Description:

Reservoir characterization and modelling challenge faces the increasing volumes of information to be coherently accounted for in the digital era reservoir operations. This includes the high quality digital data in vast volumes (seismic, continuous reservoir surveillance, etc) and heritage data, which is often variable quality and subject to uncertainty in interpretation and convention (sedimentary logs, core, wireline, analogues, etc).

The workshop aims to provide an overview of the state-of-the-art neural computing reservoir applications and set up a round discussion of the opportunities provided by computer based learning to tackle difficult data and uncertainty rich reservoir problems.