Identification And Fine Evaluation For Key Geothermal Attributes With Multi-parameter Constraints

As a stable,sustainable and competitive green energy,geothermal resources are of great practical significance and far-reaching impact on the adjustment of energy structure and the realization of the"double carbon"goal.Temperature is one of the key characteristics of the earth’s interior,the knowledge of which determines our ability to study fundamental scientific and applied geothermal problems.However,as a hot and challenging problem in geothermal exploration,subsurface temperature prediction lacks systematic research and technical breakthroughs.The stratigraphic thermal conductivity is the key parameter for thermal mechanism interpretation,geothermal resource evaluation,and geothermal exploitation optimization design.Currently,the methods of obtaining the stratigraphic thermal conductivity are mainly based on core testing or indirectly logging estimation.Still,they cannot accurately obtain the distribution characteristics of thermal conductivity in deep strata.Therefore,it is necessary to develop a high-precision subsurface temperature field prediction method based on geophysical sounding,and carry out the inversion research of 3D thermal conductivity in deep strata.The above studies not only provides an important theoretical basis and scientific evidence for the interpretation of thermal mechanism of geothermal system and the fine evaluation of multi-attribute fusion of geothermal resources,but also has an important practical significance for the sustainable development and utilization of geothermal resources on a large scale and in an efficient way.To address the key technical problems of subsurface temperature and thermal conductivity prediction and the defects in fine evaluation and regionalization of geothermal resources.In this paper,we constructed three kinds of electromagnetic geothermometers based on logging data or core tests to predict the subsurface temperature distribution in the Xiong’an New Area.In addition,we quantitatively evaluate the characteristics and laws of the three methods of subsurface temperature prediction.Meanwhile,a thermal conductivity prediction program was developed to obtain the 3D distribution characteristics of thermal conductivity of deep formation in the Xiong’an New Area with the predicted temperature field.The terrestrial heat flow distribution is also estimated.Furthermore,we also analyzed the law of heat accumulation of strata at different depths,and studied the internal relationship among resistivity,temperature and thermal conductivity of strata.Finally,based on the identification of key geothermal attributes in the deep strata of Xiong’an New Area,the fine evaluation and zoning of geothermal resources in the study area were carried out by integrating the distribution of stratigraphic attributes under heterogeneous conditions.The main achievements and understandings are as follows:（1）Three kinds of electromagnetic geothermometers were developed,namely,the optimal temperature coefficient correction method（CCMOT）,temperature-pressure coupled resistivity model（TPCRM）,and core resistivity calibration method（CRCM）at high temperature and pressure.The above three methods were used for the 3D prediction of the subsurface temperature field in the Xiong’an New Area,and the average accuracy was 88.7%,89.7%and 81.82%,respectively.Among them,the CCMOT method is simple,practical and high precision,so it has the highest promotion value.When the overlying formation pressure can be accurately calculated,the TPCRM method is preferred.The CRCM strongly depends on core testing,and the prediction accuracy of the temperature field near the test core is higher than CCMOT and TPRCM,while the prediction accuracy of the temperature field far away from the test core is lower than the above two methods.（2）We explore the sensitivity characteristics of key parameters in three methods of subsurface temperature prediction.The results show that CCMOT and TPCRM must obtain the optimal subdivision spacing of the logging data and resistivity normalized grid before the temperature field prediction.Both methods have a relatively small dependence on the number of constraint boreholes,unlike artificial neural networks or other deep learning algorithms requiring a large number of samples.For the CRCM model,the resistivity conversion coefficient greatly influences temperature field prediction,especially for the resistivity reduction coefficient.In addition,CRCM has a relatively large dependence on the test core,the temperature field prediction near the experimental core borehole is higher,while the temperature field prediction accuracy is significantly reduced at the location far away from the core borehole.（3）A 3D inversion program of subsurface thermal conductivity prediction was developed to obtain the distribution characteristics of deep formation thermal conductivity and terrestrial heat flow in the Xiong’an New Area.The inversion tests of five typical geothermal models show that the 3D inversion program of deep formation thermal conductivity based on based on the Krylov subspace algorithm developed in this study has high accuracy,resolution and stability.The characteristics of heat accumulation can be analyzed based on the predicted temperature field and thermal conductivity distribution.At a depth of 5 km,the heat reservoir mainly accumulates in depressions.At depths of less than 4 km,heat accumulation in the Niutuozhen uplift is primarily in the NE direction,while that in the Rongcheng uplift is mainly to the north,which explains the relatively low temperatures in deep strata within the uplifts of the Xiong’an New Area.At depths of 3–4 km,heat accumulation occurs in the Gaoyang uplift,but no significant heat accumulation in the shallow formation（z≤2km）.The thermal conductivity distribution is highly similar to the corresponding resistivity structure,and the location of the abnormal boundary is consistent.Formation thermal conductivity is the key factor of the subsurface temperature field.The measured and predicted values of terrestrial heat flow indicate that the mean accuracy of the predicted terrestrial heat flow is 89.23%.This also demonstrates the high accuracy of the predicted thermal conductivity in the Xiong’an New Area.（4）The traditional geothermal resource quantity assessment method was improved,and the main geothermal resource evaluation indexes of the Xiong’an New Area were obtained.A total area of 1571.56 km²in the Xiong’an New Area was divided into 14444evaluation units,and the distribution characteristics of geothermal resources and four main evaluation indicators including geothermal fluid storage,recoverable volume and recoverable heat in each unit grid were evaluated under the condition of heterogeneous physical property parameters of the thermal reservoir in the strata of Wumishan formation,Jixian system.The results show that the total geothermal resources of the Wumishan formation in the Xiong’an New Area are 9435.9×10¹⁶J,and the geothermal fluid storage is 17.9106 billion m³.The recoverable resources of geothermal fluid are8.9553×10⁶m³/a and the recoverable heat of geothermal fluid is 29.6348×10¹⁴J/a according to the extraction coefficient method.Under the condition of balanced production and reinjection,the recoverable resources of geothermal fluid are436.64×10⁶m³/a,and the recoverable heat of geothermal fluid is 1489.5×10¹⁴J/a,which is equivalent to 5.082174 million tons of standard coal per year.（5）A total of 9 parameters of four types of attributes were selected as evaluation factors and a weighted quantitative evaluation was performed to obtain the fine zoning of geothermal resources in the Wumishan formation of Xiong’an New Area.The weight of each evaluation factor was determined by the Fourier triangle method,and the comprehensive evaluation index of 14444 grid cells was calculated by weighting.The fine zoning of the Xiong’an New Area was divided into three grades:priority development zone（class I）,reserve favorable area（class II）and development potential area（class III）.Class I area is mainly distributed in the Rongcheng uplift and Niutaozhen uplift with good geothermal geological conditions.Several tensile fracture channels favorable to groundwater migration are developed nearby.The area of class I is 4.4282×10⁸m²,accounting for 28.03%of the total area of the Xiong’an New Area.Class II area is mainly distributed in the vicinity of Rongcheng uplift,Niutazhen uplift and Gaoyang low uplift,which is close to the normal tensile fault and has moderate geothermal geological conditions.Its area is 7.0836×10⁸m²,accounting for 44.84%of the total area of the Xiong’an New Area.Class III area is mainly distributed in the depressions,with an area of 4.2850×10⁸m²,accounting for 27.13%of the total area of the Xiong’an New Area.