Environment Analysis for FCC SOx Reduction
Chemicals & Petrochemicals
Oil & Gas
Power Generation
Use Case Activity
Asset Optimization
Data Analysis
Predictive Analytics
Use Case Business Improvement


In the process of selecting a SOx Reduction Additive, refinery engineers must be able to easily compare the effect of several different additives on environmental performance. They must be able to develop a model to understand how different additives and operating parameters will affect SOemissions. With the right additive and an accurate environmental model, refiners can incorporate environmental planning and compliance into operational plans and targets, allowing for the optimization of both environmental performance and operating costs. Without the proper analytics support however, development of an accurate model can be extremely time-consuming.


Seeq’s Value Search tool offers a method to easily analyze different operating periods for comparative analysis. It is also simple to compare the environmental performance with different operating parameters. For example, SOemissions during operation with and without a SOx additive can quickly be identified and compared. In addition, with Seeq’s Prediction tool, engineers can easily develop an environmental model of the system to understand the relative impact of process conditions on SOemissions. 


Seeq allows for the assessment of overall environmental performance and enables users to correlate that performance to their process parameters. With this model, engineers can identify continuous improvement projects to consistently improve environmental compliance. In addition, if analyzers are out-of-service or in calibration, these models can accurately estimate emissions from the plant. It helps operators to avoid high environmental emissions and violation of operating permits, reduces the risk of fines for permit violations, and lowers the costs of emission control chemicals. Seeq’s predictive analytics enable the incorporation of environmental compliance into production targets, allowing for co-optimization of environmental performance and additive costs.


Data Sources

  • Process Data Historian: OSIsoft PI, PHD, others  

Development of a predictive analytical model before Seeq required engineers to manually combine data from multiple sources into a spreadsheet, spending hours or even days formatting data, filtering it, and removing anything non-relevant.


Data Cleansing

Seeq users can easily find and remove all non-relevant data, like data from unit and equipment shutdowns, which speeds up the data analysis time and generates a significantly more accurate model. 

Calculations and Capsules

Seeq users can use the Value Search tool to find operational periods that they would like to compare, and then they can use Seeq Calendar Time and Capsule Time to evaluate SOemissions with and without SOx reduction additives. Finally, they are able to build a model using Seeq’s Prediction tool that enables them to understand the relative impacts of operating parameters on the SOemissions, allowing them to make improvements to the overall process.  

Summarizing Results

Seeq users are able to calculate and visualize the effects of using different levels of SOx reduction additives. This allows for the optimization of additive usage and better management of environmental impact and plant operations. The XY Scatter Plot allows for fast visualization of the prediction model for SOemissions with the actual measured stack values. Finally, the steps to develop environmental models can be documented with Seeq’s Journal, allowing future engineers to understand the model development process and make improvements if necessary.