Predicting the Future With UDAR 3D Resistivity Modeling: A New Key to Unlock Multi-Dimensional Reservoir Steering

In the realms of geosteering and reservoir mapping, predrill simulations/feasibility studies are performed mainly for three reasons: (a) confirm the applicability/viability of deploying an ultradeep azimuthal resistivity mapping (UDAR) tool in in a range of predicted resistivity contrasts and to evaluate the detection/sensitivity of the UDAR multidimensional inversions to address the objectives for the subject well, (b) confirm the optimal number of UDAR receivers and the optimal spacing between the transmitter and each receiver, and (c) confirm the optimal frequencies for each UDAR transmitter-receiver pair. For reservoir-mapping-while-drilling systems which focus on geosteering in TVD only, the workflow to perform feasibility study has matured over the last few years, but for multidimensional reservoir mapping systems, the usefulness of a UDAR feasibility study is very much dependent on having a comprehensive three-dimensional (3D) geological model that captures structural and resistivity information around the planned well. The challenge with current industry standard geological models is that the grid sizes are much larger than commonly deployed UDAR depth of detection (DOD), thus undersampling the boundary detection. Another challenge in performing a multidimensional UDAR feasibility study is the forward modeling ability that can simulate downhole raw measurements capturing all the 3D elements of the formation (dip, azimuth, resistivity anisotropy). Multidimensional UDAR feasibility has its roots in the contributing factors such as geophysical data, the grid size of geological models, and the robustness of the forward modeling algorithm. The geological and geophysical data are usually provided by the operators, and this information is further refined to be able to be used in the feasibility work. The most important step in this work is the grid refinement (x,y) to a meaningful value that is less than the DOD of the planned UDAR configuration while preserving the vertical resolution (z). The grid refinement can either be local (around the wellbore) or regional. If the grid is refined from an already-built coarse grid, there is a good chance that structural details on the scale of UDAR’s DOD are not captured. The structural model workflow presented in this paper was built from the base using a corner-point gridding method on a 5 × 5 m (x,y) scale with seismic interpretation data (fault model, seismic horizons) as the primary input. Petrophysical modeling was then performed on the high-resolution structural grid, specifically focusing on resistivity data from the nearby offset wells. Finally, a standard property modeling workflow was executed involving upscaling of well logs, data analysis (data transformations, declustering, variograms), and petrophysical modeling (both Gaussian-simulation- and Kriging-based). The resulting 3D resistivity model generated is used as an input to the UDAR multidimensional forward modeling process that uses the two-dimensional (2D) finite difference method, simulating all 3D electromagnetic (EM) components simultaneously under the given set of conditions: a formation model, a trajectory, and the UDAR sensor structure. This theoretical log response (simulated) is then input to multidimensional UDAR inversions, which form the basis of this feasibility work. The multidimensional UDAR feasibility work shared in this paper gives insight into the 3D resistivity modeling workflow and how it can be used in the well-planning stages. In real time, the UDAR results were observed to be similar to predrill simulations, which helped in a smooth execution of azimuthal geosteering strategy and drilling risks’ mitigation. The differences between simulated and real-time UDAR inversion are mainly because of predrill uncertainties with regard to geological structure; nevertheless, predrill multidimensional UDAR simulations represent a good reference for well planning and for foreseeing critical geosteering decisions along the planned well path.