The Njord Field, situated in the Haltenbanken area, is one of the most challenging reservoirs on the Norwegian shelf. The structural complexity is high, with numerous intersecting faults compartmentalizing the reservoir. The reservoir is dominated by alternating shale and sand intervals of tidal, estuarine and deltaic depositional origin.
One of the main segments on Njord – the Central Area – was the target for a one-year improved oil recovery study. The Central Area reservoir is produced by depletion, with a current recovery factor of only 6%, as most faults appear to seal during production. The previous drilling experience revealed quite large uncertainty with respect to both depth and missing faults due to poor seismic data quality.
In order to plan further wells in this area a model that comprises the full uncertainty with respect to both structural components (depth uncertainty and faults) and property components (facies, permeability, porosity) was made. The model was built by combining commercial modelling software (IRAP RMS and STORM:HORIZON) with an R&D tool (HAVANA) in a manner that has not been attempted previously, and 200 stochastic realizations were run. Each realization has a different structural 3D grid (depth and fault pattern) and different petrophysical properties. A streamline simulator in IRAP RMS was applied to rank the realizations and ten realizations were chosen for further well screening in the flow simulator (ECLIPSE). The model was applied to propose two new well targets that were robust economically (given all uncertainty). In addition, the model was applied in testing various unconventional well types, for example so-called ‘connector-wells’, which are open holes in the reservoir (but not connected to the surface), in order to connect fault blocks bounded by sealing faults.
Drilling and subsequent seismic interpretation after the model had been built revealed that the structural uncertainty was even greater than predicted. It is crucial to capture the full interpretation uncertainty and, in particular, to address the problem of jump-correlation across fault blocks. Despite this, however, the observed cumulative production from the new oil producer compares well with the prognosis from the model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.