鉴于我国氦气产业链理论技术需求,针对国内外尚无系统的氦气地质理论认识,缺乏针对性的氦气资源评价方法、参数取值标准,缺乏氦气含量综合准确检测、有利富集区优选方法,无成本指标优化体系及全产业链一体化评价方法等卡点和难点,本文运用地质、地球化学、重磁电震、投资经济等多学科方法及实验技术,集中力量攻克氦气成藏机理、资源评价及资产评价的关键技术瓶颈。研发形成1项地质理论认识和3项关键技术:基于典型富氦气藏解剖、地下流体中“氦-气-水”相平衡及相-势耦合分析,研究提出氦气“水溶相、气容相、游离相”3种主要赋存状态、“集流、渗流、扩散”3种运移机理、“近氦源、邻断裂、低压区、高部位”4项分布富集控制因素,初步建立了基于“优质氦源、高效输导、适宜载体”的氦气“生-运-聚”地质理论认识。针对国内氦气含量检测技术参差不齐、部分准确度差、与国外数据差别大、无针对性的氦气资源评价方法等系列难题,以氦气源及氦气含量为核心,研发氦气含量综合准确检测技术,构建4类10种氦气资源评价方法,解决了氦气资源分级分类评价的技术瓶颈。针对基底氦源分布、岩性识别、通源断裂刻画及含氦储层评价难题,创建了归一化重磁下延方案,研发了基于深度学习的多尺度断裂智能识别技术和不同氦气含量下的气藏声学性质模拟方法,为氦源岩分布预测、通源断裂刻画、含氦储层测井解释评价及预测奠定了基础。通过建立多元控氦的富氦区带与目标优选技术,解决了富氦区带与目标优选难题。针对国内贫氦实际情况,以提氦装置投资和操作成本最小化为目标,采用响应面法建立优化目标与各主要工艺参数的非线性回归模型,建立了氦气全产业链一体化评价技术,初步解决了天然气低成本提氦工艺流程优化的技术需求。研究成果为我国长期、安全、规模利用氦气资源资产提供了有效支撑。

China's helium industrial chain needs scientific and technological support, but there lack a systematic theoretical understanding of helium geology, along with the lacks of targeted helium resource evaluation methods and parameter selection standard, comprehensive accurate detection of helium content, helium prospecting methods, cost index system, as well as methodology for integrative evaluation of the entire helium industrial chain. To address these knowledge/technology gaps we developed a helium accumulation model and three key technologies for helium resource and asset evaluation, using interdisciplinary research methodology and experimental techniques involving geology, geochemistry, gravity-aeromagnetic-electrical-seismic, and investment and economics. Through detailed investigation of typical helium-rich gas reservoirs, combined with analysis of “helium-natural gas-water” phase equilibria and phase-potential coupling in underground fluids, we revealed three helium occurrences—water-dissolved, gas-dissolved, free-particle; three migration mechanisms—mass-flow, seepage, diffusion; and four dispersion-enrichment controlling factors—proximity to source, adjacent faults, low-pressure zone, high-location. We developed a theoretical framework for the understanding of helium geology, recognizing high-quality source, efficient migration, suitable gas-carrier are the three key controlling factors of effective helium accumulation. To overcome a series of challenges in helium detection, such as variable detection techniques, low accuracy, large discrepancies with foreign data, and no targeted resource evaluation methods, we developed a comprehensive, accurate detection technique for helium content, with helium source and content at the core, and established 10 resource evaluation methods under four categories, solving the technical bottleneck in helium resource classification and evaluation. A normalized gravity/magnetic downward extension scheme was created to address challenges in helium source-rock distribution, lithofacies identification, source-fault characterization, and reservoir evaluation. An intelligent identification technique for multi-scale faults based on deep learning and a simulation method for acoustic properties of gas reservoir under different helium contents were developed, laying the foundation of predicting source-rock distribution, characterizing source-faults, logging interpretation, and evaluating helium-bearing gas reservoirs. By establishing a multi-process helium control model for helium-rich gas zones and target optimization methodology, the problem of target optimization for helium-rich gas zones is solved. Facing the reality of helium deficiency in China, with the goal of promoting cost-effective investment in helium extraction equipment, we developed a methodology for integrative evaluation of the entire helium industrial chain by adopting response surface methodology to build a nonlinear regression model between optimization target and various main process parameters, which preliminarily addressed the technical demand for cost-effective helium extraction from natural gas. Results from this research provide effective support for China's long-term, safe, and large-scale utilization of its natural helium asset.