Schlumberger Technology Corporation

Jonathan Wun Shiung Chong

Nam H Nguyen

Sharath Chandra Mahavadi

Pengyu Yuan

Salim Taoutaou

Simon Ivar Andersen

Alexander Nebesnyy

Carlos Penedo Rocha

A liquid additive mixing apparatus is provided that has a plurality of chambers containing additives, as well as a system for mixing the additives. One or more additives are mixed with water to form a mixing fluid. The mixing fluid is placed in a first tank that is fluidly connected to a cement mixing unit. A cementing operation is executed during which the mixing fluid from the first tank is mixed with a cement to form a slurry. A capillary electrophoresis (CE) instrument is employed to monitor at least one additive parameter and detect deviations from a predetermined tolerance for the at least one additive parameter.

Indirect diagnosis of multiple fluid mixer unit performance

A method for detecting events includes receiving measurements from a plurality of sensors, and executing a machine learning model trained to identify events based on the measurements. The machine learning model identifies the events based on the measurements. The method also includes determining based on the measurements and the identified events that training applied to the machine learning model is to be modified. A modified training data set is generated based on the measurements and an initial training data set used to train the machine learning model to identify the events. The modified training data set is applied to retrain the machine learning model.

System and method for managing wellsite event detection

Growing community of inventors

Kuala Lumpur, Malaysia

Jonathan Wun Shiung Chong