Techno-Economic Framework for Converting Routinely Flared Gas into Marketable Energy Products and Feedstocks

This paper develops a stage-gated techno-economic framework that integrates engineering feasibility, market fit, uncertainty, emissions, and execution readiness for converting routinely flared gas into marketable energy products and feedstocks. The study responds to the problem that commercial recovery fails when variable supply, composition, gathering distance, product markets, financing, operations, and regulatory obligations are assessed independently, a pattern consistent with global flaring data showing that flared volumes have risen rather than fallen despite two decades of reduction commitments. It uses an integrative conceptual review of 95 scholarly and professional sources published to date, spanning gas-to-liquids, gas-to-power, mini-LNG and compressed natural gas monetization, methanol and petrochemical feedstock routes, and techno-economic analysis methodology. The framework organizes eight decision functions: resource characterization, market screening, technology matching, concept design, risk-adjusted cash-flow modelling, option and scenario analysis, delivery planning, and post-startup verification. It applies those functions across flare-gas sources, gathering network, pretreatment, conversion unit, product storage, and market and logistics interface. The analysis treats uncertainty, process safety, reliability, environmental performance, resource efficiency, economics, and organizational control as connected requirements. The proposed architecture links a system definition, evidence register, model assumptions, intervention portfolio, verification plan, and learning cycle. Its central proposition is that the framework should select and stage feasible routes for converting flare gas into pipeline gas, liquids, electricity, compressed or liquefied gas, methanol, or other products only when decisions preserve traceability from measured conditions to selected actions and verified outcomes. The paper offers testable propositions, an implementation roadmap, asset-specific application protocols, and a research agenda. The framework supports case-study testing and quantitative extension without claiming universal performance before field validation.