Revealing Subsurface Structures in Ultra-High Definition With UDAR (Ultradeep Azimuthal Resistivity) Measurements – A Case Study From Brazil

This paper discusses a novel deep and ultradeep azimuthal resistivity (DAR and UDAR) inversion workflow utilizing an advanced parametric/hybrid inversion algorithm. It has been optimized to deliver ultrahigh-definition (UHD) results in real-time with an increased capability to resolve thin layers down to 1 m and improved depth of detection (DOD). We will demonstrate the results through a case history from a well located in an offshore field in Brazil, owned by a national oil company (NOC). The new inversion workflow integrates DAR and UDAR measurements into discrete subsets according to the objective, whether that is either focusing on proactive reservoir navigation or geomapping. Then, the implementation of parameter domain scanning and forward modeling, supported by remote high-performance cluster computation, ensures results are delivered to support real-time decision making. The presence of two-dimensional (2D) influences on the inversion results are identified via data misfit and azimuthal signal differences from a range of frequencies. Where this difference is significant, a hybrid 2D inversion is applied leveraging artificial intelligence methods like artificial neural network (ANN) and a hybrid parametric inversion with the outputs’ visualization in both 2D and three-dimensional (3D) space. In 3D, the data can be displayed in several visualizations from 2D transverse and 2D longitudinal inversion profiles along the well path, within a depth window, to a 3D volumetric depiction of the resistivity model. This is done by converting the 2D inversion results into a 3D voxel-based model to quickly determine volumetric data. The 3D resistivity voxel model can then be interrogated to identify subsurface geological features at varying scales. This new approach was deployed in two horizontal oil producers and two water injectors to simultaneously conduct proactive reservoir navigation based on the high resolution of UHD inversions, while also supporting geomapping objectives by delineating remote boundaries, defining layer thickness and channel geometry, as well as apparent formation dip and petrophysics properties. These multiple objectives were achieved in real time, performing computations on a high-performance cluster. The results of UHD inversions are compared directly to high-resolution electrical resistivity images, and the resultant image interpretation illustrates good corroboration of boundary delineation and apparent formation dip of the two independent measurements. Therefore, the extrapolation of the geological interpretation from wellbore-centric to reservoir scale can be supported, providing a more field-focused analysis to deliver on fluid volumes, channel body geometry, and fault orientation at the reservoir scale. The enhancement of the real-time interpretation and strategic reservoir navigation is achieved through this new approach and delivers increased confidence in the geological interpretation of UDAR inversions and structural dips based on the deeper depths of detection delivered by ultrahigh-definition mapping. These developments support detailed analysis/interpretation of UDAR inversions in complex reservoirs with improved lateral continuity, early feature detection, and enhanced thin layer delineation possible.