Maximize Sweep Efficiency Using Proactive Tar Boundary Detection to Effectively Place a Water Injector Well Using Multiple Workflows of Distance-To-Boundary Inversion Techniques

Abstract

Abstract In most field developments, the major objectives of placing water injectors are to minimize oil column below the well trajectory, maximize the sweep efficiency and avoid drilling below tar which acts as permeability barrier reducing the effectiveness of the injectors. The case study showcases integration of two conceptual tar models in the well planning phase & implementation of multiple inversion workflows for deep azimuthal resistivity (DAR) tool to enable a successful detection & mapping of tar surface. Two tar models were generated from seismic inversion and a petroleum system study. They highlight the depth and areal extension uncertainties for tar presence to be incorporated in well planning stages. A detailed Reservoir Navigation feasibility model constructed in pre-drilling stage showed that the tar surface shows characteristic high resistivity in offset wells. This could be used for early detection and avoidance of tar by using a DAR tool, NMR-Density-Neutron, and mud logging which were selected to effectively characterize and map the tar. While drilling, Azimuthal resistivity data based multiple inversion workflows were utilized in real-time to accurately assess several possible scenarios. More guidance was applied along sections with moderate change of environment, while open models allowed to check the global equivalency or find solutions in regions where changes in resistivity were substantial. The integrated work from planning to execution stage not only saved a pilot hole, sidetrack cost but also maximized value for injector placement & subsurface characterization. The well was successfully landed above the modelled shallower tar surface. The tar presence was evaluated using joint analysis of resistivity inversion, NMR-Density-Neutron data and cutting samples. It was key to have both conceptual models to provide a much smoother well profile for accessibility and to avoid any possible sidetrack. For the subject well, inversion workflows with optimized parameter inputs provided good mapping of the tar mat. Linear uncertainty analysis of the resistivity data inversion results confirmed high accuracy of the distance to boundary estimation. The multiple inversion workflows allowed to adjust the variables based on the environment and provide an interpretation output, that mapped the tar surface with high confidence & Geosteering decisions were made timely. The resistive top tar layer was tagged for final confirmation and interpretation from cuttings & NMR-Density / Neutron tool before TD. Proactive Geosteering recommendations allowed a gentle incident angle relative to the resistive tar layer below. The well was placed around 5 ft. TVD above the tar surface, thus minimizing oil column above the tar & below the wellbore thus increasing sweep efficiency. The DAR tool enabled 5000 ft. lateral mapping of tar surface for the first time in the field and enhanced the subsurface understanding for future field development plan. Utilization of resistivity data based multiple workflow inversion in real-time provided a higher confidence level & improved proactive Geosteering decision making that enabled the best well placement for this injector well while avoiding the shallower tar.