完整的论文详细介绍了如何通过构建多个小型的、适合用途的集成自适应模型（而不是一个包罗万象的模型）来加速油藏建模工作流程并减少不确定性，即使是对于具有挑战性的绿地前景也是如此。此工作流程减少了关键路径上的项目数量，同时在静态模型最终确定之前实现了静态和动态数据的集成。此外，这种方法可以更快地评估新想法，而不会影响项目的关键路径。
自适应模型的构建是为了评估单个参数，但这并不妨碍自适应模型同时回答多个问题。自适应模型的成功使用至关重要，因为自适应模型可以快速构建。
The complete paper details how the reservoir modeling workflow can be accelerated, and uncertainty reduced, even for challenging greenfield prospects by constructing multiple small fit-for-purpose integrated adaptive models instead of one all-encompassing model. This workflow reduces the number of items on the critical path while simultaneously enabling static and dynamic data to be integrated before the static model is finalized. In addition, this approach enables new ideas to be evaluated more rapidly without affecting the critical path of the project.
Adaptive models are constructed to evaluate a single parameter, although this does not preclude an adaptive model being used to answer more than one question simultaneously. Critical to the successful use of adaptive models is the fact that they can be constructed quickly.
