Abouzaid, Ahmed (Baker Hughes) | Thern, Holger (Baker Hughes) | Said, Mohamed (Baker Hughes) | ElSaqqa, Mohammad (Khalda Petroleum Company) | Elbastawesy, Mohamed (Khalda Petroleum Company) | Ghozlan, Sherin (Khalda Petroleum Company)
The evaluation of logging data in shaly sand reservoirs can be a challenging task, particularly in the presence of accessory minerals such as glauconite. Accessory minerals affect the measurements of conventional logging tools, thus, introducing large uncertainties for estimated petrophysical properties and reservoir characterization. The application of traditional Gamma Ray and Density-Neutron crossover methods can become unreliable even for the simple objective of differentiating reservoir from non-reservoir zones.
This was the situation for many years in the glauconite-rich Upper Bahariya formation, Western Desert, Egypt. Formation evaluation was challenging and the results often questionable. Adding Nuclear Magnetic Resonance (NMR) Logging While Drilling (LWD) data in three wells changed the situation radically. The NMR data unambiguously indicate pay zones and simplify the interpretation for accurate porosity and fluid saturation dramatically. Key to success is NMR total porosity being unaffected by the presence of accessory minerals. NMR moveable fluid directly points to the pay zones in the reservoir, while clay-bound and capillary-bound water volumes reflect variations in rock quality and lithology.
Although the NMR total porosity is lithology independent, the presence of glauconite affects the NMR T2 distribution by shifting the water T2 response to shorter T2 times. This requires an adjustment of the T2 cutoff position for separating bound water from movable hydrocarbons. A varying T2 cutoff was computed by comparing NMR bound water to resistivity-based water saturation. The calibrated T2 cutoff exhibits an increase with depth indicating a decreasing amount of glauconite with depth throughout the Upper Bahariya formation. Based on these volumetrics, an improved NMR permeability log was calculated, now accurately delineating variations in rock quality throughout the different pay zones. In addition, viscosity was estimated from the oil NMR signal. The estimated values match the expected values very well and illustrate the potential of NMR to indicate viscosity variations.
Many of these results are available today already in real-time by transmitting NMR T2 distributions to surface while drilling. Besides the application for formation evaluation, the data can be used to initiate optimized side-tracking and completion decisions directly after finishing the drilling operations.