This category covers EnerTherm Engineering’s advanced process modelling services tailored for the oil and gas sector, spanning offshore platforms, onshore facilities, and refineries. Content should focus on the application of physics-based, data-driven, and hybrid modelling to achieve production uplifts, emission reductions, and asset integrity management. Key topics include reservoir flow modelling for production forecasting, pipeline thermal simulation for flow assurance (wax/hydrate management), flare system optimisation, and process unit optimisation (crude distillation, catalytic cracking, hydroprocessing). Articles should reflect the firm’s 6-step methodology: data preparation (SCADA/IoT/historian integration), model development (CFD, thermodynamic state equations, machine learning), calibration/validation (RMSE/MAPE metrics), simulation optimisation (Pareto analysis), implementation (DCS/PLC/OPC-UA integration), and lifecycle maintenance (adaptive learning/drift detection). Technical content should reference the use of industry-standard tools like OLGA, Petrel/Eclipse, and Aspen HYSYS/Plus, alongside custom Python and MATLAB frameworks. Authors should highlight deliverables such as digital twins, integrity assessments (corrosion/erosion), and production optimisation strategies, consistently linking technical processes to proven outcomes like the 12% production uplift and 20% flaring reduction.