📖 ABSTRACT/OVERVIEW
Natural gas liquids (NGL) recovery efficiency is a critical performance indicator for gas processing operations, directly determining the commercial yield of higher-value propane, butane, and condensate products from processed gas streams. This study empirically assesses NGL recovery efficiency at onshore gas processing plants in Rivers State, examining four facilities processing gas from the Eastern Niger Delta production area. The research employs a quantitative engineering performance assessment methodology, constructing a plant performance database from three years of process data including feed gas compositions, operating temperatures and pressures, refrigeration cycle performance parameters, and product stream analyses. Thermodynamic simulation models in Aspen HYSYS are calibrated against actual plant data to establish theoretical maximum recovery benchmarks for each plant's specific feed gas composition and process configuration. The study investigates the process, operational, and mechanical factors responsible for actual recovery efficiency deviating from theoretical potential, including refrigeration system capacity constraints, lean oil absorption inefficiencies, and turbo-expander performance degradation. A regression analysis is conducted to quantify the contribution of individual process variables to overall NGL recovery efficiency. Findings demonstrate that actual C3+ NGL recovery rates average 78 percent of theoretical potential, with refrigeration system under-performance during hot season ambient conditions (April to June) accounting for the largest efficiency penalty. The study fills a gap in published performance benchmarking data for onshore NGL plants in tropical Nigerian conditions. Recommendations include installation of auxiliary refrigeration capacity for hot season compensation and adoption of JT valve and turbo-expander hybrid configurations for improved recovery flexibility. Keywords: NGL recovery, gas processing, efficiency, Rivers State, thermodynamic simulation.
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