In the context of increasing global oil price volatility and escalating supply chain risks, enhancing the stability and self-sufficiency of crude oil supply has become a strategic priority for ensuring national energy security. Extra heavy oil, characterized by abundant reserves and low cost, holds significant potential to be converted into high-quality synthetic light crude through hydrogen-based deconstruction using green hydrogen. However, the economic viability of this pathway is highly sensitive to fluctuations in key factors such as extra heavy oil procurement prices, green hydrogen production costs, and renewable electricity prices. Therefore, it is essential to develop a quantitative evaluation and optimization model under multi-dimensional uncertainty to support investment decision-making. Building on conventional techno-economic analysis frameworks, this study incorporates the effects of multi-dimensional stochastic variables by employing parameter perturbation and Monte Carlo simulation methods to construct a breakeven price model under uncertainty. Based on the volatility characteristics of extra heavy oil prices, a feedstock procurement and storage optimization model is further developed, forming a systematic evaluation and optimization framework. The results show that feedstock procurement costs and green hydrogen production costs are the primary factors influencing the distribution of breakeven prices. Under the baseline scenario, the breakeven price exhibits a rightskewed distribution with a skewness coefficient of 0.76, and the 10%~90% quantile range spans from 5537 to 7601 CNY/ton. The distribution has a long-tail characteristic, with a 5% probability of exceeding 8000 CNY/ton. Mechanistically, price increases raise marginal costs and shift the breakeven point to the right. Meanwhile, greater price volatility amplifies cost uncertainty, thickens the distribution tail, and increases the risk of extreme outcomes. Under a procurement and storage optimization strategy, annual cost savings of approximately 266 million CNY can be achieved, and the breakeven price distribution transitions from right-skewed to approximately normal. Compared to the baseline scenario without optimization, the probability of extreme high breakeven prices is significantly reduced, and the 10%~90% quantile range narrows by 1519 CNY/ton. Assuming a synthetic light crude market price of 7000 CNY/ton, the probability of profitability increases from 74% to 99%. Storage optimization effectively lowers the probability of high breakeven prices and enhances profit stability. In addition, reductions in green hydrogen production costs will further improve economic performance. The study also finds that investors’ varying risk preferences significantly affect their tolerance for return uncertainty, suggesting that policy design should account for such heterogeneity to enhance plan adaptability. This research provides scientific decision-making support for investment in extra heavy oil deconstruction via green hydrogen and offers a novel and practical pathway for enhancing energy security and achieving low-carbon transition under China’s carbon neutrality goals.