Deep well gas invasion formation parameter inversion method and system based on gas-liquid two-phase flow model

Abstract

The application discloses a deep well gas channeling formation parameter inversion method and system based on a gas-liquid two-phase flow model. First, a gas-liquid two-phase flow model is established based on a wellbore flow equation, and a finite difference algorithm is used to discretely solve the mathematical model. Then, an inversion model of formation parameters is constructed in combination with an unscented Kalman filter (UKF), and the formation pressure and production index in the gas channeling process are inverted by using measured data of the difference between the standpipe pressure and the liquid inlet and outlet flow. The formation parameter inversion method provided by the application can accurately invert the formation parameters, provides a basis for accurate prediction and effective control of gas channeling, and has a wide application prospect.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas field drilling, and in particular relates to a deep well gas invasion formation parameter inversion method and system based on a gas-liquid two-phase flow model. Background Art

[0002] During the drilling of deep and ultra-deep wells, gas invasion is prone to occur due to the high temperatures, high pressures, high stresses, and complex formation environments. If gas invasion is not detected promptly and handled improperly, the continuous intrusion of formation gas and its upward migration and expansion in the wellbore will displace more drilling fluid, causing a continuous decrease in wellbore pressure and a subsequent increase in the rate of gas invasion. This vicious cycle increases well control risks and may even trigger serious blowouts. Effective wellbore pressure control is key to ensuring the safe implementation of well control measures, and accurate characterization of complex wellbore flow characteristics and pressure evolution is a prerequisite for wellbore pressure prediction and control. Therefore, accurate simulation and prediction of multiphase flow characteristics in the wellbore after gas invasion is crucial for safe and efficient drilling.

[0003] The Chinese patent CN202410794778.8 discloses a direct-push well-killing modeling method based on formation parameter inversion, including real-time acquisition of actual wellhead overflow data, actual drilling trajectory data, well depth structure data, and drill tool assembly data; pre-processing of the wellhead overflow data, actual drilling trajectory data, well depth structure data, and drill tool assembly data respectively; and establishing a direct-push well-killing model based on the mass conservation equation and the drift flow model, combined with the gas-liquid two-phase flow model. An overflow simulation model is used to simulate the change of wellhead overflow volume over time during the overflow period, and then an ant colony search algorithm is used to compare the actual wellhead overflow data obtained to invert the gas production index and formation pressure. This method requires a large amount of real-time data and requires data pre-processing, and the preliminary work is relatively complicated.

[0004] Chinese patent CN202410590140.2 discloses a method for predicting fracture morphology and inverting formation pressure in ultra-deepwater drilling. The formation parameters are inverted using gas flow and riser pressure, and mathematical expressions are obtained through simulation to perform fracture width inversion. Then, based on the correlation between the fractures, the corresponding permeability calculation formula is obtained to perform formation parameter inversion. And using the iterative method, the permeability iteration formula is obtained to perform permeability inversion. At the same time, the formation porosity is calculated, and the fracture length is inverted based on the relationship between the fracture porosity and the fracture width and fracture length. This method mainly performs inversion on formation pressure, fracture length and width, and permeability, and does not involve production index.

[0005] Habib et al. based on managed pressure drilling system, measured pump pressure and throttle pressure input to the unscented Kalman filter estimator to estimate the flow rate and gas influx of the drill bit at the same time, and the robustness of the method is verified by experimental and field data, however, the method is based on the isothermal conditions, which is not consistent with the actual high temperature and high pressure well conditions.

[0006] Sun et al. based on the mutual coupling between the wellbore and the formation and the change of annular gas volume and pressure caused by the movement and expansion of bubbles in the wellbore to establish a pore pressure inversion model during gas invasion, and a fast search algorithm is proposed to reduce the influence of measurement noise on the results. However, this method mainly focuses on inverting a single parameter of the formation, i.e. formation pressure, formation permeability, etc., and the remaining formation parameters are assumed values.

[0007] In summary, the existing inversion method of formation parameters needs to be based on complex real-time wellbore data or assumed values, but in actual drilling process, the parameters of high pressure gas layer are often unknown, which makes the current inversion method have certain limitations. Therefore, in order to clarify the evolution law of gas-liquid two-phase flow in gas invasion wellbore, improve the prediction accuracy of wellbore pressure, and realize the safe and efficient treatment of gas invasion, the key problem of "gas-liquid two-phase flow mechanism model and time sequence data fusion of formation parameter inversion" needs to be solved. SUMMARY

[0008] The present application is to solve the technical problems existing in the background art, and aims to provide a deep well gas invasion formation parameter inversion method and system based on a gas-liquid two-phase flow model, which provides a reliable basis for monitoring and controlling gas invasion caused by high temperature and high pressure and complex formation environment in deep well drilling.

[0009] In order to solve the technical problems, the technical scheme of the present application is:

[0010] A deep well gas invasion formation parameter inversion method based on a gas-liquid two-phase flow model, the method comprising:

[0011] establishing a wellbore flow model and discretely solving the model by using a finite difference algorithm; combining an unscented Kalman filter UKF to construct an inversion model of formation parameters, and using the measurement data of the difference between the standpipe pressure and the liquid inlet and outlet flow to invert the formation pressure and production index during gas invasion.

[0012] Further, the wellbore flow model is established, specifically comprising:

[0013] Firstly, a gas-liquid two-phase flow control model in the annulus is constructed:

[0014] First, the model neglects the cross-sectional velocity distribution, the temperature gradient is linear, and the influence of drilling cuttings is not considered. Then, the following equations are established: the drilling fluid mass conservation equation, the intruding gas mass conservation equation, and the gas-liquid mixture momentum conservation equation.

[0015] The drilling fluid mass conservation equation is:

[0016]

[0017] Where: ρ a is the drilling fluid density in the annulus, kg / m 3 ; α l is the drilling fluid volume fraction, dimensionless; v l is the drilling fluid velocity in the annulus, m / s; A a is the cross-sectional area of ​​the annulus, m 2 ;

[0018] The mass conservation equation of the intruding gas is:

[0019]

[0020] Where: ρ g is the gas density, kg / m 3 ; α g is the gas phase volume fraction, dimensionless; v g is the gas velocity, m / s;

[0021] Conservation equation of mixture momentum:

[0022]

[0023] Where: g is the acceleration due to gravity, 9.81m / s 2 ;P a is the annular pressure, Pa; θ is the wellbore inclination, ° (starting from the vertical direction); F f is the friction pressure drop per unit length, Pa / m;

[0024] The sum of the drilling fluid volume fraction and the invading gas volume fraction is 1:

[0025] α g +α l =1 (4)

[0026] In the drift flow equation, the gas phase velocity can be expressed as:

[0027] v g =C0(v g α g +v l α l )+v gr (5)

[0028] Where: C0 is the slip coefficient; v gr is the slip velocity, m / s;

[0029] The slip coefficient and slip velocity can be expressed as:

[0030]

[0031] Where: A is the gas phase distribution coefficient in the liquid; γ is the reduction term of the slip coefficient; v c is the characteristic velocity, m / s;

[0032] According to the PVT model, the density of gas can be expressed as:

[0033]

[0034] Where M g is the gas molar mass, kg / mol; R is the gas constant, J / mol / K; Z is the gas deviation factor, calculated using the following formula:

[0035]

[0036] In the formula, A1~A 11 is the coefficient; T r is the comparative temperature, dimensionless; ρ r is the comparative density, dimensionless;

[0037] The second step is to construct the governing equation of the single-phase flow of liquid in the drill pipe:

[0038] The governing equations of the single-phase flow of liquid in the drill pipe include two equations: the drilling fluid mass conservation equation and the drilling fluid momentum conservation equation;

[0039] The drilling fluid mass conservation equation is:

[0040]

[0041] Where: ρ d is the density of drilling fluid in the drill pipe, kg / m 3 ;v d is the drilling fluid velocity in the drill pipe, m / s; A d is the cross-sectional area of ​​the drill pipe, m 2 ;

[0042] The momentum conservation equation in the drill pipe is:

[0043]

[0044] Where: P d is the drilling fluid pressure in the pipe, Pa; D d is the inner diameter of the drill pipe, m;

[0045] The third step is to construct the auxiliary equation:

[0046] The momentum conservation equation, i.e. the friction pressure drop per unit length F in Equation 3 and Equation 11 f The calculation formula is:

[0047]

[0048] Where: F f is the friction pressure drop per unit length, Pa / m; f is the Moody friction factor; D is the flow channel diameter, the inner diameter of the pipe in the drill pipe; the hydraulic diameter in the annulus, m; ρ is the density, kg / m 3 ; v is the fluid velocity, m / s;

[0049] The Moody friction factor f in formula (12) takes into account the influence of wall roughness and can be obtained as follows:

[0050]

[0051] Where Re is the Reynolds number;

[0052] In the gas-liquid two-phase flow model of gas invasion, formula (14) is used to define the relationship between gas invasion rate, production index and formation pressure;

[0053] q g =J(P e -P b ) (14)

[0054] Where q g is the gas invasion rate, kg / s; J is the production index, kg / s / MPa; P e is the formation pressure, MPa; P b is the bottom hole pressure, MPa, P b It can be calculated using the gas-liquid two-phase flow model.

[0055] Furthermore, the discrete solution of the model using the finite difference algorithm specifically includes:

[0056] The entire wellbore is discretized into N nodes, and the flow control equations of the wellbore-formation system are solved using the finite difference method;

[0057] The annular flow equation is expressed as:

[0058]

[0059] Wherein, variables W, F(W), and Q(W) are functions of density, velocity, volume fraction, and pressure; j = 1, 2 represent the mass conservation equations for the liquid and gas phases; j = 3 represents the momentum conservation equation for the gas-liquid two-phases;

[0060] The mass conservation equation is expressed as:

[0061]

[0062] Further, during the gas invasion process, the ground inlet and outlet flow difference and the riser pressure are measured; the formation pressure and production index during the gas invasion process are inverted by using the measured data of the inlet and outlet flow difference and the riser pressure;

[0063] The inlet and outlet flow difference of the ground at different times is the inlet and outlet flow difference of liquid single-phase flow, which is expressed as:

[0064] Δq(t)=[Δq(t1),Δq(t2),…,Δq(t N )] (17)

[0065] Δq(t)=q out (t)-q in (t) (18)

[0066] In the formula, t is time, s; Δq is the liquid inlet and outlet flow difference, m 3 / min; q out is the liquid outlet flow difference, m 3 / min; q in is the liquid inlet flow difference, m 3 / min;

[0067] The measured riser pressure data at different times is expressed as:

[0068] P sp (t)=[P sp (t1),P sp (t2),…,P sp (t N )] (19)

[0069] In the formula, P sp is the riser pressure, MPa;

[0070] The formation pressure and production index are taken as the inversion parameters, and the inversion parameters at different times are:

[0071] P e (t)=[P e (t1),P e (t2),…,P e (t N )] (20)

[0072] J(t)=[J(t1),J(t2),…,J(t N )] (21)

[0073] Where P e is the formation pressure, MPa; J is the production index, kg / s / MPa;

[0074] Combined with the UKF algorithm, the formation pressure and production index are used as state values, and the inlet and outlet flow difference and standpipe pressure are used as observation values. The state variable (X) and observation variable (Z) in the inversion model are expressed as follows:

[0075] X(k)=[P e (k),J(k)] T (twenty two)

[0076] Z(k)=[Δq(k),P sp (k)] T (twenty three)

[0077] The state model f(·) for formation parameter inversion using the UKF algorithm is expressed as:

[0078] X(k)=X(k-1)+W(k) (24).

[0079] A deep well gas invasion formation parameter inversion system based on a gas-liquid two-phase flow model, the system comprising:

[0080] Wellbore flow modeling module, used to establish wellbore flow model;

[0081] A finite difference discretization module is used to discretize and solve the established wellbore flow model using a finite difference algorithm;

[0082] Unscented Kalman filter inversion module, used to build an inversion model of formation parameters in combination with the unscented Kalman filter UKF;

[0083] The data fusion and inversion module is used to invert the formation pressure and production index during the gas invasion process using the measurement data of the riser pressure and the liquid inlet and outlet flow difference.

[0084] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any one of the above-mentioned methods for inverting deep well gas invasion formation parameters based on a gas-liquid two-phase flow model is implemented.

[0085] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements any one of the above-mentioned deep well gas invasion formation parameter inversion methods based on a gas-liquid two-phase flow model.

[0086] Compared with the prior art, the advantages of the present invention are:

[0087] The formation parameter inversion method provided by the present invention can accurately invert the formation parameters, provide a basis for accurate prediction and effective control of gas invasion, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 , schematic diagram of gas-liquid two-phase flow in gas-invasion wellbore;

[0089] Figure 2 , the wellbore-time system grid used to solve the flow equations;

[0090] Figure 3 , formation parameter inversion flow chart;

[0091] Figure 4 , comparison chart of formation parameter inversion value and true value;

[0092] Figure 5 , the curve of the liquid level increment and bottom hole pressure of the formation parameter inversion pool changing with time;

[0093] Figure 6 , a comparison chart of the calculated and inverted values ​​of observed variables. DETAILED DESCRIPTION

[0094] The specific implementation of the present invention is described below in conjunction with examples:

[0095] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the conditions under which the present invention can be implemented. Any structural modification, change in proportional relationship or adjustment of size should still fall within the scope of the technical content disclosed in the present invention without affecting the efficacy and purpose that can be achieved by the present invention.

[0096] At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" quoted in this specification are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments to their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.

[0097] Example 1:

[0098] The present invention provides a method and system for inverting formation parameters for deep well gas invasion based on a gas-liquid two-phase flow model. First, a gas-liquid two-phase flow model is established based on the wellbore flow equation (the wellbore flow equation (model) includes: an annular transient gas-liquid two-phase flow model, a governing equation for single-phase liquid flow in the drill pipe, and auxiliary equations). The mathematical model is then discretely solved using a finite difference algorithm. An unscented Kalman filter (UKF) is then used to construct an inversion model for formation parameters. The formation pressure and production index during gas invasion are inverted using measured data of riser pressure and the difference between liquid inlet and outlet flow rates. The formation parameter inversion method provided by the present invention can accurately invert formation parameters, providing a basis for accurate prediction and effective control of gas invasion, and has broad application prospects.

[0099] The present invention provides a deep well gas invasion formation parameter inversion method, the main steps of which include:

[0100] 1. Establishment of wellbore flow model

[0101] First, in order to establish the annular transient gas-liquid two-phase flow model, the following assumptions are made:

[0102] (1) Ignore the distribution of flow velocity in the wellbore cross section and only consider the one-dimensional axial flow in the wellbore;

[0103] (2) The wellbore temperature selects a linear geothermal gradient;

[0104] (3) Ignore the effect of drilling cuttings on the annular air-liquid two-phase flow.

[0105] 1. Governing equations for gas-liquid two-phase flow in annulus

[0106] The governing equations of annular air-liquid two-phase flow include three equations: the drilling fluid mass conservation equation, the invading gas mass conservation equation, and the gas-liquid mixture momentum conservation equation.

[0107] The drilling fluid mass conservation equation is:

[0108]

[0109] Where: ρ a is the drilling fluid density in the annulus, kg / m 3 ; α l is the drilling fluid volume fraction, dimensionless; v l is the drilling fluid velocity in the annulus, m / s; A a is the cross-sectional area of ​​the annulus, m 2 .

[0110] The mass conservation equation of the intruding gas is:

[0111]

[0112] Where: ρ g is the gas density, kg / m 3 ; α g is the gas phase volume fraction, dimensionless; v g is the gas velocity, m / s.

[0113] Conservation equation of mixture momentum:

[0114]

[0115] Where: g is the acceleration due to gravity, 9.81m / s 2 ;P a is the annular pressure, Pa; θ is the wellbore inclination, ° (starting from the vertical direction); F f is the friction pressure drop per unit length, Pa / m.

[0116] The sum of the drilling fluid volume fraction and the invading gas volume fraction is 1:

[0117] α g +α l =1 (4)

[0118] In the drift flow equation, the gas phase velocity can be expressed as:

[0119] v g =C0(v g α g +v l α l )+v gr (5)

[0120] Where: C0 is the slip coefficient; v gr is the slip velocity, m / s.

[0121] According to the equation proposed by Shi et al., the slip coefficient and slip velocity can be expressed as:

[0122]

[0123] Where: A is the gas phase distribution coefficient in the liquid; γ is the reduction term of the slip coefficient; v c is the characteristic velocity, m / s.

[0124] According to the PVT model, the density of gas can be expressed as:

[0125]

[0126] Where M g is the gas molar mass, kg / mol; R is the gas constant, J / mol / K; Z is the gas deviation factor, calculated using the following formula:

[0127]

[0128] In the formula, A1~A 11 is the coefficient; T r is the comparative temperature, dimensionless; ρ r is the comparative density, dimensionless.

[0129] 2. Control equation of single-phase flow of liquid in drill pipe

[0130] The governing equations of the single-phase flow of liquid in the drill pipe include two equations: the drilling fluid mass conservation equation and the drilling fluid momentum conservation equation.

[0131] The drilling fluid mass conservation equation is:

[0132]

[0133] Where: ρ d is the density of drilling fluid in the drill pipe, kg / m 3 ;v d is the drilling fluid velocity in the drill pipe, m / s; A d is the cross-sectional area of ​​the drill pipe, m 2 .

[0134] The momentum conservation equation in the drill pipe is:

[0135]

[0136] Where: P d is the drilling fluid pressure in the pipe, Pa; D d is the inner diameter of the drill pipe, m.

[0137] 3. Auxiliary equations

[0138] The friction pressure drop per unit length F in the momentum conservation equation (Equation 3 and Equation 11) f The calculation formula is:

[0139]

[0140] Where: F f is the friction pressure drop per unit length, Pa / m; f is the Moody friction factor; D is the flow channel diameter (the inner diameter of the pipe in the drill pipe and the hydraulic diameter in the annulus), m; ρ is the density, kg / m 3 ; v is the fluid velocity, m / s.

[0141] The Moody friction factor f in formula (12) takes into account the influence of wall roughness and can be obtained as follows:

[0142]

[0143] Where Re is the Reynolds number;

[0144] In the gas-cut gas-liquid two-phase flow model, the relationship between the gas-cut rate and the production index and the formation pressure is defined by equation (14).

[0145] q g = J(P e -P b ) (14)

[0146] In equation (14), q g is the gas-cut rate, kg / s; J is the production index, kg / s / MPa; P e is the formation pressure, MPa; P b is the bottomhole pressure, MPa, and P b can be calculated by the gas-liquid two-phase flow model.

[0147] 4. Model solution (finite difference method)

[0148] The entire wellbore is discretized into N nodes, as shown in FIG. 1. The flow control equations of the wellbore-formation system are solved using the finite difference method. Figure 2

[0149] The annulus flow equation (equation 1-3) can be expressed as:

[0150]

[0151] In equation (1-3), the variables W, F(W), and Q(W) are functions of density, velocity, volume fraction, and pressure; j = 1, 2 represent the liquid and gas mass conservation equations; and j = 3 represents the gas-liquid two-phase momentum conservation equation.

[0152] The mass conservation equation can be expressed as:

[0153]

[0154] II. Formation parameter inversion method

[0155] During the gas-cut process, the surface inlet-outlet flow difference and the standpipe pressure are measurable. Therefore, the formation pressure and the production index during the gas-cut process are inverted using the measured data of the inlet-outlet flow difference and the standpipe pressure.

[0156] If the gas reaches the wellhead after the gas cut, the invasion amount is very large, and the site cannot let the gas reach the wellhead without taking well control measures (1 m 3 pool liquid level increment).

[0157] The surface inlet-outlet flow difference at different times is the liquid single-phase flow inlet-outlet flow difference, which can be expressed as:

[0158] ​Δq(t)=[Δq(t1),Δq(t2),…,Δq(t N )] (17)

[0159] Δq(t)=q out (t)-q in (t) (18)

[0160] Where t is time, s; Δq is the difference in liquid inlet and outlet flow, m 3 / min;q out is the liquid outlet flow difference, m 3 / min;q in is the liquid inlet flow difference, m 3 / min.

[0161] The riser pressure data measured at different times can be expressed as:

[0162] P sp (t)=[P sp (t1),P sp (t2),…,P sp (t N )] (19)

[0163] Where P sp is the riser pressure, MPa.

[0164] Taking formation pressure and production index as inversion parameters, the inversion parameters at different times are:

[0165] P e (t)=[P e (t1),P e (t2),…,P e (t N )] (20)

[0166] J(t)=[J(t1),J(t2),…,J(t N )] (twenty one)

[0167] Where P e is the formation pressure, MPa; J is the production index, kg / s / MPa.

[0168] Combined with the UKF algorithm, the formation pressure and production index are used as state values, and the inlet and outlet flow difference and standpipe pressure are used as observation values. The state variable (X) and observation variable (Z) in the inversion model can be expressed as follows:

[0169] X(k)=[P e (k),J(k)] T (twenty two)

[0170] Z(k)=[Δq(k),P sp (k)] T (twenty three)

[0171] The state model f(·) for formation parameter inversion using the UKF algorithm can be expressed as:

[0172] X(k)=X(k-1)+W(k) (24)

[0173] The formation parameter inversion process is as follows: Figure 3 shown.

[0174] Example 2:

[0175] The present invention will be further described below with reference to a simulated well.

[0176] Based on the gas invasion wellbore inversion model established in Example 1 above, combined with artificially generated data, real-time interpretation and calculation of formation pressure and production index were performed. First, the formation pressure and production index were preset as the true values ​​for inversion. The standpipe pressure and inlet and outlet flow rate difference were calculated using a gas-liquid two-phase flow model. Noise was added to this measured data, and inversion was performed using the inversion model. The basic data for the simulated wells used in this invention are shown in Table 1.

[0177] Table 1 Related parameters of simulated wells

[0178]

[0179] When the number of inverted formation parameters is two (i.e., formation pressure and formation production index are inverted simultaneously), the three relevant parameters in the unscented Kalman filter are set to: α = 0.1, β = 2, κ = 1. The standard deviations of the system noise of formation pressure and production index are set to 0.01 and 0.0002 respectively, and the standard deviations of the measurement noise of standpipe pressure and liquid inlet and outlet flow rate difference are set to 0.02 and 0.0001 respectively. Therefore, the covariance matrix of the inversion model is Q = diag[0.01 2 ,0.0002 2 ],R=diag[0.02 2 ,0.0001 2 ]. The initial values ​​of the inversion of formation pressure and production index are set to 75 MPa and 0.058 kg / s / MPa, respectively.

[0180] Figure 4 The inversion results of formation pressure and formation production index under this condition are shown. Figure 4 a) and the lower part ( Figure 4b) The comparison of the inversion value and the true value of the formation pressure and production index, respectively. The background color of the figure is pink (0-1640s), which is the gas invasion time period, and the gas migrates to the wellhead but does not reach the wellhead; the yellow background part (after 1840s), the gas has overflowed the wellhead. It can be seen from the figure that the formation parameters gradually approach the true value and remain stable after inversion. After 1000s, the relative error of the formation pressure is controlled within 0.1%, and the relative error of the production index is controlled within 8%. Thus, it is not difficult to conclude that the inversion of the formation parameters has achieved good results before the gas overflowed the wellhead.

[0181] Table 2 is the error analysis result of the formation pressure and the production index. During the inversion process, the RMSE of the formation pressure is 0.232, the ARE is 0.14%, the e max is the error of the inversion preset value and the true value of the formation pressure at the initial time of gas invasion, and the inversion result tends to be stable, i.e., e ave is 0.07% after 1000s. The maximum relative error of the production index is 47.8% at the initial time, the ARE is 16.2%, the root mean square error RMSE is 0.015, and e ave is 5.43% after 1000s.

[0182] Table 2-Error analysis of the inversion result of the formation parameters

[0183]

[0184] Figure 5 is the change curve of the pool liquid level increment and the bottom hole pressure with time, and from the red broken line, it can be seen that the increment increases to the warning value 1m 3 above, at this time, the bottom hole pressure drops to 74.05MPa, and before that, the model can more accurately invert the formation pressure and the production index.

[0185] Figure 6 (a) and Figure 6 (b) are the comparison of the inversion value and the observation value of the riser pressure and the liquid inlet and outlet flow difference, respectively. The observation value is calculated by the gas-liquid two-phase flow model, and the inversion value is obtained by the inversion model through UKF inversion. It can be seen that whether it is the riser pressure or the liquid inlet and outlet flow difference, the inversion value is basically consistent with the observation value. This shows that the model can quickly and accurately predict the unknown formation parameters, and provide accurate basis for subsequent wellbore pressure control.

[0186] In the inversion simulation of synthetic data, formation parameters at the initial gas invasion moment deviate significantly from their true values. However, as the inversion calculation progresses, the predicted values ​​of the state variables rapidly approach their true values ​​and remain stable, demonstrating the high accuracy of the inversion model. Furthermore, due to the different contributions of formation pressure and production index to standpipe pressure and the difference in liquid inlet and outlet flow rates, the inversion results differ. In this study, formation pressure performed better than production index in inversion.

[0187] The above data demonstrates that the present invention provides a method for inverting formation parameters for deep well gas invasion. This method can quickly and accurately invert formation parameters, and the inversion model achieves high accuracy before the pool liquid level increases to a warning value and gas overflows the wellbore. Furthermore, the inverted values ​​of standpipe pressure and the liquid inlet and outlet flow rate difference are highly consistent with the observed values, that is, the results calculated using the wellbore flow model. This also demonstrates the high accuracy and reliability of the inversion of formation pressure and production index.

[0188] Example 3:

[0189] The present invention provides a deep well gas invasion formation parameter inversion system based on a gas-liquid two-phase flow model. The system can be used to implement the above-mentioned deep well gas invasion formation parameter inversion method based on a gas-liquid two-phase flow model. Specifically, the deep well gas invasion formation parameter inversion system based on a gas-liquid two-phase flow model includes:

[0190] Wellbore flow modeling module, used to establish wellbore flow model;

[0191] A finite difference discretization module is used to discretize and solve the established wellbore flow model using a finite difference algorithm;

[0192] Unscented Kalman filter inversion module, used to build an inversion model of formation parameters in combination with the unscented Kalman filter UKF;

[0193] The data fusion and inversion module is used to invert the formation pressure and production index during the gas invasion process using the measurement data of the riser pressure and the liquid inlet and outlet flow difference.

[0194] Example 4:

[0195] This embodiment provides a terminal device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of a deep well gas invasion formation parameter inversion method based on a gas-liquid two-phase flow model, including the following steps:

[0196] A wellbore flow model was established and the finite difference algorithm was used to discretize the model. Combined with the unscented Kalman filter (UKF), an inversion model of formation parameters was constructed. The measured data of standpipe pressure and liquid inlet and outlet flow rate difference were used to invert the formation pressure and production index during the gas invasion process.

[0197] Example 5:

[0198] This embodiment provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and, of course, the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0199] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the above-mentioned embodiment related to a method for inverting deep well gas invasion formation parameters based on a gas-liquid two-phase flow model. The processor may load and execute the following steps:

[0200] A wellbore flow model was established and the finite difference algorithm was used to discretize the model. Combined with the unscented Kalman filter (UKF), an inversion model of formation parameters was constructed. The measured data of standpipe pressure and liquid inlet and outlet flow rate difference were used to invert the formation pressure and production index during the gas invasion process.

[0201] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0202] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0203] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0204] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process.Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0205] The preferred embodiments of the present invention are described in detail above, but the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

[0206] Many other changes and modifications can be made without departing from the spirit and scope of the present invention. It should be understood that the present invention is not limited to the specific embodiments, and the scope of the present invention is defined by the appended claims.

Claims

1. A deep well gas invasion formation parameter inversion method based on a gas-liquid two-phase flow model, characterized in that: The method comprises: A wellbore flow model was established and discretized using a finite difference algorithm. An unscented Kalman filter (UKF) was used to construct an inversion model for formation parameters. The measured data of standpipe pressure and the difference between liquid inlet and outlet flow rates were used to invert the formation pressure and production index during gas invasion. During the gas invasion process, the surface inlet and outlet flow difference and the riser pressure can be measured; the formation pressure and production index during the gas invasion process are inverted using the measured data of the inlet and outlet flow difference and the riser pressure; The difference in inlet and outlet flow rates at different times on the ground is the inlet and outlet flow rate difference of the liquid single-phase flow, which can be expressed as: Δq(t)=[Δq(t1),Δq(t2),…,Δq(t N )] (17) Δq(t)=q out (t)-q in (t) (18) Where t is time; Δq is the flow difference between the inlet and outlet of the liquid, m 3 / min;q out is the liquid outlet flow rate, m 3 / min;q in is the liquid inlet flow rate, m 3 / min; The riser pressure data measured at different times are expressed as: P sp (t)=[P sp (t1),P sp (t2),…,P sp (t N )] (19) Where P sp is the riser pressure, MPa; Taking formation pressure and production index as inversion parameters, the inversion parameters at different times are: P e (t)=[P e (t1),P e (t2),…,P e (t N )] (20) J(t)=[J(t1),J(t2),…,J(t N )] (21) Where P e is the formation pressure, MPa; J is the production index, kg / s / MPa; Combined with the UKF algorithm, the formation pressure and production index are used as state values, and the inlet and outlet flow difference and standpipe pressure are used as observation values. The state variable X and observation variable Z in the inversion model are expressed as follows: X(k)=[P e (k),J(k)] T (22) Z(k)=[Δq(k),P sp (k)] T (23) The state model f(·) for formation parameter inversion using the UKF algorithm is expressed as: X(k)=X(k-1)+W(k) (24).

2. The method for inversion of deep well gas invasion formation parameters based on a gas-liquid two-phase flow model according to claim 1, characterized in that: Establish a wellbore flow model, including: The first step is to build a gas-liquid two-phase flow control model in the annulus: First, the model neglects the cross-sectional velocity distribution, the temperature gradient is linear, and the influence of drilling cuttings is not considered. Then, the following equations are established: the drilling fluid mass conservation equation, the invading gas mass conservation equation, and the gas-liquid mixture momentum conservation equation. The drilling fluid mass conservation equation is: Where: ρ a is the drilling fluid density in the annulus, kg / m 3 ; α l is the drilling fluid volume fraction, dimensionless; v l is the drilling fluid velocity in the annulus, m / s; A a is the cross-sectional area of ​​the annulus, m 2 ; The mass conservation equation of the intruding gas is: Where: ρ g is the gas density, kg / m 3 ; α g is the gas phase volume fraction, dimensionless; v g is the gas velocity, m / s; Conservation equation of mixture momentum: Where: g is the acceleration due to gravity, 9.81m / s 2 ;P a is the annular pressure, Pa; θ is the wellbore inclination, °, starting from the vertical direction; F f is the friction pressure drop per unit length, Pa / m; The sum of the drilling fluid volume fraction and the gas phase volume fraction is 1: α g +α l ＝1 (4) In the drift flow equation, the gas velocity can be expressed as: v g =C0(v g α g +v l α l )+v gr (5) Where: C0 is the slip coefficient; v gr is the slip velocity, m / s; The slip coefficient and slip velocity can be expressed as: Where: A is the gas phase distribution coefficient in the liquid; γ is the reduction term of the slip coefficient; v c is the characteristic velocity, m / s; According to the PVT model, the density of gas can be expressed as: Where M g is the gas molar mass, kg / mol; R is the gas constant, J / mol / K; Z is the gas deviation factor, calculated using the following formula: In the formula, A1~A 11 is the coefficient; T r is the comparative temperature, dimensionless; ρ r is the comparative density, dimensionless; The second step is to construct the governing equation of the single-phase flow of liquid in the drill pipe: The governing equations of the single-phase flow of liquid in the drill pipe include two equations: the drilling fluid mass conservation equation and the drilling fluid momentum conservation equation; The drilling fluid mass conservation equation is: Where: ρ d is the density of drilling fluid in the drill pipe, kg / m 3 ;v d is the drilling fluid velocity in the drill pipe, m / s; A d is the cross-sectional area of ​​the drill pipe, m 2 ; The momentum conservation equation in the drill pipe is: Where: P d is the drilling fluid pressure in the pipe, Pa; D d is the inner diameter of the drill pipe, m; The third step is to construct the auxiliary equation: The momentum conservation equation, i.e. the friction pressure drop per unit length F in formula (3) and formula (11) f The calculation formula is: Where: F f is the friction pressure drop per unit length, Pa / m; f is the Moody friction factor; D is the flow channel diameter, the inner diameter of the pipe in the drill pipe; the hydraulic diameter in the annulus, m; ρ is the density, kg / m 3 ; v is the fluid velocity, m / s; The Moody friction factor f in formula (12) takes into account the influence of wall roughness and can be obtained as follows: Where Re is the Reynolds number; In the gas-liquid two-phase flow model of gas invasion, formula (14) is used to define the relationship between gas invasion rate, production index and formation pressure; q g =J(P e -P b ) (14) Where q g is the gas invasion rate, kg / s; J is the production index, kg / s / MPa; P e is the formation pressure, MPa; P b is the bottom hole pressure, MPa, P b It can be calculated using the gas-liquid two-phase flow model.

3. The deep well gas invasion formation parameter inversion system based on the gas-liquid two-phase flow model is characterized by: The system is used to perform the method according to any one of claims 1 to 2, and the system includes: Wellbore flow modeling module, used to establish wellbore flow model; A finite difference discretization module is used to discretize and solve the established wellbore flow model using a finite difference algorithm; Unscented Kalman filter inversion module, used to build an inversion model of formation parameters in combination with the unscented Kalman filter UKF; The data fusion and inversion module is used to invert the formation pressure and production index during the gas invasion process using the measurement data of the riser pressure and the liquid inlet and outlet flow difference.

4. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for inverting deep well gas invasion formation parameters based on a gas-liquid two-phase flow model according to any one of claims 1 to 2 is implemented.

5. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements a deep well gas invasion formation parameter inversion method based on a gas-liquid two-phase flow model according to any one of claims 1 to 2.

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