A rapid prediction method for bottom hole temperature in deep shale gas horizontal well drilling

Abstract

The present invention discloses a method for rapid prediction of bottom hole temperature in deep shale gas horizontal well drilling, comprising: using dimensional analysis to process the influencing parameters in dimensions to obtain parameter dimensions and basic dimensions; using Rayleigh method to process the parameters dimensionlessly to obtain dimensionless numbers; using multivariate nonlinear regression method to bring the test parameters into dimensionless numbers to obtain dimensionless number data results; screening multiple results of multivariate nonlinear regression to obtain a rapid prediction model for bottom hole temperature in drilling. The present invention fully considers the influence of multiple factors such as drilling fluid displacement, drill string rotation speed, drilling fluid density, drilling fluid inlet temperature and mechanical drilling speed, establishes a rapid prediction model for bottom hole temperature in deep shale gas horizontal well drilling, and performs multi-factor analysis to accurately predict the change of bottom hole temperature in the drilling process, which can effectively guide the drilling process of deep shale gas horizontal well.

Description

Technical Field

[0001] The present invention belongs to the technical field of deep shale gas, and in particular relates to a method for quickly predicting the bottom hole temperature of a deep shale gas horizontal well. Background Art

[0002] The target layer of deep shale gas, the Silurian Longmaxi Formation, is buried at a depth of 3600 to 5000m. The bottomhole circulation temperature during actual drilling is high, generally between 140 and 150°C. The average bottomhole circulation temperature after completion is 146°C, and the highest bottomhole circulation temperature reaches 167°C. When the bottomhole circulation temperature exceeds 140°C, the rubber parts will be damaged, and the rotary steerable instruments used generally have problems such as unstable signal transmission and frequent failures, resulting in a significant decrease in the stable downhole operation time of the rotary steerable instruments, which seriously affects the drilling time. The bottomhole temperature of deep shale gas horizontal well drilling increases with the increase of the horizontal section length, limiting the maximum extension length of the horizontal section.

[0003] At present, professional calculation software is often used to predict the bottom hole temperature of horizontal well drilling, but the existing software has slow calculation speed and is complicated to use. Or the existing software modeling process is complicated and the operation process is cumbersome, which is not convenient for reverse optimization and design of drilling fluid thermophysical parameters, and it is difficult to reduce the bottom hole temperature by adjusting the drilling fluid thermophysical parameters. Summary of the invention

[0004] The purpose of the present invention is to provide a method for quickly predicting the bottom hole temperature of deep shale gas horizontal wells in view of the above-mentioned deficiencies in the prior art, so as to solve the problems that the current calculation software for predicting the bottom hole temperature of horizontal wells is slow in calculation speed and complex in use.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for quickly predicting bottom hole temperature of a deep shale gas horizontal well, comprising the following steps:

[0007] S1. Dimensional analysis is used to process the parameters affecting the bottom hole temperature of deep shale gas horizontal well drilling to obtain parameter dimensions and basic dimensions;

[0008] S2. Based on the parameter dimension and the basic dimension, the Rayleigh method is used to perform dimensionless processing on the parameter to obtain a dimensionless number;

[0009] S3. Conduct mixed multi-factor orthogonal experimental design on the parameters affecting the bottom hole temperature of deep shale gas horizontal well drilling, and use the multivariate nonlinear regression method to bring the experimental parameters into dimensionless numbers to obtain dimensionless data results;

[0010] S4. Using different function forms to perform multivariate nonlinear regression on dimensionless data results, screening various results of multivariate nonlinear regression, and obtaining a rapid prediction model for bottom hole temperature of drilling;

[0011] S5. A rapid prediction of the well bottom temperature is achieved based on a rapid prediction model of the well bottom temperature.

[0012] Furthermore, the parameters affecting the bottom hole temperature of S1 deep shale gas horizontal well drilling include:

[0013] Drilling fluid density, specific heat capacity, thermal conductivity, displacement, well depth, surface temperature, inlet temperature, drill string speed and mechanical penetration rate;

[0014] Parameter dimensions include: bottom hole temperature dimension, drilling fluid density dimension, specific heat capacity dimension, thermal conductivity dimension, displacement dimension, well depth dimension, ground temperature dimension, inlet temperature dimension, drill string speed dimension and mechanical drilling rate dimension;

[0015] Basic dimensions include: length, mass, time, and temperature.

[0016] Furthermore, S2 specifically includes:

[0017] Based on the difference between the parameter dimension and the number of basic dimensions, the Rayleigh method is used to non-dimensionalize the parameters to obtain dimensionless numbers p1, p2, p3, p4, p5, p6;

[0018] Construct dimensionless equilibrium equations for dimensionless numbers p1, p2, p3, p4, p5, p6;

[0019] The dimensionless equilibrium equation is solved to obtain the dimensionless expression of the dimensionless number.

[0020] Furthermore, the dimensionless equilibrium equations of dimensionless numbers p1, p2, p3, p4, p5, and p6 are constructed as follows:

[0021]

[0022] Among them, T w is the bottom hole temperature; ρ is the drilling fluid density; c is the specific heat capacity; λ is the thermal conductivity; Q is the displacement; T g is the ground temperature; PRR is the drill string speed; T i is the inlet temperature; H is the well depth; ROP is the mechanical drilling rate; a 11 、a 12 、a 13 、a 14 、a 21 、a 22 、a 23 、a 24 、a 31 、a32 、a 33 、a 34 、a 41 、a 42 、a 43 、a 44 、a 51 、a 52 、a 53 、a 54 、a 61 、a 62 、a 63 、a 64 These are the unknown coefficients of the dimensionless equilibrium equations of p1, p2, p3, p4, p5, and p6.

[0023] Furthermore, the dimensionless equilibrium equations are solved, including:

[0024] Solve the dimensionless equilibrium equation for the dimensionless number p1:

[0025]

[0026] L:0=2a 12 +3a 13 +2a 14

[0027] T:0=-2a 12 -a 13 -3a 14

[0028] θ:0=1+a 11 -a 12 -a 14

[0029] a 11 =-1, a 12 =0,a 13 =0,a 14 =0

[0030] Solving the dimensionless equilibrium equation for the dimensionless number p2:

[0031]

[0032] L:0=1+2a 21 +3a 22 +a 24

[0033] T:0=-2a 21 -a 22

[0034] θ:0=a 21 -a 22 -a 24

[0035] a 21 =0.25,a 22 =0.25,a 23 =-0.5,a 24 =0

[0036] Solution of the dimensionless equilibrium equation for the dimensionless number p3:

[0037]

[0038] L:0=-3+2a 32 +3a 33 +2a 34

[0039] T:0=-2a 31 -a 33 -3a 34

[0040] θ:0=a 31 -a 32 -a 34

[0041] M=1

[0042] a 31 =0.25,a 32 =1.25,a 33 =-0.5,a 34 =-1

[0043] Solution of the dimensionless equilibrium equation for the dimensionless number p4:

[0044]

[0045] L:0=2a 42 +3a 43 +2a 44

[0046] T:0=-1-2a 42 -a 43 -3a 44

[0047] θ:0=a 41 -a 42 -a 44

[0048] a 41 =-0.75,a 42 =-0.75,a 43 =0.5,a 44 =0

[0049] Solution of the dimensionless equilibrium equation for the dimensionless number p5:

[0050]

[0051] L:0=-1+2a 52 +3a 53 +2a 54

[0052] T:0=1-2a 52 -a 53 -3a 54

[0053] θ:0=a 51 -a 52 -a 54

[0054] a 51 =-0.5,a 52 =-0.5,a 53 =0,a 54 =0

[0055] Solution of the dimensionless equilibrium equation for the dimensionless number p6:

[0056]

[0057] L:0=2a 62 +3a 63 +2a 64

[0058] T:0=-1+-2a 62 -a 63 -3a 64

[0059] θ:0=a 61 -a 62 -a 64

[0060] a 61 =-1,a 62 =-0,a 63 =0,a 64 =0

[0061] Where L is length, M is mass, T is time and θ is temperature.

[0062] Furthermore, based on the solution of the dimensionless equilibrium equation, the dimensionless expressions of dimensionless numbers are obtained, including:

[0063]

[0064]

[0065] Furthermore, the results of the multivariate nonlinear regression screened in S4 include:

[0066]

[0067] Among them, b1, b2, b3, b4, b5, and b6 are all unknown coefficients of multivariate nonlinear regression.

[0068] Furthermore, the rapid prediction model of the bottom hole temperature in S4 is:

[0069]

[0070] The method for quickly predicting the bottom hole temperature of a deep shale gas horizontal well provided by the present invention has the following beneficial effects:

[0071] The present invention fully considers the influence of multiple factors such as drilling fluid displacement, drill string rotation speed, drilling fluid density, drilling fluid inlet temperature and mechanical drilling speed, establishes a rapid prediction model for bottom hole temperature in deep shale gas horizontal well drilling, and conducts multi-factor analysis to accurately predict the change of bottom hole temperature during the drilling process, which can effectively guide the drilling process of deep shale gas horizontal wells.

[0072] The present invention can directly and quickly calculate the bottom hole temperature by using the rapid prediction model of the bottom hole temperature of drilling, and use the model to draw a design chart of the bottom hole temperature and the specific heat capacity-thermal conductivity of the drilling fluid, reversely infer and optimize the thermophysical property parameters of the drilling fluid, and provide a basis for the design of the thermophysical property parameters of the drilling fluid for downhole cooling. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 The present invention is a flow chart of a method for rapidly predicting bottom hole temperature during drilling of a deep shale gas horizontal well.

[0074] Figure 2 The figure is a comparison between the simulated bottom hole temperature and the bottom hole temperature calculated by the empirical model in Example 1 of the present invention.

[0075] Figure 3 This is a flow chart for designing the thermal physical property parameters of drilling fluid in Example 2 of the present invention.

[0076] Figure 4 This is the specific heat capacity-thermal conductivity design diagram in Example 2 of the present invention. DETAILED DESCRIPTION

[0077] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0078] Example 1

[0079] This embodiment provides a method for quickly predicting the bottom hole temperature of a deep shale gas horizontal well. Figure 1 , which specifically includes the following steps:

[0080] Step S1, using the dimensional analysis method to perform dimensional processing on the parameters affecting the bottom hole temperature of deep shale gas horizontal well drilling, to obtain parameter dimensions and basic dimensions, which specifically include the following contents:

[0081] The parameters affecting the bottom hole temperature in deep shale gas horizontal well drilling include:

[0082] Drilling fluid density, specific heat capacity, thermal conductivity, displacement, well depth, surface temperature, inlet temperature, drill string speed and mechanical penetration rate.

[0083] The parameter dimensions include: bottom hole temperature dimension, drilling fluid density dimension, specific heat capacity dimension, thermal conductivity dimension, displacement dimension, well depth dimension, ground temperature dimension, inlet temperature dimension, drill string speed dimension and mechanical drilling speed dimension, as shown in Table 1.

[0084] Table 1 Dimensions of various parameters

[0085]

[0086] The basic dimensions include: length, mass, time and temperature. See Table 2 for the basic dimensions.

[0087] Table 2 Basic dimension numbers involved in bottom hole cooling parameters

[0088]

[0089] Step S2: Based on the parameter dimension and the basic dimension, the Rayleigh method is used to perform dimensionless processing on the parameter to obtain a dimensionless number, which specifically includes the following contents:

[0090] From Table 1 and Table 2 in step S1, it can be seen that the total number of parameters n=10, the number of basic dimensions j=4, and the number of dimensionless parameters constructed k=10-4=6;

[0091] The Rayleigh method is used to non-dimensionalize the parameters and obtain dimensionless numbers p1, p2, p3, p4, p5, and p6;

[0092] Specifically, the dimensionless equilibrium equation for the dimensionless number p1 is established as follows:

[0093]

[0094] The solution to the dimensionless equilibrium equation for p1 is as follows:

[0095]

[0096] L:0=2a 12 +3a 13 +2a 14

[0097] T:0=-2a 12 -a 13 -3a 14

[0098] θ:0=1+a 11 -a 12 -a 14

[0099] a 11 =-1, a 12 =0,a 13 =0,a 14 =0

[0100] The dimensionless equilibrium equation for the dimensionless number p2 is established as follows:

[0101]

[0102] The solution to the dimensionless equilibrium equation of p2 is as follows:

[0103]

[0104] L:0=1+2a 21 +3a 22 +a 24

[0105] T:0=-2a 21 -a 22

[0106] θ:0=a 21 -a 22 -a 24

[0107] a 21 =0.25,a 22 =0.25,a 23 =-0.5,a 24 =0

[0108] The dimensionless equilibrium equation for the dimensionless number p3 is established as follows:

[0109]

[0110] The solution to the dimensionless equilibrium equation of p3 is as follows:

[0111]

[0112] L:0=-3+2a 32 +3a 33 +2a 34

[0113] T:0=-2a 31 -a 33 -3a 34

[0114] θ:0=a 31 -a 32 -a 34

[0115] M=1

[0116] a 31 =0.25,a 32 =1.25,a 33 =-0.5,a 34 =-1

[0117] The dimensionless equilibrium equation for the dimensionless number p4 is established as follows:

[0118]

[0119] The solution to the dimensionless equilibrium equation of p4 is as follows:

[0120]

[0121] L:0=2a 42 +3a 43 +2a 44

[0122] T:0=-1-2a 42 -a 43 -3a 44

[0123] θ:0=a 41 -a 42 -a 44

[0124] a 41 =-0.75,a 42 =-0.75,a 43 =0.5,a44 =0

[0125] The dimensionless equilibrium equation for the dimensionless number p5 is established as follows:

[0126]

[0127] The solution to the dimensionless equilibrium equation of p5 is as follows:

[0128]

[0129] L:0=-1+2a 52 +3a 53 +2a 54

[0130] T:0=1-2a 52 -a 53 -3a 54

[0131] θ:0=a 51 -a 52 -a 54

[0132] a 51 =-0.5,a 52 =-0.5,a 53 =0,a 54 =0

[0133] The dimensionless equilibrium equation for the dimensionless number p6 is established as follows:

[0134]

[0135] The solution to the dimensionless equilibrium equation of p6 is as follows:

[0136]

[0137] L:0=2a 62 +3a 63 +2a 64

[0138] T:0=-1+-2a 62 -a 63 -3a 64

[0139] θ:0=a 61 -a 62 -a 64

[0140] a 61 =-1,a 62 =-0,a 63 =0,a64 =0

[0141] Among them, a 11 、a 12 、a 13 、a 14 、a 21 、a 22 、a 23 、a 24 、a 31 、a 32 、a 33 、a 34 、a 41 、a 42 、a 43 、a 44 、a 51 、a 52 、a 53 、a 54 、a 61 、a 62 、a 63 、a 64 These are the unknown coefficients of the dimensionless equilibrium equations of p1, p2, p3, p4, p5, and p6.

[0142] Based on the solution of the dimensionless equilibrium equation, the dimensionless expression of the dimensionless number is obtained, as shown in Table 3.

[0143] Table 3 Dimensionless numbers and dimensionless expressions

[0144]

[0145]

[0146] The expressions in Table 3 can be expressed by the following correlation function f:

[0147] f(p1,p2,......,p6)=0

[0148] It can be seen that through the dimensional analysis of drilling fluid cooling technology, the bottom hole cooling problem is transformed into the problem of solving the correlation function f between 6 dimensionless parameters, which greatly simplifies the solution idea and reduces the difficulty of solution.

[0149] Step S3, a mixed multi-factor orthogonal experimental design is performed on the influencing parameters of the bottom hole temperature of the deep shale gas horizontal well drilling, and the experimental parameters are brought into dimensionless numbers by using the multivariate nonlinear regression method to obtain dimensionless number data results, which specifically include the following contents:

[0150] The drilling fluid circulation displacement, inlet temperature, drilling fluid specific heat capacity, thermal conductivity, density, rotation speed, and mechanical drilling speed were subjected to mixed multi-factor orthogonal experimental design, and the experimental parameters were brought into the dimensionless expression to fit the dimensionless parameters.

[0151] Specifically, there are 7 variables involved in the rapid prediction model of bottom hole temperature in deep shale gas horizontal well drilling. According to the characteristics of the parameters themselves, the 7 parameters are divided into different levels. The specific parameter value table is shown in Table 4.

[0152] Table 4 Multi-factor simulation test parameter value table

[0153]

[0154] A comprehensive experimental design for all parameters requires 32,000 groups of tests. The design scheme is streamlined and the orthogonal experimental design is used to obtain the results. The design results of the orthogonal experiment are shown in Table 5.

[0155] Table 5 Orthogonal experimental design results

[0156]

[0157]

[0158] Using the multivariate nonlinear regression method, the values ​​of the orthogonal experimental design results are substituted into the expressions of the dimensionless numbers Lp1~p6, and each dimensionless number is calculated. The calculation results are shown in Table 6.

[0159] Table 6 Dimensionless number calculation results

[0160]

[0161]

[0162] Step S4: perform multivariate nonlinear regression on the dimensionless data results using different function forms, screen the various results of the multivariate nonlinear regression, and obtain a rapid prediction model for the bottom hole temperature of the drilling well, which specifically includes the following contents:

[0163] The dimensionless parameter data results were subjected to multivariate nonlinear regression using different function forms, and the corresponding multivariate nonlinear regression results are shown in Table 7, where b1, b2, b3, b4, b5, b6, b7, b8, and b9 are unknown coefficients.

[0164] Table 7. Fitting regression values ​​of different functions

[0165]

[0166] By comparing the fitting accuracy of the above functions, the best function form is selected, and the fourth function is selected as the final correlation function fitting result. The unknown coefficients are shown in Table 8.

[0167] Table 8 Undetermined coefficients in correlation functions

[0168]

[0169] Substituting the undetermined coefficients in Table 8 into the fourth optimal function formula, a rapid prediction of the bottom hole temperature is obtained:

[0170]

[0171] Step S5: realizing a rapid prediction of the well bottom temperature based on the well bottom temperature rapid prediction model.

[0172] This embodiment further provides a verification of the rapid prediction model of the bottom hole temperature of the drilling well, which specifically includes the following steps:

[0173] refer to Figure 2 ,Comparing the bottom hole temperature of deep shale gas horizontal well drilling simulation and drilling bottom hole temperature rapid prediction model, Figure 2 It can be seen that Figure 2 The comparison between the bottom hole temperature of the drilling fluid obtained by simulation and the bottom hole temperature calculated by the empirical model is shown. The predicted values ​​of this embodiment are mostly distributed near the diagonal, and the relative error with the numerical simulation data is within 10%. Obviously, the accuracy of the rapid prediction model of the drilling bottom hole temperature of this embodiment is confirmed.

[0174] Example 2

[0175] This embodiment uses the drilling bottom temperature rapid prediction model constructed in the embodiment to draw a design chart of the bottom hole temperature and the specific heat capacity-thermal conductivity of the drilling fluid, and reversely infers and optimizes the thermal physical property parameters of the drilling fluid, which specifically includes the following contents:

[0176] The design of thermodynamic parameters for bottom hole cooling of deep shale gas horizontal wells is divided into two stages: the first stage is the design plate generation stage, and the second stage is the design of thermophysical parameters using the plate.

[0177] The first stage is the design board generation stage;

[0178] There are many factors that affect the bottom hole temperature of deep shale gas horizontal wells. Some parameters are target values ​​or engineering requirements, such as ground temperature, inlet temperature, displacement, mechanical drilling speed, drill string speed, etc. Therefore, in the rapid prediction model of drilling bottom hole temperature, the change of bottom hole temperature is affected by controlling the thermal conductivity and specific heat capacity of the drilling fluid. Figure 3 , which specifically includes the following steps:

[0179] T1. Input the parameter values ​​of drilling fluid density, displacement, rotation speed, mechanical drilling speed, well depth, inlet temperature, and ground temperature, and set the value range of drilling fluid thermal conductivity and specific heat capacity.

[0180] T2. Divide the range of drilling fluid specific heat capacity and thermal conductivity into different groups, select a group of values, and calculate the corresponding bottom hole temperature through the drilling bottom hole temperature rapid prediction model.

[0181] T3. Use the rapid prediction model of drilling bottom hole temperature to repeatedly calculate all points and obtain the bottom hole temperature T corresponding to the combination of drilling fluid specific heat capacity c and drilling fluid thermal conductivity λ under different conditions. w value.

[0182] T4. Generate a design chart of bottom hole temperature, specific heat capacity and thermal conductivity of drilling fluid.

[0183] The second stage is to design the thermophysical parameters using the design drawing, which specifically includes the following steps:

[0184] A1. Given the values ​​of the specific heat capacity c and thermal conductivity λ of the drilling fluid;

[0185] A2. Query λ on the design board min or c max The value of

[0186] A3. Bottom hole temperature T for a given drilling fluid specific heat capacity c and drilling fluid thermal conductivity λ w Carry out verification;

[0187] A4. If the bottom temperature T w If the expected temperature drop in the well is reached, then go to A4, otherwise go to A1 to readjust the values ​​of the specific heat capacity c and thermal conductivity λ of the drilling fluid until the bottom hole temperature T w Until the expected temperature drop range in the well is reached;

[0188] A5. Combine the values ​​of the specific heat capacity c and the thermal conductivity λ of the drilling fluid that meet the expected range requirements.

[0189] This embodiment is described with a specific case;

[0190] Input the basic parameter values ​​of drilling fluid density, displacement, ground temperature, inlet temperature, well depth, rotation speed and mechanical drilling speed, and design the combination of drilling fluid thermophysical property parameters, as shown in Table 9.

[0191] Table 9 Input basic parameter values

[0192] parameter value <![CDATA[ρ(kg / m 3) ]]> 2300 Q(L / s) 25 <![CDATA[T i (℃)]]> 40 PRR(rpm) 30 H(m) 6500 ROP(m / h) 10 <![CDATA[T g (℃)]]> 25

[0193] Use the drilling bottom hole temperature rapid prediction model to calculate the bottom hole temperature and draw a design chart of the bottom hole temperature, specific heat capacity and thermal conductivity of the drilling fluid, such as Figure 4 shown.

[0194] As the specific heat capacity of the drilling fluid decreases and the thermal conductivity increases, the bottom hole temperature T w Assuming that the expected bottom hole temperature is 128.5℃, it can be seen from the design drawing that in the combination of thermal conductivity and specific heat capacity of the designed drilling fluid, the maximum thermal conductivity cannot exceed 0.39W / (m·K) and the minimum specific heat capacity cannot be less than 1041.2J / (kg·K).

[0195] Although the specific implementation of the invention is described in detail in conjunction with the drawings, it should not be understood as limiting the scope of protection of this patent. Within the scope described in the claims, various modifications and variations that can be made by those skilled in the art without creative work still fall within the scope of protection of this patent.

Claims

1. A method for rapid prediction of bottom hole temperature during drilling of deep shale gas horizontal wells, characterized in that: The following steps are involved: S1. Dimensional analysis is used to process the parameters affecting the bottom hole temperature of deep shale gas horizontal well drilling to obtain parameter dimensions and basic dimensions; S2. Based on the parameter dimension and the basic dimension, the Rayleigh method is used to perform dimensionless processing on the parameter to obtain a dimensionless number; S3. Conduct mixed multi-factor orthogonal experimental design on the parameters affecting the bottom hole temperature of deep shale gas horizontal well drilling, and use the multivariate nonlinear regression method to bring the experimental parameters into dimensionless numbers to obtain dimensionless data results; S4. Using different function forms to perform multivariate nonlinear regression on dimensionless data results, screening various results of multivariate nonlinear regression, and obtaining a rapid prediction model for bottom hole temperature of drilling; S5. Realize the rapid prediction of the bottom hole temperature of the drilling well based on the rapid prediction model of the bottom hole temperature of the drilling well; The parameters influencing the bottom hole temperature of the S1 medium-deep shale gas horizontal well drilling include: Drilling fluid density, specific heat capacity, thermal conductivity, displacement, well depth, surface temperature, inlet temperature, drill string speed and mechanical penetration rate; Parameter dimensions include: bottom hole temperature dimension, drilling fluid density dimension, specific heat capacity dimension, thermal conductivity dimension, displacement dimension, well depth dimension, ground temperature dimension, inlet temperature dimension, drill string speed dimension and mechanical drilling rate dimension; Basic dimensions include: length, mass, time, and temperature; The S2 specifically includes: Based on the difference between the parameter dimension and the number of basic dimensions, the Rayleigh method is used to non-dimensionalize the parameters to obtain dimensionless numbers p1, p2, p3, p4, p5, p6; Construct dimensionless equilibrium equations for dimensionless numbers p1, p2, p3, p4, p5, p6; Solve the dimensionless equilibrium equation to obtain the dimensionless expression of the dimensionless number; The rapid prediction model for the bottom hole temperature in S4 is: Among them, T w is the bottom hole temperature; ρ is the drilling fluid density; c is the specific heat capacity; λ is the thermal conductivity; Q is the displacement; T g is the ground temperature; PRR is the drill string speed; T i is the inlet temperature; H is the well depth; ROP is the mechanical drilling rate.

2. The method for rapid prediction of bottom hole temperature during drilling of deep shale gas horizontal wells according to claim 1, characterized in that: Construct the dimensionless equilibrium equations of dimensionless numbers p1, p2, p3, p4, p5, and p6, respectively: Among them, a 11 、a 12 、a 13 、a 14 、a 21 、a 22 、a 23 、a 24 、a 31 、a 32 、a 33 、a 34 、a 41 、a 42 、a 43 、a 44 、a 51 、a 52 、a 53 、a 54 、a 61 、a 62 、a 63 、a 64 These are the unknown coefficients of the dimensionless equilibrium equations of p1, p2, p3, p4, p5, and p6.

3. The method for rapid prediction of bottom hole temperature during drilling of deep shale gas horizontal wells according to claim 2, characterized in that: Solve dimensionless equilibrium equations, including: Solve the dimensionless equilibrium equation for the dimensionless number p1: <h2 style=";text-align:left;direction:ltr">L:0=2a<h2 style=";text-align:left;direction:ltr"> 12 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 13 <h2 style=";text-align:left;direction:ltr"> +2a<h2 style=";text-align:left;direction:ltr"> 14 T:0=-2a 12 -a 13 -3a 14 θ:0=1+a 11 -a 12 -a 14 a 11 =-1,a 12 =0,a 13 =0,a 14 =0 Solving the dimensionless equilibrium equation for the dimensionless number p2: <h2 style=";text-align:left;direction:ltr">L:0=1+2a<h2 style=";text-align:left;direction:ltr"> 21 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 22 <h2 style=";text-align:left;direction:ltr"> +a<h2 style=";text-align:left;direction:ltr"> 24 T:0=-2a 21 -a 22 θ:0=a 21 -a 22 -a 24 a 21 =0.25,a 22 =0.25,a 23 =-0.5,a 24 =0 Solution of the dimensionless equilibrium equation for the dimensionless number p3: <h2 style=";text-align:left;direction:ltr">L:0=-3+2a<h2 style=";text-align:left;direction:ltr"> 32 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 33 <h2 style=";text-align:left;direction:ltr"> +2a<h2 style=";text-align:left;direction:ltr"> 34 T:0=-2a 31 -a 33 -3a 34 θ:0=a 31 -a 32 -a 34 M＝1 a 31 =0.25,a 32 =1.25,a 33 =-0.5,a 34 =-1 Solution of the dimensionless equilibrium equation for the dimensionless number p4: <h2 style=";text-align:left;direction:ltr">L:0=2a<h2 style=";text-align:left;direction:ltr"> 42 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 43 <h2 style=";text-align:left;direction:ltr"> +2a<h2 style=";text-align:left;direction:ltr"> 44 T:0=-1-2a 42 -a 43 -3a 44 θ:0=a 41 -a 42 -a 44 a 41 =-0.75,a 42 =-0.75,a 43 =0.5,a 44 =0 Solution of the dimensionless equilibrium equation for the dimensionless number p5: <h2 style=";text-align:left;direction:ltr">L:0=-1+2a<h2 style=";text-align:left;direction:ltr"> 52 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 53 <h2 style=";text-align:left;direction:ltr"> +2a<h2 style=";text-align:left;direction:ltr"> 54 T:0=1-2a 52 -a 53 -3a 54 θ:0=a 51 -a 52 -a 54 a 51 =-0.5,a 52 =-0.5,a 53 =0,a 54 =0 Solution of the dimensionless equilibrium equation for the dimensionless number p6: <h2 style=";text-align:left;direction:ltr">L:0=2a<h2 style=";text-align:left;direction:ltr"> 62 <h2 style=";text-align:left;direction:ltr"> +3a<h2 style=";text-align:left;direction:ltr"> 63 <h2 style=";text-align:left;direction:ltr"> +2a<h2 style=";text-align:left;direction:ltr"> 64 T:0=-1+-2a 62 -a 63 -3a 64 θ:0=a 61 -a 62 -a 64 a 61 =-1,a 62 =-0,a 63 =0,a 64 =0 Where L is length, M is mass, T is time and θ is temperature.

4. The method for rapid prediction of bottom hole temperature during drilling of deep shale gas horizontal wells according to claim 3, characterized in that: Based on the solution of the dimensionless equilibrium equation, the dimensionless expressions of dimensionless numbers are obtained, including:

5. The method for rapid prediction of bottom hole temperature during drilling of deep shale gas horizontal wells according to claim 1, characterized in that: The results of the multivariate nonlinear regression screened in S4 include: Among them, b1, b2, b3, b4, b5, and b6 are all unknown coefficients of multivariate nonlinear regression.

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