In the production process of natural gas one of the major problems is
the formation of hydrate crystals creating hydrate plugs in the pipeline.
The hydrate plugs increase production losses, because the removal of the
plugs is a high cost, time consuming procedure. One of the solutions used to
prevent hydrate formation is the injection of modern compositions to the gas
flow, helping to dehydrate the gas. Dehydratation obviously means that the
size of hydrate crystals does not increase. The substances used in low
concentrations, have to be locally injected at the gas well sites. Inhibitor
dosing depends on the amount of gas hydrate present. In the article two
Artificial Neural Network (ANN)-based predictive detection solutions are
presented. In both cases the goal is to predict hydrate formation. Data used
come from two solutions. In the first one measurements were performed by a
self-developed and -produced equipment in this case, differential pressure
was used as input. In the second solution data are used from the measurement
system of a motorised chemical-injector device, in this case pressure,
temperature, quantity and type of inhibitor were used as inputs. Both
systems are presented in the article.