to be calculated is any one of the multiple mud filtrate types for which a mud filtrate viscosity calculation model has been established in the aforementioned model building stage.

[0063] During cable formation testing operations, after the cable formation testing instrument is lowered to the target depth, its downhole sensors can simultaneously measure the current downhole temperature and pressure at that depth. This data will serve as input parameters for the mud filtrate viscosity calculation model, used to calculate the mud filtrate viscosity under the current downhole temperature and pressure conditions. It is understood that temperature and pressure can also be obtained from other downhole measurement tools, as long as they can provide measured data of the current downhole temperature and pressure conditions.

[0064] Based on the mud filtrate type of the well to be calculated, the corresponding model is matched from a pre-built viscosity calculation model for various mud filtrate types. For example, based on the mud filtrate type identifier of the well to be calculated, the mud filtrate viscosity calculation model corresponding to that type identifier is called from the model library.

[0065] By substituting the current downhole temperature and pressure into a mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, the mud filtrate viscosity of the well under the current temperature and pressure conditions can be calculated. The current downhole temperature and pressure may change with depth, so the mud filtrate viscosity can be calculated in real time.

[0066] Through the above methods, this application achieves real-time and accurate calculation of drilling mud filtrate viscosity under high-temperature and high-pressure downhole conditions, effectively improving the interpretation accuracy of formation mobility and permeability, reducing the uncertainty of reservoir evaluation, and optimizing drilling fluid performance, thus providing technical support for the efficient development of oil and gas reservoirs. Drilling mud is widely used in drilling unconventional reservoirs such as shale oil and gas and tight sandstone. This application provides key parameter support for the interpretation of pressure mobility in these complex reservoirs, contributing to the efficient development of unconventional oil and gas resources.

[0067] Figure 6 A structural block diagram of a mud filtrate viscosity calculation device according to an embodiment of this application is shown, as follows: Figure 6 As shown, the device includes: The chart creation module 601 is suitable for obtaining the viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions, and creating mud filtrate viscosity charts corresponding to each mud filtrate type based on the mud filtrate viscosity. The model building module 602 is suitable for determining the influence of temperature and pressure on the viscosity of mud filtrate based on the mud filtrate viscosity chart, and constructing a corresponding mud filtrate viscosity calculation model for each type of mud filtrate according to the influence law. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable. The calculation module 603 is adapted to obtain the mud filtrate type, current downhole temperature and current downhole pressure of the well to be calculated, and substitute the current downhole temperature and current downhole pressure into the mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculate the mud filtrate viscosity of the well to be calculated.

[0068] Optionally, the mud filtrate viscosity chart includes at least one of the following plotting methods: plotting multiple mud filtrate viscosity-temperature variation curves under different pressure conditions in the same coordinate system with temperature as the abscissa and mud filtrate viscosity as the ordinate; and / or plotting multiple mud filtrate viscosity-pressure variation curves under different temperature conditions in the same coordinate system with pressure as the abscissa and mud filtrate viscosity as the ordinate.

[0069] Optionally, the model building module is further adapted to: determine the influence law of temperature on the viscosity of mud filtrate by comparing the viscosity-temperature change curves of mud filtrate under the same pressure conditions: under constant pressure conditions, the viscosity of mud filtrate decreases as the temperature increases; Based on the comparison of the viscosity-pressure change curves of mud filtrate under the same temperature conditions, the influence law of pressure on mud filtrate viscosity is determined as follows: under constant temperature conditions, the viscosity of mud filtrate increases with increasing pressure.

[0070] Optionally, the model building module is further adapted to: construct an initial mathematical model based on the influence law, wherein the initial mathematical model takes temperature as the variable and mud filtrate viscosity as the dependent variable, and includes multiple model parameters that correspond to pressure; Under each pressure condition, the initial mathematical model was fitted using the viscosity of the mud filtrate at different temperatures to obtain the model parameter values ​​under each pressure condition; Using the model parameter values ​​obtained by fitting under various pressure conditions, a functional relationship between each model parameter and pressure is established; Substituting the functional relationship between each model parameter and pressure into the initial mathematical model, we obtain the mud filtrate viscosity calculation model.

[0071] Optionally, the initial mathematical model is:

[0072] Where η is viscosity, T is temperature, a, b and k are model parameters, a and b are related to pressure, and k is a fixed value related to the type of mud filtrate.

[0073] Optionally, if the mud filtrate type is water-based mud filtrate, then the relationship between model parameters a and b and pressure is:

[0074] If the mud filtrate type is oil-based mud filtrate, then the relationship between model parameters a and b and pressure is:

[0075] Where P represents pressure.

[0076] The descriptions of the above modules refer to the corresponding descriptions in the method embodiments, and will not be repeated here.

[0077] This application enables real-time and accurate calculation of drilling mud filtrate viscosity under high-temperature and high-pressure downhole conditions, effectively improving the interpretation accuracy of formation mobility and permeability, reducing the uncertainty of reservoir evaluation, and optimizing drilling fluid performance, thus providing technical support for the efficient development of oil and gas reservoirs. Drilling mud is widely used in drilling unconventional reservoirs such as shale oil and gas and tight sandstone. This application provides key parameter support for the interpretation of pressure mobility in these complex reservoirs, contributing to the efficient development of unconventional oil and gas resources.

[0078] This application provides a non-volatile computer storage medium storing at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the mud filtrate viscosity calculation method in any of the above method embodiments.

[0079] This application provides a computer program product, which includes at least one executable instruction or computer program that enables a processor to perform the operation corresponding to the mud filtrate viscosity calculation method in any of the above method embodiments.

[0080] Figure 7 The diagram shows a structural schematic of a computing device according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the computing device.

[0081] like Figure 7 As shown, the computing device may include: a processor 702, a communication interface 704, a memory 706, and a communication bus 708.

[0082] The processor 702, communication interface 704, and memory 706 communicate with each other via communication bus 708.

[0083] The communication interface 704 is used to communicate with other network elements such as clients or other servers.

[0084] The processor 702 is used to execute program 710, specifically to execute the relevant steps in the above-described mud filtrate viscosity calculation method embodiment.

[0085] Specifically, program 710 may include program code that includes computer operation instructions.

[0086] The processor 702 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computing device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0087] Memory 706 is used to store program 710. Memory 706 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0088] Specifically, program 710 can be used to cause processor 702 to execute the mud filtrate viscosity calculation method in any of the above method embodiments. The specific implementation of each step in program 710 can be found in the corresponding descriptions of the steps and units in the above mud filtrate viscosity calculation method embodiments, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described equipment and modules can be referred to the corresponding process descriptions in the foregoing method embodiments, and will not be repeated here.

[0089] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the teachings herein. The required structure for constructing such systems is apparent from the above description. Furthermore, this application is not directed to any particular programming language. It should be understood that the content of this application described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of this application.

[0090] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0091] Similarly, it should be understood that, in order to streamline this disclosure and aid in understanding one or more of the various aspects of the invention, in the above description of exemplary embodiments of the present application, various features of the present application are sometimes grouped together into a single embodiment, figure, or description thereof.

[0092] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying abstract and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying abstract and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0093] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of this application and form different embodiments.

[0094] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components according to the embodiments of this application. This application can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

Claims

1. A method for calculating the viscosity of mud filtrate, characterized in that, The method includes: The viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions was obtained. Based on the viscosity of the mud filtrate, a mud filtrate viscosity chart corresponding to each mud filtrate type was established. Based on the mud filtrate viscosity chart, the influence of temperature and pressure on mud filtrate viscosity was determined. Based on the influence, a corresponding mud filtrate viscosity calculation model was constructed for each mud filtrate type. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable. Obtain the mud filtrate type, current downhole temperature, and current downhole pressure of the well to be calculated. Substitute the current downhole temperature and current downhole pressure into the mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculate the mud filtrate viscosity of the well to be calculated.

2. The method for calculating the viscosity of mud filtrate according to claim 1, characterized in that, The mud filtrate viscosity chart includes at least one of the following plotting methods: plotting multiple mud filtrate viscosity-temperature variation curves under different pressure conditions in the same coordinate system with temperature as the abscissa and mud filtrate viscosity as the ordinate; and / or plotting multiple mud filtrate viscosity-pressure variation curves under different temperature conditions in the same coordinate system with pressure as the abscissa and mud filtrate viscosity as the ordinate.

3. The method for calculating the viscosity of mud filtrate according to claim 2, characterized in that, The step of determining the influence of temperature and pressure on the viscosity of mud filtrate based on the mud filtrate viscosity chart further includes: Based on the comparison of the viscosity-temperature change curves of mud filtrate under the same pressure conditions, the influence law of temperature on mud filtrate viscosity is determined as follows: under constant pressure conditions, the viscosity of mud filtrate decreases as the temperature increases. Based on the comparison of the viscosity-pressure change curves of mud filtrate under the same temperature conditions, the influence law of pressure on mud filtrate viscosity is determined as follows: under constant temperature conditions, the viscosity of mud filtrate increases with increasing pressure.

4. The method for calculating the viscosity of mud filtrate according to any one of claims 1-3, characterized in that, The step of constructing a corresponding mud filtrate viscosity calculation model for each type of mud filtrate based on the aforementioned influence law further includes: Based on the aforementioned influence patterns, an initial mathematical model is constructed. This initial mathematical model uses temperature as the variable and mud filtrate viscosity as the dependent variable, and includes multiple model parameters that correspond to pressure. Under each pressure condition, the initial mathematical model was fitted using the viscosity of the mud filtrate at different temperatures to obtain the model parameter values ​​under each pressure condition; Using the model parameter values ​​obtained by fitting under various pressure conditions, a functional relationship between each model parameter and pressure is established. Substituting the functional relationship between the model parameters and pressure into the initial mathematical model, the mud filtrate viscosity calculation model is obtained.

5. The method for calculating the viscosity of mud filtrate according to claim 4, characterized in that, The initial mathematical model is as follows: Where η is viscosity, T is temperature, a, b and k are model parameters, a and b are related to pressure, and k is a fixed value related to the type of mud filtrate.

6. The method for calculating the viscosity of mud filtrate according to claim 5, characterized in that, If the mud filtrate type is water-based mud filtrate, then the relationship between model parameters a and b and pressure is: If the mud filtrate type is oil-based mud filtrate, then the relationship between model parameters a and b and pressure is: Where P represents pressure.

7. A mud filtrate viscosity calculation device, characterized in that, The device includes: The chart creation module is suitable for obtaining the viscosity of mud filtrate samples of various mud filtrate types under different temperature and pressure conditions, and creating mud filtrate viscosity charts corresponding to each mud filtrate type based on the mud filtrate viscosity. The model building module is adapted to determine the influence of temperature and pressure on the viscosity of mud filtrate based on the mud filtrate viscosity chart, and to build a corresponding mud filtrate viscosity calculation model for each type of mud filtrate based on the influence law. The mud filtrate viscosity calculation model is a functional relationship with temperature and pressure as independent variables and mud filtrate viscosity as dependent variable. The calculation module is adapted to obtain the mud filtrate type, current downhole temperature, and current downhole pressure of the well to be calculated, and substitute the current downhole temperature and current downhole pressure into the mud filtrate viscosity calculation model that matches the mud filtrate type of the well to be calculated, and calculate the mud filtrate viscosity of the well to be calculated.

8. A computer device, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation corresponding to the mud filtrate viscosity calculation method as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores at least one executable instruction, which causes the processor to perform the operation corresponding to the mud filtrate viscosity calculation method as described in any one of claims 1-6.

10. A computer program product, characterized in that, It includes at least one executable instruction that causes the processor to perform the operation corresponding to the mud filtrate viscosity calculation method as described in any one of claims 1-6.

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