Gas 2023 Issue

Editor Rene Gonzalez editor@petroleumtechnology.com tel: +1 713 449 5817 Managing Editor Rachel Storry rachel.storry@emap.com Graphics Peter Harper US Operations Mark Peters mark.peters@emap.com tel: +1 832 656 5341 Business Development Director Paul Mason sales@petroleumtechnology.com tel: +44 7841 699431 Managing Director Richard Watts richard.watts@emap.com Circulation Fran Havard circulation@petroleumtechnology.com ptq PETROLEUM TECHNOLOGY QUARTERLY

Using model- based solutions to increase LNG

T he market size of industrial gases is expected to surpass $147 billion by 2028. Along with this increase in the global markets for gas is the level of gas processing complexity needed by 2035, which seems to vary regionally. Much of the technical developments are emerging with liquefaction-related processes, which are discussed in more detail in this annual issue of PTQ Gas 2023 . Overall, complexity depends on several factors, such as the growth in demand for natural gas, availability of gas reserves, and technological advancements in gas processing. For at least the next 50 years, natural gas-derived products will likely be a major component of the energy mix on the road to decarbonised energy products, such as renewable fuels and solar power. This growth in demand may require more complex gas processing facilities to ensure that the gas is purified to the required quality standards in the rapid push to net-zero emissions-based products. Another factor that may drive the complexity of gas processing is the availability of gas reserves. As easily accessible reserves are depleted, companies may need to extract gas from more challenging reservoirs, such as deepwater or shale gas formations. These types of reservoirs require more advanced processing technologies to extract and refine the gas. For example, advancements in carbon capture and stor - age (CCS) technologies may require additional processing steps to capture and sequester carbon dioxide (CO 2 ) from natural gas. With more gas production coming from relatively small-scale fields, low-capital, temporary in-the-field gas processing facilities have become increasingly popular in recent years to maximise the moneti- sation of fields of all sizes, including 98% recovery of flared or vented gas. Against this backdrop, one of the most capital-intensive components in the gas industry is the liquefaction section of liquefied natural gas (LNG) plants, used to convert natural gas into LNG for transport and storage. Increasing throughput from existing liquefaction trains is a high priority for LNG producers, as it helps improve efficiency, reduce costs, and increase profits. Model-based solutions offer a prom - ising approach for achieving additional throughput from existing liquefaction trains. Some examples include advanced process control (APC) systems using math- ematical models and algorithms to optimise process operations and increase throughput. APC improves control of key process variables, such as temperature, pressure, and flow rate, which can improve the efficiency and capacity of existing liquefaction trains. APC can also help reduce process variability, especially around turbocompressors, which can improve product quality and reduce downtime. Data analytics tools can be used to analyse large amounts of data from the lique- faction process, such as sensor readings, process parameters, and operating con- ditions. By identifying patterns and trends in the data, operators can gain insights into the performance of the liquefaction process and identify opportunities for opti- misation of the capital-intensive rotating equipment. Model predictive control (MPC), a type of advanced process control that uses mathematical models to predict the behaviour of the process under different condi- tions to optimise process operations in real-time, leads to increased throughput and improved efficiency. MPC can also help optimise energy use and other resources, which can reduce operating costs. In summary, model-based solutions offer a powerful set of tools for increasing throughput from existing liquefaction trains. Using mathematical models and data analytics to optimise process operations, operators can improve efficiency, reduce costs, and increase profits in the LNG industry.

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PTQ (Petroleum Technology Quarterly) (ISSN No: 1632-363X, USPS No: 014-781) is published quarterly plus annual Catalysis edition by EMAP and is distributed in the US by SP/Asendia, 17B South Middlesex Avenue, Monroe NJ 08831. Periodicals postage paid at New Brunswick, NJ. Postmaster: send address changes to PTQ (Petroleum Technology Quarterly), 17B South Middlesex Avenue, Monroe NJ 08831. Back numbers available from the Publisherat $30 per copy inc postage.

Rene Gonzalez

Gas 2023