As development progresses, reservoirs become more complex and require integrated analysis across static,dynamic, production, operations, and measure data. Challenges include:
Static and dynamic data are dispersed across systems without unified standards,hindering
integrated,intelligence-based
analysis.
Lack of tools that combine static/dynamic data with modeling and simulation to provide a comprehensive,intuitive view of reservoir and production status.
Dynamic problems are handled without multi-dimensional,multi-level,multi-method automated analysis;collboration is limited.
Decisions rely on experience rathet han full-dimension,problem-oriented models and decision-support logic based on all available datadimensions.
For challenging formations like carbonates,especially in stages with low recovery factors and high water cut,lack of targeted analytical tools and methodologies leads to inefficient analysis and unreliable results.
Lack of real-time detection and intelligent analysis of anomalies results in delayed problem detection, long analysis cycles, and both efficiency and precision falling short of operational demands.
