Recurrent neural networks (RNN), which are able to capture temporal natures of a signal,
are becoming more common in machine learning applied to petroleum engineering …

The margin between pore pressure and fracture gradient in new offshore discoveries
continues to get narrower. This poses greater risks and higher cost of ensuring safety of …

Timely detection and classification of faults on transmission lines are crucial requirements
for maintaining a reliable power supply to consumers. Rapid fault detection demands the …

Drilling fluid is pivotal for efficient drilling. However, the gelation performance of drilling fluids
is influenced by various complex factors, and traditional methods are inefficient and costly …

Oil and gas exploration is facing an ever-increasing demand for cost-efficient drilling
operations. Improvement of the rate of penetration (ROP) of the drill bit is key in solving the …

Abstract Machine Learning adoption within drilling is often impaired by the necessity to train
the model on data collected from wells analogous in lithology and equipment used to the …

Climate change threats make it difficult to perform reliable and quick predictions on floods
forecasting. This gives rise to the need of having advanced methods, eg, computational …

In oil and gas and geothermal installations, open channels followed by sieves for removal of
drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid …

Drilling is a costly operation, especially offshore, and disturbances caused by drilling fluid
influxes (kicks or loss) pose persistent challenges and operational costs during drilling …

Open channel flow of complex fluids is found in many offshore applications and is currently
monitored using Coriolis meters (good uncertainty with an expensive device) and simple …