The increase of computational power allows engineers and geoscientists to understand the intrinsic nature of uncertainty associated to the subsurface studies. Modern characterization workflows have been tailored to produce multiple geological realizations and development scenarios; however, the amount of data generated from assisted history matching and uncertainty analysis processes is nearly unmanageable difficulting the quick extraction of results to support decisions efficiently; in other words, deep technical workflows are disconnected from business processes.
Moreover, the proliferation of data analytics and easy-access business intelligence (BI) tools facilitate the quick dissection and data analysis, once the data is properly formatted.
We focus on bridging the gap between the complexity of the modern workflows and BI tools by tackling key post-processing bottlenecks, by managing and classifying scenarios and cases, by integrating production profiles and economics, and by streamlining performance indicators to quickly support key decisions.
Download the presentation material here.