Automation, control, and real-time surveillance of geothermal power plants require robust
and accurate predictive models. However, building physics-based models is fraught with …

This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-
step-ahead prediction and fault detection of a geothermal power plant's operation. The …

Management and optimization of energy recovery from geothermal reservoirs rely on
accurate prediction of energy production performance for alternative development …

ABSTRACT Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of
geothermal energy. Heat is extracted from this engineered system by injecting cold water …

Geothermal energy is getting more and more attention these days due to its nature of being
a clean source of renewable energy sources provider with a zero-carbon footprint, free and …

Accurate prediction of geothermal reservoir responses to alternative energy production
scenarios is critical for optimizing the development of the underlying resources. While the …

Optimization of energy production from geothermal reservoirs requires reliable prediction of
energy production performance under alternative operation and development scenarios …

ABSTRACT Pattern Recognition and Classification present a comprehensive introduction to
the core concepts involved in automated pattern recognition and classification. There are …

Reliable prediction of energy production performance from geothermal reservoirs is needed
for optimizing sustainable development of the underlying resources. While conventional …

Sensor readings play a critical role in the prediction performance of AI-based data-driven
fault-detection and diagnostics for borehole heat exchangers in heating and cooling …