Abstract:
Despite the large natural gas reserve in Nigeria and increasing global demand for Liquefied Natural
Gas (LNG), prospective investors appear hesitant in doing LNG business in Nigeria. One major
reason is that the existing LNG business cost estimation models are inadequate to incorporate
various business factors such as long life-span risky events and capital intensiveness. A Life Cycle
Costing (LCC) model was developed to accommodate these factors using System Dynamics (SD)
principles.
Ten LNG business firms operating in Nigeria and abroad were studied and seven randomly selected
stakeholders interviewed for insights on LNG business processes. Operating sectors were identified
using SD principles. Input and output sector quantities and their inter-relationships were determined
using system causal loop, while flow diagramming approach was used to characterise the LNG value
chain operations. The LNG-process equations were formulated in terms of plant availability,
production workforce capability and shipment delivery rate. These were synthesised to evolve an
SD-LNG-LCC model. The model was applied to predict a set of twenty-one year (1999-2019) values
of LNG volume shipped and revenue. These were compared to the actual values obtained from an
LNG-firm in West Africa. The firm’s LCC, Unit Production Cost (UPC), Return on Investment
(ROI), Net Present Value (NPV) and Profitability Index (PI) were also obtained. The viability of
the firm’s Greenfield-Brownfield investments and the model’s performance were further evaluated
using different scenarios of NG base-prices. Data were analysed using student t-test at α0.05.
The identified operating sectors were production, maintenance and finance. Capital and operating
expenditures; NG-LNG prices; Train-Capacity; equipment and spares; planned manpower;
maintenance-effectiveness; discount-rate, and equipment-failure probabilities were identified sector
input quantities, while LCC, production volume, revenue, return on investment, payback period,
discounted profit, equipment availability were the outputs. Plant availability, production workforce
capability and shipment delivery rate were 0.90, 2310.92 m3gas/man-hour and 6 deliveries/shipyear,
respectively. The model predicted LNG volume shipped was (13.46±0.02)×109 tonne per annum
(TPA) while the firm’s actual value was (13.62±0.02)×109 TPA. Similarly, the revenue from the
predicted and actual were (₦864.00±572.43)×109 [($5.40±3.58)×109] and (₦870.40±561.14)×109
[($5.44±3.51)×109]. These indicated that there was no significant difference between the predicted
and actual values. The firm’s LCC, UPC, ROI, NPV and PI were ₦10000.00×109 ($62.50×109),
₦662.40 ($4.14) per MMBTU, 26.01%, ₦2369.60×109 ($14.81×109) and 1.59, respectively. For
expansion alternatives, the Greenfield LCC was ₦109264.60 [$682.91] per tonneyear relative to the
Brownfield’s ₦76235.20 ($476.47) per tonneyear. In model sensitivity, 50% increase in NG baseprice yielded LCC of ₦7359.80×109 ($45.98×109) compared to ₦12640.20×109 ($79.02)×109 yield
by a 150% increase.
A liquefied natural gas life cycle costing model was developed using system dynamics principles.
The developed model is a useful instrument for determining costs and decision support for liquefied
natural gas project investments.
