Strategic Engineering

Motivation

Traditional oil-field design fixes capacity on static assumptions about reservoir size and oil prices, often leading to costly mismatches between installed capacity and actual yield. This research was motivated by repeated post-project losses in the industry, seeking a systematic way to integrate uncertainty and adaptability directly into design decisions rather than treating them afterward through sensitivity testing.

Methodologies

• Four-Step Integrated Framework: Develop base-case model → simulate outcomes → identify flexible options → select most valuable.
• Simulation-Based Real Options Analysis: Quantified the Value of Flexibility (VOF) using probabilistic oil-in-place data.
• Monte Carlo & Decision Trees: Modeled 200+ production scenarios for Sample and Rother fields.
• Value-at-Risk-and-Gain (VARG): Graphical analysis of risk/gain distributions (p. 9).
• Scenario & Sensitivity Analysis: Evaluated oil-price volatility ( ± US $5 per barrel ) and CAPEX trade-offs.

Insights

• Economic Impact: Adding two extra wells increased ENPV from $22.9 billion to $24.6 billion.
• Cost-Benefit: Flexibility worth ≈ $1.7 billion at a cost of $34 million (≈ 50× return).
• Risk Reduction: Downside NPV risk cut by ≈ 40 %.
• Decision Clarity: VARG curves revealed trade-offs between gain and exposure.
• Strategic Shift: Flexibility offers a new design paradigm for major projects, integrating economic and technical resilience from the outset.

Training

Relevant lectures and skills:

• Real Options Analysis
• Monte Carlo Simulation
• Decision Tree Modelling
• Scenario Analysis
• Sensitivity Analysis
• Value-at-Risk (VARG)

Gallery