The choice of the EOR process for reservoir management is a lengthy process, necessitating characterization and integration of studies at different scales. Current EOR method choices are based on general technical criteria and a-priori expert knowledge of different teams participating. Since all options cannot be fully explored, management needs to evaluate the degree of “fuzziness” involved in order to assess the “knowledge situation” prior to decision
The goals are to create a sophisticated snapshot of the available data at a given time, checking the main EOR drivers and the statistics governing them. This approach offers an iterative method to calibrate knowledge and biases within team members and experts, constructing a tool with which a quicker decision can be taken in absence of hard data (or hard evidence..)
We propose to build a standalone software able to evaluate and process information and knowledge data meeting specifications indicated above.
We illustrated the methodology on several examples, and are currently developing a prototype solution. A dedicated patent application was also submitted.
In addition, we also aim at packaging the algorithms into a web service, which could be interfaced to reference reservoir modeling software as a “preliminary” data analysis before simulation.