Case studies

Transocean is a Swiss offshore drilling company that provides rig-based well construction services worldwide. The company is one of the largest contractors in its sector and has offices in 20 countries. It operates a fleet of versatile, mobile, offshore units comprised of midwater, deep water, ultra-deep water, and harsh environment floaters. The company decided to build a digital twin of its well construction processes to enable prediction and advanced planning capabilities with the aim of optimizing operations across its fleet.

YPF is the largest oil and gas company in Argentina. YPF was aiming to reduce its costs associated with oil wells’ maintenance downtime and equipment breakdown. The analysis showed that the root cause of inefficiencies was the lack of a robust maintenance scheduling process. YPF approached Simcastia to develop a scheduling tool to streamline asset management at all YPF facilities.

Canada is the third largest country to have oil reserves. However, most of the oil is in oil sand – the mixture of sand, oil, and water – which has to be heated up with steam to emit the oil. It is costly to maintain such a distribution system, and outages may lead to disruptions in steam injection and oil production. Stream Systems company applied AnyLogic simulation modeling to optimize expenditures and capture production lags.

Transocean is one of the largest offshore drilling companies that provides rig-based well construction services worldwide. Offshore oil and gas well construction is a complex process that takes a considerable amount of time. It demands certain sequences of both manual and semi-automated operations carried out in unison, as safely and efficiently as possible. Different kinds of equipment are usually created and operated independently. However, at the rig, all technical units are integrated. Any kind of delay in machinery increases the critical time path, which reduces the efficiency of the...

One of the largest oil and gas pipeline operators in North America was delivering oil to a client that was not always able to accept the incoming batches. The operator was challenged to quantify the system impacts of deferred downstream deliveries. They also needed to determine whether the existing tankage at upstream oil terminals would be adequate to store the deferred batches.

One of the largest oil and gas companies faced financial inefficiency from depleting deposits: approximately 20% of the deposits yielded little if any profit. In order to maintain a strong performance in a context of high uncertainty, the company had to make operational decisions about whether they should shut down or retain their marginally profitable wells, and whether it made sense to repair breakages.

The Novoportovskoye oil and gas condensate field is located in the Yamal peninsula and owned by Gazprom Neft, the fourth largest oil producer in Russia. Oil from the field is transferred via 100km pipeline to the sea terminal at Cape Kamenny, where it is loaded into arctic cargo tanks for further transportation. The main issues in planning tanker transportation in an arctic region are the harsh ice environment and difficult sea conditions.

The Prirazlomnaya oil-producing platform owned by Gazprom Neft company is currently the first Russian hydrocarbon production project on the Arctic shelf. Since it was designed for the Arctic region, the platform can be used in extreme weather conditions and withstand maximum ice loads, which makes it a unique and technically complex project. The first loading of oil from the platform to an arctic tanker was carried out in April 2014, while by 2021 the platform operator is planning to increase the rate of oil production up to five million tons. However, gained experience revealed that a...

Fracking is the process of cracking rocks using a combination of sand and water at high pressure to release trapped gas. Tecpetrol needed to optimize sand transportation for their fracking operations from various warehouses. They could do this best using a simulation model with a parameter variation experiment and then a simulation experiment. In the first 8 months of implementing this model, Eurystic saved an estimated $500,000.