A Technical Review of Chemical Engineers in Hydrocarbon Recovery Using Petrel Reservoir Engineering (Petrel RE)

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@article{1719034,
      author = {Anietie Akpan, Abiodun Awe, Akpan Uko Ben},
      title = {A Technical Review of Chemical Engineers in Hydrocarbon Recovery Using Petrel Reservoir Engineering (Petrel RE)},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {12},
      pages = {2067-2071},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719034.pdf},
      abstract = {Chemical engineers are at the forefront of hydrocarbon recovery innovation, applying enhanced oil recovery (EOR) techniques and advanced reservoir simulation tools. This technical review examines the critical role of chemical engineers in advancing hydrocarbon recovery by integrating core principles of thermodynamics, transport phenomena, and reaction kinetics into the Petrel Reservoir Engineering (Petrel RE) simulation platform. By bridging laboratory-scale data with field-scale development, chemical engineers utilize Petrel RE to optimize enhanced oil recovery (EOR) techniques—such as polymer flooding, surfactant flooding, and miscible CO2 injection—resulting in material recovery factor gains of up to 25% while simultaneously minimizing subsurface volumetric uncertainties and identifying flow assurance bottlenecks early in the exploration lifecycle. Furthermore, the paper synthesizes how this integrated, static-to-dynamic workflow supports dual-purpose CO2-EOR carbon management objectives by evaluating long-term sequestration mechanisms alongside emerging digital transformation technologies like real-time digital twins, cloud-based scalability, and machine learning models that reduce predictive error margins by 20–30%. Ultimately, the review underscores that the industry's most robust recovery and sequestration outcomes are achieved when complex subsurface fluid chemistry is coupled with unified, uncertainty-aware simulation workflows to overcome persistent operational challenges.},
      keywords = {CO2-EOR, Enhanced Oil Recovery, Machine Learning, Petrel RE, Polymer Flooding, Reservoir Simulation},
      month = {June},
      doi = {https://doi.org/10.64388/IREV9I12-1719034}
  }