Processing, April 2020

OIL GAS Reduce emissions by improving sulfur recovery unit performance with self service industrial analytics New technology makes it easy for process engineers to optimize processes by themselves By Julian Pereira TrendMiner il and gas companies are continuously striving to optimize overall equipment effectiveness performance and profitability within a highly volatile and regulated O environment Several of those regulations are coming from an increasing industry effort toward the reduction of emissions that affect both health and the environment And these initiatives are growing from both industry and governmental groups For example oil and gas companies that operate in the UK Continental Shelf commonly known in the North Sea are stepping up to reduce carbon emissions to net zero by 2050 in the UK Another example is the decarbonization efforts led by the European Commission which aim to initiate the transition toward a climate neutral economy by 2050 This will require the active involvement and investment of different industry technology and governmental sectors for mid and long term solutions To start getting results today it is key to take advantage of underutilized data in combination with process expertise that is already in place aiming to improve process workflows to have a better and more efficient emissions control and reduction There is an increasing need to exploit the large set of data being generated from sensors instruments and assets Traditional methods of big data solutions require complex IT projects and data scientists to build and maintain models Aside from being costly and time consuming this way of working can also create resource bottlenecks in the organization and underutilize the process and asset experts Turning big industrial data into actionable information may seem like a huge task but self service industrial analytics makes it easy for process engineers to optimize the processes by themselves Results are delivered quickly and directly into the hands of the process experts who can really provide meaningful interpretations to the data allowing them to uncover insights at all levels of production improving day today decision making Case in point Process experts improve SRU performance This article is focused on a unit that is present in all refineries and gas plants Sulfur recovery units SRU are becoming more and more important not only due to the rising demand for sulfur in various applications but mainly due to the increasing concern and number of regulations around emissions control and climate change SRUs typically include burners catalytic stages and most of the time a Superclaus unit and a tail gas incinerator The Claus process partially burns the Hydrogen Sulfide H2S It then converts catalytically the H2S and the Carbon Dioxide CO2 combustion products to elemental sulfur and water vapor One of the most important process KPIs is the sulfur recovery Low process efficiency in this case lower than 992 results in lower sulfur recovery and unprocessed and unwanted H2S and sulfur dioxide SO2 emissions The next paragraphs will explain how process engineers can monitor and increase the SRU operational performance by using self service industrial analytics without the need of complex Excel sheets or long data modeling projects Analyzing the data A prerequisite for data analytics is to have the data readily available through a live connection to the historian to automatically visualize the tags in userfriendly trend views The next step is to start the data exploration and searching for specific process events in the SRU throughout multiple years of data With the use of modern self service industrial analytics software the process expert can focus on discovering the periods of low sulfur recovery over the last two years The process expert will search for and visualize the low recovery periods focusing on the H2S content behavior The sulfur that is recovered has a high dependency on the H2S content that is measured before the Superclaus unit whenever the H2S online analyzer has sudden increases the sulfur recovery rate will decrease In this use case the search showed 15 periods of low recovery out of which nine presented a similar increase pattern of the H2S content The process expert decided to set up a monitor to follow the pattern of sudden increases of the H2S content independent of the absolute value Through patented pattern recognition technology the process expert identified particular behaviors for periods longer than 20 minutes By saving the search the H2S content behavior can be monitored in real time Each time a user configurable percentage of similarity is matched an alert via email is sent to the operator to take appropriate measures to control the process Operational context accelerates root cause analysis The monitor created by the process expert running in the background can be used to capture specific low recovery events which can be combined with other operational contextual data from other systems This can be shown in a Gantt chart view Figure 2 that 22 Processing APRIL 2020 Figure 1 Schematic flow diagram of a straight through 3 reactor converter Claus sulfur recovery unit All images ourtesy of TrendMiner