Horizontal well multiphase flow temperature prediction method and device considering micro-thermal effect and formation damage

Abstract

The invention discloses a horizontal well multiphase flow temperature prediction method and device considering a micro-thermal effect and formation damage. The method comprises the steps that S01, an oil reservoir model is established, wherein the oil reservoir model comprises an oil reservoir seepage model and an oil reservoir thermal model considering at least one micro-thermal effect; s02, a wellbore model is established, wherein the wellbore model comprises a wellbore flow model and a wellbore thermal model considering the Joule-Thomson effect and the heat exchange and gravity effect between a wellbore and a stratum; s03, an oil reservoir and wellbore coupling model is established, the inflow temperature of fluid flowing into the wellbore from the oil reservoir at the well wall is calculated, the influence of damage of strata nearby the wellbore on temperature distribution is considered in the process, and the inflow temperature is determined by solving a radial temperature equation for distinguishing a damaged area and an undamaged area; and S04, on the basis of the model and the inflow temperature, a numerical solution method is adopted for iterative solution, and the temperature profile along the horizontal well shaft is obtained. The horizontal well temperature distribution can be predicted more accurately, and technical support is provided for efficient development of oil and gas fields.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field exploration and development, and in particular to a technology for predicting the temperature field of an oil and gas well, and more particularly to a method and device for accurately predicting the temperature profile of a horizontal well multiphase flow taking into account the influence of microthermal effects and formation damage. Background Art

[0002] Horizontal wells are widely used in the efficient development of modern oil and gas fields due to their advantages, such as large contact area with the reservoir and high single-well production. However, during horizontal well production, the temperature distribution within the wellbore is affected by a variety of complex factors. Accurately predicting the temperature profile of horizontal wells is crucial for understanding fluid production dynamics, identifying water- or gas-producing zones, optimizing production schedules, and making intelligent completion decisions.

[0003] Existing wellbore temperature prediction models often have limitations when dealing with horizontal wellbore problems. For example, some models may simplify thermal physics processes and ignore subtle thermal effects generated by fluid flow in porous media and wellbores, such as the Joule-Thomson effect, viscous dissipation, and thermal expansion of the fluid. For horizontal wells, since the wellbore is typically located in the same or adjacent formations with relatively small geothermal variations, the contribution of these microthermal effects to the wellbore temperature distribution can become significant.

[0004] Furthermore, during drilling, completion, and production, formation damage zones may form near the wellbore due to factors such as drilling fluid filtrate intrusion and solid particle blockage. This damage can reduce permeability near the wellbore, generating additional pressure drop, which in turn affects the fluid inflow temperature and the temperature distribution within the wellbore. Existing models do not adequately consider the coupling of formation damage with temperature prediction.

[0005] Therefore, how to establish a more accurate horizontal well multiphase flow temperature prediction model that can comprehensively consider the micro-thermal effect and formation damage is a technical problem that needs to be solved urgently in the current oil and gas extraction field. Summary of the Invention

[0006] The purpose of the present invention is to provide a method and device for predicting the temperature of multiphase flow in horizontal wells taking into account micro-thermal effects and formation damage, aiming to solve the technical problem that the horizontal well temperature prediction model in the existing technology does not take micro-thermal effects and formation damage into consideration, resulting in low prediction accuracy.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for predicting the temperature of multiphase flow in a horizontal well taking into account microthermal effects and formation damage, comprising the following steps:

[0008] S01. Establishing a reservoir model, the reservoir model comprising: a reservoir flow model describing the multiphase fluid flow process in the reservoir; and a reservoir thermal model describing the energy transfer process in the reservoir, the reservoir thermal model taking into account at least one microthermal effect of heat conduction, heat convection, Joule-Thomson effect, viscous dissipation, and thermal expansion;

[0009] S02. Establishing a wellbore model, wherein the wellbore model includes: a wellbore flow model describing the flow state of multiphase fluid in the horizontal wellbore; and a wellbore thermal model describing the energy transfer process in the horizontal wellbore, wherein the wellbore thermal model takes into account the Joule-Thomson effect, heat exchange between the wellbore and the formation, and gravity effect;

[0010] S03. Establishing a coupling model between the reservoir model and the wellbore model, and calculating the inflow temperature of the fluid flowing from the reservoir into the wellbore at the wellbore wall using the coupling model, wherein the influence of formation damage near the wellbore on the temperature distribution is further considered when calculating the inflow temperature;

[0011] S04. Based on the inflow temperature calculated by the reservoir model, the wellbore model, and the coupling model, a numerical solution method is used to iteratively solve the inflow temperature to obtain a temperature profile along the horizontal wellbore.

[0012] As a preferred solution, the reservoir thermal model is based on the principle of conservation of energy and describes the change of reservoir temperature T through the following equation:

[0013]

[0014] Where φ is the porosity, S i is the saturation of phase i fluid, ρ i is the density of phase i fluid, C pi is the specific heat capacity of phase i fluid, ρ r is the rock density, C pr is the specific heat capacity of rock, t is time, β i is the isobaric thermal expansion coefficient of phase i fluid, p i is the pressure of phase i fluid, u i is the seepage velocity vector of phase i fluid, g is the acceleration of gravity, D is the vertical depth, and λ is the comprehensive thermal conductivity of the reservoir.

[0015] As another preferred solution, the wellbore thermal model is based on the principle of conservation of energy and describes the change of the wellbore temperature T along the wellbore axis x by the following equation:

[0016]

[0017] Where p is the wellbore pressure, K TT is the Joule-Thomson coefficient, R is the wellbore radius, T1 is the inflow temperature, αT,1 is the total heat transfer coefficient considering the degree of wellbore opening, θ is the well inclination angle, subscript T represents the sum of multiphase mixed fluid, ρv is the mass flow rate, C p is the specific heat capacity.

[0018] As a further preferred solution, the inflow temperature T1 considering the influence of formation damage is obtained by solving the radial steady-state temperature equation, which is established in the damaged zone and the undamaged area respectively, and considers the continuity of temperature and heat flux density inside and outside the damaged zone.

[0019] Furthermore, the radial steady-state temperature equation is in the form of:

[0020]

[0021] Where r is the radial distance, T is the temperature at the radial distance, λ is the thermal conductivity, C1, C2, and C3 are coefficients related to fluid properties, flow parameters, and formation permeability; within the damage zone, the formation permeability is taken as the damage zone permeability k d .

[0022] As a further preferred solution, the numerical solution method includes discretizing the reservoir model and the wellbore model using a finite difference method, and iteratively solving the coupled system.

[0023] To achieve the above-mentioned objectives, the present invention also provides a horizontal well multiphase flow temperature prediction device taking into account micro-thermal effects and formation damage, which includes: one or more processors; and a memory, in which instructions executed by the one or more processors are stored, and the instructions are used to execute any of the aforementioned methods.

[0024] Specifically, the instructions of the device can be configured to include: a reservoir modeling module, which is used to establish a reservoir model including a reservoir seepage model and a reservoir thermal model that takes into account at least one micro-thermal effect; a wellbore modeling module, which is used to establish a wellbore model including a wellbore flow model and a wellbore thermal model that takes into account the Joule-Thomson effect, heat exchange between the wellbore and the formation, and gravity effect; a coupling modeling module, which is used to establish a reservoir and wellbore coupling model and calculate the inflow temperature that takes into account the influence of formation damage; and a model solving module, which is used to perform iterative solving based on the reservoir model, wellbore model and inflow temperature to obtain a temperature profile along the horizontal wellbore.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] By comprehensively considering various micro-thermal effects such as heat conduction, heat convection, Joule-Thomson effect, viscous dissipation and thermal expansion in the reservoir thermal model, and combining the consideration of Joule-Thomson effect, heat exchange and gravity effect in the wellbore thermal model, the present invention can more finely characterize the thermal physical processes in the horizontal well system, improve the physical authenticity of temperature prediction, and is particularly suitable for horizontal well sections where the geothermal gradient does not change significantly.

[0027] The present invention innovatively introduces a quantitative calculation of the impact of formation damage into the reservoir and wellbore coupling model. By establishing a radial temperature distribution equation to distinguish between the damaged zone and the undamaged zone, and solving it to obtain the inflow temperature taking the damage into account, it can more accurately reflect the actual impact of the additional pressure drop caused by formation damage on the wellbore temperature profile, which is particularly important for temperature prediction of damaged wells.

[0028] By combining a detailed reservoir model, a wellbore model, and a coupled inflow temperature model that considers formation damage, and employing a numerical iterative solution method, this paper constructs a more complete and robust framework for predicting multiphase flow temperature in horizontal wells. This method comprehensively analyzes the complex influences of multiple factors on temperature distribution, thereby providing more accurate predictions of horizontal well temperature profiles. This provides a reliable foundation for subsequent applications such as interpretation of production profiles and identification of water outlet points. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings are briefly described below:

[0030] Figure 1 A schematic flow chart of a method for predicting temperature of multiphase flow in horizontal wells taking into account microthermal effects and formation damage provided by the present invention;

[0031] Figure 2 solving iterative steps for the coupled model of the present invention;

[0032] Figure 3 A schematic diagram of a grid for coupling a wellbore and an oil reservoir according to the present invention;

[0033] Figure 4 This is a schematic diagram of the formation damage zone of the present invention;

[0034] Figure 5 A schematic diagram of the module structure of a horizontal well multiphase flow temperature prediction device considering micro-thermal effects and formation damage provided by the present invention. DETAILED DESCRIPTION

[0035] The software embodiments of the present invention are further described below in conjunction with the accompanying drawings, but the present invention is not limited to the following embodiments. It should be understood by those skilled in the art that the steps, modules, parameters, and equations described in this specification are merely exemplary and are intended to clearly illustrate the core concept of the present invention and are not intended to limit the scope of the present invention. Various modifications and combinations of these specific implementations may be made without departing from the spirit and scope of the present invention.

[0036] Example 1:

[0037] In order to better understand the present invention, the following Figure 1 The first embodiment of the method for predicting temperature of multiphase flow in horizontal wells taking into account micro-thermal effects and formation damage provided by the present invention is described in detail.

[0038] like Figure 1 As shown, the method of the present invention may include the following steps:

[0039] First, execute step S01: Establish a reservoir model. The reservoir model is used to describe the flow and heat transfer of fluids in the formation surrounding the wellbore. This model typically includes a reservoir flow model and a reservoir thermal model. a) Reservoir flow model: This model describes the flow behavior of multiphase fluids such as oil and water in porous media based on the principle of mass conservation and Darcy's law for multiphase flow. For oil-water two-phase flow, the continuity equation can be expressed as:

[0040]

[0041] Among them, ρ o ,ρ w are the densities of the oil phase and the water phase, respectively; u o ,u w are the seepage velocity vectors of the oil phase and water phase respectively; φ is the formation porosity; S o ,S w are the saturations of the oil phase and the water phase respectively; t is the time. The seepage velocity is given by Darcy's law:

[0042]

[0043] Where, subscript i represents the fluid phase (oil phase o or water phase w); k is the absolute permeability of the formation; k ri is the relative permeability of phase i; μ i is the viscosity of phase i; p i is the pressure of phase i; g is the gravitational acceleration scalar; is the depth gradient vector. Combining the continuity equation and Darcy's law, we can obtain a set of partial differential equations describing the pressure and saturation distribution.

[0044] b) Reservoir thermal model: This model is based on the principle of energy conservation and describes the temperature changes in the reservoir caused by fluid flow, heat conduction, heat convection, and various microthermal effects. The reservoir temperature equation considering microthermal effects is:

[0045]

[0046] The physical meanings of each term are as follows: the first term on the left side of the equation is the rate of change of the internal energy of the reservoir system (fluid and rock); the second term is the thermal expansion effect caused by the change of pressure over time. The first term on the right side of the equation is the thermal convection term, which represents the transport of heat carried by fluid flow; the second term is the viscous dissipation term, which represents the conversion of work done by the fluid to heat energy by overcoming flow resistance; the third term is the thermal expansion effect caused by the pressure gradient (a manifestation of the Joule-Thomson effect); the fourth term is the potential energy change term; and the fifth term is the heat conduction term, which represents the heat transfer of molecular thermal motion through temperature difference. Among them, φ is the porosity, S i is the saturation of phase i fluid, ρ i is the density of phase i fluid, C pi is the specific heat capacity of phase i fluid, ρ r is the rock density, C pr is the specific heat capacity of rock, t is the time, is the isobaric thermal expansion coefficient of phase i fluid, p i is the pressure of phase i fluid, u i is the seepage velocity vector of phase i fluid, g is the acceleration of gravity, D is the vertical depth, and λ is the comprehensive thermal conductivity of the reservoir. In essence The Joule-Thomson effect is primarily due to the temperature change caused by pressure changes, and is related to the thermal expansion coefficient.

[0047] Then, execute step S02: establish a wellbore model. The wellbore model is used to describe the flow and heat transfer process of multiphase fluid in the horizontal wellbore. This model usually includes a wellbore flow model and a wellbore thermal model. a) Wellbore flow model: This model calculates parameters such as pressure, flow rate, and phase holdup at each point in the wellbore based on the principles of conservation of mass and momentum. For steady-state multiphase flow, the wellbore pressure gradient equation can be expressed as:

[0048]

[0049] Where p is the wellbore pressure, x is the distance along the wellbore axis, and ρ m is the density of the mixed fluid, f is the Fanning friction coefficient, v m is the mixed fluid velocity, R is the wellbore radius, g is the acceleration due to gravity, and θ is the well inclination angle. The exact momentum equation is more complex, but the core is to consider frictional pressure drop, acceleration pressure drop, and gravity pressure drop.

[0050] b) Wellbore thermal model: This model is based on the principle of conservation of energy and describes the temperature changes of the fluid in the wellbore due to heat exchange with the formation, Joule-Thomson effect, frictional heating (already included in the temperature change caused by the pressure gradient). The steady-state wellbore temperature equation is:

[0051]

[0052] Where T is the wellbore temperature, T1 is the inflow temperature of the fluid flowing from the formation into the wellbore at the wellbore wall. The first term is the temperature change caused by the Joule-Thomson effect (including fluid expansion / compression and phase change); the second term is the convective heat transfer between the wellbore and the formation (through the total heat transfer coefficient α T,1 This coefficient takes into account the wellbore opening degree γ, the heat capacity of the inflowing fluid, and the heat transfer coefficient α between the wellbore wall and the formation; the third term is the temperature change corresponding to the potential energy change (potential height change) caused by gravity. Where H is enthalpy. The overall heat transfer coefficient α T,1 Defined as γ(ρvC p ) T,1 +(1-γ)α.

[0053] Next, execute step S03: establish a coupled model of the reservoir and wellbore, calculate the inflow temperature T1, and consider formation damage. The inflow temperature T1 is a key parameter connecting the reservoir model and the wellbore model. It is the temperature of the fluid before it enters the wellbore from the reservoir and mixes with the main fluid in the wellbore. Figure 3 , the fluid flows from the reservoir equivalent boundary (radius r e , temperature T e , pressure P e ) flows into the wellbore (radius r w , temperature T wb , pressure P wb If there is formation damage, there will be a damage zone (radius r) near the wellbore wall. d , permeability k d ), whose permeability is lower than the original formation permeability k. Inflow temperature T1 (i.e. r=r w The calculation of the formation fluid temperature at the reservoir requires solving the radial steady-state or transient temperature distribution equation from the reservoir to the wellbore. In this embodiment, the steady-state radial temperature equation is used. This equation is a second-order ordinary differential equation:

[0054]

[0055] The coefficients C1, C2, and C3 are defined as follows (refer to the original OCR content formula 4-176):

[0056]

[0057] Here m=(P e -P wb ) / ln(r e / r w ) is a coefficient related to the pressure gradient. The general solution of the equation is in:

[0058]

[0059] According to the solution of Euler's equation, n1 and n2 are the roots of the characteristic equation λn(n-1)+C1n-C2=0. The coefficient a corresponds to (C1-λ) / λ, and the constant term b corresponds to C3 / C2. The boundary conditions are:

[0060]

[0061] Where α is the convection heat transfer coefficient at the well wall. The integration constants l1 and l2 can be determined by these two boundary conditions. Then the inflow temperature T1 = T(r w ).

[0062] When considering formation damage (see Figure 3 ), the solution area is divided into the unharmed area (r d ≤r≤r e ) and the damage area (r w ≤r≤r d ):

[0063] When r d ≤r≤r e Time (undamaged area, permeability k)

[0064] When r w ≤r≤r d When (damage area, permeability k d )

[0065] In the damage zone, the permeability k in the equation is replaced by the damage zone permeability k d , so the coefficients C1, C2, C3 become C′1, C′2, C′3, the characteristic roots become n3, n4, and the constant term becomes The additional boundary condition is that r = r d The temperature and heat flux are continuous at:

[0066] T(r d ) 未伤害区 =T(r d ) 伤害区

[0067]

[0068] Simultaneous boundary conditions (acting on r e ), (acts on r w ), and, we can solve the four integral constants c1, c2, c3, c4. Then the inflow temperature considering the formation damage is

[0069] Finally, execute step S04: solve the coupling model to obtain the temperature profile. The reservoir seepage model, reservoir thermal model, wellbore flow model, wellbore thermal model and the calculated inflow temperature T1 are combined to form a complex nonlinear coupling equation system. A numerical solution method, such as the finite difference method, is used to discretize time and space. Figure 2 , the solution process is usually iterative:

[0070] (1) Input basic parameters, including reservoir and wellbore parameters, fluid physical properties, production system parameters and thermodynamic parameters;

[0071] (2) In each time step, the reservoir pressure and saturation distribution are calculated using the reservoir flow model;

[0072] (3) Calculate the wellbore pressure distribution using the wellbore pressure gradient equation;

[0073] (4) Substitute the calculated reservoir pressure and saturation into the reservoir temperature equation to calculate the reservoir temperature distribution;

[0074] (5) Using the reservoir temperature T calculated in the previous time step e,n and wellbore temperature T wb,n Substitute into the coupled temperature equation to calculate the inflow temperature T I,n+1 ;

[0075] (6) The calculated T I,n+1 Substitute into the wellbore temperature equation to calculate the new wellbore temperature T wb,n+1 ;

[0076] (7) The wellbore temperature T wb,n+1 and T wb,n Comparison is performed. If the accuracy requirement is met, the wellbore temperature is converged. Otherwise, the inflow temperature distribution and the wellbore temperature distribution are iteratively updated until convergence.

[0077] Finally, the temperature profiles along the horizontal wellbore at different times are obtained.

[0078] Example 2:

[0079] Reference Figure 5The present invention also provides an embodiment of a device 10 for predicting the temperature of multiphase flow in horizontal wells that takes into account micro-thermal effects and formation damage. The device 10 can be a general-purpose computer device, a dedicated data processing server or an embedded system, and its core is the computing logic for implementing the aforementioned method. The device 10 may include: one or more processors 20 (such as CPU, GPU or dedicated processor); a memory 30 (such as RAM, ROM, hard disk drive), and the memory 30 stores computer program instructions that can be executed by the processor 20. When the processor 20 executes these instructions, the device 10 is configured to implement the method described in Example 1. Specifically, these instructions can be organized into the following functional modules (logically divided, physically may be executed by the same processor):

[0080] Reservoir modeling module 21: used to execute method step S01. This module is responsible for establishing a reservoir seepage model and a reservoir thermal model based on input reservoir geological parameters and fluid physical parameters. The thermal model has built-in calculation logic for micro-thermal effects such as heat conduction, heat convection, Joule-Thomson effect, viscous dissipation, and thermal expansion.

[0081] Wellbore modeling module 22: used to execute method step S02. This module is responsible for establishing a wellbore flow model and a wellbore thermal model based on input wellbore structural parameters, completion parameters, fluid physical properties, etc. The thermal model has built-in calculation logic for the Joule-Thomson effect, heat exchange between the wellbore and the formation, and gravity effects.

[0082] The coupled modeling module 23 is used to execute step S03 of the method. This module is responsible for calculating the inflow temperature T1 of the fluid flowing from the reservoir into the wellbore at the wellbore wall. The core function is to solve the radial temperature distribution equation, especially including the consideration of formation damage, that is, to be able to calculate the radial temperature distribution equation based on the existence of the damage zone and the parameters of the damage zone (such as permeability k d , radius r d ), select appropriate boundary conditions and solution strategies to determine the inflow temperature T1.

[0083] Model Solver Module 24: Executes step S04. This module integrates the reservoir model, wellbore model, and the inflow temperature T1 calculated by the coupled modeling module 23. It solves the entire coupled system using a numerical solution algorithm (e.g., finite difference method combined with iterative techniques). It controls the entire computational process, including time stepping and iterative convergence determination, ultimately outputting a temperature profile along the horizontal wellbore.

[0084] In addition, the device 10 may further include an input / output interface for receiving model parameters, production data, etc. input by a user, and outputting the calculated temperature profile results, for example, in the form of a data file or a graphical interface.

[0085] It should be noted that the above embodiments are intended only to illustrate the present invention and are not intended to limit it. Any modifications or equivalent substitutions made by persons skilled in the art within the scope of this disclosure are encompassed by the scope of protection of this invention. For example, the specific numerical solution method, the combination of microthermal effects, and the specific parameterization of the formation damage model are all subject to numerous variations.

Claims

1. A method for predicting temperature of multiphase flow in horizontal wells considering microthermal effect and formation damage, characterized in that: The steps include: S01. Establishing a reservoir model, the reservoir model comprising: a reservoir flow model describing the multiphase fluid flow process in the reservoir; and a reservoir thermal model describing the energy transfer process in the reservoir, the reservoir thermal model taking into account at least one microthermal effect of heat conduction, heat convection, Joule-Thomson effect, viscous dissipation, and thermal expansion; S02. Establishing a wellbore model, wherein the wellbore model includes: a wellbore flow model describing the flow state of multiphase fluid in the horizontal wellbore; and a wellbore thermal model describing the energy transfer process in the horizontal wellbore, wherein the wellbore thermal model takes into account the Joule-Thomson effect, heat exchange between the wellbore and the formation, and gravity effect; S03. Establishing a coupling model between the reservoir model and the wellbore model, and calculating the inflow temperature of the fluid flowing from the reservoir into the wellbore at the wellbore wall using the coupling model, wherein the influence of formation damage near the wellbore on the temperature distribution is further considered when calculating the inflow temperature; S04. Based on the inflow temperature calculated by the reservoir model, the wellbore model, and the coupling model, a numerical solution method is used to iteratively solve the inflow temperature to obtain a temperature profile along the horizontal wellbore.

2. The method according to claim 1, characterized in that The reservoir thermal model is based on the principle of energy conservation and describes the change of reservoir temperature T through the following equation: Where φ is the porosity, S i is the saturation of phase i fluid, ρ i is the density of phase i fluid, C pi is the specific heat capacity of phase i fluid, ρ r is the rock density, C pr is the specific heat capacity of rock, t is time, β i is the isobaric thermal expansion coefficient of phase i fluid, p i is the pressure of phase i fluid, u i is the seepage velocity vector of phase i fluid, g is the acceleration of gravity, D is the vertical depth, and λ is the comprehensive thermal conductivity of the reservoir.

3. The method according to claim 1, characterized in that The wellbore thermal model is based on the principle of energy conservation and describes the change of wellbore temperature T along the wellbore axis x by the following equation: Where p is the wellbore pressure, K TT is the Joule-Thomson coefficient, R is the wellbore radius, T1 is the inflow temperature, α T,1 is the total heat transfer coefficient considering the degree of wellbore opening, θ is the well inclination angle, subscript T represents the sum of multiphase mixed fluid, ρv is the mass flow rate, C p is the specific heat capacity.

4. The method according to claim 3, characterized in that The inflow temperature T1 considering the influence of formation damage is obtained by solving the radial steady-state temperature equation, which is established in the damaged zone and the undamaged area respectively, and considers the continuity of temperature and heat flux density inside and outside the damaged zone.

5. The method according to claim 4, characterized in that The radial steady-state temperature equation is of the form: Where r is the radial distance, T is the temperature at the radial distance, λ is the thermal conductivity, C1, C2, and C3 are coefficients related to fluid properties, flow parameters, and formation permeability; within the damage zone, the formation permeability is taken as the damage zone permeability k d .

6. The method according to claim 1, wherein The numerical solution method includes discretizing the reservoir model and the wellbore model using a finite difference method, and iteratively solving the coupled system.

7. A device for predicting temperature of multiphase flow in horizontal wells taking into account microthermal effects and formation damage, characterized in that: include: one or more processors; and a memory storing instructions executed by the one or more processors, wherein the instructions are used to perform the method according to any one of claims 1 to 6.

8. The device according to claim 7, characterized in that The instructions are specifically used to: establish a reservoir modeling module for a reservoir model, wherein the reservoir model includes a reservoir seepage model and a reservoir thermal model that takes into account at least one micro-thermal effect; establish a wellbore modeling module for a wellbore model, wherein the wellbore model includes a wellbore flow model and a wellbore thermal model that takes into account the Joule-Thomson effect, heat exchange between the wellbore and the formation, and gravity effect; establish a coupling modeling module for a reservoir and wellbore coupling model, which is used to calculate the inflow temperature that takes into account the influence of formation damage; and establish a model solving module that performs iterative solutions based on the reservoir model, wellbore model, and inflow temperature, which is used to obtain a temperature profile along the horizontal wellbore.

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