A method and system for calculating the temperature field distribution in an ultra-deep well under different working conditions

Abstract

This invention belongs to, but is not limited to, the technical field of oil and gas well drilling engineering, and discloses a method and system for calculating the temperature field distribution of the wellbore under different operating conditions in ultra-deep wells. Based on a wellbore temperature model for ultra-deep well drilling under different operating conditions, and utilizing the law of conservation of energy, fundamental theories of heat transfer, and basic theories of fluid mechanics, this invention analyzes the energy conservation equations of micro-elements in various regions within the wellbore, thus obtaining a method for calculating the temperature field of the wellbore under different operating conditions. The micro-elements include one or more of the following: fluid inside the drill pipe, drill pipe wall, fluid inside the annulus, casing, cement sheath, and the formation surrounding the wellbore. This invention establishes a mathematical model for the temperature field distribution of the ultra-deep wellbore, which can accurately calculate the temperature field distribution of the wellbore under various operating conditions, including drilling process, drilling fluid circulation, and well shut-in. This improves the applicability of predicting wellbore temperature distribution, wellhead return temperature, and local high-temperature locations during ultra-deep well operations.

Description

Technical Field

[0001] This invention belongs to, but is not limited to, the technical field of oil and gas well engineering and drilling engineering, and particularly relates to a method and system for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells. Background Technology

[0002] As oil and gas resource exploration and development continues to expand into deeper and ultra-deep strata, the proportion of field operations for ultra-deep wells, ultra-high temperature wells, and wells with complex structures is steadily increasing. The wellbore temperature field is a core fundamental parameter for the design and construction of ultra-deep well drilling projects. Its distribution directly affects the regulation of drilling fluid rheological properties, wellbore stability analysis, precise control of bottom hole pressure, safety assurance of downhole tool operations, and optimization of cementing construction quality, playing a crucial role in the safe and efficient drilling of ultra-deep wells.

[0003] Currently, extensive research has been conducted in this field on the heat transfer process between fluids within the wellbore, the tubing string, and the formation, resulting in various wellbore temperature field calculation methods and related technical solutions. These can provide some technical support for predicting wellbore temperature distribution under conventional operating conditions. However, under the extremely complex conditions of ultra-deep wells—high temperature and pressure, long operation cycles, and multiple operating condition switching—existing technologies still have many limitations and shortcomings, making it difficult to meet the actual field application needs of ultra-deep well drilling projects. Specifically:

[0004] Existing wellbore temperature field calculation methods are only applicable to a single working condition and can only predict wellbore temperature distribution under simple circulation conditions or specific environmental conditions. They cannot uniformly characterize the differences in the evolution of wellbore temperature field under different operating conditions such as drilling, circulation, and shut-in. The applicability of these methods is limited and cannot meet the calculation needs of multiple working conditions switching throughout the entire process of ultra-deep well drilling.

[0005] Existing calculation methods set the density, specific heat capacity, thermal conductivity, and rheological parameters of drilling fluid to constant values, or preset the convective heat transfer coefficient in the wellbore to a fixed value. They do not fully consider the dynamic evolution characteristics of the thermal and rheological parameters of drilling fluid with temperature and pressure under the extreme high temperature and pressure environment of ultra-deep wells. This results in a large deviation between the predicted temperature field of the wellbore and the actual working conditions on site, and cannot meet the needs of high-precision temperature field prediction for ultra-deep wells.

[0006] While some existing calculation methods can solve for the temperature distribution inside the wellbore, they generally simplify the drilling fluid inlet temperature to a fixed constant, without simultaneously considering the heat dissipation effect of the surface mud pit to the environment, as well as the feedback effect of the wellbore return fluid on the mud pit temperature. This makes it impossible to accurately characterize the dynamic change of the drilling fluid inlet temperature over time during long-term continuous operation, thereby reducing the overall calculation accuracy of the temperature field of the entire wellbore.

[0007] For continuous drilling operations in ultra-deep wells, existing calculation methods rarely consider the coupled effects of real-time increases in well depth, dynamic expansion of the calculation grid, and frictional heat generation between the drill bit and the formation on the temperature field in the bottom well region during drilling. They cannot achieve dynamic and continuous calculation of the wellbore temperature field throughout the entire drilling cycle of ultra-deep wells, and are difficult to adapt to the operational characteristics of continuous deepening of ultra-deep wells.

[0008] Therefore, developing a wellbore temperature field distribution calculation method applicable to different operating conditions of ultra-deep wells, which can comprehensively couple multiple factors such as dynamic changes in drilling fluid thermophysical properties, mud pit temperature feedback, and dynamic increase in well depth during drilling, has become an urgent technical problem to be solved in this field. Summary of the Invention

[0009] To address the problems existing in the prior art, this invention provides a method for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells, in order to solve the problems of insufficient unified description capability for multiple working conditions, overly simplified treatment of drilling fluid properties, distorted inlet temperature setting, and insufficient characterization of drilling dynamic process in the prior art.

[0010] This invention is implemented as follows: A method for calculating the temperature field distribution of an ultra-deep well under different operating conditions includes:

[0011] S1. Obtain the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes at least formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters.

[0012] S2. Based on the aforementioned basic data, establish an axial-radial coupled computational domain for the wellbore. Divide the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain. Establish corresponding initial temperature fields and boundary conditions.

[0013] S3 determines the wellbore's current operating status as either drilling, circulation, or shut-in, and updates the well depth, boundary conditions, and heat source conditions accordingly.

[0014] S4, within the current time step, update the density, specific heat capacity, thermal conductivity and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature, and calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number and heat transfer coefficient in the well accordingly;

[0015]

[0016] S5. Calculate the heat dissipation of the mud pit based on the geometric dimensions of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the energy balance of the mud pit. Use the updated mud pit temperature as the inlet temperature of the next time step.

[0017]

[0018] S6. Based on the energy conservation relationship and the heat transfer parameters obtained in step S4, the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore is solved to obtain the wellbore temperature field distribution at the current time step.

[0019]

[0020] S7. Repeat steps S3 to S6 according to the preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

[0021] Furthermore, the basic data includes: formation layer depth, formation density, formation specific heat capacity, and formation thermal conductivity; number of casing layers, casing depth, casing inner and outer diameters, and their thermal properties; drill pipe segment length, drill pipe inner and outer diameters, and their thermal properties; initial density, specific heat capacity, thermal conductivity, viscosity, or rheological parameters of drilling fluid in the drill pipe and annulus; mud pit volume and its length, width, and height; and one or more of the following: surface temperature, geothermal gradient, displacement, drilling pressure, rotational speed, drilling speed, or mechanical drilling speed.

[0022] Furthermore, in step S2, a discretization method combining axial and radial grids is adopted, wherein the axial grid is discretized along the well depth direction, and the radial grid extends radially from the outer wall of the well to the formation to a preset influence radius, so as to construct an axisymmetric two-dimensional transient heat transfer model.

[0023] Furthermore, in step S3, when the operation status is drilling, the well depth is dynamically updated over time, and the axial grid is automatically expanded when the newly added well depth exceeds the current grid coverage range, so as to realize the dynamic solution of the wellbore temperature field during drilling.

[0024] In step S3, the additional heat source for the wellbore under different working conditions can be one or more combinations of additional heat sources. The additional heat sources are heat dissipation due to drilling fluid viscosity, heat from drill pipe rotation and contact friction, and heat power from drill bit friction.

[0025] Furthermore, in step S4, the thermal properties of the drilling fluid are updated according to a temperature function, and the thermal properties include at least density, specific heat capacity, and thermal conductivity; the rheological parameters include at least Herba dynamic shear force, consistency coefficient, and flow index.

[0026] In step S4, the Herschel-Bulkley rheological model or the power-law rheological model is used to characterize the rheological properties of the drilling fluid, and the apparent viscosity of the drilling fluid in the drill pipe and annulus is calculated based on the shear rate.

[0027] Furthermore, in step S5, the heat dissipation of the mud pit includes at least the natural convection heat dissipation from the top and sidewalls of the mud pit to the external environment, and the energy exchange between the wellhead return fluid and the mud pit fluid updates the mud pit temperature.

[0028] Step S6 employs an explicit finite difference method for time-progression solution, with the time step determined based on the axial mesh size and fluid velocity to meet numerical stability requirements.

[0029] Another objective of this invention is to provide a system for calculating the temperature field distribution in an ultra-deep well under different operating conditions, comprising:

[0030] The data acquisition module is used to acquire the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes at least formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters.

[0031] The partitioning module is used to establish an axial-radial coupled computational domain of the wellbore based on the basic data, dividing the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain, and establishing corresponding initial temperature fields and boundary conditions;

[0032] The determination module is used to determine whether the wellbore is in drilling, circulation, or shut-in operation based on the current operating status, and to update the well depth, boundary conditions, and heat source conditions according to the corresponding operation.

[0033] The calculation module is used to update the density, specific heat capacity, thermal conductivity and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature in the current time step, and to calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number and heat transfer coefficient in the well based on these parameters.

[0034] The update module is used to calculate the heat dissipation of the mud pit based on the geometry of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the energy balance of the mud pit, and use the updated mud pit temperature as the inlet temperature of the next time step.

[0035] The solver module is used to solve the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore based on the energy conservation relationship and the heat transfer parameters obtained in step S4, so as to obtain the wellbore temperature field distribution at the current time step.

[0036] The output module is used to repeatedly execute steps S3 to S6 according to a preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

[0037] Another object of the present invention is to provide a computer device, the computer device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the method for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells.

[0038] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells.

[0039] Another objective of this invention is to provide an information data processing terminal, which includes a wellbore temperature field distribution calculation system under different working conditions of the ultra-deep well.

[0040] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this invention are as follows:

[0041] First, this invention incorporates drilling conditions, circulation conditions, and shut-in conditions into the same transient calculation framework, which is beneficial for achieving continuous prediction of the temperature field throughout the entire process of ultra-deep well operations.

[0042] This invention synchronously updates the thermal properties, rheological parameters, hydraulic parameters, and heat transfer parameters of the drilling fluid at each time step, which can more realistically reflect the impact of changes in drilling fluid properties on the temperature field under high temperature and high pressure conditions.

[0043] This invention calculates the inlet temperature using a mud pit heat dissipation model and outflow fluid energy feedback, avoiding the bias caused by the assumption of a constant inlet temperature, and thus improving the reliability of long-term simulation results.

[0044] This invention takes into account the increase in well depth, the dynamic expansion of the wellbore grid, and the frictional heat of the drill bit during the drilling process, which is beneficial to improving the applicability of temperature field calculation near the bottom of the well during the ultra-deep well drilling stage.

[0045] This invention provides a basis for temperature field calculations for bottom hole high temperature risk analysis, drilling fluid performance evaluation, downhole tool temperature resistance verification, and operation parameter optimization.

[0046] Secondly, as supporting evidence of the inventiveness of this invention, it is also reflected in the following important aspects:

[0047] (1) The expected benefits and commercial value of the technical solution of this invention after transformation are as follows:

[0048] Existing research on wellbore temperature fields has established several fundamental models, such as wellbore temperature field prediction methods, deep-water circulation temperature-pressure coupling calculation methods, wellbore temperature field determination methods under composite processes, and wellbore temperature control methods under special environments. These studies provide a foundation for wellbore heat transfer, temperature-pressure coupling, and temperature calculations in specific scenarios. However, in actual ultra-deep well drilling operations, the wellbore temperature field is still jointly affected by factors such as changes in drilling fluid thermophysical properties, rheological parameters, wellbore pressure distribution, heat transfer coefficient changes, mud pool reflux heat transfer, and the dynamic increase in drilling depth.

[0049] Based on the aforementioned research, this invention incorporates different operating conditions such as ultra-deep well drilling, circulation, and shut-in into a unified transient calculation framework, and introduces hourly coupled updates of thermophysical, rheological, and hydraulic parameters, as well as a mud pit inlet temperature feedback mechanism. After conversion, this technical solution can be used as a software module or computational service for ultra-deep well drilling engineering design, drilling fluid performance verification, downhole tool temperature resistance verification, bottom hole temperature risk analysis, and on-site operational parameter optimization, demonstrating clear engineering application scenarios.

[0050] Its expected benefits and commercial value are mainly reflected in the following aspects: First, it can improve the applicability of temperature distribution prediction in ultra-deep wells, providing a basis for the selection of drilling fluid systems, the selection of temperature resistance levels of downhole instruments, and the analysis of well control safety windows in high-temperature environments; Second, it can reduce drilling fluid performance instability, downhole tool thermal failure, and repeated adjustments of operating parameters caused by temperature prediction deviations, thereby reducing non-productive time and on-site trial and error costs; Third, it can be embedded in digital drilling, drilling engineering simulation, and wellbore multiphysics prediction software to form a replicable engineering calculation module; Fourth, it can provide decision support for design units, oilfield service companies, and drilling sites of ultra-deep wells, high-temperature and high-pressure wells, and complex structure wells, and has good industrialization and promotion value.

[0051] (2) The technical solution of this invention fills a technical gap in the industry both domestically and internationally:

[0052] Existing research often focuses on establishing wellbore temperature field models based on a specific type of problem. For example, some schemes emphasize general prediction of the wellbore temperature field, others focus on temperature-pressure coupling in deep-water gas-liquid two-phase flow, some address heat transfer in fixed well sections under heavy oil composite processes, and others address temperature control in special environments such as polar cold seas. While these schemes each have their own applicable scenarios, they cannot directly cover the temperature field calculation needs under the combined effects of multiple operating conditions switching, changes in drilling fluid properties with temperature and pressure, mud pit backflow heat transfer feedback, and dynamic increases in drilling depth throughout the entire ultra-deep well drilling process.

[0053] The technical gap filled by this invention is that it proposes a unified transient wellbore temperature field calculation method for different operating conditions in ultra-deep wells; it simultaneously considers the coupled heat transfer between the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the well within the same calculation framework; it updates the drilling fluid density, specific heat capacity, thermal conductivity, yield stress, consistency coefficient, flow behavior index, apparent viscosity, pressure distribution, Reynolds number, Prandtl number, Nusselt number, and heat transfer coefficient in each time step; and it further corrects the inlet temperature through heat dissipation in the mud pit and energy feedback from the fluid returning from the wellhead.

[0054] Therefore, this invention is not a simple replacement of the existing single temperature field model, but rather fills the technical gap in the combined scenario of multi-condition ultra-deep wells, variable physical property and rheological properties, hydraulic heat exchange linkage, mud pit feedback, and dynamic drilling depth, based on the previous achievements in wellbore heat transfer, temperature-pressure coupling, and scenario-based temperature calculation.

[0055] (3) The technical solution of the present invention overcomes technical bias:

[0056] In existing wellbore temperature field calculations, a common approach in the industry is to reduce computational complexity by employing several simplification assumptions. These include treating drilling fluid thermal properties as constants, rheological parameters as constants, pre-setting heat transfer coefficients, using inlet temperature as a fixed boundary, or establishing models only for single-cycle conditions, special environmental conditions, or fixed well section processes. This approach has some practicality in shallow wells, short-term cycles, or scenarios with minimal changes in operating conditions, and it easily leads technicians to believe that wellbore temperature field calculations only require solving the heat transfer equations under given boundary conditions, and that mud pit feedback, rheological changes, and dynamic well depth growth can be ignored as secondary factors.

[0057] However, this simplistic understanding leads to significant biases for ultra-deep and high-temperature, high-pressure wells. Factors such as changes in drilling fluid properties with temperature and pressure, variations in mud pit inlet temperature due to backflow and heat dissipation, and the continuous increase in well depth during drilling all exert a sustained influence on the temperature field. Using fixed physical properties, fixed inlet boundaries, or single-condition models will fail to accurately reflect the temperature evolution during ultra-deep well operations.

[0058] This invention overcomes the aforementioned technical biases: it no longer treats the inlet temperature as a constant, nor the drilling fluid properties and rheological parameters as constants, nor does it separate drilling, circulation, and shut-in processes into unrelated individual models. Instead, it treats these factors as core variables affecting the accuracy of temperature field calculations and updates them in a coupled manner. This approach breaks through the conventional technical path of simplifying boundaries, fixing properties, and solving under single operating conditions, demonstrating creativity that distinguishes it from existing technologies. Attached Figure Description

[0059] Figure 1This is a flowchart of the method for calculating the temperature field distribution of an ultra-deep well under different working conditions, provided in an embodiment of the present invention.

[0060] Figure 2 This is a system structure block diagram of the method for calculating the temperature field distribution of ultra-deep wells under different working conditions provided in this embodiment of the invention;

[0061] Figure 3 This is a schematic diagram of the temperature field distribution model of an ultra-deep wellbore provided in an embodiment of the present invention;

[0062] Figure 4 This is a schematic diagram of the overall solution process of the method provided in the embodiment of the present invention;

[0063] Figure 5 This is a schematic diagram of the axial-radial coupling computational domain partitioning of the wellbore provided in an embodiment of the present invention;

[0064] Figure 6 This is a schematic diagram of the calculated wellbore temperature field results provided in an embodiment of the present invention;

[0065] Figure 7 is a schematic diagram of the distribution of wellhead return temperature, bottom hole temperature, drill pipe fluid temperature, annular fluid temperature, drill pipe wall temperature and formation temperature around the well provided in Scheme 1 of the present invention; wherein, (a) the curves of the change of bottom hole temperature, outlet temperature and inlet temperature over time, and (b) the temperature distribution curve.

[0066] Figure 8 is a schematic diagram of the distribution of wellhead return temperature, bottom hole temperature, drill pipe fluid temperature, annular fluid temperature, drill pipe wall temperature and formation temperature around the well provided in Scheme 2 of the present invention; wherein, (a) the curves of the change of bottom hole temperature, outlet temperature and inlet temperature over time, and (b) the temperature distribution curve.

[0067] Figure 9 is a schematic diagram of the distribution of wellhead return temperature, bottom hole temperature, drill pipe fluid temperature, annular fluid temperature, drill pipe wall temperature and formation temperature around the well in Scheme 3 provided by the embodiment of the present invention; wherein, (a) the curves of the change of bottom hole temperature, outlet temperature and inlet temperature over time, and (b) the temperature distribution curve. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0069] like Figure 1 As shown in the embodiment of the present invention, the method for calculating the temperature field distribution of an ultra-deep well under different working conditions includes the following steps:

[0070] S1. Obtain the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes at least formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters.

[0071] S2. Based on the aforementioned basic data, establish an axial-radial coupled computational domain for the wellbore. Divide the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain, and establish corresponding initial temperature fields and boundary conditions.

[0072] S3. Determine whether the wellbore is in any of the following conditions based on the current operating status: drilling, circulation, or shut-in; and update the well depth, boundary conditions, and heat source conditions according to the corresponding condition.

[0073] S4. Within the current time step, update the density, specific heat capacity, thermal conductivity, and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature, and calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number, and heat transfer coefficient in the well accordingly.

[0074]

[0075] S5. Calculate the heat dissipation of the mud pit based on the geometric dimensions of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the mud pit energy balance, and use the updated mud pit temperature as the inlet temperature of the next time step.

[0076]

[0077] S6. Based on the energy conservation relationship and the heat transfer parameters obtained in step S4, solve the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore to obtain the wellbore temperature field distribution at the current time step.

[0078]

[0079] S7. Repeat steps S3 to S6 according to the preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

[0080] The basic data provided in this invention embodiment include: formation layer depth, formation density, formation specific heat capacity, and formation thermal conductivity; number of casing layers, casing depth, casing inner and outer diameters, and their thermal properties; drill pipe segment length, drill pipe inner and outer diameters, and their thermal properties; initial density, specific heat capacity, thermal conductivity, viscosity, or rheological parameters of drilling fluid in the drill pipe and annulus; mud pit volume and its length, width, and height; and one or more of the following: surface temperature, geothermal gradient, displacement, drilling pressure, rotational speed, drilling speed, or mechanical drilling speed.

[0081] In step S2 of this embodiment of the invention, a discretization method combining axial and radial grids is used. The axial grid is discretized along the well depth direction, and the radial grid extends radially from the outer wall of the well to the formation to a preset influence radius, so as to construct an axisymmetric two-dimensional transient heat transfer model.

[0082] In step S3 provided in this embodiment of the invention, when the working state is drilling, the well depth is dynamically updated over time, and the axial grid is automatically expanded when the newly added well depth exceeds the current grid coverage range, so as to realize the dynamic solution of the wellbore temperature field during drilling.

[0083] In step S3, the additional heat source for the wellbore under different working conditions can be one or more combinations of additional heat sources. The additional heat sources are heat dissipation due to drilling fluid viscosity, heat from drill pipe rotation and contact friction, and heat power from drill bit friction.

[0084] In step S4 provided in this embodiment of the invention, the thermal properties of the drilling fluid are updated according to a temperature function. The thermal properties include at least density, specific heat capacity, and thermal conductivity; the rheological parameters include at least Herba dynamic shear force, consistency coefficient, and flow index.

[0085] In step S4, the Herschel-Bulkley rheological model or the power-law rheological model is used to characterize the rheological properties of the drilling fluid, and the apparent viscosity of the drilling fluid in the drill pipe and annulus is calculated based on the shear rate.

[0086] In step S5 provided in this embodiment of the invention, the heat dissipation of the mud pool includes at least the natural convection heat dissipation from the top and sidewalls of the mud pool to the external environment, and the temperature of the mud pool is updated by the energy exchange between the wellhead return fluid and the mud pool fluid.

[0087] Step S6 employs an explicit finite difference method for time-progression solution, with the time step determined based on the axial mesh size and fluid velocity to meet numerical stability requirements.

[0088] like Figure 2 As shown in the figure, an embodiment of the present invention provides a wellbore temperature field distribution calculation system under different working conditions, comprising:

[0089] The data acquisition module is used to acquire the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes at least formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters.

[0090] The partitioning module is used to establish an axial-radial coupled computational domain of the wellbore based on the basic data, dividing the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain, and establishing corresponding initial temperature fields and boundary conditions;

[0091] The determination module is used to determine whether the wellbore is in drilling, circulation, or shut-in operation based on the current operating status, and to update the well depth, boundary conditions, and heat source conditions according to the corresponding operation.

[0092] The calculation module is used to update the density, specific heat capacity, thermal conductivity and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature in the current time step, and to calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number and heat transfer coefficient in the well based on these parameters.

[0093] The update module is used to calculate the heat dissipation of the mud pit based on the geometry of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the energy balance of the mud pit, and use the updated mud pit temperature as the inlet temperature of the next time step.

[0094] The solver module is used to solve the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore based on the energy conservation relationship and the heat transfer parameters obtained in step S4, so as to obtain the wellbore temperature field distribution at the current time step.

[0095] The output module is used to repeatedly execute steps S3 to S6 according to a preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

[0096] Basic data acquisition: First, acquire basic data for the ultra-deep well, including formation stratification information, casing program, drill pipe segment structure, drilling fluid basic properties, mud pit geometry, and operational parameters. These operational parameters include one or more of the following: total simulation duration, initial well depth, surface temperature, geothermal gradient, displacement, drilling pressure, rotational speed, and mechanical drilling rate.

[0097] Computational domain establishment: An axial grid is established along the well depth direction based on the wellbore and drill pipe structures, and a radial grid is established based on the wellbore outer diameter to a preset radius of influence, forming an axisymmetric two-dimensional computational domain. The computational domain includes at least the following regions: the fluid region inside the drill pipe; the drill pipe wall region; the annular fluid region; and the casing, cement sheath, and surrounding formation region. Along the well depth direction, corresponding physical property parameters are automatically matched according to formation layers, casing layers, and drill pipe segments; along the radial direction, the thermal conductivity, density, and specific heat capacity of different media are distributed layer by layer according to the wellbore structure.

[0098] Initial and Boundary Conditions: Initially, the formation temperature around the well is determined based on the surface temperature and geothermal gradient, while the fluid and pipe wall temperatures inside the wellbore are set according to the initial operating conditions. At the top boundary of the wellbore, the drill pipe inlet temperature is not directly set to a fixed value but is determined by the mud pit temperature. At the bottom boundary of the wellbore, the bottom formation temperature is updated based on the current well depth and geothermal gradient; during drilling operations, drill bit frictional heat is also introduced at the bottom of the well. At the radial outer boundary, the original formation temperature distribution is used as the far-field temperature boundary.

[0099] Different working conditions are determined based on the current operating parameters: 1. When the well depth increases with time (there is mechanical drilling rate) and there is circulating flow, it is determined to be drilling condition; 2. When the well depth does not increase (mechanical drilling rate is 0) but there is circulating flow, it is determined to be circulating condition; 3. When the circulating flow is zero, it is determined to be shut-in condition.

[0100] When drilling is in progress, the well depth is updated over time using the following formula:

[0101]

[0102] Where H is the current well depth, ROP is the mechanical drilling rate, and Δt is the time step. When the well depth increases to the point that the existing grid cannot cover the new well section, an axial grid layer is automatically added, and the relevant temperature, physical properties, and geometric parameter arrays are expanded simultaneously.

[0103] Drilling fluid thermophysical and rheological parameter updates: Within each time step, the drilling fluid's thermophysical and rheological parameters can be either kept constant or updated based on the current temperature. If the parameters are updated with temperature, the update method can be as follows:

[0104] The drilling fluid specific heat capacity and thermal conductivity are updated based on the current temperature T. Preferably, the following form can be used:

[0105]

[0106] in, , For reference specific heat capacity and reference thermal conductivity, and For the temperature correction function relating to the specific heat capacity and thermal conductivity of drilling fluid, the parameter correction function can preferably be:

[0107]

[0108] The drilling fluid rheological parameters are preferably derived from the Herschel-Bulkley model, and the Herschel dynamic shear force, consistency coefficient, and flow regime index can all be expressed as the product of the reference temperature and a dimensionless temperature correction function.

[0109]

[0110] in, For Heba's dynamic shear force, This is the consistency coefficient. It is a flow pattern index. For shear rate, , and These are the reference Herba dynamic shear force, reference consistency coefficient, and reference flow pattern index, respectively. , and This is the corresponding dimensionless temperature correction function. Furthermore, the apparent viscosity is calculated from this function. .

[0111]

[0112] After obtaining the thermal and rheological parameters of the drilling fluid, the Reynolds number, Prandtl number, and Nusselt number are further calculated, and the heat transfer coefficients inside the drill pipe and on the annulus side are obtained from these calculations.

[0113] Mud pit feedback model: Mud pit temperature is calculated through mud pit energy balance. Heat dissipation between the mud pit and the environment includes at least natural convection heat dissipation from the top and sidewalls, and energy exchange exists between the returning drilling fluid and the fluid within the mud pit. The updated mud pit temperature is used as the drill pipe inlet temperature for the next time step, achieving dynamic feedback of the inlet temperature.

[0114] Preferably, the temperature update of the mud pit satisfies:

[0115]

[0116] in, Temperature of the mud pit, Mass of fluid in the mud pit The specific heat capacity of the fluid in the mud pit. The temperature of the returning fluid, This refers to the heat lost from the mud pit to the environment.

[0117] Temperature field solution: After updating the thermal properties, rheological parameters, hydraulic parameters and boundary conditions, transient heat transfer equations for the fluid inside the drill pipe, the drill pipe wall, the annular fluid and the formation around the well are established based on the energy conservation relationship, and the explicit finite difference method is used for time-progression solution.

[0118] For the fluid inside the drill pipe, consider axial convection, axial heat conduction, and heat exchange with the drill pipe wall;

[0119]

[0120] For annular fluid, axial convection, axial heat conduction, heat exchange with the drill pipe wall, and heat exchange with the surrounding formation are considered.

[0121]

[0122] For the drill pipe wall, consider the bidirectional heat transfer between the drill pipe fluid and the annular fluid, as well as axial heat conduction.

[0123]

[0124] For the formation around the well, radial heat transfer and axial heat transfer are considered.

[0125]

[0126] The optimal time step is determined based on the axial grid scale and fluid velocity according to stability conditions to ensure the stability of the explicit solution process.

[0127] Additional heat sources for wellbore under different operating conditions: Additional heat sources for wellbore under different operating conditions can selectively adopt one or more combinations of additional heat sources, and the selectable additional heat sources can be represented as follows:

[0128]

[0129]

[0130]

[0131] in, To reduce heat loss due to the viscosity of the drilling fluid, The wall friction force is generated by the viscosity of the drilling fluid. This is the drilling fluid friction coefficient. The wetted perimeter of the drilling fluid area. The heat distribution coefficient, The heat generated is from the friction between the rotating drill pipe and the contact surface. For the total friction force, The relative sliding speed, For frictional torque, Angular velocity, This represents the total length of the drill pipe. Where is the frictional heat power of the drill bit, WOB is the drill pressure, and M is the drill bit torque. This represents the unit length at the drill bit.

[0132] Example 1

[0133] Taking an ultra-deep well as an example, input the formation layering parameters, casing structure, drill pipe structure, initial drilling fluid parameters and mud pit size, set the total simulation time, initial well depth, surface temperature, geothermal gradient, displacement, drilling pressure and rotation speed, and use the above methods to calculate the wellbore temperature field under drilling, circulation and shut-in conditions respectively.

[0134] Table 1 Engineering parameters of the embodiment

[0135]

[0136] In the calculation process, a two-dimensional computational domain is first established according to the formation and wellbore structure; then, the distribution of drilling fluid thermophysical parameters and rheological parameters is updated at each time step; the inlet temperature is then corrected by combining feedback from the mud pit; finally, the explicit finite difference method is used to obtain the wellbore temperature field at the current time and output the temperature distribution at the target time.

[0137] The method of this invention can reflect the impact of changes in inlet temperature and local heat transfer capacity on the temperature field during long-term operation of ultra-deep wells, and is applicable to temperature field prediction and operation parameter analysis of ultra-deep wells.

[0138] Evidence related to the technical effects obtained by the embodiments of the present invention.

[0139] To verify the technical effects achievable by the method of the present invention, comparative calculation examples are provided. These comparative calculation examples preferably include traditional fixed-property calculation methods and the thermorheological-hydraulic coupling calculation method described in this invention, which considers mud pit feedback. By comparing the distributions of wellhead return temperature, bottom hole temperature, drill pipe fluid temperature, annular fluid temperature, drill pipe wall temperature, and formation temperature around the well obtained by different methods, the technical effects of the present invention can be demonstrated.

[0140] Specifically, under the same formation parameters, wellbore structure, drill string structure, initial drilling fluid parameters, and operating parameters, the following three sets of calculation schemes are compared: Scheme 1 is a wellbore temperature field calculation scheme with fixed physical properties and a fixed inlet temperature; Scheme 2 is the method described in this invention, which updates the drilling fluid thermophysical parameters, rheological parameters, hydraulic parameters, and heat transfer parameters at each time step, and dynamically updates the inlet temperature by combining mud pit heat dissipation and return fluid energy feedback; Scheme 3 is also the method described in this invention, except that the calculation conditions are changed to drilling conditions.

[0141] As shown in Figure 7(a), Scheme 1: Curves showing the changes in bottom hole temperature, outlet temperature, and inlet temperature over time;

[0142] As shown in Figure 7(b), Scheme 1: Temperature distribution curve;

[0143] As shown in Figure 8(a), Scheme 2: Curves showing the changes in bottom hole temperature, outlet temperature, and inlet temperature over time;

[0144] As shown in Figure 8(b), Scheme 2: Temperature distribution curve;

[0145] Figure 9(a) shows the curves of the changes in bottom hole temperature, outlet temperature, and inlet temperature over time for Scheme 3.

[0146] As shown in Figure 9(b), Scheme 3, temperature distribution curve.

[0147] The above comparison yields the following evidence of technical effectiveness:

[0148] In high-temperature and high-pressure well sections, Scheme 1 approximates drilling fluid density, specific heat capacity, thermal conductivity, and rheological parameters as constants, which makes it difficult to reflect the impact of temperature and pressure changes on the flow regime and heat transfer capacity in the well. This invention further corrects the pressure distribution, Reynolds number, Prandtl number, Nusselt number, and heat transfer coefficient by updating temperature- and pressure-related thermophysical properties and rheological parameters, so that the wellbore temperature field calculation can reflect the impact of drilling fluid performance changes under the high-temperature and high-pressure environment of ultra-deep wells.

[0149] For drilling operations, traditional fixed-depth models are difficult to describe the process of heat transfer as the well depth increases over time with the addition of new well sections. This invention dynamically expands the axial grid according to the increase in well depth during drilling and updates the temperature, geometry, and physical property parameters of the newly added well sections. It can be used to describe the continuous evolution of the temperature field near the bottom of the well with time and well depth during drilling.

[0150] The results output by this invention include not only the wellbore temperature value at a certain moment, but also the temperature distribution of the fluid inside the drill pipe, the annular fluid, the formation temperature around the well, the pressure distribution inside the well, the distribution of drilling fluid physical parameters, and the location of the highest temperature and its corresponding depth at different target moments. Therefore, it can provide more complete data for drilling fluid system design, downhole tool temperature resistance verification, and optimization of field operation parameters.

[0151] It should be noted that embodiments of the present invention can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuitry such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of the above-described hardware circuitry and software, such as firmware.

[0152] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for calculating the temperature field distribution in an ultra-deep well under different operating conditions, characterized in that, Includes the following steps: S1, Obtain the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters. S2. Based on the aforementioned basic data, establish an axial-radial coupled computational domain for the wellbore. Divide the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain. Establish corresponding initial temperature fields and boundary conditions. S3 determines the wellbore's current operating status as either drilling, circulation, or shut-in, and updates the well depth, boundary conditions, and heat source conditions accordingly. S4, within the current time step, update the density, specific heat capacity, thermal conductivity and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature, and calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number and heat transfer coefficient in the well accordingly; ； S5. Calculate the heat dissipation of the mud pit based on the geometric dimensions of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the energy balance of the mud pit. Use the updated mud pit temperature as the inlet temperature of the next time step. ； S6. Based on the energy conservation relationship and the heat transfer parameters obtained in step S4, the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore is solved to obtain the wellbore temperature field distribution at the current time step. ； S7. Repeat steps S3 to S6 according to the preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

2. The method for calculating the temperature field distribution of an ultra-deep well under different operating conditions as described in claim 1, characterized in that, The basic data include: formation layer depth, formation density, formation specific heat capacity, and formation thermal conductivity; number of casing layers, casing depth, casing inner and outer diameters, and their thermal properties; drill pipe segment length, drill pipe inner and outer diameters, and their thermal properties; initial density, specific heat capacity, thermal conductivity, viscosity, or rheological parameters of drilling fluid in the drill pipe and annulus; mud pit volume and its length, width, and height; and one or more of the following: surface temperature, geothermal gradient, displacement, drilling pressure, rotational speed, drilling speed, or mechanical drilling speed.

3. The method for calculating the temperature field distribution of an ultra-deep well under different operating conditions as described in claim 1, characterized in that, In step S2, a discretization method combining axial and radial grids is adopted. The axial grid is discretized along the well depth direction, and the radial grid extends radially from the outer wall of the well to the formation to a preset influence radius, so as to construct an axisymmetric two-dimensional transient heat transfer model.

4. The method for calculating the temperature field distribution of an ultra-deep well under different operating conditions as described in claim 1, characterized in that, In step S3, when the operation status is drilling, the well depth is dynamically updated over time, and the axial grid is automatically expanded when the newly added well depth exceeds the current grid coverage range, so as to realize the dynamic solution of the wellbore temperature field during drilling. In step S3, the additional heat source for the wellbore under different working conditions can be one or more combinations of additional heat sources. The additional heat sources are heat dissipation due to drilling fluid viscosity, heat from drill pipe rotation and contact friction, and heat power from drill bit friction.

5. The method for calculating the temperature field distribution of an ultra-deep well under different operating conditions as described in claim 1, characterized in that, In step S4, the thermal properties of the drilling fluid are updated according to a temperature function. The thermal properties include density, specific heat capacity, and thermal conductivity. The rheological parameters include Herba dynamic shear force, consistency coefficient, and flow index. In step S4, the Herschel-Bulkley rheological model or the power-law rheological model is used to characterize the rheological properties of the drilling fluid, and the apparent viscosity of the drilling fluid in the drill pipe and annulus is calculated based on the shear rate.

6. The method for calculating the temperature field distribution of an ultra-deep well under different operating conditions as described in claim 1, characterized in that, In step S5, the heat dissipation of the mud pit includes the natural convection heat dissipation from the top and sidewalls of the mud pit to the external environment, and the temperature of the mud pit is updated by the energy exchange between the wellhead return fluid and the mud pit fluid. Step S6 employs an explicit finite difference method for time-progression solution, with the time step determined based on the axial mesh size and fluid velocity to meet numerical stability requirements.

7. A system for calculating the temperature field distribution of an ultra-deep well under different operating conditions, implementing the method described in any one of claims 1-6, characterized in that, include: The data acquisition module is used to acquire the basic data required for calculating the temperature field of the ultra-deep wellbore. The basic data includes at least formation parameters, wellbore structure parameters, drill pipe structure parameters, drilling fluid parameters, mud pit parameters, and operating condition parameters. The partitioning module is used to establish an axial-radial coupled computational domain of the wellbore based on the basic data, dividing the computational domain into a fluid domain inside the drill pipe, a drill pipe wall domain, annular fluid domain, a medium domain surrounding the wellbore, and a formation domain, and establishing corresponding initial temperature fields and boundary conditions; The determination module is used to determine whether the wellbore is in drilling, circulation, or shut-in operation based on the current operating status, and to update the well depth, boundary conditions, and heat source conditions according to the corresponding operation. The calculation module is used to update the density, specific heat capacity, thermal conductivity and rheological parameters of the drilling fluid in the drill pipe and annulus according to the temperature in the current time step, and to calculate the apparent viscosity, Reynolds number, Prandtl number, Nusselt number and heat transfer coefficient in the well based on these parameters. The update module is used to calculate the heat dissipation of the mud pit based on the geometry of the mud pit, the ambient temperature and the temperature of the fluid returning from the wellhead, and update the mud pit temperature through the energy balance of the mud pit, and use the updated mud pit temperature as the inlet temperature of the next time step. The solver module is used to solve the transient temperature field of the fluid inside the drill pipe, the drill pipe wall, the annular fluid, and the formation around the wellbore based on the energy conservation relationship and the heat transfer parameters obtained in step S4, so as to obtain the wellbore temperature field distribution at the current time step. The output module is used to repeatedly execute steps S3 to S6 according to a preset time step until the set simulation duration is reached, and output the wellbore temperature field distribution results at different times.

8. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the method for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the method for calculating the temperature field distribution of the wellbore under different working conditions in ultra-deep wells as described in any one of claims 1-6.

10. An information data processing terminal, characterized in that, The information data processing terminal includes the wellbore temperature field distribution calculation system under different working conditions of ultra-deep wells as described in claim 7.

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