The Petroleum industry is divided into three major operations: upstream, midstream and downstream. There are many definitions for these operations but I believe the ones below are generally accepted.
This whitepaper describes the application of performance forecasting tools, Maros and Taro, to logistics operations. Enjoy your read!
The Upstream operation, also known as the Exploration and Production (E&P) sector, covers the activities from the drilling of oil and gas well to separation processes of gas and crude oil until the export operation. Midstream operations typically involve transporting the oil from the platform to the refining complex. The Downstream operation is a term commonly used to refer to the refining of crude oil, the selling and distribution of end products (including natural gas).
The midstream represents a crucial stage to ensure the continuity of production in the whole supply chain. For instance, on the upstream operation, there is a need to supply a certain amount of the oil and gas to the processing units or onshore storage terminals – a failure on this stage of operation will impact directly on the operation downstream. At the downstream operation, the transportation of products is critical because the product is frequently delivered directly to the end user.
The always increasing demand for shorter and reliable delivery times of oil crude transportation plays a key role on the world-wide chain of supply. Despite the recession in the United States in 2010, the logistics operations costs reached $1.2 trillion, an increase of $114 billion from 2009. The number is even more incredible when the contribution on the nation’s gross domestic product (GDP) is compared. The Logistics participation on the U.S. economy represents 8.3 per cent of the nation’s gross domestic product (GDP) in 2010, compared with 7.8 per cent in recession-wracked 2009.
Therefore, logistics operations play a crucial role in any company’s operation and are a critical contributor to the competitiveness of that company. The demand for products can only be satisfied through the proper and cost-effective delivery of goods and services. These operations represent a big share of the market and the expenditures on these operations are in the order of trillions of dollars annually.
Modelling the transportation scenario normally involves the upstream, midstream and downstream operations. Taking for example, the downstream operation with refining and petrochemical facilities where the production efficiency is a complex interaction between reliability, blending and yield rules, flow routing (including recycle) where intermediate storage options are not easy and could be very time-consuming. At the advent of computational models, an opportunity of dealing with such a complex scenario was achieved.
Typically, logistics operations account for:
- Customer Contracts: This represents the customers’ actual need of Product. In this case, Oil and Gas. Usually, suppliers have several contracts with different customers, for Products with different specification. Managing all this contracts is one of the most difficult tasks in a logistic assessment.
- Buffer Level Management: The objective of Buffer Level Management is to align and maintain the lowest quantities possible that will meet the contracts agreed with the Customers.
- Supply: is the process of building inventory to the targets established in Buffer Level Management planning. Make sure the levels on tanks are in agreement to what need to exported
- Transportation: physically links the sources of supply chosen in sourcing with the customers. This actually involves many different resources that must be aligned to achieve the best efficiency
- Storage: in an ideal scenario where the activities above are well implemented, the storage activity may be outsourced. However, failure in a critical equipment of a platform might shut-down the production for days stopping the whole process. Storage tanks increases the availability of a certain product when it is demanded or, in the case where the transfer is delayed, the product can be held without the need to stop the whole system. It also gives the operator more time to adjust the product within a certain specification or, more related to the purpose of this article, to prepare for expected or unexpected outages.
DNV has developed an extensive expertise on the transport logistics modelling. If you want to have more information about RAM analysis and bulk transport logistics modelling, please get in touch with Guy Cozon, heading the Performance Forecasting department in London.
Big thanks to Marcela Palmer for contributing to the text.
Author: Victor Borges