阅读说明：本技术 利用地震资料确定Russell流体因子的方法及系统 (Method and system for determining Russell fluid factor by utilizing seismic data ) 是由 张世鑫 杜向东 韩文明 孙林洁 李欣 于 2020-12-24 设计创作，主要内容包括：本发明涉及一种利用地震资料确定Russell流体因子的方法及系统,其中,所述方法包括以下步骤：1)先进行叠前地震角度道集的解释性处理,再结合地层速度模型进行叠前地震角度道集的分角度叠加,获得小、中、大角度叠加的分角度地震数据体；2)提取小、中、大分角度地震数据体的子波,在地层层位框架约束下构建小、中、大角度的RMD-EI模型,利用低通滤波处理得到参与反演的低频模型,基于小、中、大分角度地震数据体开展RMD-EI反演,最终获得小、中、大角度的RMD-EI的反演结果；3)对获得的小、中、大角度的RMD-EI反演结果进行对数处理,结合测井统计信息构建Russell流体因子的求解方程,求解方程获得最终的Russell流体因子数据体。本发明能够满足实际生产中储层烃类检测的需求,可靠性高。(The invention relates to a method and a system for determining Russell fluid factors by utilizing seismic data, wherein the method comprises the following steps: 1) firstly, performing explanatory processing on a prestack seismic angle gather, and then performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume; 2) extracting wavelets of the small, medium and large differential angle seismic data volumes, constructing small, medium and large angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by utilizing low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining the inversion results of the small, medium and large angle RMD _ EI; 3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body. The invention can meet the requirement of reservoir hydrocarbon detection in actual production and has high reliability.)

1. A method for determining Russell fluid factors using seismic data, comprising the steps of:

1) acquiring data of a prestack seismic angle gather and a stratum velocity model, performing explanatory processing on the prestack seismic angle gather, and performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume;

2) calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI curves, extracting wavelets of small, medium and large differential angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining small, medium and large-angle RMD _ EI inversion results;

3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.

2. Method according to claim 1, characterized in that said step 1) comprises the following sub-steps:

1.1) acquiring data of pre-stack seismic angle gather data and stratum velocity model data;

1.2) carrying out random noise removal and seismic homophase axis leveling treatment on the pre-stack seismic angle gather data;

1.3) carrying out sub-angle superposition processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes.

3. Method according to claim 2, characterized in that said step 1.3) comprises the following sub-steps:

1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, and converting the offset and the incident angle by using the depth of a target layer and the maximum offset length according to the following conversion basis: the ratio of half of the offset distance to the depth is the tangent value of the incident angle;

1.3.2) comprehensively analyzing multiple factors of the theoretical maximum incident angle and the coverage times, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;

1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form small, medium and large-angle seismic data volumes.

4. Method according to claim 1, characterized in that said step 2) comprises the following sub-steps:

2.1) calculating small-angle, medium-angle and large-angle RMD _ EI parameters by using a logging curve, and obtaining small-angle, medium-angle and large-angle RMD _ EI parameter curves;

2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large differential angle seismic data volumes, and calibrating the time depths of the small, medium and large differential angle seismic data volumes;

2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;

2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;

and 2.5) performing elastic impedance inversion of the RMD _ EI by using small-angle, medium-angle and large-branch-angle seismic data volumes and using a constraint sparse pulse inversion method to obtain the inversion results of the RMD _ EI at small angle, medium angle and large angle.

5. Method according to claim 4, characterized in that said step 2.1) comprises the following sub-steps:

2.1.1) calculating Russell fluid factor F by formula (1) using compressional velocity, shear velocity and density log data_RCalculating the shear modulus mu through a formula (2);

in the formula, V_pRepresenting the velocity of longitudinal waves; v_sRepresents the shear wave velocity; ρ represents the rock density;represents the square of the dry rock compressional-shear velocity ratio;

μ＝ρV_s ² (2)

in the formula, V_sRepresents the shear wave velocity; ρ represents the rock density;

2.1.2) Russell-based fluid factor F_RAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:

in the formula, F_RRepresents Russell fluid factor; μ represents a shear modulus; ρ represents the rock density; θ represents an incident angle; representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; f_R0、μ₀And ρ₀Defined as the average of Russell fluid factor, shear modulus and density parameters, respectively; RMD _ EI₀Is the normalization factor.

6. Method according to claim 4, characterized in that said step 3) comprises the following sub-steps:

3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);

3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);

wherein t represents time; theta₁Represents a small angle of incidence; theta₂Represents the medium angle of incidence; theta₃Represents a large angle of incidence;

3.3) solving the equation set constructed in the step 3.2), obtaining a result, and performing exponential operation on the result to obtain final Russell fluid factor data.

7. A system for determining Russell fluid factor using seismic data, comprising:

the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;

the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the layer position constraint, extracting small, medium and large-angle seismic wavelets, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;

and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.

Technical Field

The invention relates to the technical field of geophysical exploration, in particular to a method and a system for determining Russell fluid factors by utilizing seismic data.

Background

The fluid indication parameters are the main identification basis for detecting underground reservoir hydrocarbons, and the pre-stack seismic inversion is the main technical means for calculating the fluid indication parameters. In order to improve the accuracy of hydrocarbon detection, researchers have been dedicated to improving the hydrocarbon identification sensitivity of fluid indicator parameters and increasing the reliability of the calculation method, but there are still many problems to be solved, which are limited by the complexity of the underground medium and the pathological solution of the seismic inversion method.

The Russell fluid factor is a fluid indication parameter which is proposed by Russell and others in 2003 based on a Biot-Gassmann pore elastic medium theory, and the elastic parameter can well reduce oil-water identification artifacts caused by reservoir pore heterogeneity, so that the underground medium oil-gas content can be reliably indicated, and the Russell fluid factor has sensitive reservoir hydrocarbon identification sensitivity. At present, pre-stack earthquakes are mostly taken as main bodies in the related industry, longitudinal wave velocity, transverse wave velocity and density parameters are calculated by adopting an AVO synchronous inversion method, and then three elastic parameters are further utilized to calculate Russell fluid factors. With the gradual turning of an oil and gas exploration target to deep, deep water and lithology targets, the conventional Russell fluid factor calculation method is difficult to meet the requirements of actual production, particularly for deep water and deep targets under the condition of few wells, the general quality of pre-stack seismic gather data of the targets is poor, the number of well data is limited by the condition of less number and the like, the accuracy of longitudinal wave velocity, transverse wave velocity and density parameters of pre-stack AVO synchronous inversion is low, the reliability of indirectly calculated Russell fluid factors is further influenced, and the requirements of reservoir hydrocarbon detection in actual production are difficult to meet.

Disclosure of Invention

In view of the above problems, the present invention aims to provide a method and a system for determining Russell fluid factors by using seismic data, which have high reliability and can meet the requirement of reservoir hydrocarbon detection in actual production.

In order to achieve the purpose, the invention adopts the following technical scheme:

the method for determining Russell fluid factor by using seismic data comprises the following steps:

1) acquiring data of a prestack seismic angle gather and a stratum velocity model, performing explanatory processing on the prestack seismic angle gather, and performing sub-angle stacking on the prestack seismic angle gather by combining a stratum velocity model to obtain a small, medium and large angle stacked sub-angle seismic data volume;

2) calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI curves, extracting wavelets of small, medium and large differential angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large differential angle seismic data volumes, and finally obtaining small, medium and large-angle RMD _ EI inversion results;

3) and carrying out logarithm processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.

The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 1):

1.1) acquiring data of pre-stack seismic angle gather data and stratum velocity model data;

1.2) carrying out random noise removal and seismic homophase axis leveling treatment on the pre-stack seismic angle gather data;

1.3) carrying out sub-angle superposition processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes.

The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 1.3):

1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, and converting the offset and the incident angle by using the depth of a target layer and the maximum offset length according to the following conversion basis: the ratio of half of the offset distance to the depth is the tangent value of the incident angle;

1.3.2) comprehensively analyzing multiple factors of the theoretical maximum incident angle and the coverage times, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;

1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form small, medium and large-angle seismic data volumes.

The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 2):

2.1) calculating small-angle, medium-angle and large-angle RMD _ EI parameters by using a logging curve, and obtaining small-angle, medium-angle and large-angle RMD _ EI parameter curves;

2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large differential angle seismic data volumes, and calibrating the time depths of the small, medium and large differential angle seismic data volumes;

2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;

2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;

and 2.5) performing elastic impedance inversion of the RMD _ EI by using small-angle, medium-angle and large-branch-angle seismic data volumes and using a constraint sparse pulse inversion method to obtain the inversion results of the RMD _ EI at small angle, medium angle and large angle.

The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 2.1):

2.1.1) calculating Russell fluid factor F by formula (1) using compressional velocity, shear velocity and density log data_RCalculating the shear modulus mu through a formula (2);

in the formula, V_pRepresenting the velocity of longitudinal waves; v_sRepresents the shear wave velocity; ρ represents the rock density;representing the square of the dry rock compressional-to-shear velocity ratio.

μ＝ρV_s ² (2)

In the formula, V_sRepresents the shear wave velocity; ρ represents the rock density;

2.1.2) Russell-based fluid factor F_RAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:

in the formula, F_RRepresents Russell fluid factor; μ represents a shear modulus; ρ represents the rock density; θ represents an incident angle; representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; f_R0、μ₀And ρ₀Defined as the average of Russell fluid factor, shear modulus and density parameters, respectively; RMD _ EI₀Is the normalization factor.

The method for determining Russell fluid factor by using seismic data preferably comprises the following sub-steps of step 3):

3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);

3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);

wherein t represents time; theta₁Represents a small angle of incidence; theta₂Represents the medium angle of incidence; theta₃Represents a large angle of incidence;

3.3) solving the equation set constructed in the step 3.2), obtaining a result, and performing exponential operation on the result to obtain final Russell fluid factor data.

The invention discloses a system for determining Russell fluid factor by utilizing seismic data, which comprises the following components:

the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;

the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the layer position constraint, extracting small, medium and large-angle seismic wavelets, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;

and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.

Due to the adoption of the technical scheme, the invention has the following advantages:

according to the invention, on the basis of improving the AVO (amplitude versus offset) characterization of the pre-stack earthquake by using the pre-stack sub-angle stacking, the direct calculation of the Russell fluid factor is realized by using the pre-stack elastic impedance inversion, the conventional method that the longitudinal wave velocity, the transverse wave velocity and the density are obtained firstly and then the accumulated error introduced by the Russell fluid factor is calculated indirectly is avoided, and the calculation accuracy of the Russell fluid factor is improved. Therefore, the method can improve the hydrocarbon detection reliability of the complex geological target, particularly the deep water reservoir and the deep reservoir under the condition of few wells, and provides technical support for solving the hydrocarbon detection problem of the complex reservoir.

Drawings

FIG. 1 is a schematic flow diagram of a method of the present invention for calculating Russell fluid factor using seismic data;

FIG. 2 is a schematic flow chart of the present invention for obtaining a sub-angle seismic data volume;

FIG. 3 is a schematic diagram of a process for obtaining RMD _ EI data according to the present invention;

FIG. 4 is a schematic flow chart of the present invention for obtaining a Russell fluid factor based on RMD _ EI;

FIG. 5 is a schematic flow diagram of a Russell fluid factor calculation system in accordance with the present invention.

Detailed Description

The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the objects, features and advantages of the invention can be more clearly understood. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the present invention, but are merely intended to illustrate the spirit of the technical solution of the present invention.

As shown in FIG. 1, the present invention provides a method for determining Russell fluid factor using seismic data, comprising the steps of:

1) data such as a prestack seismic angle gather and stratum velocity model data are obtained, the prestack seismic angle gather is subjected to explanatory processing, and then the stratum velocity model data are combined to carry out sub-angle stacking of the prestack seismic angle gather, so that a small, medium and large angle stacked sub-angle seismic data body is obtained.

As shown in fig. 2, the specific process of step 1) is as follows:

1.1) acquiring data of a prestack seismic angle trace set and stratum velocity model data;

1.2) carrying out treatments such as random noise removal, seismic in-phase axis leveling and the like on the pre-stack seismic angle gather;

1.3) carrying out sub-angle stacking processing on the pre-stack seismic angle gather to obtain small, medium and large angle sub-angle seismic data volumes, wherein the specific process is as follows:

1.3.1) converting seismic data from a time domain to a depth domain based on a stratum velocity model, converting the offset and the incident angle by using the depth of a target layer and the maximum offset length, and taking the conversion as the tangent value of the incident angle according to the ratio of half of the offset to the depth;

1.3.2) comprehensively analyzing multiple factors such as the theoretical maximum incident angle, the covering times and the like, determining the interval of the effective incident angle of the prestack seismic angle gather, carrying out trisection on the interval of the incident angle, and determining the median of each trisection range as the numerical values of a small angle, a medium angle and a large angle according to the sequence from the small angle to the large angle;

1.3.3) correspondingly stacking the pre-stack seismic angle gathers in the small-angle incidence angle equal-dividing range, correspondingly stacking the pre-stack seismic angle gathers in the medium-angle incidence angle equal-dividing range, and correspondingly stacking the pre-stack seismic angle gathers in the large-angle incidence angle equal-dividing range to form a small-angle, medium-angle and large-angle seismic data body.

2) Calculating small, medium and large-angle RMD _ EI parameters by using logging curve data, acquiring small, medium and large-angle RMD _ EI parameter curves, extracting wavelets of small, medium and large-angle sub-angle seismic data volumes, constructing small, medium and large-angle RMD _ EI models under the constraint of a stratum horizon frame, obtaining low-frequency models participating in inversion by using low-pass filtering processing, carrying out RMD _ EI inversion based on the small, medium and large-angle sub-angle seismic data volumes, and finally obtaining small, medium and large-angle inversion results of the RMD _ EI;

as shown in fig. 3, the specific process of step 2) is as follows:

2.1) calculating the RMD _ EI parameters of the small angle, the medium angle and the large angle by using the logging curve data, and obtaining the RMD _ EI parameter curves of the small angle, the medium angle and the large angle, wherein the specific process is as follows:

2.1.1) calculating Russell fluid factor F by using longitudinal wave velocity, transverse wave velocity and density logging curve data through formulas (1) and (2) respectively_RAnd shear modulus μ:

in the formula, V_pRepresenting the velocity of longitudinal waves; v_sRepresents the shear wave velocity; ρ represents the rock density;represents the square of the dry rock compressional-shear velocity ratio;

μ＝ρV_s ² (2)

in the formula, V_sRepresents the shear wave velocity; ρ represents the rock density;

2.1.2) Russell-based fluid factor F_RAnd a shear modulus mu, calculating the RMD _ EI parameters of a small angle, a medium angle and a large angle respectively through a formula (3), and obtaining RMD _ EI parameter curves of the small angle, the medium angle and the large angle respectively:

wherein θ represents an incident angle; representing the square of the velocity ratio of the longitudinal wave and the transverse wave of the saturated fluid rock; f_R0、μ₀And ρ₀Defined as Russell fluid factor, shear modulus and density, respectivelyAn average value of the parameter; RMD _ EI₀Is the normalization factor.

2.2) acquiring the time depth relation of the well drilling, extracting the seismic wavelets of the small, medium and large angle angular separation seismic data bodies, and carrying out time depth calibration on the small, medium and large angle angular separation seismic data bodies;

2.3) acquiring a seismic interpretation horizon, constructing a horizon frame, and realizing data interpolation of the RMD _ EI parameters calculated in the step 2.1) by using a global kriging interpolation algorithm under the constraint of the horizon frame to obtain a corresponding RMD _ EI model data volume;

2.4) filtering the small-angle, medium-angle and large-angle RMD _ EI model data volume obtained in the step 2.3) through a 0-10Hz low-pass filter to obtain a low-frequency model participating in inversion;

and 2.5) performing elastic impedance inversion of the RMD _ EI by using a constraint sparse pulse inversion method according to the sub-angle seismic data volumes of the small angle, the medium angle and the large angle to obtain the inversion results of the RMD _ EI of the small angle, the medium angle and the large angle.

And 3) carrying out logarithmic processing on the obtained RMD _ EI inversion results at small, medium and large angles, constructing a solution equation of the Russell fluid factor by combining logging statistical information, and solving the equation to obtain a final Russell fluid factor data body.

As shown in fig. 4, the specific process of step 3) is as follows:

3.1) carrying out logarithm operation on the small, medium and large angle RMD _ EI inversion result data obtained in the step 2.5);

3.2) constructing a solution equation set of the Russell fluid factor according to the formula (4);

wherein t represents time; theta₁Represents a small angle of incidence; theta₂Represents the medium angle of incidence; theta₃Indicating a large angle of incidence.

3.3) solving the equation set constructed in the step 3.2), and carrying out exponential operation on the result to obtain final Russell fluid factor data.

The invention also provides a system for calculating Russell fluid factor by using seismic data, which comprises:

the data input module is used for acquiring high-quality angle stacking seismic data, improving the quality of an angle gather by utilizing an explanatory preprocessing technology, and acquiring the sub-angle seismic data volumes of three angles after carrying out angle stacking processing of small, medium and large angles;

the RMD _ EI inversion module is used for acquiring small, medium and large-angle RMD _ EI data, acquiring a logging scale RMD _ EI curve based on the logging curve, acquiring a low-frequency model required by RMD _ EI inversion by using a global Krigin interpolation calculation method under the horizon constraint, extracting seismic wavelets of small, medium and large-angle-divided seismic data volumes, and performing small, medium and large-angle RMD _ EI inversion to acquire large-angle, medium and small-angle RMD _ EI data;

and the data output module is used for acquiring Russell fluid factor data, and constructing a solution equation of the Russell fluid factor by utilizing the RMD _ EI data of the large angle, the medium angle and the small angle to obtain the final Russell fluid factor.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.