Application of integrated geophysical techniques in geothermal exploration in Binhai County, Jiangsu Province

Integrated geophysical technology is a necessary and effective means for geothermal exploration.However,integration of geophysical technology for large‐scale surveys with those for geothermal reservoir localization is still in development.This study used the controlled source audio‐frequency magnetotelluric method technology for large‐scale exploration to obtain underground electrical structure information and micromotion detection technology to obtain underground wave velocity structure information.The combination of two detection technologies was used for local identification of geothermal reservoirs.Further,auxiliary correction and inversion constraint were implemented through the audio magnetotelluric sounding technology for maximum authenticity restoration of the near‐and transition‐field data.Through these technology improvements,a geothermal geological model was established for the Binhai County of Jiangsu Province in China and potential geothermal well locations were identified.On this basis,a geothermal well was drilled nearly 3000m deep,with a daily water volume of over 2000m3/day and a geothermal water temperature of 51°C at the well head.It is found that predictions using the above integrated geophysical exploration technology are in good agreement with the well geological formation data.This integrated geophysical technology can be effectively applied for geothermal exploration with high precision and reliability.

Applications of artificial intelligence in geothermal resource exploration: A review

Artificial intelligence (AI) has become increasingly important in geothermal exploration,significantly improving the efficiency of resource identification.This review examines current AI applications,focusing on the algorithms used,the challenges addressed,and the opportunities created.In addition,the review highlights the growth of machine learning applications in geothermal exploration over the past decade,demonstrating how AI has improved the analysis of subsurface data to identify potential resources.AI techniques such as neural networks,support vector machines,and decision trees are used to estimate subsurface temperatures,predict rock and fluid properties,and identify optimal drilling locations.In particular,neural networks are the most widely used technique,further contributing to improved exploration efficiency.However,the widespread adoption of AI in geothermal exploration is hindered by challenges,such as data accessibility,data quality,and the need for tailored data science training for industry professionals.Furthermore,the review emphasizes the importance of data engineering methodologies,data scaling,and standardization to enable the development of accurate and generalizable AI models for geothermal exploration.It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources.By effectively addressing key challenges and leveraging AI technologies,the geothermal industry can unlock cost‐effective and sustainable power generation opportunities.

Genetic model and exploration target area of geothermal resources in Hongtang Area, Xiamen, China

The geothermal resources in Fujian Province are mainly hydrothermal resources of medium-low temperature.To better understand the whole process and conditions of heat control in the middle and deep crust,this study focuses on the analysis of heat accumulation model in Hongtang Area of Xiamen,and the main conditions of the model such as faults and sags are explored and interpreted in detail by using gravity and wide-field electromagnetic methods.4 main faults(F33,F2,F12 and HT-F1)and 10 secondary faults(HT-F2,HT-F3,HT-F4,HT-F5,HT-F6,HT-F7,HT-F8,HT-F9,HT-F10 and HT-F11)were inferred,and the distribution range of sags was delineated.The convective geothermal system is composed of four components:Heat source,geothermal reservoir,heat-conductive fault and heat retaining cover,which form a quaternary heat accumulation model.According to the model,the intersection of the main faults F12,HTF1 and F33 can be delineated as the primary target area of geothermal exploration,while the intersection of the secondary faults(F12 and HT-F6;F12 and HT-F2;HT-F9,HT-F10 and F12;F12 and HT-F11;F33 and HT-F3;HT-F8 and HT-F3;HT-F2,HT-F10 and HT-F1)can be delineated as the secondary target area.Borehole DR01,which is located in the primary target area,shows that the water temperature increases from fast to slow in the depth range of 0–500 m,and stays at 36℃below 500 m.The reliability of the heat accumulation model and the target area was tested via geothermal boreholes,which is of great significance to the exploitation and utilization of geothermal resources in Hongtang Area of Xiamen.

Crustal Thermo-Structure and Geothermal Implication of the Huangshadong Geothermal Field in Guangdong Province

Dense distribution of granites and surrounding hot springs, the high anomalous heating rates of geothermal fluids and the high geothermal gradients in shallow crust in Southeast China are revealed by previous geothermal explorations. However, there have always been debates on the genesis of geothermal anomalies of Southeast China. It is imperative to look into the genesis mechanism of geothermal anomalies through selecting a typical geothermal field, and constructing fine crustal thermostructure. In this study, in-depth excavation is implemented for the previous data of geophysical exploration and deep drilling exploration in the Huangshadong area. We synthetically analyze the results of radioactive heat productions(RHPs), thermophysical properties of rocks and audio-frequency magnetotellurics(AMT) sounding. This study concludes that the coefficient of radioactive heat generation(RHG) of crustal rocks and conduction heat of concealed granites is the main formation mechanism of geothermal anomalies of South China, where occurs a Great Granite Province. There is a regional indicating implication for the genesis of geothermal anomalies, taking the Huangshadong geothermal field as a typical example. It is also an important reference to guide the exploration, evaluation, development and utilization of geothermal resources in this region.