Stochastic-Modeling

This post outlines a platform architecture designed to model the impact of a hybrid risk registry (qualitative and quantitative risks) on an oil company’s key financial KPIs like EBITDA and Cash Flow on a monthly basis. The design emphasizes modularity, auditability, and the integration of expert judgment with stochastic simulation. 1. Core Principles & Objectives Single Source of Truth: Establish a centralized, versioned Risk Registry for all identified risks. Hybrid Modeling: Natively support both quantitative risks (modeled with probability distributions) and qualitative risks (modeled with structured expert judgment). Financial Integration: Directly link risk events to a baseline financial plan (P&L, Cash Flow statement) to quantify impact. Probabilistic Output: Move beyond single-point estimates to deliver a distribution of potential outcomes (e.g., P10/P50/P90 EBITDA). Auditability & Reproducibility: Ensure every simulation run is traceable to a specific version of the risk registry, assumptions, and financial baseline. User-Centric Workflow: Provide intuitive interfaces for risk owners to provide input without needing to be simulation experts. 2. High-Level Architecture The platform is designed as a set of modular services that interact through well-defined APIs and a shared data layer. ...

This post reconstructs the evaluation, financial modeling, and decision analytics framework used when leading an upstream (oil & gas) analytics team (circa 2015–2018). It blends technical reservoir & production modeling with fiscal, stochastic, real‑options, and portfolio layers plus emerging carbon governance. 1. Checklist (Top-Level Components) Scope definition Technical (subsurface & production) models Commercial & fiscal models Market & price modeling Cost & economic models Real options layer Stochastic engine & correlations Portfolio aggregation Risk & sensitivity Carbon / ESG integration Data architecture & governance Validation & model risk management Implementation blueprint 2. Scope & Objectives Asset lifecycle: exploration → appraisal → development planning → execution → ramp-up → plateau → decline → abandonment. Decisions supported: license bidding, sanction (FID), phasing, drilling sequence, facility sizing, hedging, M&A, divestment, suspension, expansion, abandonment timing. Outputs: NPV (pre/post tax), IRR, payback, PI, EMV / ENPV, free cash flow profiles, value at risk (P10/P50/P90), option-adjusted value, carbon-adjusted value, capital efficiency, portfolio efficient frontier. ...