Predicting Water in the Crest of a Giant Gas Field - Ormen Lange Hydrodynamic Aquifer Model (SPE 153507)

The hydrodynamic aquifer in the Norwegian Ormen Lange gas field has been assessed using isopotential mapping and dynamic simulation of the fluid-fill over geological time. These models correctly predicted the results of a 2011 appraisal well. The Ormen Lange gas field (8*40 km) is located in 700-1100m water depth with the main reservoir unit formed by a Paleocene submarine fan. The field, producing since 2007, was initially assumed to be a combined stratigraphic-structural trap with the gas-water contact delineated by a seismic DHI. A crestal 2008 appraisal well in the northern part of the field encountered only residual gas saturations in the middle of the DHI, leading to a re-appraisal of the charge history. Three subsequent appraisal wells have confirmed elevated contacts, residual gas, and pressure communication across the field. Three alternative models (breached, perched water and hydrodynamic aquifer) have been investigated to explain these observations. A phased hydrodynamic aquifer model is consistent with both field data and the basin history, where hydrodynamic flux is created by compaction of basinal shales. The aquifer has displaced the gas from the crest of the structure into the south giving a northward-thickening prism of residual gas, the base of which is imaged by a seismic DHI. Hydrodynamic aquifer conditions can result in a stepping FWL in a field, where structure does not justify perched water and without invoking the presence of sealing faults. Phased hydrodynamic conditions can lead to the presence of residual hydrocarbons beneath tilted contacts, even within stratigraphic traps with restricted aquifers. An understanding of basin hydrodynamics is critical for the correct exploration, appraisal and field development strategy and may challenge assumptions on contacts, volumes, fault-seal analysis and interpretations of DHIs and residual gas. Isopotential mapping and hydrodynamic simulation have considerable predictive power.