Quantitative petrophysical evaluation in high-angle and horizontal (HA/HZ) wells has remained elusive primarily because of the presence of complex log responses and lack of appropriate modeling capabilities. Recent advances in numerical simulation of nuclear and resisitivity logs in HA/HZ wells have significantly improved interpretation of log responses in complex borehole-formation geometries. Additionally, developments in fast simulation methods have enabled application of log response modeling in conjunction with field measurements. Although a full understanding of nuclear and resistivity logs response in HA/HZ wells is yet to be resolved, application of advanced interpretation techniques to field measurements yields more reliable petrophysical analyses.
In this paper, we implement processing methods that more effectively combine short- and long-spaced density measurements together with forward modeling of azimuthal nuclear and scalar resisistivity logging-while-drilling (LWD) logs to construct a common subsurface model. This log response-coherent model constructed from field measurements is then used for conventional petrophysical analysis. To demonstrate our workflow, we analyze four horizontal wells penetrating sand-silt sequences in the Chayvo field (northeast coast of Sakhalin Island, Russia) with apparent dip angles ranging between 80 and 90 degrees. The wells were drilled with oil-base mud (OBM) and include standard LWD triple-combo logs.
Field-based log response-coherent models of resistivity, density, and neutron measurements are used to estimate lithology volumetrics, porosity, and water saturation. Results from depth coherence processing and forward modeling show improved resolution and estimation of formation layer petrophysical properties which yield more accurate estimates of reserves in place compared to those initially estimated from field logs. Additionally, the average properties in high- and low-net intervals from the HA/HZ wells are compared to properties estimated in near offset vertical wells, which include core samples.