TY  - SER
TI  - Data-Driven Approach Detects, Classifies Screenout in Horizontal Wells
PY  - 2022///
CY  - 
PB  - 
N2  - Multistage hydraulic fracturing has gained global popularity as more tight geologic formations are developed economically for hydrocarbon resources. However, screenout is a major issue caused by the blockage of proppant inside the fractures. The complete paper presents a screenout-classification system based on Gaussian hidden Markov models (GHMMs) trained on simulated data that predicts screenouts and provides early warning by learning prescreenout patterns in surface-pressure signals. The methodology is a useful tool for early screenout detection and shows the promise of other fracturing time-series data analysis
ER  -