含硫天然气中单质硫溶解度的实验和理论研究进展  

Experimental and theoretical research progresses on the solubility of elemental sulfur in high-sulfur natural gas

作　　者：杨明理[1] 万莹[2] 霍翔宇 魏媛 王艺潼 李农[2] 岳双丽 YANG Mingli;WAN Ying;HUO Xiangyu;WEI Yuan;WANG Yitong;LI Nong;YUE Shuangli(Institute of Atomic and Molecular Physics,Sichuan University,Chengdu,Sichuan 610065,China;PetroChina Southwest Oil&Gasfield Company,Chengdu,Sichuan 610051,China;School of Physics and Opto-Electronic Technology,Baoji University of Arts and Sciences,Baoji,Shaanxi 721016,China)

机构地区：[1]四川大学原子与分子物理研究所,四川省成都市610065 [2]中国石油西南油气田公司 [3]宝鸡文理学院物理与光电技术学院

出　　处：《天然气工业》2025年第2期146-158,共13页Natural Gas Industry

摘　　要：硫沉积是高含硫天然气开发过程中面临的技术难题之一。溶解度变化是硫沉积发生的根本原因,研究高含硫气藏中单质硫的溶解度变化规律是认识和解决硫沉积问题的基础。为此,从实验测量、(半)经验模型与热力学模型、机器学习、分子模拟等角度分析了各方法的适用性和局限性,总结了天然气组分中单质硫溶解度研究领域的新进展。研究结果表明:①单质硫溶解度实验已开展多年,积累了不同天然气成分、温度和压力下的部分数据,但数据来源多样,实验条件差异较大,且数据量较少,不能满足精准预测需求;②(半)经验模型和热力学模型获得较多应用,但需根据实测数据调整参数,缺乏普适性;③机器学习方法在单质硫溶解度预测中具有较大潜力,但依赖数据质量和数量,缺乏可解释性,且泛化能力有限;④分子模拟可避免极端实验条件并可揭示单质硫溶解度的微观机制,但受限于计算资源、力场适用性和模拟时间尺度,未来需开发更精确的模型和力场,以提高其可信度和适用性。结论认为,单质硫在天然气中的溶解机制和溶解度演化规律仍然存在一些认识模糊区域,需要从理论、实验、模型、数据等多维度进一步认识硫沉积规律,包括:①针对天然气成分、温度、压力等变量空间,开展更多的实验测量和计算模拟研究,获得丰富的数据样本;②建立近真实环境的计算模型和实验装置,研究非平衡状态环境快速变化条件下的溶解度变化规律;③利用人工智能如大语言模型等方法分析单质硫溶解和析出过程中各物质的物理和化学变化数据,在复杂的变量空间认识硫溶解度的变化规律和控制因素,为控制硫沉积找到新途径。Sulfur deposition is a significant technical challenge in the development of high-sulfur natural gas reservoirs.The change in solubility is the fundamental cause of sulfur deposition.Therefore,to study the solubility change laws of elemental sulfur in high-sulfur gas reservoirs is essential in understanding and addressing sulfur deposition.In this paper,the applicability and limitations of various methods are analyzed from the aspects of experimental measurement,(semi-)empirical model and thermodynamic model,machine learning,and molecular simulation,and the latest progresses in the research field of elemental sulfur solubility in natural gas compositions are summarized.The following results are obtained.First,experimental studies on elemental sulfur solubility have been conducted for many years,generating partial data on different gas compositions,temperatures,and pressures.However,the data sources are diverse,the experimental conditions vary significantly,and the available data are insufficient to support accurate prediction.Second,(semi-)empirical model and thermodynamic model have been widely applied but require parameter adjustments based on measurement data,which restricts their generality.Third,machine learning methods show great potential in the prediction of elemental sulfur solubility,but are dependent on data quality and quantity and they lack interpretability,and have limited generalization ability.Fourth,molecular simulation can avoid extreme experimental conditions and provide insights into the microscopic mechanisms of elemental sulfur solubility.In response to the limited computational resources,force field applicability and simulation time scales,it is necessary to develop more precise models and force fields to improve the credibility and applicability.In conclusion,ambiguities remain in understanding the dissolution mechanisms and solubility evolution laws of elemental sulfur in natural gas,and it is necessary to further understand sulfur deposition in multiple scales like theory,experiment,mode

关 键 词：高含硫气藏 硫沉积 溶解度 单质硫 硫化氢 状态方程 机器学习 分子模拟 

分 类 号：TE377[石油与天然气工程—油气田开发工程]