Maros and Taro head deeper into operational stage
As part of our vision to move Maros and Taro more into supporting decision-making during the operational stage, we have made a number of great additions to the applications.
Optimum balance and cost optimization
Finding the optimum balance between production, operational expenditure (Opex) and capital expenditure (Capex) is fundamental for the oil and gas industry now that operating revenue margins are as tight as ever.
Our current flow modelling is extremely powerful and fast but an alternative method has been added to Maros. This new approach allows for optimization methods to be incorporated into the simulation process. This will be the foundation of our upcoming versions of Maros and Taro. The implementation in Maros is extremely flexible and allows users to define several objectives. The new flow method will be extended as we keep developing Maros and Taro.
On the same subject of cost optimization, maintenance strategy plays an essential role. Analysts are trying to identify repair tasks that are critical to the system from a safety and productivity perspective. This means allocating the resources to prioritized maintenance tasks plus reducing unnecessary cost associated with idle maintenance resources. To support the decision-making process in this area, maintenance strategies play an essential role. Maros and Taro has a new centralized maintenance modelling area which will help users to take advantage of the powerful maintenance strategy modelling capabilities available in the applications.
Extended storage tanks modelling empowering users to replicate real-life scenarios
Modelling the correct operations in storage tanks is extremely important when calculating the performance of a system – storage tanks have three main functions: storage of feedstock to supply a process; storage of product from a process prior to export; and intermediate storage between processes. Maros now introduces the concept of Rate Operations – previously available in our refinery design tool Taro. This new feature allows users to control the rate of the different units/nodes in the network based in level of a storage tank. This feature ensures that the right operation of storage tanks is modelled, empowering users to replicate real-life scenarios of bottlenecks and managing the inventory.
Advanced yield modelling accounting for different types of crude oil
Refineries are processing different types of crude oil that yield a different mix of products. Crude oil types are typically differentiated by their density (measured as API gravity) and their sulphur content. Crude oil with a low API gravity is considered a heavy crude oil and a larger yield of lower-valued products. Therefore, the lower the API of a crude oil, the lower the value it has to a refiner, as it will either require more processing. Thus, being able to define transient yields, based on different delivery of different crude oil types, is an important parameter when simulating performance. Taro now includes the ability to define transient yields – this is a feature that has been moved across from Maros.
Aligning with all the above, when performing a RAM analysis, analysts will fundamentally run multiple-case with the objective of improving the base case models when comparing potential sensitivities. This release includes a Comparison View, which gives the ability to easily compare the main key performance indicators in different models. This should support your decision-making process by directly assessing what performance indicators would yield higher return on investment.
What’s Next?
Maros and Taro offer great new and unrivalled features. We’re always looking for new ways to improve our products, and some of our best ideas come from our users. If you have ideas for new features, important issues we need to address or new features you’d like to see, please let us know! If you have any questions, comments or feedback, please feel free to contact us.
