Full text loading...
-
Operating Digital Oil Fields
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 79th EAGE Conference and Exhibition 2017, Jun 2017, Volume 2017, p.1 - 5
Abstract
Digital oil field of course refers to Big (Geo) Data and real time Cloud computing and that will make the difference with current geo data processing and modelling workflows. But the main issue when making E&P decision remains: Oil is a natural resource that is out of direct reach and there is no such thing as an exact representation of the subsurface that would allow for making “optimal” E&P decisions.
In the oil industry, kriging is known as a mere interpolator, it is in fact much more than that: It is a mathematical optimizer for decision making as it is designed to minimize the unknown difference that always occurs between expectations (the deterministic model or the stochastic estimate) on reservoirs characteristics and their actual values. This difference is called the estimation error and kriging minimizes the estimation variance.
By translating usual geophysical processing and modeling workflows into their mathematical stochastic counterpart, kriging enables to automate and optimize their running turnaround time. It then opens the way to the operation of digital oil fields in real time and with quantified confidence.