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Firmanjaya, I Made Bayu Sukma
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Environmental Science

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Investment Analysis Upgrading Capacity of Produced Water Treatment System (PWTS) at a Gas Processing Facility Firmanjaya, I Made Bayu Sukma; Gunarta, I Ketut
Journal Research of Social Science, Economics, and Management Vol. 5 No. 5 (2025): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i5.1237

Abstract

The oil and gas industry remains a strategic pillar for national energy security, yet it faces significant operational challenges as production fields mature. A critical issue is the exponential increase in produced water, which often surpasses the design limits of existing Produced Water Treatment Systems (PWTS). This research evaluates the investment feasibility of upgrading the PWTS capacity at a major gas processing facility where current water production has reached 3,110 BWPD, significantly exceeding the 2,000 BWPD design capacity. To address this, a hybrid framework was developed by integrating Technical and Economic Risk Assessments. Technical risks were quantified using Failure Mode and Effect Analysis (FMEA), involving 28 failure modes across seven primary equipment units. To mitigate the subjectivity of expert judgment, a Monte Carlo Simulation with 10,000 iterations was implemented, followed by a Risk Matrix to translate technical failures into quantifiable "Expected Costs." The Economic Risk Assessment was conducted via Cost-Benefit Analysis (CBA), incorporating these expected costs as avoided-loss benefits. The results identify an optimal upgrade capacity of 6,000 BWPD, which yields a Net Present Value (NPV) of USD 84.94 million, an Internal Rate of Return (IRR) of 80.88%, a Benefit-Cost Ratio (BCR) of 16.59, and a Payback Period (PP) of 24 months. Furthermore, sensitivity analysis underscores the project’s robustness, demonstrating resilience against operational expenditure (OPEX) hikes of up to 50%, while establishing a critical production decline tolerance of -1.5% per day. This integrated methodology provides a robust, data-driven decision-making tool for managing high-risk energy infrastructure investments.
Co-Authors I Ketut Gunarta