Measurement while drilling fluidity correction method under multi-factor interaction

Abstract

The invention discloses a while-drilling pressure measurement fluidity correction method under a multi-factor interaction effect, and the method comprises the steps: constructing a while-drilling pressure measurement numerical simulation model of an anisotropic stratum inclined shaft, and deducing the model as a while-drilling pressure measurement finite element model of the stratum inclined shaft; performing stratum fluidity inversion analysis on the stratum inclined shaft pressure measurement while drilling finite element model, and identifying key factors influencing the logging pressure measurement while drilling fluidity based on an analysis result; carrying out numerical simulation on the basis of the identified key factors to obtain a pressure response result of the pressure measurement while drilling, analyzing formation fluidity characteristics under the interaction of the multiple factors, and further determining a fluidity response rule expression of the pressure measurement while drilling under the interaction of the multiple factors; and substituting key factor values in the actual measurement while drilling pressure measurement process into the corresponding while drilling pressure measurement fluidity response rule expression, and further calculating to obtain the while drilling pressure measurement fluidity of the vertical well, thereby realizing the correction of the while drilling pressure measurement fluidity. The method provided by the invention provides a theoretical basis and a technical support for the use of the pressure measuring instrument while drilling.

Description

Technical Field

[0001] This invention belongs to the field of numerical simulation technology of pressure measurement while drilling in deviated wells, and specifically relates to a method for correcting the flow rate of pressure measurement while drilling under the interaction of multiple factors. Background Technology

[0002] Formation pressure refers to the pressure exerted by fluids (including oil, gas, and water) existing in the pores of underground rocks. This parameter plays a crucial role in oil and gas drilling and development. Measurement-while-drilling (MWD) formation pressure sampling technology enables real-time formation pressure measurement and fluid sampling during drilling, primarily relying on the automated operation of downhole tools. After receiving the pressure measurement and sampling command via drilling fluid pressure pulses, the tool performs operations such as probe extension and setting, depressurization to recovery, and automatic unsealing. MWD technology effectively overcomes the problems of traditional methods, such as long drilling time, difficulty in adapting to highly deviated, horizontal, and extended-reach wells, and the susceptibility to stuck pipe, and has been widely applied in oilfields. While MWD instruments are frequently used to test formation pressure and calculate formation mobility in directional and highly deviated wells, the calculated mobility is often underestimated due to factors such as pumping mode, anisotropy, and well inclination. Therefore, it is necessary to conduct theoretical model research on MWD, identify the key factors affecting mobility inversion, and propose mobility correction methods.

[0003] There are generally two methods for establishing a test-while-drilling response model: analytical method and numerical simulation method.

[0004] Analytical methods refer to obtaining precise or approximate analytical expressions (i.e., closed-form solutions) for a problem through mathematical derivation, using mathematical formulas and theorems. The solution process is based on rigorous mathematical analysis, and the results are usually in explicit functional form. Previous research has explored the use of analytical methods to establish drilling pressure testing response models. Finneran et al., based on spherical flow theory and combined with novel drilling formation testing tools, conducted research on the pressure response of drilling formation testing, providing theoretical and technical support for reservoir evaluation. Banerjee et al., based on reasonable simplification assumptions, analyzed the impact of wellbore pressurization on the pressure response of drilling formation testing by performing continuous integral transformations on the governing equations and their related initial and boundary conditions. Yang Juesuan et al., using the unsteady gauging principle and formation flow analysis method, established theoretical and mathematical models for drilling formation pressure testing, respectively, and verified the accuracy of the models and the feasibility of the calculation methods through field applications. Ma Tianshou et al. established an analytical model of the pressure response, obtained analytical solutions through continuous integral transformations, and corrected the analytical solutions using heterogeneity, skin effect, pipeline storage effect, and pressurization effect. They also designed an experimental setup to verify the effectiveness of the analytical model. Ma Tianshou et al. established an analytical model of drilling formation pressure testing response considering dynamic drilling fluid intrusion and a formation pressure inversion algorithm, and verified them using a two-dimensional numerical model.

[0005] Numerical simulation refers to the use of numerical algorithms (such as the finite difference method and the finite element method) to approximate solutions and obtain numerical approximate solutions. Numerical simulation does not provide explicit formulas, but rather demonstrates the system behavior through numerical results. In terms of numerical simulation, Lee et al. built a comprehensive experimental setup to simulate the downhole environment. Based on the single-phase spherical flow analytical model, they considered the influence of two-phase oil-water flow around the well and conducted a finite element numerical simulation of two-phase flow during drilling formation testing. The experimental results showed a high degree of agreement with the calculated results. Di et al. used an oil-water two-phase finite element numerical simulation model for the wellbore environment with water-based mud to study the effects of mud cake quality and drilling fluid intrusion on pressurization and sampling of reservoirs with different permeabilities. Ma Tianshou et al. established a mathematical model of the pressure response of transversely isotropic formations under drilling formation testing under drilling fluid intrusion conditions based on the theory of flow through anisotropic porous media. They solved the model using the finite element method, verified the model by comparing it with the classical analytical solution, and analyzed the influence of permeability anisotropy, formation occurrence, pumping interval time, and pumping probe radius on the pressure response of formation testing during drilling.

[0006] Overall, analytical methods are suitable for idealized two-dimensional problems with simple boundaries, while numerical simulation methods are more suitable for three-dimensional problems with complex formation conditions. Currently, previous studies have rarely considered the combined effects of formation anisotropy, well inclination, temperature, and tool face, making them unsuitable for numerical simulations of pressure testing while drilling in deviated wells and for analyzing key factors. Summary of the Invention

[0007] To address the aforementioned shortcomings in the existing technology, the multi-factor interaction-based drilling pressure measurement and flowability correction method provided by this invention solves the problem that existing methods do not consider the comprehensive influence of multiple factors and are difficult to accurately calculate flowability values ​​based on drilling pressure measurement data.

[0008] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: a method for correcting drilling pressure measurement and mobility under the interaction of multiple factors, comprising the following steps:

[0009] S100. Construct a numerical simulation model of pressure measurement while drilling in anisotropic formation deviated wells and derive it into a finite element model of pressure measurement while drilling in formation deviated wells.

[0010] S200. Perform formation mobility inversion analysis on the formation deviated well logging-while-drilling pressure measurement finite element model, and identify the key factors affecting logging-while-drilling pressure measurement mobility based on the analysis results;

[0011] S300. Numerical simulation is performed based on the identified key factors to obtain the pressure response results of drilling pressure measurement. The formation mobility characteristics under the interaction of multiple factors are analyzed, and then the expression of the drilling pressure measurement mobility response law under the interaction of multiple factors is determined.

[0012] S400: Substitute the values ​​of key factors in the measured drilling pressure test process into the corresponding drilling pressure test flow rate response law expression, and then calculate the drilling pressure test flow rate of the vertical well to achieve drilling pressure test flow rate correction.

[0013] Furthermore, in step S100, the numerical simulation model of the anisotropic formation deviated well during drilling includes temperature field control equations and seepage field control equations.

[0014] The temperature field control equation is as follows:

[0015]

[0016] In the formula, This represents the overall density of saturated rock. This represents the equivalent specific heat capacity of saturated rock. Indicates temperature. Represents a time variable. Indicates pore fluid density. Indicates the specific heat capacity of a fluid. Represents the velocity vector of the pore fluid. This represents the equivalent thermal conductivity of saturated rock. Represents the gradient;

[0017] The governing equation for the seepage field is:

[0018]

[0019]

[0020] In the formula, Indicates the formation porosity. Indicates fluid pressure Indicates Darcy flow velocity, Indicates the porosity of the mud cake. This indicates the fluid pressure within the mud cake. Indicates the fluid velocity within the mud cake;

[0021] in:

[0022]

[0023]

[0024]

[0025] In the formula, , , , , , , , and This represents the permeability components in each direction of the wellbore in rectangular coordinates. , and Represents the three directions in the rectangular coordinate system of the wellbore. Indicates the viscosity of degassed crude oil at the ground. Indicates the density of degassed crude oil at the ground. Indicates the content of crude oil asphalt resin. The coefficient for crude oil volume is represented by a, and the coefficients a and b are empirical coefficients. Indicates the equivalent mud cake permeability. Indicates viscosity.

[0026] Furthermore, in step S100, the boundary conditions of the numerical simulation model for drilling pressure measurement in anisotropic formation deviated wells include initial conditions and boundary conditions.

[0027] The initial conditions are:

[0028]

[0029] In the formula, Indicates the original formation pressure. Indicates the initial formation temperature;

[0030] The boundary conditions are as follows:

[0031]

[0032]

[0033]

[0034] In the formula, represents the wellbore temperature, Indicates wellbore pressure, This indicates the permeability at the suction head. Indicates penetration rate. Indicates viscosity. This indicates the change in fluid volume within the pipeline. Indicates the pipeline storage volume. Indicates the radius of the suction probe. This represents the actual volume of formation fluid pumped by the suction probe at each moment; where, , This indicates the actual formation fluid drawn up by the suction probe. This indicates the amount of fluid volume change caused by pipeline storage.

[0035] Further, in step S100, the formation deviated well drilling pressure measurement finite element model is represented as follows:

[0036]

[0037]

[0038]

[0039] In the formula, Let λs represent the trial function of formation temperature, λs represent the thermal conductivity of the rock, and λf represent the thermal conductivity of the fluid. Represents a trial function of formation pore pressure. Indicates formation porosity. The trial function represents the fluid pressure in the mud cake. Indicates mud cake domain, Indicates stratigraphic domain, Indicates the boundary of the mud cake domain. Indicates the boundary of the stratigraphic domain. The unit normal vector representing the boundary. Represents the differential symbol. Indicates the viscosity of formation fluids. This represents the equivalent mud cake permeability.

[0040] Furthermore, step S100 also includes numerical simulation and indoor test verification of the formation deviated well drilling pressure measurement finite element model to verify the accuracy of the constructed model.

[0041] Further, step S200 includes the following sub-steps:

[0042] S201. Set the basic influencing factors for numerical simulation of the formation deviated well drilling pressure measurement finite element model, and use the control variable method to perform formation mobility inversion analysis under different basic influencing factors.

[0043] S202. Based on the formation mobility inversion analysis results, the dimensionless Spearman correlation analysis method was used to identify the key factors affecting logging-while-drilling pressure measurement mobility.

[0044] The key factors include well inclination angle, formation permeability anisotropy ratio, tool face, and formation-wellbore temperature.

[0045] Further, step S300 includes the following sub-steps:

[0046] S301. Based on the degree of formation mobility, three types of formations are defined: medium-high mobility formations, low mobility formations, and ultra-low mobility formations.

[0047] S302. Numerical simulations based on the interaction of key factors were conducted on the three types of fluidity formations to obtain the pressure response results of drilling pressure measurement.

[0048] S303. The area integral method is used to perform response surface analysis on the pressure response results of drilling pressure measurement to obtain the formation mobility characteristics under the interaction of multiple factors.

[0049] S304. Based on the formation mobility characteristics under multiple factors, determine the expression of the drilling pressure measurement mobility response law of three types of mobility formations under the interaction of multiple factors when parallel bedding plane.

[0050] Further, in step S304, the expressions for the drilling pressure measurement mobility response laws corresponding to medium-high mobility formations, low mobility formations, and ultra-low mobility formations are as follows:

[0051]

[0052]

[0053]

[0054] In the formula, This represents the flowability when the bedding plane is parallel to the surface. Indicates the inverted strata mobility. Indicates the anisotropy ratio of formation permeability. Indicates the inclination angle of the well. Indicates the tool face. This indicates the temperature difference between the formation and the wellbore.

[0055] Further, step S400 includes the following sub-steps:

[0056] S401. Determine the drilling pressure response rate of the deviated well based on the measured drilling pressure response data;

[0057] S402. Estimate the anisotropy ratio of formation permeability and the formation-wellbore temperature difference;

[0058] S403. Record the wellbore surface and tool face at each measuring point during drilling pressure testing;

[0059] S404. Substitute the measured flow rate during drilling, formation permeability anisotropy ratio, formation-wellbore temperature difference, well inclination surface, and tool face into the expression for the measured flow rate response law of the corresponding flow rate formation to calculate the flow rate when parallel to the bedding plane.

[0060] Among them, the pressure measurement and mobility during drilling in inclined wells corresponds to the inverted formation mobility in the expression of the pressure measurement and mobility during drilling response law;

[0061] S405. Calculate the pressure measurement flow rate of the vertical well based on the flow rate when the bedding plane is parallel.

[0062] Furthermore, in step S405, the vertical well drilling pressure measurement and flow rate... for:

[0063]

[0064] In the formula, The permeability of the transverse isotropic surface of anisotropic strata. This represents the permeability perpendicular to the transversely isotropic surface. Indicates viscosity. This represents the ratio of permeability in the direction parallel to the stratification plane to that perpendicular to the stratification plane. This represents the flowability when parallel to the bedding plane; where, .

[0065] The beneficial effects of this invention are as follows:

[0066] (1) Taking into account a variety of complex factors such as well inclination angle, permeability anisotropy ratio, drilling fluid intrusion, dynamic generation of mud cake and thermal coupling, a thermal coupling finite element numerical simulation model suitable for pressure measurement while drilling in deviated wells was established.

[0067] (2) A corresponding finite element numerical solution method was constructed and verified by combining indoor physical model experiments and field measurement data. The results show that the model has good effectiveness and accuracy.

[0068] (3) The effects of 11 single factors, including anisotropy ratio, well inclination angle, tool face, formation pressure, overbalance pressure, formation-wellbore temperature difference, tubing volume, pumping rate, pumping duration, probe radius, and probe shape, on the measurement-while-drilling pressure and mobility inversion were simulated using the finite element method. Dimensionless Spearman correlation analysis was used to identify the key factors affecting the measurement-while-drilling pressure and mobility inversion, including well inclination angle, permeability anisotropy ratio, tool face, and formation-wellbore temperature difference, providing data support for subsequent mobility correction.

[0069] (4) Formation mobility is divided into three categories: medium-high mobility, low mobility and ultra-low mobility. Taking into account the key factors affecting mobility calculation, the influence of multi-factor interaction on the logging-while-drilling pressure measurement mobility of the three types of formations is analyzed. The logging-while-drilling pressure measurement mobility correction under multi-factor interaction is realized, and the effectiveness of the method is verified by case studies, providing theoretical basis and technical support for the use of logging-while-drilling pressure measurement instruments. Attached Figure Description

[0070] Figure 1 The flowchart of the drilling pressure measurement and flow rate correction method provided by the present invention under the multi-factor interaction is shown.

[0071] Figure 2 The finite element geometric model of the inclined shaft provided for this invention.

[0072] Figure 3The drilling pressure measurement physical model experimental device provided by the present invention.

[0073] Figure 4 The physical model of the core sample for the drilling pressure measurement experiment provided by this invention.

[0074] Figure 5 Comparison of experimental results and numerical simulation results of the drilling pressure test model provided by this invention (two pressure point experiments).

[0075] Figure 6 The results of correlation analysis of factors affecting formation mobility calculation provided by this invention.

[0076] Figure 7 The present invention provides the influence law of multi-factor interaction on drilling pressure measurement mobility in medium- to high-mobility formations.

[0077] Figure 8 The present invention describes the influence of multi-factor interaction on the pressure measurement mobility of low-liquidity formations during drilling.

[0078] Figure 9 The present invention provides the influence law of multi-factor interaction on the pressure measurement mobility of ultra-low mobility formations during drilling.

[0079] Figure 10 The distribution of pressure measurement flow rate before and after correction of the pressure measurement flow rate in the third section of the A2 block provided by this invention is compared with that of the cable pressure measurement flow rate.

[0080] Figure 11 The histogram of the pressure measurement flow rate before correction and the cable pressure measurement flow rate before drilling in the Weisan section of Block A2 provided by this invention.

[0081] Figure 12 The histogram of the corrected pressure measurement flow rate of the three sections of the A2 block and the statistical histogram of the pressure measurement flow rate of the cable is provided by the present invention. Detailed Implementation

[0082] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0083] This invention provides a method for correcting drilling pressure measurement and flow rate under the interaction of multiple factors;

[0084] See Figure 1 This includes the following steps:

[0085] S100. Construct a numerical simulation model of pressure measurement while drilling in anisotropic formation deviated wells and derive it into a finite element model of pressure measurement while drilling in formation deviated wells.

[0086] S200. Perform formation mobility inversion analysis on the formation deviated well logging-while-drilling pressure measurement finite element model, and identify the key factors affecting logging-while-drilling pressure measurement mobility based on the analysis results;

[0087] S300. Numerical simulation is performed based on the identified key factors to obtain the pressure response results of drilling pressure measurement. The formation mobility characteristics under the interaction of multiple factors are analyzed, and then the expression of the drilling pressure measurement mobility response law under the interaction of multiple factors is determined.

[0088] S500: Substitute the values ​​of key factors in the measured drilling pressure test process into the corresponding drilling pressure test flow rate response law expression, and then calculate the drilling pressure test flow rate of the vertical well to achieve drilling pressure test flow rate correction.

[0089] In step S100 of this embodiment of the invention, based on the conservation of mass and energy, and taking into account the influence of well inclination angle, permeability anisotropy, drilling fluid invasion, dynamic mud cake generation, and thermal-fluid coupling process, it is necessary to establish a numerical simulation model for borehole pressure measurement while drilling suitable for anisotropic formations. In order to simplify the modeling process, the following assumptions are made for the model: (1) the formation rock is a continuous, homogeneous, anisotropic porous medium; (2) the formation fluid flow process satisfies single-phase Darcy flow; (3) the formation porosity remains constant in all directions; (4) the influence of drilling disturbance on the formation properties around the well is ignored.

[0090] In this invention, the numerical simulation model of drilling pressure measurement in anisotropic formation deviated wells includes temperature field control equations and seepage field control equations.

[0091] Specifically, during drilling, the wellbore temperature typically differs from the formation temperature, leading to heat conduction in the formation surrounding the wellbore. Simultaneously, the pressure difference between the wellbore and the formation causes wellbore fluid to infiltrate the formation, generating thermal convection due to the temperature difference. The combined effects of heat conduction and thermal convection alter the temperature of the formation fluid around the well, thus affecting its viscosity. For the energy transfer process in saturated rock, which includes both heat conduction (the thermal conductivity of the solid skeleton and pore fluid) and thermal convection (the flow of pore fluid carrying away heat), assuming the system satisfies the law of energy conservation, an energy conservation equation can be established as the governing equation for the temperature field, expressed as:

[0092]

[0093] In the formula, This represents the overall density of saturated rock. This represents the equivalent specific heat capacity of saturated rock. Indicates temperature. Represents a time variable. Indicates pore fluid density. Indicates the specific heat capacity of a fluid. Represents the velocity vector of the pore fluid. This represents the equivalent thermal conductivity of saturated rock. Represents the gradient;

[0094] The governing equations for the seepage field include the mass conservation equations for a closed formation system and the mass conservation equations for mud cake.

[0095] Specifically, for flow problems in porous media, the governing equations for single-phase flow in porous media can be obtained using the law of conservation of mass, Darcy's law, and the equation of state. Considering the formation system as a closed system with no mass exchange with the outside world, the process can be expressed using the mass conservation equation as follows:

[0096]

[0097] In the formula, Indicates the formation porosity. Indicates fluid pressure. This indicates the Darcy flow velocity.

[0098] Permeability anisotropy reflects the differences in pore structure and fluid channels within the formation in different directions, and is a key parameter affecting the flow patterns of underground fluids. This parameter is obtained from laboratory lithological sample testing, aiming to acquire permeability in directions parallel to and perpendicular to bedding planes. Then, through axis transformation, the principal permeability tensor can be converted to permeability components in a wellbore rectangular coordinate system. After considering the effect of temperature changes on formation fluid viscosity, its seepage velocity can be expressed as:

[0099]

[0100]

[0101] In the formula, , , , , , , , and This represents the permeability components in each direction of the wellbore in rectangular coordinates. , and Represents the three directions in the rectangular coordinate system of the wellbore. Indicates the viscosity of degassed crude oil at the ground. Indicates the density of degassed crude oil at the ground. Indicates the content of crude oil asphalt resin. denoted by , where a and b represent the crude oil volume coefficient, and , where a and b represent empirical coefficients.

[0102] During drilling, solid particles in the drilling fluid gradually adhere to the wellbore and form a mud cake under the influence of positive pressure differential and the drilling fluid intrusion process. The dynamic growth of the mud cake and the drilling fluid intrusion process interact and influence each other, thus affecting the pore pressure of the formation around the well. Therefore, the impact of dynamic mud cake growth on the pore pressure around the well needs to be considered in the model. Assuming that the fluid seepage process in the mud cake still satisfies Darcy's law, and referring to the method of Feng et al. when calculating the fluid seepage velocity in the mud cake, a mass conservation equation within the mud cake is constructed based on this. The mass conservation equation within the mud cake can be expressed as:

[0103]

[0104] In the formula, Indicates the formation porosity. Indicates fluid pressure. Indicates Darcy flow velocity, Indicates the porosity of the mud cake. This indicates the fluid pressure within the mud cake. Indicates the fluid velocity within the mud cake;

[0105] in:

[0106]

[0107] In the formula, Indicates the equivalent mud cake permeability. Indicates viscosity.

[0108] Furthermore, referring to empirical coefficient expressions such as the actual dynamic permeability of mud cake and the dynamic mud cake thickness, the function for the equivalent mud cake permeability is determined as follows:

[0109]

[0110] In the formula, w o r represents the equivalent mud cake thickness. w Indicates the wellbore radius.

[0111] In step S100 of this embodiment of the invention, the boundary conditions of the numerical simulation model of the anisotropic formation deviated well drilling pressure measurement include initial conditions and boundary conditions.

[0112] For the initial conditions, before the formation is drilled through, the formation is in equilibrium, and the formation temperature and pore pressure are equal to the original formation temperature and pressure. Therefore, the initial conditions for the entire system are:

[0113]

[0114] In the formula, Indicates the original formation pressure. This indicates the initial formation temperature.

[0115] Regarding the boundary conditions, after the formation is drilled through, some of the formation rock is replaced by drilling fluid in the wellbore. Under the cooling effect of the drilling fluid, the formation temperature near the wellbore will also change, thus affecting the fluid viscosity. Therefore, the boundary conditions within the system are set as follows:

[0116]

[0117] In the formula, represents the wellbore temperature, This indicates the wellbore pressure.

[0118] The fluid change in the pipeline is:

[0119]

[0120] In the formula, This indicates the actual formation fluid drawn up by the suction probe. This indicates the amount of fluid volume change caused by pipeline storage.

[0121] Therefore, the actual volume of formation fluid pumped by the suction probe at each moment is determined as follows:

[0122]

[0123] Based on the probe's flow area, the seepage rate at the suction probe is:

[0124]

[0125] In the formula, This indicates the permeability at the suction head. Indicates penetration rate. Indicates viscosity. Indicates the pipeline storage volume. Indicates the radius of the suction probe. This indicates the actual volume of formation fluid pumped by the pumping probe at each moment.

[0126] In step S100 of this embodiment, the finite element equations are derived based on the previously established mathematical model, and then the finite element model is solved. According to the aforementioned mathematical model, the unknown variables to be solved include fluid pressure p and temperature T.

[0127] In finite element analysis, the partial differential equations to be solved need to be transformed into a weak form that can be solved at nodes. When deriving the weak form of the physical field governing equations, the above governing equations are first multiplied by the trial functions of each physical field. Based on Gauss's theorem and divergence theory, combined with the dynamic response parameter formula, the finite element model of the formation deviated well under drilling pressure measurement can be expressed as follows:

[0128]

[0129]

[0130]

[0131] In the formula, Let λs represent the trial function of formation temperature, λs represent the thermal conductivity of the rock, and λf represent the thermal conductivity of the fluid. Represents a trial function of formation pore pressure. Indicates formation porosity. The trial function represents the fluid pressure in the mud cake. Indicates mud cake domain, Indicates stratigraphic domain, Indicates the boundary of the mud cake domain. Indicates the boundary of the stratigraphic domain. The unit normal vector representing the boundary. Represents the differential symbol. Indicates the viscosity of formation fluids. This represents the equivalent mud cake permeability.

[0132] In step S100 of this embodiment of the invention, numerical simulation and indoor test verification are performed on the formation deviated well pressure measurement while drilling finite element model to verify the accuracy of the constructed model.

[0133] Specifically, when conducting numerical simulation of the formation deviated well drilling pressure measurement finite element model, the entire simulation process is divided into the following two steps:

[0134] Step 1: Drilling fluid invasion process after formation drilling. In this process, a cylinder with a radius of 1m and a height of 2m is constructed to represent the formation. A mud cake layer with a thickness of 3mm is set at the inner boundary of the formation to represent the mud cake formed on the well wall after formation drilling. The pressure value at the inner boundary of the mud cake is set as the wellbore pressure, and the mud cake properties change dynamically with the equivalent mud cake permeability to represent the impact of the dynamic growth of the well wall mud cake on drilling fluid invasion.

[0135] Step 2: Simulation of Pressure Measurement While Drilling. In this process, a small circular area will be additionally defined at the interface between the mud cake and the formation to represent the pressure measurement while drilling suction probe. Based on the designed test parameters, corresponding boundary conditions will be applied to simulate the pressure drop and pressure recovery process throughout the entire test. The established geometric model is as follows: Figure 2 As shown.

[0136] During the indoor testing and verification process, the physical simulation experimental device for testing formation pressure while drilling was mainly used to conduct physical simulation experiments. This experimental device mainly consists of a hydraulic servo system, a data acquisition system, a drive and control system, a booster cylinder, a core chamber, a pushing pressure device, and a suction pressure measuring device. The device's principle and physical diagram are shown below. Figure 3 As shown. During the experiment, the core was placed in the core cavity, which was divided into four chambers. The middle chamber housed the core and its sealing assembly, and confining pressure was applied around it. The left chamber was connected to a high-pressure fluid simulating formation pressure, and the right chamber was connected to a high-pressure fluid simulating annular pressure and housed a probe assembly. The probe assembly had relative movement with the right end of the core cavity. The core and sealing assembly were part of the interior of the core cavity. The sealing assembly circumferentially sealed the core, allowing fluids in the left and right chambers to permeate only through the core.

[0137] Based on the core physical properties and the results of the physical simulation experiment of test-and-work pressure (TMP), a finite element model matching the physical model experiment of TMP was established using the established finite element numerical simulation method for TMP. For example... Figure 4 As shown in Table 1, a numerical simulation analysis of the pressure response under the same conditions as the physical model experiment was conducted. The basic parameters used are shown in Table 1. A comparison of the physical model experimental results and the numerical simulation results is shown below. Figure 5 As shown, the two agree well, which demonstrates the accuracy of the established model and simulation method.

[0138] Table 1. Basic parameters for the drilling pressure measurement model experiment.

[0139]

[0140] Step S200 of this embodiment of the invention includes the following sub-steps:

[0141] S201. Set the basic influencing factors for numerical simulation of the formation deviated well drilling pressure measurement finite element model, and use the control variable method to perform formation mobility inversion analysis under different basic influencing factors.

[0142] S202. Based on the formation mobility inversion analysis results, the dimensionless Spearman correlation analysis method was used to identify the key factors affecting logging-while-drilling pressure measurement mobility.

[0143] Key factors include well inclination angle, formation permeability anisotropy ratio, tool face, and formation-wellbore temperature.

[0144] In a specific example of the present invention, the process for determining the aforementioned key factors is given.

[0145] The selected basic influencing factors are shown in Table 2. During the analysis, a controlled variable method was used for parametric research, meaning the analysis object was set to different values ​​while the other parameters remained unchanged from those in Table 1. Using this analytical method, simulations of the test-and-run pressure response and formation mobility inversion analyses were conducted under different permeability anisotropy ratios, well inclination angles, initial formation pressure, overbalance pressure, formation-wellbore temperature difference, pipeline storage volume, pumping rate, pumping duration, probe radius, and probe shape. It is worth noting that in anisotropic formations, the test-and-run pressure response varies with the probe setting azimuth. At different toolface angles, the formation pressure drop sweep range and shape near the probe are inconsistent (i.e., inconsistent seepage paths), leading to differences in the test-and-run pressure response and consequently affecting the mobility interpretation results. Therefore, toolface factors need to be incorporated into the test-and-run pressure response simulation and formation mobility inversion analysis.

[0146] Table 2 Basic Influencing Factors

[0147] parameter value unit <![CDATA[Well deviation angle, α b > 60 ° <![CDATA[Formation dip, β w > 0 ° Tool face, θ 0 ° <![CDATA[Stratigraphic permeability of bedding plane, k H > 20 mD <![CDATA[Permeability anisotropy ratio, k H / k v > 4 Dimensionless Formation fluid viscosity, μ 20 mPa·s <![CDATA[Wellbore radius, r w > 0.06985 m <![CDATA[Formation radius, r e > 1 m <![CDATA[Formation fluid compressibility, c f > <![CDATA[2.96×10 -9 ]]> 1 / Pa <![CDATA[Formation temperature, T0]]> 90 ℃ <![CDATA[Wellbore temperature, T w > 90 ℃ <![CDATA[Pipeline storage volume, V s > 150 cc suction rate, q 0.5 cc / s Aspiration duration, Δt 20 s <![CDATA[Probe radius, r p > 0.015 m <![CDATA[Formation fluid density, ρ f > 880 <![CDATA[kg / m 3 ]]> <![CDATA[Formation rock density, ρ s > 2300 <![CDATA[kg / m 3 ]]> <![CDATA[Original formation pressure, p i > 30 MPa <![CDATA[Wellbore pressure, p w > 30 MPa Empirical coefficient, a 3.181342 - <![CDATA[Viscosity of surface degassed crude oil, μ oa > 500 mPa·s <![CDATA[Density of surface degassed crude oil, ρ oa > 0.909 <![CDATA[g / cm 3 ]]> Crude oil resinous bitumen content, Ψ 12 % <![CDATA[Crude oil volume factor, B oi > 1.3 - Empirical coefficient, b 0.1036 - <![CDATA[Filter cake permeability, k mc > 0.0005*[3+50*exp(-0.0005*t)] mD <![CDATA[Filter cake thickness, h mc > 3*[1-0.25*exp(-0.0002*t)-0.75*exp(-0.00001*t)] mm

[0148] The key factors for formation mobility inversion were determined using Spearman correlation analysis. Spearman correlation, also known as rank correlation or grade correlation, is a non-parametric statistical method that performs linear correlation analysis on the ranks of two variables. It does not require specific distributions of the original variables and has a wide range of applications. The calculation process for the Spearman correlation coefficient rs is as follows: First, variables X and Y are sorted and ranked from smallest to largest, denoted by ranks RX and RY. During the sorting process, if data are equal, resulting in the same rank, this is called a stalemate. In this case, the average rank is taken as the rank of each data point. Spearman correlation coefficient. Calculation formula:

[0149]

[0150] The Spearman correlation coefficient (rs) ranges between -1 and 1, with rs > 0 indicating a positive correlation and rs < 0 indicating a negative correlation. The larger the absolute value of rs (|rs|), the stronger the correlation between the variables. Referring to the Pearson correlation coefficient, rs can be categorized as follows: 0.9 < |rs| < 1 indicates a high correlation; 0.7 < |rs| < 0.9 indicates a strong correlation; 0.4 < |rs| < 0.7 indicates a moderate correlation; 0.2 < |rs| < 0.4 indicates a weak correlation; and 0 < |rs| < 0.2 indicates a very weak correlation.

[0151] To conduct Spearman correlation analysis, based on the formation mobility inversion analysis results, the formation mobility inversion results under different parameter settings were statistically analyzed, and the processed results are shown in Table 3.

[0152] Table 3. Normalized results of formation mobility calculations under different design parameters

[0153] Serial Number Permeability anisotropy ratio Well inclination angle (°) Tool face (°) Formation pressure (MPa) Overbalance pressure (MPa) Temperature difference (°C) Storage volume (cc) Suction rate (cc / s) Aspiration duration (s) Probe radius (m) Formation mobility (mD / cP) 1 1 60 0 30 0 0 150 0.5 20 0.015 1.0007 2 3 60 0 30 0 0 150 0.5 20 0.015 0.5425 3 6 60 0 30 0 0 150 0.5 20 0.015 0.3794 4 10 60 0 30 0 0 150 0.5 20 0.015 0.2981 5 4 0 0 30 0 0 150 0.5 20 0.015 0.6342 6 4 15 0 30 0 0 150 0.5 20 0.015 0.6188 7 4 30 0 30 0 0 150 0.5 20 0.015 0.5802 8 4 45 0 30 0 0 150 0.5 20 0.015 0.5272 9 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 10 4 75 0 30 0 0 150 0.5 20 0.015 0.4212 11 4 90 0 30 0 0 150 0.5 20 0.015 0.3996 12 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 13 4 60 15 30 0 0 150 0.5 20 0.015 0.4754 14 4 60 30 30 0 0 150 0.5 20 0.015 0.5048 15 4 60 45 30 0 0 150 0.5 20 0.015 0.5352 16 4 60 60 30 0 0 150 0.5 20 0.015 0.5695 17 4 60 75 30 0 0 150 0.5 20 0.015 0.5915 18 4 60 90 30 0 0 150 0.5 20 0.015 0.5984 19 4 60 0 20 0 0 150 0.5 20 0.015 0.4702 20 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 21 4 60 0 40 0 0 150 0.5 20 0.015 0.4692 22 4 60 0 50 0 0 150 0.5 20 0.015 0.4691 23 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 24 4 60 0 30 1 0 150 0.5 20 0.015 0.4758 25 4 60 0 30 3 0 150 0.5 20 0.015 0.4859 26 4 60 0 30 5 0 150 0.5 20 0.015 0.492 27 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 28 4 60 0 30 0 10 150 0.5 20 0.015 0.4515 29 4 60 0 30 0 20 150 0.5 20 0.015 0.42698 30 4 60 0 30 0 30 150 0.5 20 0.015 0.4021 31 4 60 0 30 0 0 50 0.5 20 0.015 0.4726 32 4 60 0 30 0 0 100 0.5 20 0.015 0.47 33 4 60 0 30 0 0 200 0.5 20 0.015 0.4702 34 4 60 0 30 0 0 300 0.5 20 0.015 0.4705 35 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 36 4 60 0 30 0 0 150 1 20 0.015 0.4696 37 4 60 0 30 0 0 150 1.5 20 0.015 0.4699 38 4 60 0 30 0 0 150 2 20 0.015 0.4709 39 4 60 0 30 0 0 150 0.5 10 0.015 0.4766 40 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 41 4 60 0 30 0 0 150 0.5 30 0.015 0.4658 42 4 60 0 30 0 0 150 0.5 40 0.015 0.476 43 4 60 0 30 0 0 150 0.5 20 0.01 0.4569 44 4 60 0 30 0 0 150 0.5 20 0.015 0.4698 45 4 60 0 30 0 0 150 0.5 20 0.02 0.4842 46 4 60 0 30 0 0 150 0.5 20 0.025 0.5026

[0154] To avoid the influence of data type differences and numerical values ​​on the results, the data was normalized to its maximum and minimum values. Then, the Spearman correlation coefficient was calculated, and the results are as follows: Figure 6 As shown.

[0155] It can be observed that the correlation coefficients between formation mobility and permeability anisotropy ratio, well inclination angle, tool face, formation pressure, overequilibrium pressure, formation-wellbore temperature difference, pipeline storage volume, pumping rate, pumping duration, and probe radius are -0.46, -0.52, 0.43, -0.17, 0.17, -0.36, -0.0032, -0.072, -0.079, and 0.23, respectively. The analysis results indicate that the influence of different factors on the formation mobility inversion results, from largest to smallest, is as follows: well inclination angle > permeability anisotropy ratio > tool face > formation-wellbore temperature difference > probe radius > formation pressure ≈ overequilibrium pressure > pumping duration > pumping rate > pipeline storage volume. This suggests that well inclination angle, permeability anisotropy ratio, tool face, and formation-wellbore temperature are the key factors affecting mobility inversion.

[0156] Step S300 of this embodiment of the invention includes the following sub-steps:

[0157] S301. Based on the degree of formation mobility, three types of formations are defined: medium-high mobility formations, low mobility formations, and ultra-low mobility formations.

[0158] S302. Numerical simulations based on the interaction of key factors were conducted on the three types of fluidity formations to obtain the pressure response results of drilling pressure measurement.

[0159] S303. The area integral method is used to perform response surface analysis on the pressure response results of drilling pressure measurement to obtain the formation mobility characteristics under the interaction of multiple factors.

[0160] S304. Based on the formation mobility characteristics under multiple factors, determine the expression of the drilling pressure measurement mobility response law of three types of mobility formations under the interaction of multiple factors when parallel bedding plane.

[0161] In a specific example of this invention, a customized response surface methodology was used to design a numerical simulation study scheme for the interaction of key controlling factors such as formation horizontal mobility, permeability anisotropy ratio, well inclination angle, tool face, and temperature difference, targeting three types of mobility formations. The factor levels for the three types of mobility formations are shown in Tables 4, 5, and 6. In the design scheme, the experimental model was run 26 times sequentially for numerical simulation. Then, based on the pressure response results obtained from the numerical simulation during drilling, the area integration method was used to explain the formation mobility under the combined influence of multiple factors.

[0162] Table 4 Response surface factor levels of medium- and high-mobility formations

[0163] Factor code Factor Name unit low value High value Low-point code value High-point code value average value Standard deviation A Horizontal flow mD / Cp 50 500 -1 +1 311.54 199.15 B Permeability anisotropy ratio - 1 10 -1 +1 6.00 4.13 C Well inclination angle ° 0 90 -1 +1 46.73 41.21 D tool face ° 0 90 -1 +1 43.27 39.19 E Temperature difference ℃ 0 40 -1 +1 22.31 18.18

[0164] Table 5 Response surface factor levels of low-mobility formations

[0165] Factor code Factor Name unit low value High value Low-point code value High-point code value average value Standard deviation A Horizontal flow mD / Cp 1 50 -1 +1 26.08 21.24 B Permeability anisotropy ratio - 1 10 -1 +1 4.73 3.55 C Well inclination angle ° 0 90 -1 +1 45.00 40.25 D tool face ° 0 90 -1 +1 45.00 36.00 E Temperature difference ℃ 0 40 -1 +1 20.77 17.42

[0166] Table 6 Response Surface Factor Levels of Ultra-Low Mobility Formations

[0167] Factor code Factor Name unit low value High value Low-point code value High-point code value average value Standard deviation A Horizontal flow mD / Cp 0.05 1 -1 +1 0.5423 0.41 B Permeability anisotropy ratio - 1 10 -1 +1 5.73 3.84 C Well inclination angle ° 0 90 -1 +1 45.00 38.18 D tool face ° 0 90 -1 +1 45.00 40.25 E Temperature difference ℃ 0 40 -1 +1 19.23 18.31

[0168] Based on the response surface methodology, the differences in drilling pressure and mobility under multi-factor interaction conditions were obtained. The analysis results for medium-to-high mobility, low mobility, and ultra-low mobility formations are as follows: Figure 7 , Figure 8 , Figure 9 As shown, in formations with different mobility levels (medium-high mobility, low mobility, and ultra-low mobility), the mobility inversion results all exhibit similar patterns: when the horizontal mobility of the formation remains constant, the inverted mobility gradually decreases with the increase of the formation permeability anisotropy ratio; conversely, when the permeability anisotropy ratio is fixed, the inverted mobility increases with the increase of the horizontal mobility of the formation. Furthermore, when the well inclination angle remains constant, the differences in formation mobility measured at different tool faces are small; conversely, when the tool face remains constant, the measured formation mobility shows a gradual decreasing trend with the increase of the well inclination angle. These patterns are consistently verified in formations with different mobility levels, indicating that the flow inversion results are jointly influenced by the permeability anisotropy ratio, the horizontal mobility of the formation, the well inclination angle, and the tool face.

[0169] In step S304, based on the aforementioned analysis results of the drilling pressure measurement mobility response surface for formations with different mobility, the drilling pressure measurement mobility response law expressions for medium-high mobility formations, low mobility formations, and ultra-low mobility formations are constructed as follows:

[0170]

[0171]

[0172]

[0173] In the formula, This represents the flowability when the bedding plane is parallel to the surface. Indicates the inverted strata mobility. Indicates the anisotropy ratio of formation permeability. Indicates the inclination angle of the well. Indicates the tool face. This indicates the temperature difference between the formation and the wellbore.

[0174] Step S400 of this embodiment of the invention includes the following sub-steps:

[0175] S401. Determine the drilling pressure response rate of the deviated well based on the measured drilling pressure response data;

[0176] S402. Estimate the anisotropy ratio of formation permeability and the formation-wellbore temperature difference;

[0177] S403. Record the wellbore surface and tool face at each measuring point during drilling pressure testing;

[0178] S404. Substitute the measured flow rate during drilling, formation permeability anisotropy ratio, formation-wellbore temperature difference, well inclination surface, and tool face into the expression for the measured flow rate response law of the corresponding flow rate formation to calculate the flow rate when parallel to the bedding plane.

[0179] Among them, the pressure measurement and mobility during drilling in inclined wells corresponds to the inverted formation mobility in the expression of the pressure measurement and mobility during drilling response law;

[0180] S405. Calculate the pressure measurement flow rate of the vertical well based on the flow rate when the bedding plane is parallel.

[0181] In this embodiment, according to the definition of the area integral method, the formation mobility is:

[0182]

[0183] This leads to the obtaining of vertical well drilling pressure measurement and flow rate. for:

[0184]

[0185] In the formula, The permeability of the transverse isotropic surface of anisotropic strata. This represents the permeability perpendicular to the transversely isotropic surface. Indicates viscosity. This represents the ratio of permeability in the direction parallel to the stratification plane to that perpendicular to the stratification plane. This represents the flowability when parallel to the bedding plane; where, .

[0186] In one specific embodiment of the present invention, an example of formation mobility correction during drilling pressure measurement is provided.

[0187] Taking the third section of the Weizhou Formation in Block A2 as a case study for mobility correction, the pressure measurement mobility correction data of wells A2-1 and A2-2 in Block A2 are shown in Table 7. Figure 10The distribution of pressure measurement flow rate (PPFR) before and after correction in the third section of the Weizhou Formation in Block A2 is shown. It can be found that when the PFR is not corrected, the overall PFR is smaller than that of the adjacent A1 cable PFR. After the PFR is corrected, the obtained PFR is comparable to that of the cable PFR. Figures 11-12 The study presents the spectral distribution of the wellbore pressure measurement and flow rate (WVRPR) before and after correction in the three sections of the Weizhou Formation. It reveals that the dominant frequency of the WVRPR is between 100 and 500 mD / cP, while the dominant frequency of the WVRPR before correction is between 10 and 50 mD / cP, showing a significant difference. After correction, the dominant frequency of the corrected WVRPR is also between 100 and 500 mD / cP. The difference between the spectral distributions of the corrected WVRPR and the cable WVRPR becomes smaller, with the cumulative probability and probability distribution almost overlapping, significantly eliminating the influence of well deviation. The correction effect is highly satisfactory, validating the effectiveness of the flow rate correction method.

[0188] Table 7 Response Surface Factor Levels of Ultra-Low Mobility Formations

[0189] well name Test flowability while drilling Permeability anisotropy ratio Well inclination angle tool face Temperature difference Corrected pressure-while-drilling flow rate A2-1 237.39 2 53.97 0.0 10 292.8898 A2-1 167.21 5 54.17 0.0 20 253.0503 A2-1 27.59 5 53.98 0.0 20 51.5524 A2-1 92.98 5 54.01 0.0 20 161.9926 A2-2 2.81 10 59.37 69.1 20 19.6457 A2-2 35.08 10 59.45 63.1 20 144.4143 A2-2 23.55 10 59.41 57.1 20 99.5955 A2-2 13.57 10 59.54 57.1 20 60.8950 A2-2 1.85 10 59.27 57.1 20 15.3845 A2-2 12.78 10 59.25 57.1 20 57.7811 A2-2 50.37 10 59.23 57.1 20 219.5269 A2-2 1.00 10 59.34 39.1 20 11.2652 A2-2 24.82 10 59.31 69.1 20 104.7656 A2-2 4.57 10 59.30 63.1 20 26.1934 A2-2 4.67 10 59.28 63.1 20 26.5786

[0190] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0191] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for pressure buildup rate correction while drilling under the interaction of multiple factors, characterized in that, The method comprises the following steps: S100, constructing a numerical simulation model of anisotropic formation deviated well while drilling pressure measurement, and deriving the numerical simulation model into a finite element model of the formation deviated well while drilling pressure measurement; S200, performing formation mobility inversion analysis on the finite element model of the formation deviated well while drilling pressure measurement, and identifying key factors affecting the well drilling pressure measurement mobility based on the analysis result; S300, performing numerical simulation based on the identified key factors to obtain a pressure response result of the while drilling pressure measurement, analyzing formation mobility characteristics under the interaction of multiple factors, and then determining a while drilling pressure measurement mobility response law expression under the interaction of multiple factors; S400, substituting the values of the key factors in the actual while drilling pressure measurement into the corresponding while drilling pressure measurement mobility response law expression, and then calculating a straight well drilling pressure measurement mobility to realize the while drilling pressure measurement mobility correction.

2. The method of claim 1, wherein, In the step S100, the numerical simulation model of the anisotropic formation deviated well while drilling pressure measurement comprises a temperature field control equation and a percolation field control equation. The temperature field control equation is: ； wherein, represents the bulk density of the saturated rock, represents the equivalent specific heat capacity of the saturated rock, represents the temperature, represents the time variable, represents the pore fluid density, represents the specific heat capacity of the fluid, represents the velocity vector of the pore fluid, represents the equivalent thermal conductivity of the saturated rock, represents the gradient; The percolation field control equation is: ； ； wherein, represents formation porosity, represents fluid pressure represents Darcy flow velocity, represents mudcake porosity, represents fluid pressure in the mudcake, represents fluid velocity in the mudcake; Wherein: ； ； ； wherein , , , , , , , and denote permeability components in each direction in the wellbore rectangular coordinate, , and denote three directions in the wellbore rectangular coordinate, denotes the viscosity of the degassed crude oil at the surface, denotes the density of the degassed crude oil at the surface, denotes the gelled bitumen content of the crude oil, denotes the volume factor of the crude oil, a, b denote empirical coefficients, denotes the equivalent mudcake permeability, denotes the viscosity.

3. The method of claim 2, wherein, In the step S100, the definite condition of the numerical simulation model of the anisotropic formation deviated well while drilling pressure measurement comprises an initial condition and a boundary condition. The initial condition is: ； wherein P0represents the initial formation pressure, T0represents the initial formation temperature; The boundary condition is: ； ； ； wherein, represents the wellbore temperature, represents the wellbore pressure, represents the permeability at the suction head, represents the permeability, represents the viscosity, represents the amount of fluid volume change in the tubing, represents the tubing storage volume, represents the suction probe radius, represents the actual volume of formation fluid sucked by the suction probe at each time; wherein, , represents the actual formation fluid sucked by the suction probe, represents the amount of fluid volume change caused by the tubing storage.

4. The method of claim 3, wherein, In the step S100, the finite element model of the formation deviated well while drilling pressure measurement is expressed as: ； ； ； wherein, represents a formation temperature trial function, λs represents a rock thermal conductivity coefficient, λf represents a fluid thermal conductivity coefficient, represents a formation pore pressure trial function, represents a formation porosity, represents a fluid pressure trial function in the mudcake, represents a mudcake domain, represents a formation domain, represents a mudcake domain corresponding boundary, represents a formation domain corresponding boundary, represents a unit normal vector of the boundary, represents a differential symbol, represents a formation fluid viscosity, represents an equivalent mudcake permeability.

5. The method of claim 1, wherein, In the step S100, the numerical simulation and indoor test verification are further performed on the finite element model of the formation deviated well while drilling pressure measurement to verify the accuracy of the constructed model.

6. The method of claim 1, wherein, The step S200 comprises the following sub-steps: S201, setting a basic influencing factor for the numerical simulation of the finite element model of the formation deviated well while drilling pressure measurement, and performing formation mobility inversion analysis under different basic influencing factors by using the control variable method; S202, identifying key factors affecting the well drilling pressure measurement mobility by using the dimensionless Spearman correlation analysis method based on the formation mobility inversion analysis result; The key factors comprise a deviation angle, a formation permeability anisotropy ratio, a tool face, and a formation-wellbore temperature.

7. The method of claim 6, wherein, The step S300 comprises the following sub-steps: S301, setting three types of mobility formations according to the formation mobility, including a medium-high mobility formation, a low mobility formation, and an ultra-low mobility formation; S302, performing numerical simulation based on the interaction of the key factors for the three types of mobility formations respectively to obtain a while drilling pressure measurement pressure response result; S303, performing response surface analysis on the while drilling pressure measurement pressure response result by using the area integration method to obtain formation mobility characteristics under the interaction of multiple factors; S304, determining a while drilling pressure measurement mobility response law expression under the interaction of multiple factors for the three types of mobility formations respectively based on the formation mobility characteristics under the interaction of multiple factors.

8. The method of claim 1, wherein, In the step S304, the while drilling pressure measurement mobility response law expressions corresponding to the medium-high mobility formation, the low mobility formation, and the ultra-low mobility formation are respectively: ； ； ； where, representing the mobility when the parallel bedding is present, representing the inverted formation mobility, representing the formation permeability anisotropy ratio, representing the hole deviation angle, representing the tool face, representing the formation - wellbore temperature difference.

9. The method of claim 8, wherein, The step S400 comprises the following sub-steps: S401, determining a deviated well drilling pressure measurement mobility based on the measured while drilling pressure measurement pressure response data; S402, estimating a formation permeability anisotropy ratio and a formation-wellbore temperature difference; S403, record the inclination and tool face of each measuring point when pressure while drilling is performed; S404, substitute the inclination and tool face, the pressure while drilling mobility of the inclined well, the anisotropy ratio of the formation permeability, the formation-borehole temperature difference, and the inclination and tool face into the expression of the mobility response law of the corresponding mobility formation, and calculate the mobility when the parallel bedding plane is parallel to the tool face; wherein the inversion formation mobility in the expression of the mobility response law of the pressure while drilling mobility of the inclined well corresponds to the mobility of the formation; S405, calculate the pressure while drilling mobility of the vertical well according to the mobility when the parallel bedding plane is parallel to the tool face.

10. The method of claim 9, wherein, In the step S405, the straight well drilling pressure measuring flow rate is: ； wherein represents the permeability of the transverse isotropic plane of the anisotropic formation, represents the permeability perpendicular to the transverse isotropic plane, represents the viscosity, represents the ratio of the permeability in the direction parallel to the bedding plane to the permeability in the direction perpendicular to the bedding plane, represents the mobility in the direction parallel to the bedding plane; wherein, .

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