长庆油田地质工程一体化智能决策系统开发与应用

Development and application of geology and engineering integrated intelligent decision-making system of Changqing Oilfield

面对当前勘探开发对象日趋复杂和低油价的压力,针对长庆油田页岩油、致密气赋存特点探索形成了“水平井、多层系、立体式、大井丛、工厂化”开发新模式,实现了地质工程一体化规模、高效及低成本开发页岩油气资源。为了更好地适应一体化综合研究、生产组织和决策指挥等业务需求,对数字化条件下油田企业级地质工程一体化决策系统的构建与应用进行了探索研究,提出涵盖“研究+分析+决策”完整链条的设计思路,将新一代大数据、物联网及人工智能技术与页岩油气开发模式深度融合,开发建设了地质工程一体化决策支持系统(Geology&Engineering Integrated Decision Support System,简称GEDS),包括三维地震大数据可视化、地上地下一体化综合展示、三维地质快速建模数据接口、地质模型局部快速更新等关键技术模块,在页岩油勘探开发示范工程中进行推广应用,实现了室内现场远程互动、生产过程实时监控、方案部署动态优化。

Facing the pressure of the increasingly complex exploration and development objects and low oil price,Changqing Oilfield has explored and formed a new development mode of shale oil and tight gas with“horizontal well,multi series,stereoscopic,cluster wells,and factory operation”based on their geological characteristics,which enables to achieve the large-scale,high-efficiency and low-cost development of tight oil and gas resources by integrated geology and engineering.In order to better meet the business needs of integrated comprehensive study,production organization and decision-making,the construction and application of an enterprise-level geology and engineering integrated intelligent decision-making system are explored and studied against the digitization background.The design idea of a complete chain covering“research+analysis+decision making”is proposed,which deeply integrates the new generation of big data,Internet of things and artificial intelligence technology with development mode of tight oil and gas.As a result,the Geology&Engineering Integrated Decision Support System(GEDS)is developed and constructed,including key technologies such as 3D seismic data visualization,display of integrated surface and subsurface,data interface for rapid 3D geological modeling,real-time updating of geological model,etc.It has been applied in shale oil exploration and development demonstration project,realizing remote interaction between indoor and field,real-time monitoring of production process and dynamic optimization of scheme deployment.