Automatic high-resolution microseismic event detection via supervised machine learning

Microseismic methods are crucial for real-Time monitoring of the hydraulic fracturing dynamic status during the development of unconventional reservoirs. However, unlike the active-source seismic events, the microseismic events usually have low signal-To-noise ratio (SNR), which makes its data processing challenging. To overcome the noise...

Data-Driven Support Vector Machine to Predict Thin-Walled Tube Energy Absorbers Behavior

To design a more efficient energy absorber, it is critical to evaluate how changing the design parameters affects its performance, and also determine each one’s order of significance. In this paper, using a new approach, the behavior and response of straight, double-tapered, and triple-tapered thin-walled tubes with rectangular cross sections...