Intelligent hole forming design method, device and electronic equipment for medium-deep buried pipe

Abstract

The application relates to a method and device for intelligent hole-forming design of a medium-deep buried pipe and electronic equipment, wherein the method comprises the following steps: collecting a measured mud inflow temperature and a measured return mud temperature of a target medium-deep buried pipe in a construction drilling process; determining a hypothetical drilling depth according to an actual engineering progress, and generating underground soil temperature distribution information; obtaining a predicted return mud temperature based on a pre-constructed two-dimensional transient heat transfer numerical model of a drilling process column coordinate, calculating an absolute deviation value, correcting the underground soil temperature distribution, and reconstructing a geothermal field until the absolute deviation value is smaller than a preset deviation threshold; calculating a heat extraction amount of the buried pipe based on a pre-constructed buried pipe heat transfer numerical model and the geothermal field, adjusting the hypothetical drilling depth, and determining the depth and quantity of the buried pipe until the heat extraction amount exceeds a preset design value. Thus, the problems of drilling depth redundancy or deficiency, high construction cost, significant geothermal field prediction deviation and the like caused by systematic errors in depth setting in the related art are solved.

Description

Technical Field

[0001] This application relates to the field of geothermal energy development technology, and in particular to a smart borehole design method, device and electronic equipment for medium-deep buried pipes. Background Technology

[0002] Currently, medium-deep buried pipe heat pump heating systems use 2–3 km of rock and soil as a heat source, achieving efficient heat extraction through a closed-loop system. They offer significant advantages such as low carbon footprint, stability, and minimal disturbance to groundwater. However, with the large-scale application of these systems, the high cost of the drilling stage and the deviation in geothermal field response have become increasingly prominent issues. Research indicates that drilling depth, the thermal conductivity of backfill materials, and the compaction density directly determine the heat extraction power of a single well and the long-term stability of the system.

[0003] In related technologies, borehole design often relies on regional empirical geothermal gradients (such as 3.0 ℃ / hm) and limited test borehole data. Meanwhile, current borehole technology has introduced distributed optical fiber monitoring and backfill material optimization to improve the real-time monitoring capability of borehole temperature distribution and the thermal conductivity of backfill.

[0004] However, in related technologies, the borehole design assumes a homogeneous formation model, which deviates significantly from the microscale heterogeneity of the actual rock and soil mass. This leads to systematic errors in depth setting, resulting in redundant or insufficient drilling depths and significant deviations in geothermal field prediction. In areas rich in geothermal resources, excessive drilling increases mud circulation and equipment idle costs. In areas with unevenly distributed heat reservoirs, insufficient depth leads to lower-than-expected heat extraction, resulting in a decline in heating capacity in the later stages of system operation. Furthermore, the monitoring data during construction fails to form a closed-loop feedback, making it difficult to dynamically correct drilling parameters. This causes a disconnect between the "design-construction" process, which urgently needs improvement. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for intelligent borehole design of medium-deep buried pipes to solve problems in related technologies, such as redundant or insufficient drilling depth, high construction costs, significant deviations in geothermal field prediction, and difficulty in dynamically correcting drilling parameters due to systematic errors in depth setting.

[0006] The first aspect of this application provides a smart borehole design method for medium-deep buried pipes, comprising the following steps: collecting measured mud inflow temperature and measured mud return temperature of the target medium-deep buried pipe during the drilling process; determining an assumed drilling depth based on the actual progress of the project, and generating underground soil temperature distribution information of the target medium-deep buried pipe based on the thermophysical parameters of rock materials at different depths, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth; and generating underground soil temperature distribution information of the target medium-deep buried pipe based on a pre-constructed two-dimensional transient heat transfer data in cylindrical coordinates of the drilling process. The numerical model is used to obtain the predicted slurry return temperature of the deep buried pipe in the target. The absolute value of the deviation between the predicted slurry return temperature and the measured slurry return temperature is calculated to correct the underground soil temperature distribution until the absolute value of the deviation is less than a preset deviation threshold. The geothermal field of the deep buried pipe in the target is then reconstructed. Based on the pre-constructed numerical model of heat transfer of the buried pipe and the geothermal field, the heat extraction of the buried pipe is calculated to adjust the assumed drilling depth until the heat extraction exceeds a preset design value. The depth and number of deep buried pipes in the target are then determined.

[0007] Through the aforementioned technical means, the embodiments of this application can acquire thermal property parameters of rock strata at different depths in real time during the drilling process, monitor the return slurry property parameters and temperature changes in real time, construct a two-dimensional transient heat transfer model of the drilling process, analyze the heat transfer process using the finite volume method, compare the measured and predicted return slurry temperatures, iteratively reconstruct the geothermal field, predict the heat extraction based on the buried pipe heat transfer numerical model, compare it with the design value, iteratively correct the assumed drilling depth, and determine the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value.

[0008] Optionally, in one embodiment of this application, generating information on the underground soil temperature distribution of the target deep buried pipe based on the thermophysical parameters, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth includes: calculating the actual geothermal gradient based on the thermophysical parameters, the measured mud inflow temperature, and the measured mud return temperature; and determining the underground soil temperature distribution information of the target deep buried pipe based on the actual geothermal gradient and the assumed drilling depth.

[0009] Through the above-mentioned technical means, the embodiments of this application can calculate the actual geothermal gradient layer by layer along the depth using measured parameters, so as to determine the underground soil temperature distribution information of the deep buried pipe in the target, making the calculated actual geothermal gradient more consistent with the actual geological conditions of the target area, thereby improving the accuracy of the underground soil temperature distribution information and providing reliable data support for subsequent geothermal field reconstruction and drilling parameter adjustment.

[0010] Optionally, in one embodiment of this application, the cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process includes the heat transfer process inside the drill pipe, the heat transfer process outside the drill pipe, and the heat transfer process of the soil layer, wherein the fluid control equation for the heat transfer process inside the drill pipe is:

[0011] , in, T s,i The temperature of the drilling mud inside the drill pipe. T s,o The temperature of the drilling mud outside the drill pipe. u s,i The flow rate of the drilling mud inside the drill pipe is [value missing]. A in The cross-sectional area of ​​the inner sleeve is... ρ s The density of the mud. C p,s The specific heat capacity of the mud is... K dpi The heat transfer coefficient per unit length of the drill pipe is denoted as . For time parameters, z For depth parameters; The governing equations at the bottom of the well are corrected to: , Where, λ g The thermal conductivity of the soil. T g The temperature of the soil layer, Q d This is the heat generated by the drilling rig.

[0012] Through the above-mentioned technical means, the embodiments of this application can establish fluid control equations for the heat exchange process inside the drill pipe. Considering that the mud at the bottom of the drill pipe absorbs heat from the drilling rig in addition to heat exchange with the soil at the bottom of the well, a drilling rig heat term is introduced to correct the fluid control equations at the bottom of the well, thereby improving the physical authenticity of the mud return temperature prediction, making the model output more consistent with the measured data, and providing a reliable basis for geothermal field inversion.

[0013] Optionally, in one embodiment of this application, the fluid control equation for the external heat exchange process of the drill pipe is: , in, u s,o The flow rate of the drilling mud outside the drill pipe is [value missing]. A o The enclosed cross-sectional area of ​​the formed borehole and drill rod. h 6 represents the convective heat transfer coefficient between the mud and the soil on the outer wall of the well.

[0014] Through the above-mentioned technical means, the embodiments of this application can establish fluid control equations for the external heat exchange process of the drill pipe, clarify the influence of key parameters such as the external mud flow velocity, enclosed cross-sectional area, and convective heat transfer coefficient on the heat exchange process, thereby enhancing the adaptability of the model to different construction conditions, making the return mud temperature simulation closer to the actual thermal response process, and thus improving the robustness of the geothermal inversion.

[0015] Optionally, in one embodiment of this application, the governing equation for the heat transfer process in the soil layer is: , in, r For radial parameters, The density of the soil layer, C p,g The specific heat capacity of the soil layer is given. is the thermal conductivity of the soil layer.

[0016] Through the above-mentioned technical means, the embodiments of this application can clarify the control equation of the soil layer heat transfer process, accurately simulate the heat transfer law of the soil layer, further improve the heat transfer numerical model, improve the simulation accuracy of the model for the actual formation heat transfer process, and ensure that the predicted return temperature obtained based on the model is closer to the measured value, thereby providing reliable support for the reasonable determination of drilling depth and number.

[0017] A second aspect of this application provides a smart borehole design device for medium-deep buried pipes, comprising: a generation module, used to determine an assumed drilling depth based on the actual progress of the project, and generate underground soil temperature distribution information of the target medium-deep buried pipe based on the thermophysical parameters of rock materials at different depths, the measured mud inflow temperature, the measured return mud temperature, and the assumed drilling depth; a reconstruction module, used to obtain the predicted return mud temperature of the target medium-deep buried pipe based on a pre-constructed cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process, calculate the absolute value of the deviation between the predicted return mud temperature and the measured return mud temperature, so as to correct the underground soil temperature distribution until the absolute value of the deviation is less than a preset deviation threshold, and reconstruct the geothermal field of the target medium-deep buried pipe; and a design module, used to calculate the heat extraction of the buried pipe based on the pre-constructed buried pipe heat transfer numerical model and the geothermal field, so as to adjust the assumed drilling depth until the heat extraction exceeds a preset design value, and determine the depth and number of the target medium-deep buried pipes.

[0018] Through the aforementioned technical means, the embodiments of this application can acquire thermal property parameters of rock strata at different depths in real time during the drilling process, monitor the return slurry property parameters and temperature changes in real time, construct a two-dimensional transient heat transfer model of the drilling process, analyze the heat transfer process using the finite volume method, compare the measured and predicted return slurry temperatures, iteratively reconstruct the geothermal field, predict the heat extraction based on the buried pipe heat transfer numerical model, compare it with the design value, iteratively correct the assumed drilling depth, and determine the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value.

[0019] Optionally, in one embodiment of this application, the generation module includes: a calculation unit, used to calculate the actual geothermal gradient based on the thermophysical parameters, the measured mud inflow temperature, and the measured return mud temperature; and a determination unit, used to determine the underground soil temperature distribution information of the deep buried pipe in the target based on the actual geothermal gradient and the assumed drilling depth.

[0020] Through the above-mentioned technical means, the embodiments of this application can calculate the actual geothermal gradient layer by layer along the depth using measured parameters, so as to determine the underground soil temperature distribution information of the deep buried pipe in the target, making the calculated actual geothermal gradient more consistent with the actual geological conditions of the target area, thereby improving the accuracy of the underground soil temperature distribution information and providing reliable data support for subsequent geothermal field reconstruction and drilling parameter adjustment.

[0021] Optionally, in one embodiment of this application, the cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process includes the heat transfer process inside the drill pipe, the heat transfer process outside the drill pipe, and the heat transfer process of the soil layer, wherein the fluid control equation for the heat transfer process inside the drill pipe is: , in, T s,i The temperature of the drilling mud inside the drill pipe. T s,o The temperature of the drilling mud outside the drill pipe. u s,i The flow rate of the drilling mud inside the drill pipe is [value missing]. A in The cross-sectional area of ​​the inner sleeve is... ρ s The density of the mud. C p,s The specific heat capacity of the mud is... K dpi The heat transfer coefficient per unit length of the drill pipe is denoted as . For time parameters, z For depth parameters; The governing equations at the bottom of the well are corrected to: , Where, λ g The thermal conductivity of the soil. T g The temperature of the soil layer, Q d This is the heat generated by the drilling rig.

[0022] Through the above-mentioned technical means, the embodiments of this application can establish fluid control equations for the heat exchange process inside the drill pipe. Considering that the mud at the bottom of the drill pipe absorbs heat from the drilling rig in addition to heat exchange with the soil at the bottom of the well, a drilling rig heat term is introduced to correct the fluid control equations at the bottom of the well, thereby improving the physical authenticity of the mud return temperature prediction, making the model output more consistent with the measured data, and providing a reliable basis for geothermal field inversion.

[0023] Optionally, in one embodiment of this application, the fluid control equation for the external heat exchange process of the drill pipe is: , in, u s,o The flow rate of the drilling mud outside the drill pipe is [value missing]. A o The enclosed cross-sectional area of ​​the formed borehole and drill rod. h 6 represents the convective heat transfer coefficient between the mud and the soil on the outer wall of the well.

[0024] Through the above-mentioned technical means, the embodiments of this application can establish fluid control equations for the external heat exchange process of the drill pipe, clarify the influence of key parameters such as the external mud flow velocity, enclosed cross-sectional area, and convective heat transfer coefficient on the heat exchange process, thereby enhancing the adaptability of the model to different construction conditions, making the return mud temperature simulation closer to the actual thermal response process, and thus improving the robustness of the geothermal inversion.

[0025] Optionally, in one embodiment of this application, the governing equation for the heat transfer process in the soil layer is: , in, r For radial parameters, The density of the soil layer, C p,g The specific heat capacity of the soil layer is given. is the thermal conductivity of the soil layer.

[0026] Through the above-mentioned technical means, the embodiments of this application can clarify the control equation of the soil layer heat transfer process, accurately simulate the heat transfer law of the soil layer, further improve the heat transfer numerical model, improve the simulation accuracy of the model for the actual formation heat transfer process, and ensure that the predicted return temperature obtained based on the model is closer to the measured value, thereby providing reliable support for the reasonable determination of drilling depth and number.

[0027] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the intelligent borehole design method for medium-deep buried pipes as described in the above embodiments.

[0028] A fourth aspect of this application provides a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intelligent borehole design method for medium-deep buried pipes.

[0029] The fifth aspect of this application provides a computer program product that stores a computer program that, when executed by a processor, implements the above-described intelligent borehole design method for medium-deep buried pipes.

[0030] This application embodiment can acquire thermal property parameters of rock strata at different depths in real time during the drilling process, monitor the return slurry properties and temperature changes in real time, construct a two-dimensional transient heat transfer model of the drilling process, analyze the heat transfer process using the finite volume method, compare the measured and predicted return slurry temperatures, iteratively reconstruct the geothermal field, predict the heat extraction based on the buried pipe heat transfer numerical model, compare it with the design value, iteratively correct the assumed drilling depth, and determine the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value. Therefore, it solves the problems in related technologies, such as redundant or insufficient drilling depth, high construction costs, significant deviations in geothermal field prediction, and the inability to form a closed-loop feedback of monitoring data during construction, making it difficult to dynamically correct drilling parameters due to systematic errors in depth setting.

[0031] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0032] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1This is a flowchart of a smart borehole design method for medium-deep buried pipes according to an embodiment of this application; Figure 2 This is a schematic diagram illustrating the depth-by-depth calculation of the geothermal gradient reconstruction method according to an embodiment of this application; Figure 3 This is a flowchart of a smart borehole design method for medium-deep underground pipes according to an embodiment of this application; Figure 4 This is a comparative analysis chart of the measured and simulated values ​​of the return slurry temperature according to an embodiment of this application; Figure 5 This is a schematic diagram of a smart borehole design device for medium-deep underground pipes provided in accordance with an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application.

[0033] Figure label: 10-Intelligent borehole design device for medium-deep buried pipes; 100-Acquisition module, 200-Generation module, 300-Reconstruction module, 400-Design module; 601-Memory, 602-Processor, 603-Communication interface. Detailed Implementation

[0034] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0035] The following description, with reference to the accompanying drawings, describes a method, apparatus, and electronic device for intelligent borehole design of medium-deep underground pipes according to embodiments of this application. In response to the problems mentioned in the background technology, such as the systematic errors in depth setting leading to redundant or insufficient drilling depth, high construction costs, significant deviations in geothermal field prediction, and the inability to form a closed-loop feedback of monitoring data during construction, making it difficult to dynamically correct drilling parameters, this application provides a smart borehole design method for medium-deep buried pipes. This method acquires thermal property parameters of rock materials at different depths in real time during the borehole process, monitors the return slurry properties and temperature changes in real time, constructs a two-dimensional transient heat transfer model of the drilling process, analyzes the heat transfer process using the finite volume method, compares the measured and predicted return slurry temperatures, iteratively reconstructs the geothermal field, predicts the heat extraction based on the buried pipe heat transfer numerical model, compares it with the design value, iteratively corrects the assumed drilling depth, and determines the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value. This solves the problems in related technologies, such as redundant or insufficient drilling depth, high construction costs, significant deviations in geothermal field prediction, and the inability of monitoring data to form a closed-loop feedback during construction, making it difficult to dynamically correct drilling parameters.

[0036] Specifically, Figure 1 This is a flowchart illustrating a smart borehole design method for medium-deep buried pipes provided in an embodiment of this application.

[0037] like Figure 1 As shown, the intelligent borehole design method for medium-deep buried pipes includes the following steps: In step S101, the measured mud inflow temperature and measured return mud temperature of the deep buried pipe in the target are collected during the construction and drilling process.

[0038] It is understood that the measured mud inflow temperature in the embodiments of this application can be understood as the temperature measured at the mud inlet; the measured return mud temperature can be understood as the temperature measured at the mud outlet.

[0039] In actual implementation, the embodiments of this application can periodically collect, test and record relevant parameters of the deep buried pipe in the target during the construction and drilling process, including measured mud inflow temperature, measured mud return temperature, drilling depth, bottom hole temperature, ambient temperature, rock type, drilling rig power, mud pump discharge rate and other parameters; wherein, the measured mud inflow temperature and measured mud return temperature are collected in real time using temperature sensors, and the bottom hole temperature is continuously acquired using a pre-embedded fiber optic temperature sensor, with a collection frequency of not less than once every 200m well depth.

[0040] The embodiments of this application can collect the measured mud inflow and return temperatures during the drilling process in real time, obtain dynamic real-time data on heat exchange between the underground formation and the mud, and provide accurate measured basis for subsequent calculation of the actual geothermal gradient and correction of soil temperature distribution.

[0041] In step S102, the assumed drilling depth is determined according to the actual progress of the project, and the underground soil temperature distribution information of the deep buried pipe in the target is generated based on the thermal properties of rock materials at different depths, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth.

[0042] It is understood that the actual progress of the project in this application embodiment can be the drilling stage or the planning stage; the thermal properties parameters can include, but are not limited to, the thermal conductivity, density, and specific heat capacity of rock strata (soil) at different depths.

[0043] In actual implementation, this application embodiment can collect thermal property parameters of rock strata at different depths during the drilling process of medium-deep buried pipe construction in real time. An initial assumption about the drilling depth is set according to the actual progress of the project. Specifically, regarding the assumption about the drilling depth and the underground soil temperature distribution, if the actual drilling depth is used as the assumed drilling depth during the borehole formation stage, or if it is still in the planning stage, an assumption can be made based on engineering experience. Based on the thermal property parameters of rock strata at different depths, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth, the underground soil temperature distribution is generated.

[0044] The embodiments of this application can make assumptions about the drilling depth based on actual engineering conditions to obtain the underground soil temperature distribution, so that the temperature distribution information is more in line with the actual strata characteristics of the target area, avoiding the depth setting deviation caused by strata heterogeneity, and providing basic data for subsequent geothermal field reconstruction and drilling parameter adjustment.

[0045] Optionally, in one embodiment of this application, information on the underground soil temperature distribution of the deep buried pipe in the target is generated based on thermophysical parameters, measured mud inflow temperature, measured mud return temperature, and assumed drilling depth. This includes: calculating the actual geothermal gradient based on thermophysical parameters, measured mud inflow temperature, and measured mud return temperature; and determining the underground soil temperature distribution information of the deep buried pipe in the target based on the actual geothermal gradient and assumed drilling depth.

[0046] It is understood that the actual geothermal gradient in the embodiments of this application can be understood as the actual rate of change of underground soil temperature with depth in the target area.

[0047] In practical implementation, the embodiments of this application can calculate the actual geothermal gradient based on thermophysical parameters, measured mud inflow temperature, and measured mud return temperature, and combine this with depth to determine the underground soil temperature distribution information of the deep buried pipe in the target. Compared with conventional empirical values, the geothermal gradient reconstructed based on measured data better reflects the actual geological conditions of each well.

[0048] This application embodiment can calculate the actual geothermal gradient layer by layer along the depth using measured parameters to determine the underground soil temperature distribution information of the deep buried pipe in the target, so that the calculated actual geothermal gradient is more in line with the actual situation of the target area, thereby improving the accuracy of the underground soil temperature distribution information and providing reliable data support for subsequent geothermal field reconstruction and drilling parameter adjustment.

[0049] In step S103, based on the pre-constructed two-dimensional transient heat transfer numerical model of the drilling process in cylindrical coordinates, the predicted slurry return temperature of the target deep buried pipe is obtained, and the absolute value of the deviation between the predicted slurry return temperature and the measured slurry return temperature is calculated to correct the underground soil temperature distribution until the absolute value of the deviation is less than the preset deviation threshold, and the geothermal field of the target deep buried pipe is reconstructed.

[0050] It is understood that the two-dimensional transient heat transfer numerical model in cylindrical coordinates of the drilling process in the embodiments of this application can be used to accurately describe the heat exchange of mud during the drilling process; the preset deviation threshold can be 0.5℃, and the preset deviation threshold can be set by those skilled in the art according to the actual situation, without any specific limitation here.

[0051] In actual implementation, the embodiments of this application can construct a two-dimensional transient heat transfer numerical model in cylindrical coordinates for the drilling process, predict the return temperature based on the model, and obtain the predicted return temperature; calculate the absolute value of the deviation between the predicted return temperature and the measured return temperature. If the absolute value of the deviation is ≤0.5℃, it is confirmed that the underground soil temperature distribution conforms to the actual formation conditions; if the absolute value of the deviation is >0.5℃, the underground soil temperature distribution is corrected according to the deviation and recalculated, and the geothermal field is reconstructed based on the underground soil temperature distribution output by the model.

[0052] The modeling adopts the following assumptions: the thermal properties of the heat exchange medium, buried pipe, backfill material and surrounding rock strata are constant; the effects of groundwater flow, soil porosity and contact thermal resistance between the outer pipe and the soil are not considered separately, but their combined effect is included in the contact thermal resistance of the outer pipe; the three-dimensional unsteady heat transfer problem is simplified into a two-dimensional transient problem to improve computational efficiency.

[0053] For example, before substituting the measured data into the calculation, the measured data is interpolated at 5m depth intervals, and the drilling time corresponding to each depth is calculated based on the drilling time record. Subsequently, the interpolated measured data is extracted at 2-hour drilling time intervals as input for model calculation.

[0054] Figure 2 This diagram illustrates the depth-by-depth layer-by-layer calculation method for geothermal gradient reconstruction in this embodiment. As shown, the method employs a depth-by-depth layer-by-layer calculation approach. The calculation is completed in the first layer corresponding to time τ-1. Figure 2 After the calculation process, the calculated results are used. T t (τ-1) with respect to depth l τ-1 The geothermal field is reconstructed; subsequently, when performing the second-layer calculation corresponding to time τ, it is only necessary to assume l τ - l τ-1 The distribution of ground temperature in the section, l τ-1 The geothermal distribution of the segment remains consistent with the calculation results of the previous layer. The overall calculation process is then performed again, and the calculation results are used to reconstruct the data. l τ - l τ-1 The geothermal field of the section.

[0055] This application embodiment can analyze the heat transfer process during drilling and operation based on a two-dimensional transient heat transfer model in cylindrical coordinates using the finite volume method. It comprehensively considers the influence of geological conditions, circulation flow rate and other factors on heat transfer efficiency, thereby achieving a return temperature prediction error of ≤0.5℃ through dynamic inversion. This significantly improves the accuracy of geothermal field reconstruction, solves the problem of geothermal field response deviation in the prior art, and provides accurate core basis for subsequent heat extraction calculation and drilling depth adjustment.

[0056] Optionally, in one embodiment of this application, the cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process includes the heat transfer process inside the drill pipe, the heat transfer process outside the drill pipe, and the heat transfer process of the soil layer, wherein the fluid control equation for the heat transfer process inside the drill pipe is: , in, T s,i The temperature of the drilling mud inside the drill pipe. T s,o The temperature of the drilling mud outside the drill pipe. u s,i The flow rate of the drilling mud inside the drill pipe. A in The cross-sectional area of ​​the inner sleeve is... ρ s The density of the mud. C p,s The specific heat capacity of the mud. K dpi The heat transfer coefficient per unit length of the drill pipe is denoted as . For time parameters, z For depth parameters; The governing equations at the bottom of the well are corrected to: , Where, λ g The thermal conductivity of the soil. T g The temperature of the soil layer, Q d This is the heat generated by the drilling rig.

[0057] In actual implementation, the embodiments of this application can address the heat exchange process inside the drill pipe. During this process, the mud flows from top to bottom within the drill pipe and exchanges heat with the mud outside the drill pipe. Heat is continuously transferred inward through the drill pipe wall. The fluid control equation is shown below: , in, T s,i Temperature of the drilling mud inside the drill pipe, in °C; T s,o Temperature of the drilling mud outside the drill pipe, in °C; u s,i The velocity of the drilling mud inside the drill pipe is expressed in m / s. A in The cross-sectional area of ​​the inner sleeve is expressed in meters (m²). 2 ; ρ s The density of the mud is expressed in kg / m³. 3 ; C p,s Specific heat capacity of mud, in kJ / (kg·℃); This is a time parameter, in seconds (s). z This is a depth parameter, in meters (m). K dpi Let be the heat transfer coefficient per unit length of the drill pipe, and its calculation formula is as follows: , in, r dpi The inner diameter of the drill pipe is in meters (m). r dpo The outer diameter of the drill pipe is in meters (m). h 4 represents the heat transfer coefficient of the inner surface of the drill pipe, in W / (m·°C). h 5 represents the heat transfer coefficient of the drill pipe's outer surface, in W / (m·°C).

[0058] Furthermore, at the bottom of the well, the drilling mud inside and outside the drill pipe is connected, and isothermal conditions are established, meaning the temperature of the mud inside and outside the drill pipe is equal. However, because the drilling power of the drill bit at the bottom of the well is converted into heat, the mud at the bottom of the drill pipe absorbs heat from the drilling rig in addition to heat exchange with the bottom soil. The fluid control equation for the bottom layer then transforms into the following equation: , Where, λ g is the thermal conductivity of the soil, expressed in W / (m·°C); T g Temperature of the soil layer, in °C; Q d The heat output of the drilling rig is expressed in kW.

[0059] The embodiments of this application can establish fluid control equations for the heat exchange process inside the drill pipe. Considering that the mud at the bottom of the drill pipe absorbs heat from the drilling rig in addition to heat exchange with the soil at the bottom of the well, a drilling rig heat term is introduced to correct the fluid control equations at the bottom of the well, thereby improving the physical accuracy of the mud return temperature prediction, making the model output more consistent with the measured data, and providing a reliable basis for geothermal field inversion.

[0060] Optionally, in one embodiment of this application, the fluid control equation for the external heat exchange process of the drill pipe is: , in, u s,o The flow velocity of the drilling mud outside the drill pipe. A o The enclosed cross-sectional area of ​​the formed borehole and drill rod. h 6 represents the convective heat transfer coefficient between the drilling mud and the soil on the outer wall of the well.

[0061] In actual implementation, the embodiments of this application can address the heat exchange process outside the drill pipe. In this process, the mud flows from bottom to top outside the drill pipe and directly exchanges heat with the soil layer, while simultaneously exchanging heat with the mud inside the drill pipe. The fluid control equation formula is as follows:

[0062] in, u s,o The velocity of the drilling mud outside the drill pipe is expressed in m / s. A o The unit is the enclosed cross-sectional area of ​​the borehole and drill pipe, expressed in meters (m). 2 ; h 6 represents the convective heat transfer coefficient between the drilling mud and the soil on the outer wall of the well, in W / (m·°C).

[0063] The embodiments of this application can establish fluid control equations for the external heat exchange process of the drill pipe, clarify the influence of key parameters such as the external mud flow velocity, enclosed cross-sectional area, and convective heat transfer coefficient on the heat exchange process, thereby enhancing the model's adaptability to different construction conditions, making the return mud temperature simulation closer to the actual thermal response process, and thus improving the robustness of the geothermal inversion.

[0064] Optionally, in one embodiment of this application, the governing equation for the heat transfer process in the soil layer is: , in, r For radial parameters, The density of the soil layer, C p,g The specific heat capacity of the soil layer, The thermal conductivity of the soil layer is given.

[0065] In actual implementation, the embodiments of this application can be used for the heat transfer process in the soil layer, the expression of which is as follows: , in, r Radial parameter, in meters (m); The density of the soil layer, in kg / m³ 3 ; C p,g Specific heat capacity of the soil layer, in kJ / (kg·℃); while is the thermal conductivity of the soil layer, expressed in W / (m·°C).

[0066] For the heat transfer process described above, the finite volume method is used to numerically simulate and solve the mud heat transfer process. Taking the mud outside the drill pipe as an example, its fluid control equations can be discretized as follows: , In the formula, The unit grid length represents the depth direction, in meters (m). The unit represents the time interval, in seconds (s). To further accelerate the calculation process, this study also sets the soil layer grid to a non-uniform grid, the expression of which is: , In the formula, r b Represents the radius of the borehole wall for buried pipes, in meters (m).

[0067] The embodiments of this application can clarify the governing equations of the soil layer heat transfer process, accurately simulate the heat transfer law of the soil layer, further improve the heat transfer numerical model, enhance the model's simulation accuracy of the actual formation heat transfer process, and ensure that the predicted return temperature obtained based on the model is closer to the measured value, thereby providing reliable support for the reasonable determination of drilling depth and number.

[0068] In step S104, based on the pre-built numerical model of heat transfer of the buried pipe and the geothermal field, the heat extraction of the buried pipe is calculated to adjust the assumed drilling depth until the heat extraction exceeds the preset design value, and the depth and number of the target deep buried pipe are determined.

[0069] It is understood that the buried pipe heat transfer numerical model in the embodiments of this application can simulate the heat exchange of heat source water flowing downward in the outer pipe and upward in the inner pipe, including heat exchange between the outer pipe wall and the backfill material, heat exchange between the inner pipe wall and the water in the inner pipe, and heat transfer between the backfill material and the soil layer; the preset design value can be understood as the project design requirement. Based on the heating demand of the target area and the minimum heat extraction requirement of the buried pipe determined by the engineering design standards, the preset design value can be set by those skilled in the art according to the actual situation, and no specific restrictions are made here.

[0070] In actual implementation, the embodiments of this application can substitute the reconstructed underground soil temperature distribution into the buried pipe heat transfer numerical model, and use the finite volume method to solve the two-dimensional transient heat transfer process to obtain the heat extracted by the buried pipe.

[0071] Furthermore, the predicted heat recovery from a single well is compared with the designed heat recovery from the engineering project to determine whether the predicted heat recovery meets the project design requirements, i.e., exceeds the preset design value. If the predicted value is less than the design value, the assumed drilling depth is adjusted and recalculated; if the predicted value is greater than or equal to the design value, the heat recovery is confirmed to meet the requirements, and the depth of the buried pipe and the number of wells are determined.

[0072] This application embodiment can accurately calculate the heat extraction of the buried pipe by pre-constructing a numerical model of heat transfer in the buried pipe and combining it with precisely reconstructed geothermal field data. This allows for dynamic adjustment of the drilling depth and determination of the number of buried pipes based on the heat extraction, thereby optimizing the layout of the buried pipes, achieving adaptive optimization of the construction depth, and avoiding excessively long drilling cycles and costs, or insufficient heat extraction due to experience-based design.

[0073] Specifically, it can be combined with Figure 3 and Figure 4 As shown, the working principle of the intelligent borehole design method for medium-deep buried pipes in this application is explained in detail with a specific embodiment.

[0074] like Figure 3 As shown, embodiments of this application may include the following steps: Step S301: Collect thermal property parameters of rock materials at different depths and measure the grout return temperature.T s,o,ture Measured mud inflow temperature T s,i .

[0075] In this embodiment, the thermal properties of rock materials at different depths can be collected in real time, and the mud inflow temperature, return temperature and physical properties can be monitored and recorded.

[0076] Step S302: Assume drilling depth and geothermal distribution T t .

[0077] In this application, the drilling depth and initial geothermal distribution can be assumed based on engineering conditions.

[0078] Step S303: Numerical model of heat transfer during drilling process, prediction of return soil temperature T s,o,pre Determine if the condition is met. T s,o,pre - T s,o,ture If the temperature is ≤0.5℃, then correct the assumed geothermal distribution of S302; if it is, then reconstruct the geothermal field. T t .

[0079] In this embodiment, a two-dimensional transient heat transfer numerical model in cylindrical coordinates can be constructed to predict the return temperature of the drilling process. If the absolute value of the deviation is ≤0.5℃, the geothermal field is reconstructed; otherwise, the process returns to step S302 to optimize the assumed geothermal distribution.

[0080] Step S304: Numerical model of heat transfer in underground pipes and calculation of heat extraction from underground pipes.

[0081] In this embodiment, the reconstructed geothermal field can be substituted into the buried pipe heat transfer numerical model to calculate the heat extraction.

[0082] Step S305: Determine whether the calculated heat output is greater than or equal to the designed heat output. If not, correct the assumed drilling depth in S302. If yes, determine the depth and quantity of the buried pipe.

[0083] In this embodiment, it can determine whether the calculated heat extraction meets the design requirements. If it does, the depth and number of buried pipes are determined; otherwise, the process returns to step S302 to adjust the assumed depth.

[0084] The intelligent borehole design method for medium-deep underground pipelines according to a specific embodiment of this application is described in detail. In this embodiment, intelligent borehole design was carried out based on measured data collected during the borehole formation of six 2500m deep medium-deep underground pipelines.

[0085] During the drilling process, all the mechanical energy of the drill pipe is converted into heat energy and absorbed by the drilling mud, which is taken as the measured drilling rig power of 630kW. The physical property parameters of each component involved in the above heat exchange process are shown in Table 1, which is the physical property parameter table of the medium-deep buried pipe heat exchanger.

[0086] Table 1

[0087] Subsequently, based on the measured data collected during the drilling process, a predictive analysis of heat extraction was conducted. Furthermore, based on the embodiments of this application, the theoretical values ​​of the return grout temperature at different construction depths were calculated.

[0088] like Figure 4 As shown, the calculated slurry return temperature is generally consistent with the measured value, but there is still a certain deviation. Taking Well No. 1 as an example, in the early stage of drilling (depth 20m), the measured slurry return temperature was 16.27℃, while the model predicted a value of 19.95℃, with the calculated value being about 3.7℃ higher; at a depth of 1000m, the measured value was 27.91℃, and the predicted value was 27.85℃, with the deviation narrowing to 0.06℃; and at a depth of 2500m, the measured value differed from the predicted value by 0.6℃.

[0089] Subsequently, geothermal gradient values ​​at different depths were obtained. Compared with conventional empirical values, the geothermal gradient reconstructed based on measured data better reflects the actual geological conditions of each well. The complexity of underground soil and its influence by factors such as groundwater flow mean that even wells only a hundred meters apart can have significantly different geothermal distributions. The average geothermal gradients of six wells were further calculated: Well 1 was 3.049℃ / hm², Well 2 was 3.174℃ / hm², Well 3 was 2.903℃ / hm², Well 4 was 2.869℃ / hm², Well 5 was 2.892℃ / hm², and Well 6 was 2.857℃ / hm², all higher than empirical values. The predicted temperature at a depth of 2500 meters was 84.25℃, while the actual calculated values ​​were 89.22℃, 92.35℃, 85.58℃, 84.73℃, 85.3℃, and 84.43℃, all higher than empirical estimates. This indicates that overestimating the actual geothermal gradient can lead to greater heat extraction potential, providing a better heat source basis for system design and operation.

[0090] Based on the reconstructed geothermal gradient, it was substituted into the numerical model of heat transfer in medium-deep buried pipes to further predict the heat extraction capacity under extreme operating conditions. Using an influent water temperature of 5℃ and a heat source-side flow rate of 30 m³ / h as boundary conditions, the average heat extraction for the first 30 days was calculated and compared with conventional empirical values. The results show that the predicted actual heat extraction values ​​for wells 1 to 6 are 570.96 kW, 580.81 kW, 557.78 kW, 552.38 kW, 556.03 kW, and 550.47 kW, respectively, representing increases of 3.93%, 5.72%, 1.53%, 0.55%, 1.21%, and 0.20% compared to the conventional empirical value of 549.36 kW. This result indicates that the measured parameters obtained based on the dynamic inversion method can significantly improve the accuracy of heat extraction prediction, resulting in an actual heat extraction capacity higher than the design value during future operation. This improvement not only optimizes the heating performance of the heat pump system but also provides important support for the project's economic viability and sustainability.

[0091] The intelligent borehole design method for medium-deep buried pipes proposed in this application can acquire thermal property parameters of rock materials at different depths in real time during the borehole process, monitor the return slurry properties and temperature changes in real time, construct a two-dimensional transient heat transfer model of the drilling process, analyze the heat transfer process using the finite volume method, compare the measured and predicted return slurry temperatures, iteratively reconstruct the geothermal field, predict the heat extraction based on the buried pipe heat transfer numerical model, compare it with the design value, iteratively correct the assumed drilling depth, and determine the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value. This solves the problems in related technologies where systematic errors in depth setting lead to redundant or insufficient drilling depths, high construction costs, significant deviations in geothermal field prediction, and the failure of monitoring data to form a closed-loop feedback mechanism during construction, making it difficult to dynamically correct drilling parameters.

[0092] Next, referring to the accompanying drawings, the intelligent borehole design device for medium-deep buried pipes proposed according to the embodiments of this application is described.

[0093] Figure 5 This is a schematic diagram of the intelligent borehole design device for medium-deep buried pipes according to an embodiment of this application.

[0094] like Figure 5 As shown, the intelligent borehole design device 10 for medium-deep buried pipes includes: a data acquisition module 100, a generation module 200, a reconstruction module 300, and a design module 400.

[0095] Among them, the acquisition module 100 is used to acquire the measured mud inflow temperature and measured mud return temperature of the deep buried pipe in the target during the construction and drilling process; The generation module 200 is used to determine the assumed drilling depth according to the actual progress of the project, and generate underground soil temperature distribution information of the deep buried pipe in the target based on the thermal properties of rock materials at different depths, the measured mud inflow temperature, the measured mud return temperature and the assumed drilling depth. The reconstruction module 300 is used to obtain the predicted slurry return temperature of the deep buried pipe in the target based on the pre-built two-dimensional transient heat transfer numerical model of the drilling process in cylindrical coordinates, calculate the absolute value of the deviation between the predicted slurry return temperature and the measured slurry return temperature, correct the underground soil temperature distribution, until the absolute value of the deviation is less than the preset deviation threshold, and reconstruct the geothermal field of the deep buried pipe in the target. Design module 400 is used to calculate the heat extraction of the buried pipe based on a pre-built numerical model of buried pipe heat transfer and geothermal field, so as to adjust the assumed drilling depth until the heat extraction exceeds the preset design value, and determine the depth and number of deep buried pipes in the target.

[0096] Optionally, in one embodiment of this application, the generation module 200 includes a calculation unit and a determination unit.

[0097] The calculation unit is used to calculate the actual geothermal gradient based on thermophysical parameters, measured mud inflow temperature, and measured mud return temperature.

[0098] The determination unit is used to determine the underground soil temperature distribution information of the deep buried pipe in the target based on the actual geothermal gradient and the assumed drilling depth.

[0099] Optionally, in one embodiment of this application, the cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process includes the heat transfer process inside the drill pipe, the heat transfer process outside the drill pipe, and the heat transfer process of the soil layer, wherein the fluid control equation for the heat transfer process inside the drill pipe is: , in, T s,i The temperature of the drilling mud inside the drill pipe. T s,o The temperature of the drilling mud outside the drill pipe. u s,i The flow rate of the drilling mud inside the drill pipe. A in The cross-sectional area of ​​the inner sleeve is... ρ s The density of the mud. C p,s The specific heat capacity of the mud. K dpi The heat transfer coefficient per unit length of the drill pipe is denoted as . For time parameters, z For depth parameters; The governing equations at the bottom of the well are corrected to: , Where, λ g The thermal conductivity of the soil. T g The temperature of the soil layer, Q d This is the heat generated by the drilling rig.

[0100] Optionally, in one embodiment of this application, the fluid control equation for the external heat exchange process of the drill pipe is: , in, u s,o The flow velocity of the drilling mud outside the drill pipe. A o The enclosed cross-sectional area of ​​the formed borehole and drill rod. h 6 represents the convective heat transfer coefficient between the drilling mud and the soil on the outer wall of the well.

[0101] Optionally, in one embodiment of this application, the governing equation for the heat transfer process in the soil layer is: , in, r For radial parameters, The density of the soil layer, C p,g The specific heat capacity of the soil layer, The thermal conductivity of the soil layer is given.

[0102] It should be noted that the foregoing explanation of the embodiment of the intelligent borehole design method for medium-deep buried pipes also applies to the intelligent borehole design device for medium-deep buried pipes in this embodiment, and will not be repeated here.

[0103] The intelligent borehole design device for medium-deep buried pipes proposed in this application can acquire thermal property parameters of rock strata at different depths in real time during the borehole process, monitor the return slurry properties and temperature changes in real time, construct a two-dimensional transient heat transfer model of the drilling process, analyze the heat transfer process using the finite volume method, compare the measured and predicted return slurry temperatures, iteratively reconstruct the geothermal field, predict the heat extraction based on the buried pipe heat transfer numerical model, compare it with the design value, iteratively correct the assumed drilling depth, and determine the depth and number of buried pipes. This achieves adaptive optimization of construction depth, improves the construction efficiency and prediction accuracy of medium-deep buried pipe heat pump systems, enhances long-term operational stability, supports real-time iterative adjustments, is applicable to various geothermal resource conditions, improves project controllability and economy, and has significant engineering application value. Therefore, it solves the problems in related technologies where systematic errors in depth setting lead to redundant or insufficient drilling depths, high construction costs, significant deviations in geothermal field prediction, and the failure of monitoring data to form a closed-loop feedback during construction, making it difficult to dynamically correct drilling parameters.

[0104] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0105] When the processor 602 executes the program, it implements the intelligent borehole design method for medium-deep buried pipes provided in the above embodiments.

[0106] Furthermore, electronic devices also include: Communication interface 603 is used for communication between memory 601 and processor 602.

[0107] The memory 601 is used to store computer programs that can run on the processor 602.

[0108] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0109] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0110] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0111] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0112] This application also provides a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intelligent borehole design method for medium-deep buried pipes.

[0113] This application also provides a computer program product storing a computer program that, when executed by a processor, implements the above-described intelligent borehole design method for medium-deep buried pipes.

[0114] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0115] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0116] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0117] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0118] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0119] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0120] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0121] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A smart borehole design method for medium-deep buried pipes, characterized in that, Includes the following steps: The measured mud inflow temperature and measured mud return temperature were collected during the drilling process of the deep buried pipe in the target area. The assumed drilling depth is determined based on the actual progress of the project, and the underground soil temperature distribution information of the target deep buried pipe is generated based on the thermal properties of rock materials at different depths, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth. Based on a pre-constructed two-dimensional transient heat transfer numerical model of the drilling process in cylindrical coordinates, the predicted slurry return temperature of the deep buried pipe in the target is obtained. The absolute value of the deviation between the predicted slurry return temperature and the measured slurry return temperature is calculated to correct the underground soil temperature distribution until the absolute value of the deviation is less than a preset deviation threshold, and the geothermal field of the deep buried pipe in the target is reconstructed. Based on the pre-constructed numerical model of heat transfer in the buried pipe and the geothermal field, the heat extraction of the buried pipe is calculated to adjust the assumed drilling depth until the heat extraction exceeds the preset design value, thereby determining the depth and number of the target deep buried pipe.

2. The method according to claim 1, characterized in that, The information on the underground soil temperature distribution of the deep buried pipe in the target area, generated based on the thermophysical parameters, the measured mud inflow temperature, the measured mud return temperature, and the assumed drilling depth, includes: The actual geothermal gradient is calculated based on the aforementioned thermophysical parameters, the measured mud inflow temperature, and the measured mud return temperature. Based on the actual geothermal gradient and the assumed drilling depth, the underground soil temperature distribution information of the deep buried pipe in the target is determined.

3. The method according to claim 1, characterized in that, The cylindrical coordinate two-dimensional transient heat transfer numerical model of the drilling process includes the heat transfer process inside the drill pipe, the heat transfer process outside the drill pipe, and the heat transfer process in the soil layer. The fluid control equation for the heat transfer process inside the drill pipe is: ， in, T s,i The temperature of the drilling mud inside the drill pipe. T s,o The temperature of the drilling mud outside the drill pipe. u s,i The velocity of the drilling mud inside the drill pipe is given. A in The cross-sectional area of ​​the inner sleeve is... ρ s The density of the mud. C p,s The specific heat capacity of the mud is... K dpi The heat transfer coefficient per unit length of the drill pipe is denoted as . For time parameters, z For depth parameters; The governing equations at the bottom of the well are corrected to: ， Where, λ g The thermal conductivity of the soil. T g The temperature of the soil layer, Q d This is the heat generated by the drilling rig.

4. The method according to claim 3, characterized in that, The fluid control equation for the external heat exchange process of the drill pipe is: ， in, u s,o The flow rate of the drilling mud outside the drill pipe is [value missing]. A o The enclosed cross-sectional area of ​​the formed borehole and drill rod. h 6 represents the convective heat transfer coefficient between the mud and the soil on the outer wall of the well.

5. The method according to claim 3, characterized in that, The governing equation for the heat transfer process in the soil layer is: ， in, r For radial parameters, The density of the soil layer, C p,g The specific heat capacity of the soil layer is... is the thermal conductivity of the soil layer.

6. A smart borehole design device for medium-deep buried pipes, characterized in that, include: The data acquisition module is used to collect the measured mud inflow temperature and measured mud return temperature of the deep buried pipe in the target during the construction and drilling process. The generation module is used to determine the assumed drilling depth based on the actual progress of the project, and generate the underground soil temperature distribution information of the target deep buried pipe based on the thermal properties of rock materials at different depths, the measured mud inflow temperature, the measured mud return temperature and the assumed drilling depth. The reconstruction module is used to obtain the predicted slurry return temperature of the deep underground pipe in the target based on a pre-built two-dimensional transient heat transfer numerical model in cylindrical coordinates of the drilling process, calculate the absolute value of the deviation between the predicted slurry return temperature and the measured slurry return temperature, correct the underground soil temperature distribution, until the absolute value of the deviation is less than a preset deviation threshold, and reconstruct the geothermal field of the deep underground pipe in the target. The design module is used to calculate the heat extraction of the buried pipe based on a pre-built numerical model of heat transfer in the buried pipe and the geothermal field, so as to adjust the assumed drilling depth until the heat extraction exceeds the preset design value, and determine the depth and number of the target deep buried pipe.

7. The apparatus according to claim 6, characterized in that, The generation module includes: The calculation unit is used to calculate the actual geothermal gradient based on the thermophysical parameters, the measured mud inflow temperature, and the measured mud return temperature. The determining unit is used to determine the underground soil temperature distribution information of the deep buried pipe in the target based on the actual geothermal gradient and the assumed drilling depth.

8. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the intelligent borehole design method for medium-deep buried pipes as described in any one of claims 1-5.

9. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the intelligent borehole design method for medium-deep buried pipes as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the intelligent borehole design method for medium-deep buried pipes as described in any one of claims 1-5.

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