Conventional decoupled reservoir modeling systematically underestimates asset potential by neglecting critical
feedback mechanisms between subsurface and surface components, leading to suboptimal field development
strategies. This study presents a novel Integrated Asset Modeling (IAM) framework that dynamically couples highfidelity
reservoir simulation with surface production network constraints while explicitly incorporating an autonomous
subsea choke control mechanism to capture emergent system behaviors. Latin Hypercube Sampling (LHS) enables
computationally efficient uncertainty quantification across many operational control scenarios, maintaining statistical
robustness within practical computational constraints. Probabilistic forecasting demonstrates that intelligent choke
management alone enhances recovery factor by 2.7%, validating the economic significance of integrated optimization
over traditional sequential workflows. A subsequent global sensitivity analysis deconstructed this variance, identifying
four of the ten production wells as the dominant control levers that collectively govern over 70% of the system’s
variability. Targeted optimization of these high-leverage control parameters yields 43 MMSTB incremental recovery
beyond the 337 MMSTB deterministic baseline—a 12.8% uplift representing $2.15 billion additional value at $50/bbl.
The probabilistic IAM framework quantifies previously unrecognized value creation opportunities in complex subsea
architectures by capturing nonlinear system interactions and operational feedback loops that conventional decoupled
approaches inherently cannot resolve. This rigorously validated methodology empowers operators with decisionsupport
tools for designing adaptive automation strategies, optimizing capital allocation, and executing risk-informed
asset lifecycle management. The integrated approach directly addresses the industry's dual imperative of maximizing
hydrocarbon recovery while ensuring economic resilience in capital-intensive subsea developments facing volatile
market conditions.
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