In a deep-water green field's development, horizontal wells are drilled to exploit the reservoir with the aim of reducing drilling cost and time to first oil.
During geosteering operations, Ultra Deep Azimuthal Electro-Magnetic (E.M.) measurements permit investigating the reservoir around the borehole up to a maximum depth of 30 m, in a good resistivity contrast environment. Acquired data are inverted on a vertical section, providing multi-boundary reservoir mapping along well path.
With such a depth of investigation, the reservoir mapping is an excellent bridge between conventional logging-while-drilling (LWD) and seismic images. The integration of acquired wellbore data with high-resolution attributes, from seismic inversion, maximizes well placement results when operating in complex subsurface geology and expands the perspectives of geosteering application.
A workflow to calibrate the reservoir structural and stratigraphyc setting has been assessed, via integration of seismic and Borehole Data. Enhancement of reservoir geometry interpretation during geosteering provides revised structural surfaces suitable for a quick update of the velocity model and a depth-calibration of all the seismic attributes used to steer wells.
We describe an application of the workflow to an infill well, targeting channel and crevasse splays deposits drilled through a structurally complex oil field in the Norwegian offshore. The availability of seismic attributes (probabilities of facies and petrophysical properties) allowed improving the overall results of the well placement operation.
Reservoir mapping identifies in real time Geo-bodies crossed by the well and within the range of investigation of Ultra Deep E.M. tool based on tool configuration, frequencies analysed and resistivity contrasts of the rocks. Stratigraphic correlation with offset wells, using conventional LWD data supported by Image Log interpretation, allowed allocating resistivity boundaries in terms of stratigraphic surfaces. These data are then integrated in near real time to depth calibrate maps, update the velocity model, hence the depth image of seismic attributes.
After depth calibration, Geo-bodies recognized on seismic show a good correspondence with those identified on the resistivity inversion and a detailed correlation of the heterogeneous fluvial sand was possible, even in presence of minor faults. In this challenging structural and stratigraphic environment, the correlation supported decision making during well operations to target the well on the pay sand.
The application proves that a detailed stratigraphic interpretation is an achievable goal in real time to steer successfully the well and to be used afterwards in a detailed reservoir model update.