Environment & Safety Gas Processing/LNG Maintenance & Reliability Petrochemicals Process Control Process Optimization Project Management Refining

Instrumentation

ProSep to deliver its Multiphase Adjustable Xtreme test units to Polish refiner

For the contract, ProSep will deliver one of its Multiphase Adjustable Xtreme (MAX+) Mixer's test units to a refinery in central Poland. 

BGEN signs five-year contract with INEOS O&P UK

BGEN has announced that it has signed a five-year contract with the petrochemical manufacturer INEOS O&P UK. BGEN will provide a range of services to help INEOS optimize plant efficiency at its site in Grangemouth, Stirlingshire.

The Gulf Energy Information Excellence Awards 2024 winners honored at live Houston gala

The 2024 Gulf Energy Information Excellence Awards was held on Wednesday evening at the Post Oak Hotel in Houston, Texas (U.S.). The black-tie gala recognized the energy industry’s leading innovations and thought leaders.

Aspen Technology launches microgrid management system to address power reliability and meet net-zero goals

Aspen Technology introduced the AspenTech Microgrid Management System™, a solution for customers with heavy electrical power requirements in refining, chemicals, mining and other asset-intensive industries that manage their own on-site conventional and renewable power generation in orchestration with active load management and energy storage.

Digital Feature: Refiner improves operational technology risk measurement and management: A Case Study on addressing the cyber risks in the oil and gas industry

This case study details how a U.S.-based Fortune 50 petroleum refiner used proprietary technology to improve operational technology (OT) cybersecurity. By automating asset inventory and vulnerability assessments, the company reduced manual processes, enhanced visibility into cyber risks and improved safety, ultimately saving millions of dollars in program costs.

Truly effective reliability requires predictive maintenance

Emerson: Kleinubing, R.

To navigate this new digital world, organizations must find ways to bring in new technologies to support the limited personnel they have, but without increasing the complexity of those people’s jobs or overwhelming them with raw data they are not trained to use. The solution is to implement a predictive maintenance technology plan founded on a boundless automation vision of seamlessly moving contextualized data wherever it is needed.

Gulf Energy Information and Hydrocarbon Processing announce strategic partnership with Chempute Software

Gulf Energy Information, a leading B2B media and market intelligence provider in the international energy industry, and its flagship publication, Hydrocarbon Processing, are pleased to announce a strategic partnership with Chempute, a renowned provider of engineering software solutions.

Thermal decomposition of particulate mercury sulfides in petroleum—Part 1

Chevron Energy Technology Co.: Das, T.  |  Hatakeyama, E.  |  Hoelen, T. P.
Contributing Author: O'Rear, D.

Traces of particulate mercury sulfide (HgS) in stabilized crude oils transform to elemental mercury below 400°C in refinery distillation units. The authors evaluated this transformation and measured reaction rates and activation energies in crude oil and Hg-spiked mineral oil, using glass vessels at atmospheric pressure and a microunit at 1,000 psig.

Deliver sustainable benefits through site-wide process digital twins

Saudi Aramco: Bazuher, E. A.
KBC, a Yokogawa Company: Chellani, J.

Refiners have used offline process models for decades. The next generation of solutions is anticipated to operate automatically, integrate with legacy systems and provide transparency site-wide.  

Prompt engineering: Extracting operational excellence knowledge from AI—Part 1

CEPSA: Larraz, R.

Prompt engineering is an emerging discipline at the intersection of AI and process engineering and will undoubtedly contribute to the hydrocarbon and green molecules processing industries. Parts 1 and 2 (October 2024) of this article explore and provide a glimpse of how this technique can help process engineers and operators to manage the power of advanced AI models to optimize processes, contribute to solve complex problems, and improve operational efficiency in refineries and petrochemical plants.