Deepwater lobe turbidites are difficult to model geologically, but they are known to be very prolific producers, once their stratigraphic setting and lobe stacking architecture are understood. Variability in rock quality distribution, permeability, and flow barriers strongly impact productivity and development strategy for economic hydrocarbon recovery. Additional complexity is imposed with structural faulting. After the discovery well in one of the faulted blocks for the Gulf of Mexico (GOM) example presented, additional appraisal close proximity penetrations were planned to fully understand the geology setting.
Advanced evaluation technologies were deployed including a combination of while-drilling magnetic resonance to fully understand porosity, permeability, and fluid composition independent of anisotropic effects in laminate-turbidite setting. High-resolution geological borehole imaging, nuclear porosity measurements, formation pressures while drilling, wireline evaluation, core data, and seismic data were integrated.
The integrated study showed the sand lobes to have similar reservoir characteristics of the discovery and existing offset wells. Gathering data early via the logging-while-drilling (LWD) combination of gamma ray, resistivity, density, neutron, nuclear magnetic resonance(NMR) and pressures enabled better data-gathering decisions post drill.
The permeability profile of the sands reservoirs was found to be consistent with the lobe turbidite geologic model. A real-time permeability profile from the NMR helped define the lobe stack sequence. Hydrocarbon identification in a laminated margin section, which extended the proved hydrocarbon limits, was achieved utilizing a new real-time compression of the NMR T2 spectrum distribution. A perched-water feature was observed at the base of a lobe sequence, not previously observed in other sand compartments. In addition to providing a framework to model the geologic setting, reservoir connectivity was also evaluated by integrating pressure measurements and dynamic fluid sampling.
