27 results about "Geothermal gradient" patented technology

The invention discloses a buried pipe temperature response calculation method considering underground water seepage and ground temperature gradient, and belongs to the field of building environment and energy application engineering.The buried pipe temperature response calculation method comprises the steps that a shallow buried pipe heat exchanger is regarded as a finite long-line heat source model, and when underground water seepage passes, the shallow buried pipe heat exchanger is regarded as a finite long-line heat source seepage model; an energy control equation containing a soil heat conduction item, an underground water seepage convection item and a ground temperature gradient correlation item at the same time is established, and initial temperature distribution based on ground temperature gradient, ground surface fixed wall temperature and boundary conditions of an underground limited boundary are set; and finally, obtaining an analytical solution expression of the change of the temperature at any position of the underground soil along with the time through analytical solution. According to the method, the defect that a traditional model ignores key environmental factors is overcome, the heat transfer process of heat conduction and convection coupling can be accurately simulated, the accuracy of temperature field prediction and the reliability of long-term performance evaluation are remarkably improved, meanwhile, the complexity of numerical calculation is avoided, and the calculation efficiency is improved.

The application provides a shale free oil saturation calculation method and device. Through obtaining the surface temperature, geothermal gradient and spectrum of shale, the logging interpretation data is calculated by using a functional relationship; then a training data set and a verification data set are established, the verification data set is sent to a machine learning algorithm model trained by using the training data set, and a data learning result is obtained; based on the data learning result and the spectrum without three-peak characteristics, free oil signal data in the spectrum without three-peak characteristics is determined, the free oil signal data is fitted, and a normal distribution expression of the free oil spectrum is obtained; and the ratio of the free oil porosity component and the effective porosity component is used to calculate the free oil saturation of the target shale, so that the problems of high data acquisition cost and large calculation error in the existing shale free oil saturation calculation method are solved.

The application relates to a deep rock mass displacement monitoring method based on segmented temperature compensation and relates to the technical field of geotechnical engineering monitoring.The deep rock mass displacement meter (single-point or multi-point displacement meter) is arranged in a borehole, a hollow measuring rod is adopted, and a temperature sensor is arranged in the hollow measuring rod to realize real-time collection of multiple points of temperature along the length direction of the measuring rod; the measuring rod is divided into multiple monitoring sections, the temperature deformation of each section of the measuring rod is calculated according to the measured temperature of the corresponding depth of each section of the measuring rod, the displacement measurement value of each measuring point is compensated by the segmented temperature deformation, the true displacement of the bedrock is obtained after the temperature influence is eliminated, and thus the quantitative description of the bedrock creep process is realized.The application overcomes the system error caused by the uneven distribution of the ground temperature gradient, significantly improves the deep displacement monitoring precision, is compatible with the existing deep rock mass displacement meter structure, is easy to implement, and is suitable for the bedrock creep mechanism research and long-term safety monitoring of major projects.

The invention discloses a method, device and equipment for quantitatively characterizing a formation heat convection effect and a storage medium, and the method comprises the following steps: determining a layered interface of an upper formation and a lower formation according to an obtained ground temperature gradient; determining the actually measured surface heat flow of the upper stratum according to the average ground temperature gradient of the upper stratum and the harmonic heat conductivity of the upper stratum; pure heat conduction surface heat flow is determined according to the average ground temperature gradient of the lower stratum, the blending heat conductivity of the lower stratum and radioactive element heat production of the upper stratum; and determining a heat convection value of the stratum according to the actually measured surface heat flow of the upper stratum and the pure heat conduction surface heat flow. The method aims at solving the problems that in an existing method, complexity of a stratum structure is not considered, and accurate quantitative analysis is lacked, the stratum heat convection effect is quantitatively represented through steady-state temperature data and accurate stratum in-situ thermophysical properties, and the more accurate and comprehensive quantitative analysis effect is achieved.

The invention discloses a recharge well optimization design and intelligent monitoring system in geothermal resource development, and relates to the technical field of geothermal resource exploitation. Environmental parameters in a recharge well are collected in real time through installed monitoring equipment, and meanwhile a three-dimensional model is constructed based on the collected environmental parameters; after acquisition is completed, thermodynamic analysis is conducted on the recharge well of the corresponding three-dimensional model in a data analysis mode, the ground temperature gradient in the engineering area and a heat conduction model of the recharge well after analysis are determined, and after analysis is completed, a relation model between the temperature and the pressure in the current recharge well is determined through a control variable method; meanwhile, a recharge well optimization decision model is constructed based on a relation model between the temperature and the pressure in the current recharge well; and finally, on the basis of the constructed recharge well optimization decision model, the relation model between the temperature and the pressure in the current recharge well and the environment data acquired in real time, optimizing and monitoring the recharge well in geothermal resource development in a dynamic data simulation mode, so that the accuracy of intelligent monitoring of the recharge well is improved.

This disclosure relates to a method, apparatus, device, storage medium, and product for predicting porosity, applied in the field of seismic exploration technology. In this disclosure, well logging data from a target well is acquired; based on the measured temperature and geothermal gradient data in the well logging data, a temperature set of the target formation is determined. The porosity of the target formation is determined based on the temperature set of the target formation and a first mapping relationship, whereby the first mapping relationship is a mapping relationship between elastic parameters and porosity at different temperatures of the target formation. The reservoir temperature at different depths of the target formation will vary, thus affecting the prediction results of elastic parameters and porosity. By considering temperature change as an indicator when establishing the relationship between elastic parameters and porosity, more geological factors are taken into account when predicting porosity results, making it adaptable to more complex geological conditions. Therefore, the accuracy of porosity prediction can be improved.

The invention discloses a hydrogen source rock in-situ identification method and device which can be used in the field of oil-gas exploration and new energy development, and the method comprises the steps: obtaining multi-dimensional drilling data collected in situ in hydrogen source rock drilling, and obtaining a multi-dimensional real-time data flow; separating independent signals of different alteration processes from the multi-dimensional real-time data stream by adopting an independent component analysis algorithm to obtain a plurality of independent alteration components; an entropy weight method is adopted to calculate the weight of each independent alteration component, according to the obtained ground temperature gradient, each independent alteration component and the weight of each independent alteration component, a continuous hydrogen generation index of each stratum of the hydrogen source rock is determined, and the hydrogen generation index is used for quantifying the hydrogen generation capacity of the hydrogen source rock; and mapping continuous hydrogen generation indexes of all stratums of the hydrogen source rock in the three-dimensional geological network model around the well of the hydrogen source rock drilling. According to the method, cross interference in hydrogen source rock identification can be eliminated, and the hydrogen source rock exploration efficiency and accuracy are improved.

The invention discloses a clastic rock reservoir corrosion porosity prediction method, device and equipment, and the method comprises the steps: carrying out the calibration through employing single well data based on the seismic section geological interpretation data of a target region, and determining the stratigraphic data of each section point of the target region; based on the regional geological data of the target region, acquiring the earth heat flow value and the earth temperature gradient of the target region to determine the formation temperature of each section point formation layer in each geological period; based on the organic acid concentration and the stratum temperature in the stratum layering organic matter hydrocarbon evolution process of each section point of the target area, the PH value of underground fluid of the stratum in each geological period is determined; correcting a time temperature-fluid pH value index of the stratum based on the time temperature index of the stratum and the pH value of the underground fluid; and based on the corrosion amount of the stratum and the time temperature-fluid acidity and alkalinity index of the stratum, fitting an incidence relation between the corrosion amount and the time temperature-fluid acidity and alkalinity index to predict the corrosion porosity of the target layer, and realizing quantitative prediction of the corrosion porosity.

The invention relates to the technical field of terrestrial heat control, and discloses a deep terrestrial heat cascade development system and control method based on multi-source heat storage cooperative scheduling, and the system comprises a multi-source heat storage perception and fusion subsystem, a dynamic heat flow scheduling subsystem and a cascade heat energy release subsystem. The method comprises the following steps: merging multi-source original heat storage distribution data into a heat storage state diagram containing real-time temperature, pressure and permeability parameters of heat storage; converting the heat storage state diagram into a real-time heat flow scheduling plan, wherein the heat flow scheduling plan specifies the rate, sequence and path of extracting heat energy from each heat storage; according to a real-time heat flow scheduling plan, heat energy is released step by step from high temperature to low temperature through a multi-stage heat exchange sequence, and heat energy of different grades is generated and output for power generation or heating. Accurate three-dimensional modeling of underground heat storage parameters is achieved, and the technical bottlenecks of low energy utilization efficiency, high stratum disturbance risk and fast productivity attenuation in traditional geothermal development are broken through.

The invention provides an in-situ measurement method and device for stratum thermophysical parameters, a terminal and a storage medium, and belongs to the technical field of full-well-section stratum thermal parameter measurement, and the measurement method comprises the following steps: starting a drilling machine lifting device, lowering a side wall coring instrument to a to-be-measured stratum depth, and drilling a to-be-measured rock core by using the side wall coring instrument; starting the thermal parameter measuring device, heating the resistance wire at constant power, and measuring the resistance change value of the resistance wire caused by the temperature change of the to-be-measured core; according to the basic physical parameters of the resistance wire, the relation between the temperature change and the resistance change and the mathematical relation between the thermophysical parameters, the thermophysical parameters of the rock core of each test point and the stratum temperature gradient of the whole well section are calculated. The in-situ measurement method and device for the stratum thermophysical parameters, the terminal and the storage medium have the technical effects that the stratum thermophysical parameters can be measured, the stratum temperature gradient of the whole well section can be calculated, the ground temperature gradient can be rapidly obtained, and the geothermal resource quantity can be accurately evaluated.

The invention discloses a method, a system and equipment for evaluating the installation depth of a multi-stage throttle valve and a medium, relates to evaluation of the installation depth of a throttle valve in oil and gas exploitation, and aims to solve the technical problem that the installation depth of the multi-stage throttle valve cannot be evaluated in the process of installing the throttle valve. Comprising the following steps: acquiring initial data of an oil well, constructing a shaft infinitesimal section, setting a ground temperature gradient, setting pressure change, calculating outlet pressure, calculating pressure deviation, judging that a wellhead is reached, comparing errors, updating the pressure change, updating pressure before throttling, calculating outlet temperature, adjusting mounting parameters of a throttling valve, calculating data after throttling, and replacing the pressure and the temperature. Judging other throttle valves, and outputting results and corresponding logics and algorithms. According to the depth of the shaft and the corresponding pressure and temperature, the temperature and pressure change conditions of the whole well section can be obtained, and the downstream cooling effect of each stage of throttling valve under the corresponding depth can be evaluated by setting the nozzle diameter and the installation depth for each stage of the multi-stage throttling valve.

The present application relates to the technical field of in-situ acquisition of seabed, in particular to a new gravity sampling and geothermal gradient measuring device and measuring method. The measuring device comprises: an impact unit, including an outer cylinder and a transmission cylinder, the transmission cylinder is located on the annular inner side of the outer cylinder, and the transmission cylinder rotates along the annular inner surface of the outer cylinder, an impact mechanism is arranged in the outer cylinder, and the transmission cylinder drives the impact mechanism to generate a downward impact force on the probe rod unit during rotation; a probe rod unit, fixedly connected with the bottom of the impact unit, comprising a probe rod and a plurality of temperature sensing units arranged on the probe rod. It can realize large-depth penetration of the probe, and complete in-situ temperature acquisition and in-situ sample collection during continuous downward penetration.

The present application relates to a kind of rift basin present geothermal field prediction method.The method first obtains the mean of well point stable section geothermal gradient in study area, and according to stratigraphic compaction coefficient and other parameters, the study area is divided into multiple sub-regions;Subsequently, the preliminary prediction model between geothermal gradient and Moho depth, basement depth, stratigraphic thermal conductivity weighted average value is established in each sub-region;By identifying the residual of preliminary prediction model, the geothermal gradient high well site is systematically screened out, and then the quantitative analysis of the enhancement effect of deep fault on geothermal field is carried out: that is, based on three-dimensional seismic data, the temperature control influence range of each fault is determined, the distance of well site from fault is calculated, and the enhancement efficiency coefficient of fault is obtained by linear regression, and the preliminary model is corrected, to obtain the final prediction model;Finally, based on regional base map and the final model, high-precision geothermal gradient distribution map is generated by gridding calculation.

The invention discloses a stratum denudation thickness calculation method, which comprises the following steps: acquiring different-depth ground temperature data of a target stratum through a thermal advection coupling ground temperature field inversion model, extracting paleo-temperature data of a fluid inclusion in a rock core sample by using a fluid inclusion paleo-temperature scale denudation model, and determining paleo-ground temperature gradient change characteristics; processing mudstone porosity data by adopting a mudstone compaction curve dynamic fitting algorithm, establishing a dynamic relationship between the porosity and the buried depth, and optimizing a compaction curve; the data are input into a three-dimensional stratum denudation modeling analysis platform, a target stratum three-dimensional space structure model is constructed, modeling parameters are adjusted in combination with ground temperature gradient change and ancient ground temperature evolution characteristics, and the stratum denudation process is simulated; and finally, according to a simulation result and mudstone compaction degree parameters, calculating denudation thicknesses of different positions of the target stratum. According to the method, through cooperative application of multiple models and an algorithm, the accuracy of stratum denudation thickness calculation is improved.

The invention discloses a continental facies mud shale gas geological evolution simulation analysis method, and relates to the technical field of oil-gas exploration, the method comprises the following steps: drilling a test shale core sample and sandstone sample combination to obtain a simulation geological sample; according to the stratum burying mode, the ground temperature gradient and the pressure, performing a hot-pressing simulation experiment on the simulation geological sample to obtain a simulation experiment product; calculating HI and TOC parameter values of the simulation experiment product, and obtaining a geological maturity Ro value corresponding to each experiment temperature point; according to the Ro value, obtaining an oil discharge efficiency curve of the simulated geological sample at different geological maturity; and performing reservoir space evolution simulation and shale pore quantitative analysis on the simulation experiment product to obtain a shale reservoir sample analysis result. Through combination of a hot-pressing simulation experiment and liquid hydrocarbon / gaseous hydrocarbon separation analysis, the oil discharge efficiency and the pore evolution characteristics are synchronously quantified, and the problems that the hydrocarbon discharge efficiency error is large and the pore structure is difficult to accurately evaluate in a traditional method are solved.

This invention discloses a calculation method for the temperature response of buried pipes considering groundwater seepage and geothermal gradients, belonging to the field of building environment and energy application engineering. The method includes: treating the shallow buried pipe heat exchanger as a finite-length heat source model, and treating it as a finite-length heat source seepage model when groundwater seeps through it; establishing an energy control equation that simultaneously includes soil thermal conductivity, groundwater seepage convection, and geothermal gradient correlation terms; setting boundary conditions based on the initial temperature distribution of the geothermal gradient, the constant surface wall temperature, and the finite underground boundary; and finally obtaining an analytical solution expression for the temperature change of any location in the underground soil over time through analytical solving. This invention overcomes the shortcomings of traditional models that ignore key environmental factors, accurately simulates the coupled heat transfer process of conduction and convection, significantly improves the accuracy of temperature field prediction and the reliability of long-term performance evaluation, while avoiding the complexity of numerical calculations and improving computational efficiency.

The present application belongs to the technical field of frozen ground foundation engineering, and in particular to a frozen ground foundation bearing behavior prediction method with multi-pile length cooperation. A three-dimensional geological-temperature database of the frozen ground foundation is constructed, stratum distribution, water content, fine particle content and geothermal gradient data are integrated, frozen layers and unfrozen layers are divided, and high, medium and low frost heaving sensitive zones are identified. Based on the sensitive zone distribution, a three-level differentiated pile type of "short pile-medium pile-long pile" is designed, a coupling relationship between pile length and frost heaving sensitivity is established, a group pile soil resistance correction model considering pile length difference is constructed by introducing a multi-pile length cooperation effect coefficient, and a frozen layer rigid shell effect correction model and an unfrozen layer bearing decay model are integrated. Through the differentiated pile type design and the cooperation effect model, the problem that the traditional method cannot handle the spatial variability of frozen soil, resulting in inaccurate bearing behavior prediction, is solved, and the present application has the advantages of accurate prediction, optimized design, improved safety and economy.

The invention relates to the technical field of ground source heat pumps, in particular to a ground source heat pump system heat energy conversion efficiency prediction method which comprises the steps that the outlet temperature, the inlet temperature, the ground temperature gradient and energy consumption information of a ground source heat pump during operation are recorded; taking the ground temperature gradient in the current scene as a reference, performing coupling processing on the inlet temperature and the outlet temperature, and determining an environment parameter set under scene coupling; performing correlation explanation on the environmental parameter set by using energy consumption information, and constructing a heat supply load change curve in combination with actual operation time distribution of the ground source heat pump; based on the heat supply load change curve at any moment, predicting the energy efficiency ratio of the heat supply load, and determining a predicted value of the energy efficiency ratio; and mixing the predicted value of the energy efficiency ratio with actual data, calculating a predicted residual error of the energy efficiency ratio, determining a maximum prediction proportion of the energy efficiency ratio according to an anchoring scene of the energy efficiency ratio, carrying out data binding on the maximum prediction proportion, and outputting the data. The accuracy and the processing efficiency of thermal conversion prediction are realized.

The present application relates to a kind of large-scale water guide fault heat accumulation effect evaluation method and system of fault basin, belong to geothermal resource development technical field, the large-scale water guide fault heat accumulation effect evaluation method of fault basin obtains the thermal physical data of rock sample of different rock strata units in fault basin karst geothermal region, constructs the geothermal geological model of fault basin karst geothermal region, constructs the heat conduction geothermal geological mathematical model and heat convection geothermal geological mathematical model considering large-scale water guide fault, based on the boundary condition and thermal physical parameter of set geothermal geological model, respectively to heat conduction geothermal geological mathematical model and heat convection geothermal geological mathematical model are simulated and solved, obtain the first geothermal gradient and second geothermal gradient of geothermal geological model;First heat flux value and second heat flux value of geothermal geological model are calculated, to evaluate large-scale water guide fault heat accumulation effect, improve the accuracy of heat accumulation effect intensity and spatial distribution law.

The invention relates to the technical field of tunnel engineering, and provides a high-ground-temperature tunnel ground stress inversion method based on a refined three-dimensional geologic model aiming at the defects that the influence of temperature stress is ignored and a geologic model cannot dynamically adapt to a construction process in an existing method. According to the method, multi-source geological information in the exploration stage and the construction stage is fused, and a refined three-dimensional geological model dynamically updated along with tunnel excavation is constructed; temperature stress is calculated according to the ground temperature gradient, the rock mass thermodynamic parameters and the burial depth, after the temperature stress is separated from the actually measured ground stress, a ground stress field is obtained through support vector regression (SVR) inversion, and then the temperature stress field is superposed to obtain real ground stress distribution; and along with tunnel excavation, the process is repeated to realize dynamic updating of the crustal stress field. The geologic model accuracy and the crustal stress inversion accuracy are improved, dynamic adaptation of the crustal stress field is achieved, and accurate data support is provided for high-ground-temperature tunnel construction safety early warning and support design optimization.

The present application relates to the technical field of monitoring systems, in particular to a plateau clean energy power generation capacity prediction system and method based on high-altitude characteristics. It comprises a multi-source data acquisition module configured to acquire frozen soil freeze-thaw cycle data, freeze-thaw depth data, ultraviolet radiation intensity data, canyon terrain wind field data, atmospheric pressure data, snow reflectivity data, and ground temperature gradient data; a data processing module configured to calculate frozen soil deformation coefficients, ultraviolet attenuation coefficients, wind field distortion coefficients, air thinning correction coefficients, thermal spot attenuation coefficients, foundation settlement coefficients, and fan aerodynamic correction coefficients based on multi-source data; and a prediction model construction module configured to construct a coupling prediction model containing the frozen soil deformation coefficients, ultraviolet attenuation coefficients, wind field distortion coefficients, air thinning correction coefficients, thermal spot attenuation coefficients, foundation settlement coefficients, and fan aerodynamic correction coefficients. The present application can adapt to the complex environment of the plateau and comprehensively consider the coupling influence of multiple factors on power generation capacity.

The invention belongs to the technical field of geothermal resource exploration, and discloses a ground temperature gradient prediction and target region optimization method and system based on multi-well joint Bayesian calibration, and the method comprises the steps: automatically selecting a random forest or Bayesian regression model for initial prediction according to the sample size; data of multiple wells are comprehensively utilized in a spatial neighborhood, and physical priori is constructed through distance and data quality dual weighting; bayesian fusion is adopted to calibrate machine learning prediction and physical prior; based on the prediction uncertainty, the goodness of fit and the spatial distance, adaptively adjusting the weight of the model; theoretical lower limit soft constraint is applied to guarantee physical rationality; and finally, result display and target area automatic optimization are realized through a visual platform. According to the method, the precision and reliability of ground temperature gradient prediction under the sparse well data condition are remarkably improved, and effective technical support is provided for geothermal exploration.

The invention relates to the technical field of monitoring systems, in particular to a plateau clean energy generating capacity prediction system and method based on high altitude characteristics. Comprising a multi-source data acquisition module configured to acquire frozen soil freezing and thawing cycle period data, freezing and thawing depth data, ultraviolet radiation intensity data, canyon terrain wind field data, atmospheric pressure data, accumulated snow reflectivity data and ground temperature gradient data; the data processing module is configured to calculate a frozen soil deformation coefficient, an ultraviolet attenuation coefficient, a wind field distortion coefficient, an air rarefaction correction coefficient, a hot spot attenuation coefficient, a foundation settlement coefficient and a fan pneumatic correction coefficient based on the multi-source data; the prediction model construction module is configured to construct a coupling prediction model comprising the frozen soil deformation coefficient, the ultraviolet attenuation coefficient, the wind field distortion coefficient, the air rarefaction correction coefficient, the hot spot attenuation coefficient, the foundation settlement coefficient and the fan pneumatic correction coefficient; the method can adapt to the plateau complex environment, and comprehensively considers the generating capacity influenced by multi-factor coupling.

The invention relates to the technical field of geothermal exploration, and particularly discloses a geothermal resource quantity estimation and evaluation method, which comprises the following steps of S1, delimiting a target geothermal area, and establishing a three-dimensional concept geologic model of the target geothermal area based on multi-source data fusion; s2, according to the three-dimensional concept geologic model, the spatial form and parameters of target heat storage are determined, and the parameters comprise the heat storage area, the thickness, the porosity, the rock density and the rock specific heat capacity; s3, based on the three-dimensional concept geologic model and the ground temperature gradient data or the borehole temperature measurement data, calculating the heat storage amount of the target heat storage by adopting a volumetric method; and S4, on the basis of hydrogeological test data, geochemical data and the three-dimensional concept geologic model, the geothermal fluid exploitable quantity of the target heat reservoir is estimated. According to the geothermal resource quantity estimation and evaluation method, the three-dimensional solid model capable of accurately depicting the heat storage heterogeneity and the heat control-water guide structure is constructed, and the problem that a traditional model is excessively simplified is fundamentally solved.

The invention relates to the technical field of mineral exploration, in particular to a deep metallogenic prediction method for a tectonic altered rock type gold mine, which comprises the following steps: S1, data acquisition and preprocessing; s2, tectonic stress field simulation; s3, ground temperature field and ground electric field analysis: identifying a deep hydrothermal activity abnormal area by combining ground temperature gradient and ground electric field data; s4, multi-source data fusion: generating a comprehensive geological anomaly map; s5, constructing a model; and S6, performing metallogenic prediction and verification: performing metallogenic prediction on the deep area by using the trained model, arranging drill holes in the predicted metallogenic favorable area and acquiring drill hole data in the metallogenic prediction, comparing the prediction result with the drill hole data, evaluating the prediction precision and generating a metallogenic prediction report. According to the method, a series of non-dominant geological information such as a tectonic stress field, a ground temperature field, a geoelectric field and primary halo and a multi-source data fusion technology are introduced, and a deep learning algorithm is combined, so that the precision and reliability of deep metallogenic prediction are improved.

The invention discloses a geothermal well group deployment optimization design device under the influence of thermal storage heterogeneity, and relates to the technical field of geothermal resource exploration and development, and the device comprises an earthquake ground temperature denoising module which is used for collecting ground temperature gradient and earthquake activity frequency data, and de-noising and pattern recognition are carried out by adopting a hybrid algorithm of wavelet transform and a support vector machine to eliminate data fluctuation noise and extract effective features. Multi-scale analysis is carried out by fusing ground temperature gradient and seismic activity frequency data, the quantification precision of thermal storage heterogeneity is remarkably improved, thermal storage parameter modeling based on the spatial variation function and the Kriging interpolation algorithm can accurately describe the spatial variation rule of reservoir attributes, and the method has the advantages of being high in accuracy and high in reliability. And the seismic activity frequency is used as a dynamic constraint condition to carry out distribution correction, so that the identification capability of the heterogeneous characteristics of the fracture development area is further enhanced, and a more reliable geological basis is provided for well position deployment.

The invention relates to a method for predicting a current ground temperature field of a broken basin. The method comprises the following steps: firstly, acquiring a ground temperature gradient mean value of a well point stable section in a research area, and dividing the research area into a plurality of sub-areas according to parameters such as a stratum compaction coefficient; then, establishing a preliminary prediction model between the ground temperature gradient and the weighted average value of the mourphy surface depth, the substrate depth and the stratum thermal conductivity in each sub-region; and systematically screening out a well location with a relatively high ground temperature gradient by identifying the residual error of the preliminary prediction model, and further quantitatively analyzing the enhancement effect of deep and large fractures on a ground temperature field, namely determining the temperature control influence range of each fracture based on three-dimensional seismic data, calculating the distance between the well location and the fracture, and obtaining the enhancement efficiency coefficient of the fracture through linear regression. Correcting the preliminary model to obtain a final prediction model; and finally, based on the regional basic map and the final model, performing gridding calculation and generating a high-precision ground temperature gradient distribution map.