New tools predict monoethylene glycol injection rate for natural gas hydrate inhibition

• Least squares support vector machine algorithm predicts monoethylene glycol injection rate.
• The new technique determines both gas hydrate formation temperature depression and hydrate formation pressure.
• The model is implemented on the basis of 172 data points for MEG flow rate.
• An excellent agreement is attained between predictions and reported data.

In the oil and gas production operations, hydrates deposition leads to serious problems including over pressuring, irreparable damages to production equipment, pipeline blockage, and finally resulting in production facilities shut down and even human life and the environment dangers. Hence, it is of great importance to forecast the hydrate formation conditions in order to overcome problems associated with deposition of hydrate. In this article, an effective, mathematical and predictive strategy, known as the least squares support vector machine, is employed to determine the hydrate forming conditions of sweet natural gases as well as the monoethylene glycol (MEG) flow-rate and desired depression of the gas hydrate formation temperature (DHFT). The outcome of this study reveals that the developed technique offers high predictive potential in precise estimation of this important characteristic in the gas industry. Beside the accuracy and reliability, the proposed model includes lower number of coefficients in contrast with conventional correlations/methods, implying an interesting feature to be added to the modeling simulation software packages in gas engineering.