Geothermal Resource

Geothermal resource development aims to harness Earth's internal heat for sustainable energy production, focusing on efficient extraction and minimizing induced seismicity. Current research emphasizes the application of machine learning, particularly deep learning architectures like convolutional and recurrent neural networks, and reinforcement learning algorithms, to optimize well control, predict geothermal gradients, and improve resource assessment, often incorporating federated learning for data privacy and efficiency. These advancements offer significant potential for enhancing the accuracy and speed of geothermal exploration and exploitation, leading to more efficient and environmentally responsible energy production.