CN115629102B - A method for identifying geothermal property parameters based on geological stratification - Google Patents

Abstract

The invention discloses a geotechnical thermophysical parameter identification method based on geological stratification. The method comprises the steps of constructing an experimental model of the ground heat exchanger, carrying out a thermal response experiment on rock and soil to be identified by using the experimental model of the ground heat exchanger, obtaining measured temperature values of all temperature sensors in the experimental model of the ground heat exchanger in the thermal response experiment process, constructing a numerical simulation model of the rock and soil thermal response experiment by using finite element simulation software based on the experimental model of the ground heat exchanger, simulating the thermal response experiment by using the numerical model of the rock and soil thermal response experiment, obtaining simulation temperatures of all the temperature sensors at different moments, constructing an objective function, optimizing the objective function by using an L-M algorithm, and determining the optimal solution of the thermal physical parameters of the rock and soil to be identified. According to the invention, the rock-soil thermal response experiment is combined with the finite element numerical simulation method, so that the working condition of the buried pipe heat exchanger is truly reduced, the accurate acquisition of the multi-layer rock-soil thermal physical parameters is realized, and a foundation is laid for guiding the design scheme of the buried pipe heat exchanger.

Description

A method for identifying geothermal property parameters based on geological stratification

Technical Field

The present invention relates to the technical field of ground source heat pumps, and in particular to a method for identifying geothermal property parameters based on geological stratification.

Background Art

As a renewable energy, geothermal energy has attracted much attention due to its green and environmentally friendly, large reserves, wide distribution, strong adaptability and recyclability. Ground source heat pumps use shallow geothermal resources as low-grade energy and provide heat (cold) to buildings by inputting a small amount of high-grade energy (such as electricity) to achieve the purpose of heating (cooling).

As the core component of the ground source heat pump system, the design of the buried pipe heat exchanger directly affects the operating performance and economic value of the ground source heat pump. The geothermal parameters are an important basis for the design of the buried pipe heat exchanger. Usually, the buried depth of the vertical buried pipe heat exchanger is 50 to 200 meters. There is a high probability that there will be obvious stratification of the underground rock and soil along the depth direction, and the thermophysical parameters of different rock and soil layers may vary greatly. Therefore, accurate identification of the thermophysical parameters of the local rock and soil is of guiding significance for the design of the buried pipe, which can directly affect the heat exchange efficiency and initial investment of the buried pipe heat exchanger.

At present, the internationally accepted method for determining the thermophysical parameters of geotechnical materials is the field thermal response test (TRT). By loading heat or cold into the ground pipe heat exchanger, the thermal response of the soil is reflected in the temperature change of the inlet and outlet circulating fluid of the ground pipe heat exchanger, and the thermophysical parameters of geotechnical materials are inverted by combining other original experimental setting parameters. However, due to the complex heat exchange process of the ground pipe underground, the ground pipe heat exchanger is often regarded as a linear heat source in the process of solving this problem, and the result obtained is the average thermophysical parameters of the local geotechnical materials. There are certain limitations, and it is difficult to solve the thermophysical parameters of multi-layered geotechnical materials, and it is impossible to accurately calculate the thermophysical parameters of each layer of geotechnical materials.

Summary of the invention

The present invention aims to realize accurate calculation of thermophysical property parameters of layered rock and soil, and proposes a method for identifying thermophysical property parameters of rock and soil based on geological stratification. By combining the rock and soil thermal response experiment with the finite element numerical simulation method, the L-M algorithm is used to optimize the thermophysical property parameters of the rock and soil to be identified, and the accurate acquisition of the thermophysical property parameters of multi-layer rock and soil is achieved, laying a foundation for guiding the design of buried pipe heat exchangers.

The present invention adopts the following technical solutions:

A method for identifying geothermal property parameters based on geological stratification, specifically comprising the following steps:

Step 1: construct a ground pipe heat exchanger experimental model, obtain the structural parameters of the ground pipe heat exchanger in the ground pipe heat exchanger experimental model, and determine the stratification of the rock and soil to be identified in the ground pipe heat exchanger experimental model and the density of each layer of rock and soil;

Step 2: Use the underground heat exchanger experimental model to conduct a thermal response experiment on the rock and soil to be identified, set the experimental parameters of the thermal response experiment, and measure the temperature of the U-shaped buried pipe inlet pipe, the temperature of the liquid outlet pipe in the underground heat exchanger experimental model, and the temperature of each layer of rock and soil in the rock and soil to be identified in real time during the thermal response experiment;

Step 3: Based on the underground heat exchanger experimental model, a numerical simulation model of the geotechnical thermal response experiment is constructed using finite element simulation software, boundary conditions of the numerical simulation model of the geotechnical thermal response experiment are set, and the numerical simulation model of the geotechnical thermal response experiment is meshed;

Step 4, according to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment constructed in step 3, the simulated temperature of each temperature sensor at different times in the thermal response experiment is obtained, and the objective function is constructed;

Step 5, using the L-M algorithm to optimize the objective function and obtain the optimal solution of the thermal physical property parameters of the rock and soil to be identified;

Step 6: output the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and obtain the thermophysical property parameter values of the rock and soil to be identified.

Preferably, the buried pipe heat exchanger experimental model includes a buried pipe heat exchanger and rock and soil to be identified, and the buried pipe heat exchanger is buried in the rock and soil to be identified; the rock and soil to be identified has a multi-layer structure, and temperature sensors are arranged in each layer of rock and soil, and each temperature sensor is tightly attached to the inner wall of the borehole and is respectively located at different height positions on the inner wall of the borehole; the buried pipe heat exchanger includes a borehole, backfill material and a U-shaped buried pipe, one end of the U-shaped buried pipe is arranged as a liquid inlet pipe, and the other end is arranged as a liquid outlet pipe, and circulating fluid is injected into the interior, and temperature sensors are arranged at the liquid inlet pipe mouth and the liquid outlet pipe mouth of the U-shaped buried pipe.

Preferably, the thermophysical property parameters of the rock and soil to be identified include thermal conductivity and constant-pressure heat capacity of each layer of rock and soil in the rock and soil to be identified.

Preferably, the structural parameters of the buried pipe heat exchanger include the drilling depth of the buried pipe heat exchanger, the drilling diameter, the thermal conductivity of the backfill material, the inner diameter of the U-shaped buried pipe, the outer diameter of the U-shaped buried pipe, the pipe spacing of the U-shaped buried pipe and the thermal conductivity of the U-shaped buried pipe wall.

Preferably, in step 2, the experimental parameters include the flow rate, specific heat, density, heating power and experimental duration of the circulating fluid in the U-shaped buried pipe, and the initial temperature of each layer of rock and soil in the rock and soil to be identified.

Preferably, the objective function F(α) is as shown in formula (1):

Where, T _sim,i,j is the measured temperature of the i-th temperature sensor in the ground pipe heat exchanger experimental model at the j-th moment, T _exp,i,j is the simulated temperature of the i-th temperature sensor in the numerical simulation model of the geotechnical thermal response experiment at the j-th moment, n is the number of selected moments, and N is the number of temperature sensors.

Preferably, the step 5 specifically includes the following steps:

Step 5.1, setting the initial values of the thermophysical property parameters of the rock and soil to be identified, and setting the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the initial values of the thermophysical property parameters of the rock and soil to be identified;

Step 5.2, setting the termination tolerance ξ and correction factor β of the iterative update;

Step 5.3: According to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment to obtain the simulated temperature of each temperature sensor at different times, and the objective function F(α _k ) before this iterative update is calculated. The thermal physical property parameters of the geotechnical to be identified are optimized based on the LM algorithm to obtain the updated thermal physical property parameters of the geotechnical to be identified, as shown in formula (2):

Wherein, α _k+1 is the thermophysical parameter of the rock to be identified after the k-th iterative update, α _k is the thermophysical parameter of the rock to be identified in the numerical simulation model of the rock thermal response experiment, Δα _k is the change of the thermophysical parameter of the rock to be identified before and after the k-th time, F(α _k ) is the objective function obtained by the k-th iterative update, λ is the adjustment factor, I is the unit matrix, and A(α _k ) is the Jacobian matrix;

Step 5.4, according to the updated thermophysical parameter α _k+1 of the rock to be identified, reset the thermophysical parameter of the rock to be identified in the numerical simulation model of the rock thermal response experiment, simulate the thermal response experiment using the numerical simulation model of the rock thermal response experiment according to the experimental parameters of the thermal response experiment in step 2, obtain the simulated temperature of each temperature sensor at different times, and calculate the iteratively updated objective function F(α _k+1 );

Step 5.5, if the objective function F(α _k+1 ) after iterative updating is smaller than the objective function F(α _k ) before iterative updating, then go to step 5.6; otherwise, the adjustment factor is corrected by using the correction coefficient β, and the current adjustment factor value is multiplied by the correction coefficient as the corrected adjustment factor value, and the thermal physical property parameters of the rock to be identified in the numerical simulation model of the rock thermal response experiment are reset according to the thermal physical property parameters of the rock to be identified obtained after this iterative updating, and then return to step 5.3;

Step 5.6, determine the relationship between the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update and the termination allowable value ξ. If the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update is less than the termination allowable value ξ, stop the iterative update, obtain the value of the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment at the end of the iterative update, obtain the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and enter step 5.7; otherwise, use the correction coefficient β to correct the adjustment factor, divide the current adjustment factor value by the correction coefficient as the corrected adjustment factor value, and reset the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the thermophysical property parameters of the rock and soil to be identified obtained after this iterative update, continue the iterative update, and return to step 5.3;

Step 5.7, stop optimizing the thermal physical property parameters of the rock and soil to be identified, and output the optimal solution of the thermal physical property parameters of the rock and soil to be identified.

The present invention has the following beneficial effects:

The present invention combines the rock and soil thermal response experiment with the finite element numerical simulation method, and proposes a rock and soil thermophysical property parameter identification method based on geological stratification, which avoids the influence of factors such as ambient temperature, power change, flow change, etc. on the thermal response experiment during the laboratory thermal response experiment, overcomes the deficiency that the traditional line heat source model cannot accurately obtain the multi-layer rock and soil thermophysical property parameters, more realistically restores the actual working conditions of the buried pipe heat exchanger application, and realizes the accurate acquisition of the multi-layer rock and soil thermophysical property parameters, laying a foundation for guiding the design of the buried pipe heat exchanger.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a horizontal cross-sectional view of the ground pipe heat exchanger experimental model.

FIG2 is a vertical cross-sectional view of the ground pipe heat exchanger experimental model.

Figure 3 is a schematic diagram of the numerical simulation model of geotechnical thermal response experiment after meshing.

Figure 4 is the change curve of the objective function during the iterative update process.

FIG5 is a diagram for verifying the accuracy of the results of identifying the thermal physical property parameters of rock and soil using the method of the present invention.

DETAILED DESCRIPTION

The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments:

The present invention proposes a method for identifying geothermal property parameters based on geological stratification, which specifically includes the following steps:

Step 1: construct a ground pipe heat exchanger experimental model, obtain the structural parameters of the ground pipe heat exchanger in the ground pipe heat exchanger experimental model, and determine the stratification of the rock and soil to be identified in the ground pipe heat exchanger experimental model and the density of each layer of rock and soil.

The experimental model of the buried pipe heat exchanger is shown in Figures 1 and 2, and includes rock and soil to be identified and a buried pipe heat exchanger buried in the rock and soil to be identified. The rock and soil to be identified has a multi-layer structure. In this embodiment, the rock and soil to be identified is set as a three-layer structure, which is set as a clay layer, a gravel layer and a granite layer from top to bottom, wherein the thickness of the clay layer is set to 20m, the thickness of the gravel layer is set to 30m, and the thickness of the granite layer is set to 50m. Temperature sensors are set in each layer of rock and soil, a temperature sensor T1 is set in the clay layer, and the temperature sensor T1 is set at 10m from the surface of the rock and soil to be identified, a temperature sensor T2 is set in the gravel layer, and the temperature sensor T2 is set at 35m from the surface of the rock and soil to be identified, and a temperature sensor T3 is set in the granite layer, and the temperature sensor T3 is set at 75m from the surface of the rock and soil to be identified.

The buried pipe heat exchanger includes a drilled hole, backfill material and a U-shaped buried pipe. One end of the U-shaped buried pipe is set as a liquid inlet pipe, and the other end is set as a liquid outlet pipe. Circulating fluid is injected into the inside. A temperature sensor T_inlet is set at the liquid inlet pipe mouth of the U-shaped buried pipe, and a temperature sensor T_out is set at the liquid outlet pipe mouth of the U-shaped buried pipe.

The structural parameters of the buried pipe heat exchanger include the drilling depth of the buried pipe heat exchanger, the drilling diameter, the thermal conductivity of the backfill material, the inner diameter of the U-shaped buried pipe, the outer diameter of the U-shaped buried pipe, the pipe spacing of the U-shaped buried pipe and the thermal conductivity of the U-shaped buried pipe wall. In this embodiment, the drilling depth of the buried pipe heat exchanger is 100m, the drilling diameter is 0.22m, the inner diameter of the U-shaped buried pipe is 0.026m, the outer diameter of the U-shaped buried pipe is 0.032m, and the pipe spacing of the U-shaped buried pipe is 0.07m.

Step 2: Use the buried pipe heat exchanger experimental model to conduct a thermal response experiment on the rock and soil to be identified. According to the "Technical Specifications for Ground Source Heat Pump System Engineering", the experimental parameters of the thermal response experiment are set, including the flow rate, specific heat, density, heating power and experimental duration of the circulating fluid in the U-shaped buried pipe, and the initial temperature of each layer of rock and soil in the rock and soil to be identified. During the thermal response experiment, the measured temperature of each temperature sensor is obtained in real time, including the pipe mouth temperature of the U-shaped buried pipe liquid inlet pipe, the pipe mouth temperature of the liquid outlet pipe, and the temperature of each layer of rock and soil in the rock and soil to be identified.

During the thermal response experiment of this embodiment, the temperature sensors T1, T2 and T3 are used to obtain the temperature of each layer of rock and soil in the rock and soil to be identified in real time, and the temperature sensors T_inlet and T_out are used to obtain the temperature at the inlet and outlet pipes of the U-shaped buried pipe in real time.

Step 3: Based on the underground heat exchanger experimental model, a numerical simulation model of the geotechnical thermal response experiment is constructed using finite element simulation software, the boundary conditions of the numerical simulation model of the geotechnical thermal response experiment are set, and the numerical simulation model of the geotechnical thermal response experiment is meshed, as shown in FIG3 .

Step 4: According to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment constructed in step 3 to obtain the simulated temperature of each temperature sensor at different times in the thermal response experiment, and construct the objective function F(α), as shown in formula (1):

Where, T _sim,i,j is the measured temperature of the i-th temperature sensor in the ground pipe heat exchanger experimental model at the j-th moment, T _exp,i,j is the simulated temperature of the i-th temperature sensor in the numerical simulation model of the geotechnical thermal response experiment at the j-th moment, n is the number of selected moments, and N is the number of temperature sensors.

Step 5, based on the objective function F(α), the objective function F(α) is optimized using the L-M algorithm to obtain the optimal solution of the thermophysical parameters of the rock to be identified (thermal conductivity and constant pressure heat capacity of each layer of rock in the rock to be identified), which specifically includes the following steps:

Step 5.1, setting the initial values of the thermophysical property parameters of the rock and soil to be identified, and setting the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the initial values of the thermophysical property parameters of the rock and soil to be identified.

Step 5.2, setting the termination tolerance value ξ and correction factor β of the iterative update. In this embodiment, the termination tolerance value ξ=0.01, and the correction factor β=10.

Step 5.3: According to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment to obtain the simulated temperature of each temperature sensor at different times in the thermal response experiment, and the objective function F(α _k ) before this iterative update is calculated. The thermal physical property parameters of the geotechnical to be identified are optimized based on the LM algorithm to obtain the updated thermal physical property parameters of the geotechnical to be identified, as shown in formula (2):

Wherein, α _k+1 is the thermophysical parameter of the rock to be identified after the k-th iterative update, α _k is the thermophysical parameter of the rock to be identified in the numerical simulation model of the rock thermal response experiment, Δα _k is the change of the thermophysical parameter of the rock to be identified before and after the k-th time, F(α _k ) is the objective function obtained by the k-th iterative update, λ is the adjustment factor, I is the unit matrix, and A(α _k ) is the Jacobian matrix.

Step 5.4, according to the updated thermophysical parameters α _k+1 of the rock to be identified, reset the thermophysical parameters of the rock to be identified in the numerical simulation model of the rock thermal response experiment, simulate the thermal response experiment using the numerical simulation model of the rock thermal response experiment according to the experimental parameters of the thermal response experiment in step 2, obtain the simulated temperature of each temperature sensor at different times in the thermal response experiment, and calculate the iteratively updated objective function F(α _k+1 ).

Step 5.5, if the objective function F(α _k+1 ) after iterative updating is smaller than the objective function F(α _k ) before iterative updating, then go to step 5.6; otherwise, the adjustment factor is corrected by using the correction coefficient β, and the current adjustment factor value is multiplied by the correction coefficient as the corrected adjustment factor value. The thermal physical property parameters of the rock and soil to be identified in the numerical simulation model of the geotechnical thermal response experiment are reset according to the thermal physical property parameters of the rock and soil to be identified obtained after this iterative updating, and then return to step 5.3.

Step 5.6, determine the relationship between the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update and the termination allowable value ξ. If the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update is less than the termination allowable value ξ, stop the iterative update, obtain the value of the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment at the end of the iterative update, obtain the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and enter step 5.7; otherwise, use the correction coefficient β to correct the adjustment factor, divide the current adjustment factor value by the correction coefficient and use it as the corrected adjustment factor value, and reset the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the thermophysical property parameters of the rock and soil to be identified obtained after this iterative update, continue the iterative update, and return to step 5.3.

Step 5.7, stop optimizing the thermal physical property parameters of the rock and soil to be identified, and output the optimal solution of the thermal physical property parameters of the rock and soil to be identified.

The change curve of the objective function during the iterative update process of this embodiment is shown in FIG4 .

Step 6: output the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and obtain the thermophysical property parameter values of the rock and soil to be identified.

In order to verify the accuracy of the identification results of geotechnical thermophysical property parameters of the method of the present invention, the numerical simulation model of geotechnical thermal response experiment is reset according to the values of geotechnical thermophysical property parameters determined by the method of the present invention. Under the same thermal response experimental parameter conditions, the numerical simulation model of geotechnical thermal response experiment is used to simulate the simulated temperature value of each temperature sensor. At the same time, the thermal response experiment is measured using the buried pipe heat exchanger experimental model to obtain the measured temperature value of each temperature sensor. By comparing the simulated temperature value of each temperature sensor with the measured temperature value, as shown in Figure 5, it is found that the two are highly consistent, which verifies the accuracy of the identification results of geotechnical thermophysical property parameters of the method of the present invention.

Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the protection scope of the present invention.

Claims (4)

1. A method for identifying geothermal property parameters based on geological stratification, characterized in that it specifically includes the following steps: Step 1: construct a ground pipe heat exchanger experimental model, obtain the structural parameters of the ground pipe heat exchanger in the ground pipe heat exchanger experimental model, and determine the stratification of the rock and soil to be identified in the ground pipe heat exchanger experimental model and the density of each layer of rock and soil; Step 2: Use the underground heat exchanger experimental model to conduct a thermal response experiment on the rock and soil to be identified, set the experimental parameters of the thermal response experiment, and measure the temperature of the U-shaped buried pipe inlet pipe, the temperature of the liquid outlet pipe in the underground heat exchanger experimental model, and the temperature of each layer of rock and soil in the rock and soil to be identified in real time during the thermal response experiment; Step 3: Based on the underground heat exchanger experimental model, a numerical simulation model of the geotechnical thermal response experiment is constructed using finite element simulation software, boundary conditions of the numerical simulation model of the geotechnical thermal response experiment are set, and the numerical simulation model of the geotechnical thermal response experiment is meshed; Step 4, according to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment constructed in step 3, the simulated temperature of each temperature sensor at different times in the thermal response experiment is obtained, and the objective function is constructed; Step 5, using the L-M algorithm to optimize the objective function and obtain the optimal solution of the thermal physical property parameters of the rock and soil to be identified; Step 6, outputting the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and obtaining the thermophysical property parameter values of the rock and soil to be identified; The underground heat exchanger experimental model includes an underground heat exchanger and rock and soil to be identified, and the underground heat exchanger is buried in the rock and soil to be identified; the rock and soil to be identified is a multi-layer structure, and temperature sensors are arranged in each layer of rock and soil, and each temperature sensor is in close contact with the inner wall of the borehole and is respectively located at different height positions of the inner wall of the borehole; the underground heat exchanger includes a borehole, backfill material and a U-shaped buried pipe, one end of the U-shaped buried pipe is arranged as a liquid inlet pipe, and the other end is arranged as a liquid outlet pipe, and a circulating fluid is injected into the inside, and temperature sensors are arranged at the liquid inlet pipe mouth and the liquid outlet pipe mouth of the U-shaped buried pipe; The objective function F(α) is shown in formula (1): Where, T _sim,i,j is the measured temperature of the i-th temperature sensor in the ground pipe heat exchanger experimental model at the j-th moment, T _exp,i,j is the simulated temperature of the i-th temperature sensor in the geotechnical thermal response experimental numerical simulation model at the j-th moment, n is the number of selected moments, and N is the number of temperature sensors; The step 5 specifically includes the following steps: Step 5.1, setting the initial values of the thermophysical property parameters of the rock and soil to be identified, and setting the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the initial values of the thermophysical property parameters of the rock and soil to be identified; Step 5.2, setting the termination tolerance ξ and correction coefficient β of the iterative update; Step 5.3: According to the experimental parameters of the thermal response experiment in step 2, the thermal response experiment is simulated using the numerical simulation model of the geotechnical thermal response experiment to obtain the simulated temperature of each temperature sensor at different times, and the objective function F(α _k ) before this iterative update is calculated. The thermal physical property parameters of the geotechnical to be identified are optimized based on the LM algorithm to obtain the updated thermal physical property parameters of the geotechnical to be identified, as shown in formula (2): Wherein, α _k+1 is the thermophysical parameter of the rock to be identified after the k-th iterative update, α _k is the thermophysical parameter of the rock to be identified in the numerical simulation model of the rock thermal response experiment, Δα _k is the change of the thermophysical parameter of the rock to be identified before and after the k-th time, F(α _k ) is the objective function obtained by the k-th iterative update, λ is the adjustment factor, I is the unit matrix, and A(α _k ) is the Jacobian matrix; Step 5.4, according to the updated thermophysical parameter α _k+1 of the rock to be identified, reset the thermophysical parameter of the rock to be identified in the numerical simulation model of the rock thermal response experiment, simulate the thermal response experiment using the numerical simulation model of the rock thermal response experiment according to the experimental parameters of the thermal response experiment in step 2, obtain the simulated temperature of each temperature sensor at different times, and calculate the iteratively updated objective function F(α _k+1 ); Step 5.5, if the objective function F(α _k+1 ) after iterative updating is smaller than the objective function F(α _k ) before iterative updating, then go to step 5.6; otherwise, the adjustment factor is corrected by using the correction coefficient β, and the current adjustment factor value is multiplied by the correction coefficient as the corrected adjustment factor value, and the thermal physical property parameters of the rock to be identified in the numerical simulation model of the rock thermal response experiment are reset according to the thermal physical property parameters of the rock to be identified obtained after this iterative updating, and then return to step 5.3; Step 5.6, determine the relationship between the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update and the termination allowable value ξ. If the change Δα _k of the thermophysical property parameters of the rock and soil to be identified before and after this iterative update is less than the termination allowable value ξ, stop the iterative update, obtain the value of the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment at the end of the iterative update, obtain the optimal solution of the thermophysical property parameters of the rock and soil to be identified, and enter step 5.7; otherwise, use the correction coefficient β to correct the adjustment factor, divide the current adjustment factor value by the correction coefficient as the corrected adjustment factor value, and reset the thermophysical property parameters of the rock and soil to be identified in the numerical simulation model of the rock and soil thermal response experiment according to the thermophysical property parameters of the rock and soil to be identified obtained after this iterative update, continue the iterative update, and return to step 5.3; Step 5.7, stop optimizing the thermal physical property parameters of the rock and soil to be identified, and output the optimal solution of the thermal physical property parameters of the rock and soil to be identified. 2. A method for identifying thermal physical property parameters of rock and soil based on geological stratification as described in claim 1, characterized in that the thermal physical property parameters of the rock and soil to be identified include the thermal conductivity and constant-pressure heat capacity of each layer of rock and soil in the rock and soil to be identified. 3. A method for identifying geothermal property parameters based on geological stratification as described in claim 1, characterized in that the structural parameters of the buried pipe heat exchanger include the drilling depth of the buried pipe heat exchanger, the drilling diameter, the thermal conductivity of the backfill material, the inner diameter of the U-shaped buried pipe, the outer diameter of the U-shaped buried pipe, the pipe spacing of the U-shaped buried pipe and the thermal conductivity of the U-shaped buried pipe wall. 4. A method for identifying thermal physical property parameters of rock and soil based on geological stratification as described in claim 1, characterized in that in step 2, the experimental parameters include the flow rate, specific heat, density, heating power and experimental duration of the circulating fluid in the U-shaped buried pipe, and the initial temperature of each layer of rock and soil in the rock and soil to be identified.