Enhancement of dynamic reservoir interpretation using the well2seis technique
Abstract
The study in this thesis shows that dynamic reservoir interpretation can be enhanced by
directly correlating the attributes from many repeated 4D seismic monitors to the
production and injection behaviour of one or a group of wells. This ‘well2seis’ cross-correlation is achieved by defining a linear relationship between pressure and saturation-related 4D seismic responses and their corresponding changes in the cumulative fluid
volumes at the wells. With a properly determined threshold, the spatial distribution of the
well2seis correlation attribute can reveal key reservoir connectivity features, such as the
seal of faults and intra-reservoir shale layers, fluid flows and pressure diffusion pathways,
and communication between neighbouring compartments or fields. It is also shown that
the enhanced interpretation from well2seis becomes more reliable when combined with
the conventional “well2well” methods that are based on well production and injection
rate fluctuations and bottom-hole pressure measurements. To appropriately make of use
the well2seis interpretations, a workflow is proposed to close the loop between 4D
seismic and reservoir engineering data. Firstly, the reservoir model is directly updated
using the improved understanding of reservoir structure and connectivity. Seismic
assisted history matching (AHM) is then performed to quantitatively use the well2seis
attribute to honour data from both seismic and reservoir engineering domains, whilst
simultaneously preserving the reservoir geology. Compared to traditional history
matching approaches that attempt to match individual seismic time-lapse attributes and
production observations, the proposed approach utilises the well2seis correlation attribute
that condenses 4D seismic and production data. In addition, the approach is observed to
improve the history matching efficiency as well as the reservoir model predictability.
The proposed technique is firstly validated by synthetic field cases and then applied to
the 4D seismic data from several fields. In its application to the fault-compartmentalised
Heidrun field, the well2seis correlations are obtained as a consequence of the reservoir
fluid communication and compartmentalisation across the compartments, while in
Harding and Gryphon, the pressure communications between the neighbouring fields are revealed. The results of both applications suggest that the proposed well2seis technique
can be an efficient tool for assessing intra- and inter- reservoir connectivity. The
combination between well2seis and well2well is tested on the Norne field, demonstrating
that the well injection and production fluctuations can assist in the selection of appropriate
wells as input to the well2seis. This makes the 4D interpretation on Norne become more
robust, detecting the pressure diffusion and fluid flow pathways consistently with bottom-hole pressure measurements and sea water production breakthrough observations.
Furthermore, the field applications also identify key fault barriers which were not
considered in the initial structure models. The quantitative use of the well2seis attribute
is validated on another North Sea field for reservoir model updating. After the static
model updating and assisted history matching, the desired loops are closed by efficiently
updating the reservoir simulation model, and this is indicated by a 90% reduction in the
misfit errors and 89% lowering of the corresponding uncertainty bounds. Overall, my
studies indicate that the well2seis technique initiates a new direction to acquire insights
into the dynamic reservoir changes by bridging the gap between 4D seismic and reservoir
engineering.