In several locations in the world the petrophysical analysis of hydrocarbon reservoirs is complicated by the presence of sands derived from volcanic sources. The interpretation of the fluids present in such rock is problematic in many ways as is the identification of potential reservoirs themselves. One particular example is the Cook Inlet in Alaska. This is a fluvial depositional system with sands, shales and silt, rich in minerals with a volcanic origin. There are also many coal layers present and these are the source rock for these mainly gas reservoirs. Several fields have clearly identifiable gas and oil-bearing zones and these have been well produced. Operators are now actively searching for those more complex hydrocarbon zones that may have been overlooked in the past and also for information to help to update the reservoir models based on which zones still have gas present and to identify fault barriers in currently producing zones.
The presence of sand reservoirs containing a high percentage of volcanic minerals and lithoclasts causes problems with standard gamma ray interpretation. Also, low and variable salinity result in Rw variation that are not predictable and wet zones that may have anomalously high resistivity. There are additional problems with the interpretation of density/neutron information to identify gas pay as the presence of volcanic minerals will tend to inhibit the occurrence of the neutron-density cross-over. The use of compressional and shear sonic data in combination with standard log interpretation is key to understanding these zones. In the studied well the presence of the coal layers and the associated poor wellbore and logging conditions, along with the wellbore deviation, meant that running wireline-conveyed sonic logging tools was not the preferred option. Instead the full logging suite was acquired using logging-while drilling (LWD) technology. Recently developed multi-pole LWD sonic tools are now able to deliver consistent shear data across a wide range of formation travel times, along with high-quality compressional data. The examples shown demonstrate the problems with interpreting fluid content without the sonic data and the conclusions that would be drawn in this case. The addition of compressional and shear data is shown to improve the interpretation and to identify potential reservoirs that would otherwise have been overlooked. The sonic data are also shown to provide information on previous production zones that are now depleted and swept by water, thus helping in understanding regional connectivity developing reservoir production strategies.