top of page

The right dose of chemicals to purify water, according to its temperature and quality

Industry: Renewable energy
Site: Seawater RO plant
Use Case: Silt Density Index (SDI) Value Prediction
Region: Arabia Saudi - Middle East
Year: 2020



Coagulation and flocculation processes in seawater reverse osmosis (SWRO) pre-treatment operations involves removal of colloidal and suspended particles from raw seawater through the addition of a determined amount of chemical coagulants



The primary issue with coagulation process is the inability to control the chemical dosages at the optimum level due to periodic variations in seawater temperature and quality. When coagulation is ineffective, the plant fails to meet water quality standards, chemicals are wasted and downstream filtration operation becomes inefficient due to unsettled flocs formation. This increases the fouling potential of membranes and they require frequent chemical cleaning which increases operational costs and increases plant downtime.


The goal is to leverage new technologies to create efficiencies:

  1. IoT (Internet of Things) from which historical measurements are obtained from sensors located in the plant

  2. Machine Learning (ML) to predict the current and future value of the SDI



The Silt Density Index (SDI) is a parameter that allows to identify the fouling potential of the water, therefore it acts as an indicator of the efficiency of the coagulation and flocculation processes. It is important to frequently know the value of SDI of raw seawater to be able to determine the optimal dose of coagulant and to obtain the highest quality water. Hence, there is a need to use prediction models to determine optimum coagulant doses.

bottom of page