Predicting Dynamic Reservoir Connectivity from Historical Oil Field Production Data: Implications for CO2 Injection
Hedley, Ben 1; Davies, Richard 1; Gluyas,
Jon 1; Hanstock, David 2; Mathias, Simon 1;
Aldersey-Williams, John 3
(1)Earth Science, University of Durham, Durham, United Kingdom. (2) Progressive Energy Ltd, Stonehouse, United Kingdom. (3) Redfield Consulting, Monymusk, United Kingdom.
UK North Sea field studies indicate potential to increase field life by 15 to 20 years and produce an additional 3 billion bbl of oil. However, injecting CO2 into produced and pressured depleted reservoirs presents numerous challenges, significantly then effects of compartmentalising structures that prevent pressure communication across the field.
Understanding reservoir architecture is critical if CO2 EOR is to be cost effective, avoid the rapid pressure increase predicted by some workers and deliver the reservoir sweep required to have a material impact on EOR. Static modelling of connectivity is common place, but dynamic reconstructions of reservoir pressure conditions are rare in literature.
In this study we compare a UK North Sea field that produced from a turbiditic sand reservoir; to a deep saline formation (DSF) hosted in a clastic aeolian sandstone. Utilising 2D and 3D seismic mapping to identify large scale flow barriers and examine the communication across them. We model the implications of differing virgin pressure systems on CO2 storage capacity and injectivity in the DSF.
We examine the full pressure history of the oil field from all producing wells over the field lifespan to create a static reservoir model. Based upon this, we model the dynamic change in pressure from virgin pressure over the operational life of the field. We examine the role of water injection on reservoir pressure and its potential effects on CO2 injection for EOR. We model the communication between injector and producer to avoid CO2 breakthrough and optimise recovery.
Findings from the DSF indicate that the flow barriers creating a sealed system reduce the storage capacity to 0.3 Mt CO2 from 28 Mt CO2 in a fully connected system using a single well method in a 4 way dip closure and to 0.34Gt from 2.7Gt in a large scale stratigraphic trap. Probabilistic approaches indicate rock compressibility in sealed systems increases available storage volume by a factor of 10, that tailoring the DOE efficiency factor method to be site specific can increase CO2 capacity by an order of magnitude, and that method is severely limited in its standard form when applied to specific targets.
AAPG Search and Discovery Article #90135©2011 AAPG International Conference and Exhibition, Milan, Italy, 23-26 October 2011.