Geothermal wellhead temperature prediction method, device, equipment, storage medium and product

Abstract

The invention discloses a geothermal well mouth temperature prediction method and device, equipment, a storage medium and a product, and relates to the technical field of geothermal resource utilization, and the method comprises the steps: building a heat flow coupling model of a geothermal well; converting the ground pressure into bottom hole pressure according to the heat flow coupling model, and inverting a formation flow coefficient based on the bottom hole pressure; fitting the actually measured temperature through a heat flow coupling model, and inverting an average thermal diffusion coefficient from a production layer to a geothermal storage layer according to a fitting result; and predicting the distribution condition of the geothermal wellhead temperature through the formation flow coefficient and the average thermal diffusion coefficient. According to the method, the formation flow coefficient and the average thermal diffusion coefficient are inverted through the heat flow coupling model, and the distribution condition of the geothermal wellhead temperature is predicted through the formation flow coefficient and the average thermal diffusion coefficient obtained through inversion, so that accurate prediction of the temperature distribution condition of the geothermal wellhead is realized; and scientific guidance can be provided for efficient development of terrestrial heat.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geothermal resource utilization, and particularly relates to a geothermal wellhead temperature prediction method, device, equipment, storage medium and product. BACKGROUND

[0002] With the continuous improvement of people's living standards, higher requirements are put forward for living and living environment. As a clean renewable energy, geothermal energy is increasingly concerned and developed. At present, the test analysis means in the oil field can be used to analyze geothermal data for geothermal development. The method adopted is to analyze the changes of flow and pressure by establishing Agarwal-Gardner chart.

[0003] However, since the essence of geothermal energy is mass transfer and heat transfer of fluid in the formation and wellbore, the above method does not consider temperature change, and therefore is not suitable for geothermal data analysis, and cannot accurately predict the temperature distribution of geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal energy.

[0004] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0005] The main purpose of the present application is to provide a geothermal wellhead temperature prediction method, device, equipment, storage medium and product, which aims to solve the technical problem that the prior art does not consider temperature change, cannot accurately predict the temperature distribution of geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal energy.

[0006] To achieve the above purpose, the present application provides a geothermal wellhead temperature prediction method, which comprises:

[0007] establishing a heat flow coupling model of a geothermal well;

[0008] converting surface pressure into bottom hole pressure according to the heat flow coupling model, and inverting formation flow coefficient based on the bottom hole pressure;

[0009] fitting the measured temperature by the heat flow coupling model, and inverting the average thermal diffusion coefficient from the production layer to the geothermal storage layer according to the fitting result;

[0010] predicting the distribution of geothermal wellhead temperature by the formation flow coefficient and the average thermal diffusion coefficient.

[0011] In an embodiment, the step of establishing a heat flow coupling model of a geothermal well comprises:

[0012] determining fluid dynamics equation according to fluid density, fluid velocity and fluid pressure;

[0013] determining a heat conduction equation according to the wellbore temperature and the comprehensive thermal conductivity coefficient;

[0014] determining a heat flow coupling model based on the fluid dynamics equation and the heat conduction equation.

[0015] In an embodiment, the step of converting the surface pressure to the bottom hole pressure according to the heat flow coupling model and inverting the formation flow coefficient based on the bottom hole pressure, comprises:

[0016] determining a pressure correspondence between the bottom hole and the wellhead according to the fluid dynamics equation in the heat flow coupling model;

[0017] converting the surface pressure to the bottom hole pressure according to the pressure correspondence;

[0018] determining a bottom hole pressure curve of the bottom hole pressure changing with time;

[0019] inverting the formation flow coefficient through the bottom hole pressure curve.

[0020] In an embodiment, the step of inverting the formation flow coefficient through the bottom hole pressure curve, comprises:

[0021] determining a bottom hole pressure equation according to the bottom hole pressure curve;

[0022] extracting a target factor related to a time parameter in the bottom hole pressure equation;

[0023] plotting a relation graph between the bottom hole pressure and the target factor;

[0024] inverting the formation flow coefficient through the slope of a straight line segment in the relation graph.

[0025] In an embodiment, the step of fitting the measured temperature through the heat flow coupling model and inverting the average thermal diffusion coefficient from the production layer to the geothermal reservoir layer according to the fitting result, comprises:

[0026] determining a temperature correspondence between the bottom hole and the wellhead according to the heat conduction equation in the heat flow coupling model;

[0027] fitting the measured temperature through the temperature correspondence;

[0028] adjusting the heat conduction equation according to the fitting result and inverting the average thermal diffusion coefficient from the production layer to the geothermal reservoir layer according to the adjusted heat conduction equation.

[0029] In an embodiment, the step of adjusting the heat conduction equation according to the fitting result and inverting the average thermal diffusion coefficient from the production layer to the geothermal reservoir layer according to the adjusted heat conduction equation, comprises:

[0030] determining whether a temperature error between the calculated temperature and the measured temperature is greater than a preset threshold value;

[0031] if not, adjusting the heat conduction equation and returning to the step of determining the temperature correspondence between the well bottom and the well head according to the heat conduction equation in the heat flow coupling model until the temperature error is less than the preset threshold value;

[0032] when the temperature error is less than the preset threshold value, inversely calculating the average thermal diffusion coefficient from the production layer to the geothermal reservoir according to the parameters in the adjusted heat conduction equation.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a geothermal well head temperature prediction device, which comprises:

[0034] a model establishing module for establishing a heat flow coupling model of a geothermal well;

[0035] a formation flow coefficient inversion module for converting a surface pressure into a well bottom pressure according to the heat flow coupling model and inversely calculating a formation flow coefficient based on the well bottom pressure;

[0036] an average thermal diffusion coefficient inversion module for fitting a measured temperature through the heat flow coupling model and inversely calculating an average thermal diffusion coefficient from a production layer to a geothermal reservoir layer according to a fitting result;

[0037] a well head temperature prediction module for predicting a distribution of a geothermal well head temperature through the formation flow coefficient and the average thermal diffusion coefficient.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a geothermal well head temperature prediction device, which comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the geothermal well head temperature prediction method as described above.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer readable storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the steps of the geothermal well head temperature prediction method as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the geothermal well head temperature prediction method as described above.

[0041] The application provides a geothermal wellhead temperature prediction method, device, equipment, storage medium and product. The geothermal wellhead temperature prediction method comprises the following steps: establishing a heat flow coupling model of a geothermal well; converting a ground pressure into a bottom hole pressure according to the heat flow coupling model, and inversing a formation flow coefficient based on the bottom hole pressure; fitting a measured temperature by using the heat flow coupling model, and inversing an average thermal diffusion coefficient from a production layer to a geothermal storage layer according to a fitting result; and predicting a distribution of the geothermal wellhead temperature by using the formation flow coefficient and the average thermal diffusion coefficient. The application inverses the formation flow coefficient and the average thermal diffusion coefficient by using the heat flow coupling model, and predicts the distribution of the geothermal wellhead temperature based on the inversing formation flow coefficient and the average thermal diffusion coefficient, so that the application considers temperature change in geothermal analysis, realizes accurate prediction of the temperature distribution of the geothermal wellhead, can be applied to geothermal data analysis, and can further provide scientific guidance for efficient development of geothermal energy. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 A flowchart is provided for the geothermal wellhead temperature prediction method embodiment one of the application.

[0043] Figure 2 A flowchart is provided for the geothermal wellhead temperature prediction method embodiment two of the application.

[0044] Figure 3 A flowchart is provided for the geothermal wellhead temperature prediction method embodiment three of the application.

[0045] Figure 4 A module structure diagram of the geothermal wellhead temperature prediction device of the embodiment of the application is provided.

[0046] Figure 5 A device structure diagram of a hardware running environment related to the geothermal wellhead temperature prediction method in the embodiment of the application is provided.

[0047] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the application, and are not used to limit the application.

[0049] In order to better understand the technical solutions of the application, the following will be described in detail in combination with the accompanying drawings and specific embodiments.

[0050] The main solution of the embodiment of the application is: a heat flow coupling model of a geothermal well is established; ground pressure is converted into bottom hole pressure according to the heat flow coupling model, and a formation flow coefficient is inverted based on the bottom hole pressure; measured temperature is fitted through the heat flow coupling model, and an average thermal diffusion coefficient from a production layer to a geothermal storage layer is inverted according to a fitting result; and a distribution of geothermal wellhead temperature is predicted through the formation flow coefficient and the average thermal diffusion coefficient.

[0051] In the embodiment, for convenience of description, a geothermal wellhead temperature prediction device is taken as an execution subject for description.

[0052] It should be noted that the execution subject of the embodiment can be a computing service device with functions of geothermal wellhead temperature prediction, network communication and program running, such as a tablet computer, a personal computer, a mobile phone and the like, or an electronic device capable of realizing the above functions, geothermal wellhead temperature prediction and the like. The embodiment and each of the following embodiments are described below by taking a geothermal wellhead temperature prediction device (referred to as a prediction device) as an example.

[0053] Since the prior art analyzes the changes of flow rate and pressure by establishing an Agarwal-Gardner chart, and does not consider temperature changes, for geothermal energy, ground pressure, temperature and flow rate data changing with time are generally measured, and therefore the existing method is not applicable to geothermal data analysis, and cannot accurately predict the temperature distribution of the geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal energy.

[0054] The application provides a solution, which inverts a formation flow coefficient and an average thermal diffusion coefficient through a heat flow coupling model, and predicts the distribution of geothermal wellhead temperature based on the inverted formation flow coefficient and average thermal diffusion coefficient, so that the application considers temperature changes in geothermal analysis, can accurately predict the temperature distribution of the geothermal wellhead, is applicable to geothermal data analysis, and can provide scientific guidance for efficient development of geothermal energy.

[0055] Based on this, the embodiment of the application provides a geothermal wellhead temperature prediction method, which refers to Figure 1 , Figure 1 The flowchart provided for the first embodiment of the geothermal wellhead temperature prediction method of the application is shown.

[0056] In the embodiment, the geothermal wellhead temperature prediction method includes steps S10-S40:

[0057] Step S10, a heat flow coupling model of a geothermal well is established.

[0058] In a specific implementation, the prediction device can establish fluid dynamics equations and heat conduction equations of the geothermal well formation and wellbore, and establish a heat flow coupling model of the geothermal well based on the fluid dynamics equations and the heat conduction equations.

[0059] In one possible implementation, the step S10 can include steps S101-S103.

[0060] In step S101, fluid dynamics equations are determined according to fluid density, fluid velocity, and fluid pressure.

[0061] In a specific implementation, the fluid dynamics equations include mass conservation equations, momentum conservation equations, and energy conservation equations.

[0062] The mass conservation equation is:

[0063]

[0064] wherein ρ is fluid density, v is fluid velocity, t is time, and z is vertical direction.

[0065] The momentum conservation equation is:

[0066]

[0067] wherein ρ is fluid density, v is fluid velocity, t is time, z is vertical direction, p is fluid pressure, g is gravitational acceleration, f is pipe friction coefficient, and D is wellbore diameter.

[0068] The energy conservation equation is:

[0069]

[0070] wherein ρ is fluid density, v is fluid velocity, t is time, z is vertical direction, g is gravitational acceleration, f is pipe friction coefficient, D is wellbore diameter, c p,1 is fluid specific heat capacity at constant pressure, T is temperature, δq is energy transferred between the wellbore and the formation, and A is wellbore cross-sectional area.

[0071] In step S102, heat conduction equations are determined according to wellbore temperature and comprehensive thermal conductivity.

[0072] In a specific implementation, in the wellbore temperature and pressure calculation, the region in heat exchange with the wellbore is the upper part of the producing formation, and this part of the reservoir has no fluid flow, so only heat conduction can be considered, and the heat conduction equation can be:

[0073]

[0074] wherein T is temperature, ρ is fluid density, c eff is reservoir comprehensive specific heat capacity, and λeff where t is time.

[0075] In step S103, a thermal flow coupling model is determined based on the fluid dynamics equation and the heat conduction equation.

[0076] In a specific implementation, the prediction device above combines the fluid dynamics equation and the heat conduction equation, and takes the equation set composed of the mass conservation equation, the momentum conservation equation, the energy conservation equation and the heat conduction equation as the thermal flow coupling model.

[0077] In step S20, the surface pressure is converted into the bottom hole pressure according to the thermal flow coupling model, and the formation flow coefficient is inverted based on the bottom hole pressure.

[0078] It should be noted that the formation flow coefficient can be a coefficient affecting the flow speed and range of the underground fluid in the rock pore.

[0079] In a specific implementation, the mass conservation equation, the momentum conservation equation and the energy conservation equation in the thermal flow coupling model above contain the distribution of the pressure in the vertical direction, so the prediction device above can determine the pressure correspondence between the bottom hole and the wellhead by solving the mass conservation equation, the momentum conservation equation and the energy conservation equation, convert the surface pressure to the bottom hole through the pressure correspondence, determine the bottom hole pressure, and then invert the formation flow coefficient according to the characteristics of the geothermal well flow variation and the bottom hole pressure.

[0080] In step S30, the measured temperature is fitted through the thermal flow coupling model, and the average thermal diffusion coefficient from the production layer to the geothermal storage layer is inverted according to the fitting result.

[0081] It should be noted that the average thermal diffusion coefficient can be a coefficient representing the diffusion speed and capacity of the heat in the formation.

[0082] In a specific implementation, the prediction device above can determine the temperature correspondence between the bottom hole and the wellhead through the heat conduction equation in the thermal flow coupling model, collect the measured temperature of the geothermal well, fit the measured temperature through the temperature correspondence, adjust the heat conduction equation through the fitting result, and when the fitting is completed, invert the average thermal diffusion coefficient from the production layer to the geothermal storage layer through the finally adjusted heat conduction equation.

[0083] In step S40, the distribution of the geothermal wellhead temperature is predicted through the formation flow coefficient and the average thermal diffusion coefficient.

[0084] In practical implementation, the formation flow coefficient can be used to predict the movement of underground fluids within the formation, thereby assessing the heat transfer efficiency during the flow process. A larger flow coefficient indicates faster fluid flow underground, potentially promoting rapid heat transfer, while a smaller flow coefficient can lead to heat accumulation in localized areas, affecting the wellhead temperature distribution. The average thermal diffusivity coefficient can be used to predict the range and speed of heat diffusion within the formation. A larger average thermal diffusivity coefficient indicates faster heat diffusion within the formation, potentially leading to a rapid increase in wellhead temperature, while a smaller average thermal diffusivity coefficient may result in a slower change in wellhead temperature. Therefore, the aforementioned prediction equipment can accurately predict the distribution of geothermal wellhead temperature using the formation flow coefficient and the average thermal diffusivity coefficient.

[0085] The geothermal wellhead temperature prediction method in this embodiment establishes a thermal-fluid coupling model for the geothermal well; converts surface pressure into bottom-hole pressure based on the thermal-fluid coupling model, and inverts the formation flow coefficient based on the bottom-hole pressure; fits the measured temperature to the thermal-fluid coupling model, and inverts the average thermal diffusivity from the producing layer to the geothermal reservoir based on the fitting results; and predicts the distribution of geothermal wellhead temperature using the formation flow coefficient and the average thermal diffusivity. Because this embodiment inverts the formation flow coefficient and the average thermal diffusivity using the thermal-fluid coupling model, and predicts the distribution of geothermal wellhead temperature based on the inverted formation flow coefficient and the average thermal diffusivity, this embodiment considers temperature changes in geothermal analysis, achieving accurate prediction of the temperature distribution at the geothermal wellhead. This method is applicable to geothermal data analysis and can provide scientific guidance for efficient geothermal development.

[0086] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating Embodiment 2 of the geothermal wellhead temperature prediction method of this application.

[0087] In this embodiment, step S20 includes steps S201 to S204:

[0088] Step S201: Determine the pressure correspondence between the bottom of the well and the wellhead based on the fluid dynamics equations in the heat-fluid coupling model.

[0089] In practical implementation, the aforementioned prediction device can solve the fluid dynamics equations, that is, request a set of equations consisting of the mass conservation equation, the momentum conservation equation, and the energy conservation equation, to determine the pressure correspondence between the bottom of the well and the wellhead.

[0090] For example, the solution of the fluid dynamics equations using the finite difference method is taken as an example. The momentum conservation equation is rewritten as:

[0091] Δp + p v Δv + W + F = 0

[0092]

[0093]

[0094] where p is fluid density, v is fluid velocity, t is time, z is vertical direction, p is fluid pressure, g is gravitational acceleration, f is pipe friction coefficient, D is wellbore diameter, W is pressure drop caused by gravity, F is pressure drop caused by friction, and G is gravity.

[0095] A second-order central difference is used to obtain a difference format of the energy conservation equation from the above energy conservation equation, as follows:

[0096]

[0097] wherein, is temperature, A j,i , C j,i , D j,i , F j,i , E j,i , G j,i , U j,i are all calculation coefficients, n is time step number, i = 1, 2, …, n, j = 1, 2, …, n, A is wellbore cross-sectional area, Δt is time step length, λ j-1 is thermal conductivity of the previous time step, λ j is thermal conductivity of the current time step, c eff is comprehensive specific heat capacity of the reservoir, and z is vertical direction.

[0098] It should be noted that solving the difference format of the energy conservation equation can determine the pressure correspondence between the well bottom and the wellhead.

[0099] Step S202, converting the surface pressure to the well bottom pressure according to the pressure correspondence.

[0100] Step S203, determining a well bottom pressure curve of the well bottom pressure changing with time.

[0101] In a specific implementation, the prediction device can convert the surface pressure to the well bottom according to the pressure correspondence, determine the well bottom pressure, and obtain a group of well bottom pressure curves of the well bottom pressure changing with time.

[0102] Step S204, inverting the formation flow coefficient through the well bottom pressure curve.

[0103] In practice, the aforementioned prediction equipment can inversely derive the formation flow coefficient by integrating a piecewise linear function onto the bottom hole pressure curve.

[0104] In one feasible implementation, step S204 may include steps S2041 to S2044:

[0105] Step S2041: Determine the bottom hole pressure equation based on the bottom hole pressure curve.

[0106] In practical implementation, for a variable-yield production well in a formation with an infinite mean, its bottomhole pressure equation can be expressed as:

[0107]

[0108] In the formula, p wf p is the bottom hole pressure. i denoted as ρ, where B is the original formation pressure, B is the formation volume coefficient, and μ is the fluid viscosity.

[0109] Step S2042: Extract the target factors related to the time parameter in the bottom hole pressure equation.

[0110] It should be noted that because geothermal wells record production daily, there is a large amount of flow data, and the current flow correction time requires the use of all previous flow data. If there are errors in the previous flow data, they will be propagated, leading to a continuous increase in accumulated error. Although the flow rate changes daily, it can be approximated as linear over a longer period.

[0111] For example, as time t→∞, Bottom hole pressure p wf (t) can be approximated as:

[0112]

[0113] In the formula, p wf p is the bottom hole pressure. i denoted as ρ, where B is the original formation pressure, B is the formation volume coefficient, and μ is the fluid viscosity.

[0114] Using the superposition principle, t can be obtained. N-1 ~t N The bottom pressure during the time period was:

[0115]

[0116] In the formula, p wf p is the bottom hole pressure. i denoted as ρ, where B is the original formation pressure, B is the formation volume coefficient, and μ is the fluid viscosity.

[0117] When the time is long, a parameter related to the time parameter can be extracted as a target factor, that is, the target factor is:

[0118]

[0119] In step S2043, a relationship graph between the bottom hole pressure and the target factor is drawn.

[0120] In a specific implementation, based on the above example, the target factor is substituted into t N-1 ~t N in the bottom hole pressure equation in the time period, and a relationship graph between the bottom hole pressure and the target factor is drawn.

[0121] In step S2044, the formation flow coefficient is inverted through the slope of a straight line segment in the relationship graph.

[0122] In a specific implementation, there is a straight line segment in the relationship graph, and the formation flow coefficient can be inverted through the slope of the straight line segment, and the intercept of the straight line segment can invert the original formation pressure.

[0123] The calculation formula of the formation flow coefficient is:

[0124]

[0125] In the formula, kh / μ is the formation flow coefficient, B is the formation volume factor, m is the slope, and q N is the flow rate.

[0126] The calculation formula of the original formation pressure is:

[0127]

[0128] In the formula, p i is the original formation pressure, b is the intercept, m is the slope, q N is the flow rate, and q0 is the initial flow rate.

[0129] In this embodiment, the pressure correspondence between the well bottom and the well head is determined according to the fluid dynamics equation in the heat flow coupling model; the surface pressure is converted into the bottom hole pressure according to the pressure correspondence; the bottom hole pressure curve of the bottom hole pressure changing with time is determined; the bottom hole pressure equation is determined according to the bottom hole pressure curve; the target factor related to the time parameter in the bottom hole pressure equation is extracted; the relationship graph between the bottom hole pressure and the target factor is drawn; and the formation flow coefficient is inverted through the slope of a straight line segment in the relationship graph. Since this embodiment draws the relationship graph between the bottom hole pressure and the target factor, and inverts the formation flow coefficient through the slope of a straight line segment in the relationship graph, the inversion accuracy of the formation flow coefficient can be effectively improved.

[0130] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as the above-mentioned embodiments one or two can be referred to the above description, and the subsequent will not be described in detail. On this basis, please refer to Figure 3 , Figure 3 The flowchart diagram provided for the third embodiment of the geothermal wellhead temperature prediction method of the present application.

[0131] In the present embodiment, the step S30 includes steps S301-S203:

[0132] Step S301, determining the temperature corresponding relationship between the well bottom and the wellhead according to the heat conduction equation in the heat flow coupling model.

[0133] In a specific implementation, the heat conduction equation is differentiated to obtain the difference format of the formation temperature equation, as follows:

[0134]

[0135] In the formula, is the temperature, A j,i , C j,i , D j,i , F j,i , E j,i , G j,i , U j,i are all calculation coefficients, n is the time step, i=1, 2, …, n, j=1, 2, …, n.

[0136] It should be noted that the difference format of the heat conduction equation is solved to determine the temperature corresponding relationship between the well bottom and the wellhead.

[0137] Step S302, fitting the measured temperature through the temperature corresponding relationship.

[0138] In a specific implementation, the prediction device can fit the measured temperature based on the temperature corresponding relationship, wherein the temperature at the wellhead, the initial temperature at the well bottom, the thermal diffusion coefficient of the geothermal reservoir and other parameters are combined with the temperature corresponding relationship to calculate the calculated temperature of the well bottom or wellhead at different time points. The calculated temperature can be a temperature prediction value, and each calculated temperature and the measured temperature are fitted.

[0139] Step S303, adjusting the heat conduction equation according to the fitting result, and inverting the average thermal diffusion coefficient from the production layer to the geothermal storage layer according to the adjusted heat conduction equation.

[0140] In a specific implementation, the prediction device can adjust the heat conduction equation according to the difference between the calculated temperature and the measured temperature in the fitting result, and then invert the average thermal diffusion coefficient from the production layer to the geothermal storage layer according to the parameters in the adjusted heat conduction equation.

[0141] In an implementation, step S303 can include steps S3031-S3033.

[0142] In step S3031, it is determined whether the temperature error between the calculated temperature and the measured temperature is greater than a preset threshold.

[0143] It should be noted that the preset threshold can be a threshold for determining whether the temperature error between the calculated temperature and the measured temperature meets the accuracy requirement. When the temperature error is greater than the preset threshold, it is determined that the temperature error does not meet the accuracy requirement, and conversely, when the temperature error is less than the preset threshold, it is determined that the temperature error meets the accuracy requirement.

[0144] In step S3032, if not, the heat conduction equation is adjusted, and the step of determining the temperature correspondence between the well bottom and the wellhead according to the heat conduction equation in the heat flow coupling model is returned until the temperature error is less than the preset threshold.

[0145] In a specific implementation, when the temperature error between the calculated temperature and the measured temperature is less than the preset threshold, the prediction device determines that the temperature error does not meet the accuracy requirement, and can adjust each parameter in the heat conduction equation, and then returns to the step of determining the temperature correspondence between the well bottom and the wellhead according to the heat conduction equation in the heat flow coupling model, and repeats the above fitting process until the temperature error is less than the preset threshold.

[0146] In step S3033, when the temperature error is less than the preset threshold, the average thermal diffusion coefficient from the production layer to the geothermal reservoir is inversed according to the parameters in the adjusted heat conduction equation.

[0147] In a specific implementation, when the temperature error in the fitting process is less than the preset threshold, the prediction device determines that the temperature error meets the accuracy requirement, determines that the fitting is completed, determines the adjusted heat conduction equation at the time of completion of the fitting, extracts the comprehensive thermal conductivity, the reservoir comprehensive specific heat capacity and the fluid density in the adjusted heat conduction equation, and calculates the average thermal diffusion coefficient according to the comprehensive thermal conductivity, the reservoir comprehensive specific heat capacity and the fluid density. The calculation formula of the average thermal diffusion coefficient is:

[0148]

[0149] In the formula, D eff is the average thermal diffusion coefficient, λ eff is the comprehensive thermal conductivity, c p is the reservoir comprehensive specific heat capacity, and p is the fluid density.

[0150] The embodiment determines the temperature correspondence between the well bottom and the wellhead according to the heat conduction equation in the heat flow coupling model; fits the measured temperature according to the temperature correspondence; adjusts the heat conduction equation according to the fitting result, and inversely calculates the average thermal diffusion coefficient from the production layer to the geothermal reservoir layer according to the adjusted heat conduction equation. The embodiment fits the measured temperature according to the temperature correspondence, adjusts the heat conduction equation according to the fitting result, and inversely calculates the average thermal diffusion coefficient according to the adjusted heat conduction equation, so that the precision of the average thermal diffusion coefficient can be effectively improved.

[0151] It should be noted that the above examples are only used for understanding the present application and do not constitute a limitation on the geothermal wellhead temperature prediction method of the present application. More forms of simple transformation based on this technical concept are within the protection scope of the present application.

[0152] The present application also provides a geothermal wellhead temperature prediction device, which is described below. Figure 4 Figure 4 The present application also provides a geothermal wellhead temperature prediction device, which is described below.

[0153] The model establishing module 10 is configured to establish a heat flow coupling model of the geothermal well.

[0154] The formation flow coefficient inversion module 20 is configured to convert the surface pressure into the well bottom pressure according to the heat flow coupling model, and inversely calculate the formation flow coefficient based on the well bottom pressure.

[0155] The average thermal diffusion coefficient inversion module 30 is configured to fit the measured temperature according to the heat flow coupling model, and inversely calculate the average thermal diffusion coefficient from the production layer to the geothermal reservoir layer according to the fitting result.

[0156] The wellhead temperature prediction module 40 is configured to predict the distribution of the geothermal wellhead temperature according to the formation flow coefficient and the average thermal diffusion coefficient.

[0157] The geothermal wellhead temperature prediction device provided by the present application adopts the geothermal wellhead temperature prediction method in the above embodiment, and can solve the technical problem that the prior art does not consider temperature change, cannot accurately predict the temperature distribution of the geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal resources. Compared with the prior art, the geothermal wellhead temperature prediction device provided by the present application has the same beneficial effects as the geothermal wellhead temperature prediction method provided by the above embodiment, and other technical features in the geothermal wellhead temperature prediction device are the same as the features disclosed in the above embodiment, which will not be described here.

[0158] ​The application provides a geothermal wellhead temperature prediction device, which comprises at least one processor and a memory connected with the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the geothermal wellhead temperature prediction method in the first embodiment.

[0159] Reference will be made to the drawings Figure 5 , Figure 5 The device structure diagram of a hardware running environment involved in the geothermal wellhead temperature prediction method in the embodiments of the application is shown. The diagram shows a structure diagram of a geothermal wellhead temperature prediction device suitable for implementing the embodiments of the application. The geothermal wellhead temperature prediction device in the embodiments of the application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), vehicle-mounted terminals (for example, vehicle-mounted navigation terminals) and the like, and fixed terminals such as digital TVs, desktop computers and the like. Figure 5 The shown geothermal wellhead temperature prediction device is only an example, and should not bring any limitation to the functions and use range of the embodiments of the application.

[0160] As Figure 5As shown, the geothermal wellhead temperature prediction device can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a read only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for operation of the geothermal wellhead temperature prediction device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the geothermal wellhead temperature prediction device to communicate with other devices wirelessly or by wire to exchange data. Although the geothermal wellhead temperature prediction device with various systems is shown in the figure, it should be understood that all the shown systems are not required to be implemented or possessed. More or less systems can be alternatively implemented or possessed.

[0161] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0162] The geothermal wellhead temperature prediction device provided by the present disclosure adopts the geothermal wellhead temperature prediction method in the above-mentioned embodiments, and can solve the technical problem that the prior art does not consider temperature changes, cannot accurately predict the temperature distribution of the geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal. Compared with the prior art, the geothermal wellhead temperature prediction device provided by the present disclosure has the same beneficial effects as the geothermal wellhead temperature prediction method provided by the above-mentioned embodiments, and other technical features in the geothermal wellhead temperature prediction device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0163] It should be understood that various parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the above-described embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0164] The above description is merely that of a specific implementation of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, and all such changes or replacements should be encompassed within the scope of protection of the present application. Therefore, the scope of protection of the present application should be subject to the scope of protection of the claims.

[0165] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e., computer programs) for performing the geothermal wellhead temperature prediction method in the above-described embodiments.

[0166] The computer readable storage medium provided by the present application may, for example, be a U disk, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system or device, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more conductive wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer readable storage medium can be transmitted in any suitable medium, including but not limited to electrical wire, optical cable, RF (Radio Frequency), etc., or any suitable combination of the above.

[0167] The above-described computer readable storage medium can be included in the geothermal wellhead temperature prediction device; or can exist separately without being assembled into the geothermal wellhead temperature prediction device.

[0168] The computer readable storage medium described above carries one or more programs, when the one or more programs are executed by the geothermal wellhead temperature prediction device, cause the geothermal wellhead temperature prediction device to: establish a heat flow coupling model of a geothermal well; convert a surface pressure into a bottom hole pressure according to the heat flow coupling model, and invert a formation flow coefficient based on the bottom hole pressure; fit a measured temperature through the heat flow coupling model, and invert an average thermal diffusion coefficient from a production layer to a geothermal reservoir layer according to a fitting result; and predict a distribution of the geothermal wellhead temperature through the formation flow coefficient and the average thermal diffusion coefficient.

[0169] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0170] The flow diagrams and the block diagrams in the drawings are illustrations of possible architectures, functions, and operations for systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.

[0171] The modules described in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0172] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the geothermal wellhead temperature prediction method described above, and can solve the technical problem that the prior art does not consider temperature changes, cannot accurately predict the temperature distribution of the geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal resources. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the geothermal wellhead temperature prediction method provided by the above embodiments, and will not be described here.

[0173] The present application also provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the geothermal wellhead temperature prediction method described above.

[0174] The computer program product provided by the present application can solve the technical problem that the prior art does not consider temperature changes, cannot accurately predict the temperature distribution of the geothermal wellhead, and thus cannot provide scientific guidance for efficient development of geothermal resources. Compared with the prior art, the computer program product provided by the present application has the same beneficial effects as the geothermal wellhead temperature prediction method provided by the above embodiments, and will not be described here.

[0175] The above only describes some embodiments of the present application, and does not limit the patent scope of the present application, and any equivalent structural transformation made by using the content of the present application specification and drawings, or direct / indirect application in other related technical fields is included in the patent protection scope of the present application.

Claims

1. A method for predicting geothermal wellhead temperature, characterized in that, The method includes: Establish a heat flow coupling model for geothermal wells; The surface pressure is converted into bottom hole pressure according to the heat-flow coupling model, and the formation flow coefficient is inverted based on the bottom hole pressure; The measured temperature is fitted using the heat flow coupling model, and the average thermal diffusivity from the producing layer to the geothermal storage layer is retrieved based on the fitting results. The distribution of geothermal wellhead temperature is predicted using the formation flow coefficient and the average thermal diffusivity.

2. The geothermal wellhead temperature prediction method as described in claim 1, characterized in that, The steps for establishing a heat flow coupling model for geothermal wells include: The fluid dynamics equations are determined based on fluid density, fluid velocity, and fluid pressure. The heat conduction equation is determined based on the wellbore temperature and the overall thermal conductivity. The heat-fluid coupling model is determined based on the fluid dynamics equation and the heat conduction equation.

3. The geothermal wellhead temperature prediction method as described in claim 2, characterized in that, The step of converting surface pressure into bottom hole pressure according to the heat-flow coupling model and inverting the formation flow coefficient based on the bottom hole pressure includes: The pressure relationship between the bottom of the well and the wellhead is determined based on the fluid dynamics equations in the heat-fluid coupling model. Based on the pressure correspondence, the surface pressure is converted into the bottom hole pressure; Determine the bottom hole pressure curve as a function of time; The formation flow coefficient is inverted using the bottom hole pressure curve.

4. The geothermal wellhead temperature prediction method as described in claim 3, characterized in that, The step of inverting the formation flow coefficient through the bottom hole pressure curve includes: Determine the bottom hole pressure equation based on the bottom hole pressure curve; Extract the target factors related to the time parameter from the bottom hole pressure equation; Plot the relationship between the bottom hole pressure and the target factor; The formation flow coefficient is inverted using the slope of the straight line segment in the aforementioned relationship diagram.

5. The geothermal wellhead temperature prediction method as described in claim 2, characterized in that, The step of fitting the measured temperature using the heat flow coupling model and inverting the average thermal diffusivity from the producing layer to the geothermal reservoir based on the fitting results includes: The temperature relationship between the bottom of the well and the wellhead is determined based on the heat conduction equation in the heat flow coupling model. The measured temperature is fitted using the aforementioned temperature correspondence; The heat conduction equation is adjusted based on the fitting results, and the average thermal diffusivity from the producing layer to the geothermal reservoir is inverted based on the adjusted heat conduction equation.

6. The geothermal wellhead temperature prediction method as described in claim 5, characterized in that, The step of adjusting the heat conduction equation based on the fitting result and inverting the average thermal diffusivity from the producing layer to the geothermal reservoir based on the adjusted heat conduction equation includes: Determine whether the temperature error between the calculated temperature obtained by fitting and the measured temperature is greater than a preset threshold. If not, adjust the heat conduction equation and return to the step of determining the temperature correspondence between the bottom of the well and the wellhead based on the heat conduction equation in the heat flow coupling model, until the temperature error is less than the preset threshold. When the temperature error is less than the preset threshold, the average thermal diffusivity from the generating layer to the geothermal storage is inverted based on the parameters in the adjusted heat conduction equation.

7. A geothermal wellhead temperature prediction device, characterized in that, The device includes: The model building module is used to build a heat flow coupling model of a geothermal well; The formation flow coefficient inversion module is used to convert surface pressure into bottom hole pressure according to the heat-fluid coupling model, and invert the formation flow coefficient based on the bottom hole pressure; The average thermal diffusivity inversion module is used to fit the measured temperature through the heat flow coupling model and invert the average thermal diffusivity from the producing layer to the geothermal storage layer based on the fitting results. The wellhead temperature prediction module is used to predict the distribution of geothermal wellhead temperature based on the formation flow coefficient and the average thermal diffusivity.

8. A geothermal wellhead temperature prediction device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the geothermal wellhead temperature prediction method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the geothermal wellhead temperature prediction method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the geothermal wellhead temperature prediction method as described in any one of claims 1 to 6.

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