- Industry: Oil/Gas/Energy
- Product(s): @RISK
- Application: Refinery Optimization
Fernando Montemayor, Global Analysis Vice President of the consulting firm Throughput Professionals, and his team worked with the largest oil refinery company in Colombia (producing 250,000 barrels per day) to identify opportunities for optimizing their refining processes. Through analyzing the refinery’s processes with @RISK, Montemayor was able to identify the top key variables that drove efficiency, increasing yield by 1.5% and resulting in a savings of $40M.
The customer was very happy with results. Now they are working on optimizing the rest of the refinery areas.Fernando Montemayor, Global Analysis Vice President, Throughput Professionals
In the oil production process, the Colombian oil refinery managed over 5,000 variables by production unit, many of which were controlled automatically through computer systems—and most of which were operating at "sub-optimal" settings. They called on Throughput Professionals to help them to determine if greater yields could be achieved.
Using @RISK to Identify Key Inputs and Processes
Montemayor and his team first determined that to improve efficiency, the refinery needed to narrow down the list of variables that are considered key drivers of the refinery process. Montemayor examined inputs such as pressures, flows, temperatures, while also consulting with engineers and experts at the refinery, to identify which processes were truly the most important in efficiency. To do this, they identified potential variables through a SIPOC diagram (Suppliers, Inputs, Process, Outputs & Customers). After narrowing the list down to 50-100 variables, Montemayor ran multiple regressions and analysis of variance in @RISK, using historical data to identify the variables that most significantly drive those yields.
Using @RISK's Monte Carlo Simulation to Identify Optimum Setups
@RISK modeling further reduced the number of variables down to only five per production Unit. With these now identified, the team simulated the refinery process and identified the optimum setup for each variable, again with help from @RISK. To implement these changes on the process, the team used Statistical Process Control to maintain the variables in control at the optimum setup and at short intervals. Additionally, Montemayor made sure to incorporate all necessary safety parameters and limits on all the variables. Elements of the Management Operating System were used to ensure corrective actions were being taken on deviations, and to make sure they were driving results.
Fuel Production Yields Increased by 1.5%, for Savings of US $40M
By improving the setup and control system of the key driving variables that drives process efficiency, the oil refinery was able to increase the yield of the topping process—the process by which petrochemical feedstocks are prepared for fuel production--by 1.5%, resulting in benefits of US$40 M. “The customer was very happy with results,” says Montemayor. “Now they are working on optimizing the rest of the refinery areas.”