Identification and Suppression of Multicomponent Noise in Audio Magnetotelluric Data Based on Convolutional Block Attention Module

Audio magnetotelluric (AMT) is commonly used in mineral resource exploration. However, the weak energy of AMT signals makes them susceptible to being overwhelmed by noise, leading to erroneous geophysical interpretations. In recent years, deep learning has been applied to AMT denoising and has shown better denoising performance compared to...

Mechanistic Investigation of Vertical Sweep Efficiency in Miscible CO2-Water- Coinjection for EOR and CCUS

The main objective of this study is to understand the vertical sweep efficiency with miscible CO2-water-coinjection as a secondary recovery method, from multiple perspectives: phase behavior, total relative mobility, fluid densities/viscosities, the driving forces and consequent phase distributions etc. We also seek to provide insights into...

Prediction of River Pollution Under the Rainfall-Runoff Impact by Artificial Neural Network: A Case Study of Shiyan River, Shenzhen, China

Climate change and rapid urbanization have made it difficult to predict the risk of pollution in cities under different types of rainfall. In this study, a data-driven approach to quantify the effects of rainfall characteristics on river pollution was proposed and applied in a case study of Shiyan River, Shenzhen, China. The results indicate...