Abstract: The present invention relates to an universal integrated environmental monitoring and management technique for operating underground storage sites of gaseous substances including CO2 capture and storage (CCS) site. According to the present invention, Firstly, a base dataset for observed soil gases and related surrounding environmental variables by a step of configuring/refining procedures. Next, extracting the time varying characteristics of the base dataset using wavelet-based multiresolution state-space modeling, and identifying the driving forces that governing the soil gases dynamics and evaluating their contributions through multiscale time-frequency domain correlation analysis. And finally, predicting and forecasting future scenarios with deep leaning models which intensively trained by the key driving forces. Furthermore, the present invention can provide quantitative based for analyzing the causation between driving forces and observed soil gases.

Abstract: The present invention relates to an apparatus for optimizing training indicators of an environmental prediction model and an operation method thereof. A training indicator optimization apparatus according to an embodiment includes a pre-processor for constructing a base dataset for environmental measurement data; a dynamic feature processor for identifying and extracting dynamic features for the constructed base dataset through multi-resolution wavelet analysis and a dimensionality reduction technique; a key feature group selector for identifying and evaluating driving force for environmental measurement data based on the extracted dynamic features and selecting a key feature group in response to the evaluation result; and an indicator optimizer for receiving the selected key feature group and the environmental measurement data as inputs and controlling a plurality of training indicators corresponding to an environmental prediction model.