Optimizing in silico sour gas processing for offshore deepwater gas technology applications in the Eastern Mediterranean Region

Growing global demand for natural gas (NG), together with the depletion of easily accessible hydrocarbon reserves, has pushed the industry toward technically challenging deepwater targets. Where these contain sour components, offshore sour gas management may constrain development flexibility and limit viable development options. A sour gas field is defined as a gas containing hydrogen sulfide (H2S) levels above 4 parts per million of volume (ppmv), while a gas that includes significant concentrations of H2S and/or CO2 is referred to as acid gas and presents considerable challenges for extraction and processing. The process of removing H2S, termed NG sweetening, is critical due to its toxicity, associated health risks, and strict environmental regulations governing both offshore and onshore processing. Offshore deepwater processing faces unique challenges compared to onshore operations, including space constraints, stringent health, safety, and environmental (HSE) requirements, offshore operating conditions, reservoir location and hydrocarbon characteristics, and development plans requiring high natural gas flow rates.

This study contains a practical option for sour gas management based on natural gas desulfurization, simulated using Aspen Plus to evaluate the feasibility of an integrated process lineup for offshore application. The proposed configuration consists of an amine unit, a thermal oxidizer, a seawater scrubber column, and an aeration tank. The proposed line-up was optimized under a natural gas flow rate range of 200-600 MMscfd and an H2S concentration range of 50-300 ppmv. A sensitivity analysis, performed using a tornado graph, identified key operational parameters that affect emissions, including seawater temperature, gas flow rate, seawater flow rate, and H2S concentration.

COMSOL Multiphysics software was used to develop a comprehensive numerical model for efluent dispersion generated by the processing unit upon discharge to the marine environment. The numerical framework enabled the assessment of hydrodynamic transport, dilution behaviour, concentration distribution and pH evolution, providing valuable insight into the dispersion of the efluent and its compliance with regulatory pH discharge limits. For the efluent dispersion modeling, the limited availability of a fully parametrized and validated MATLAB Gaussian plume model led to the adaption and full parametrization of a Gaussian Plume formulation using CFD dispersion model.