Integrated multi-scale reservoir data representation and indexing for reservoir data management and characterization

Single-scale models cannot satisfy the requirements of oil reservoir researchers. The management of multi-scale data is thus important to ensure appropriate representation of geological structures and reservoir characterization. However, existing methods generally focus on two-dimensional maps. Moreover, existing multi-scale models and 3D indexing methods are not completely suitable for organizing and managing oil reservoir data; the relationship between spatial objects and the heterogeneity in spatial variations are not considered. To address this issue, this study aimed to develop a multi-scale oil reservoir model from the finest existing reservoir model, establish the relationship between models of different scales, and integrate multi-scale oil reservoir models. This paper proposes a multi-scale tree representation and generation method, based on corner point grid(CPG), that integrates multi-scale reservoir model representation and a spatial index. Experiments on integrated indexing and rendering were performed using the proposed method, and its performance was then evaluated via comparisons with existing methods. The results showed that the proposed integrated indexing method is significantly faster than one that does not use vertical geologic layer indexing. In addition, the proposed algorithm required much less time to render geological objects than a popular program and also performed operations such as translation and rotation more rapidly. Overall, the proposed algorithm allowed for efficient querying and visualization of arbitrary layers at arbitrary scales and regions. •The representation and indexing of multi-scale reservoir data are integrated.•The method employs the level-of-details, corner point grid and octree techniques.•Combined query of spaces, attributes and LODs, and visualization could be achieved.