Formation damage poses a widespread challenge in the oil and gas industry, leading to
diminished permeability, flow rates, and overall well productivity. Acidizing is a commonly …

With the increased directional drilling activities in the oil and gas industry, combined with the
digital revolution amongst all industry aspects, the need became high to optimize all …

With the rapid progress of big data and artificial intelligence, machine learning technologies
such as learning and adaptive control have emerged as a research focus in petroleum …

This paper compares the performance of two data-driven methods, Signal-Matching
Predictor (SMP) and Long Short-Term Memory (LSTM), for predicting drilling strength (E s) …

Accurate well productivity prediction plays a significant role in formulating reservoir
development plans. However, traditional well productivity prediction methods lack accuracy …

This study addresses the integration of machine learning (ML) with supervisory control and
data acquisition (SCADA) systems to enhance predictive maintenance and operational …

Multistage hydraulic fracturing is essential to unlock the potential of unconventional
reservoirs and produce them economically. Data acquisition technologies, such as …

This study introduces an innovative framework for harnessing Machine Learning (ML) within
production engineering. The objective is to offer engineers a comprehensive framework for …

Forecasting the estimated ultimate recovery (EUR) for extremely tight gas sites with long-
term transient behaviors is not an easy task. Because older, more established methods used …

The escalating concerns regarding urban air pollution and its detrimental effects on public
health necessitate advanced real-time air quality monitoring solutions. This paper introduces …