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2D Reservoir Imaging Using Deep Directional Resistivity Meas

Deep directional electromagnetic (EM) logging-while-drilling technology is the principal enabler of proactive well placement. The reservoir-scale measurements are used to map boundaries and fluid contacts more than 30m away from the wellbore and to optimize well placement in increasingly more-complex scenarios. As the drilling progresses, deep directional resistivity (DDR) data are continuously inverted to estimate a 1D formation resistivity profile locally, and the inversion results are stacked to create a 2D reservoir map. This approach is adequate if the formation is layered and slowly varying laterally. However, in complex reservoir scenarios with locally 2D or 3D structures or where the formation changes abruptly, the 1D approximation used in real-time inversion may not be the most accurate solution.

We introduce a new, minimally biased pixel-based inversion to accurately map 2D complex reservoir structures. The inversion uses a 2.5D EM simulator, makes no assumption about the reservoir model, and is able to image non-1D geological structures, such as faults, sand injectites, shale lenses, and other complex geometries with arbitrary anisotropic resistivity distributions. An adaptive regularization ensures that the most plausible resistivity distribution with the least resistivity variation, consistent with the data, is found. The algorithm is parallelized to run on a cluster and is feasible for real-time application, provided relatively moderate c omputational resources are available.

The new reservoir maps derived from the 2D inversion enable more quantitative and informed well-placement decisions, deliver detailed insight about the reservoir structure, and allow a precise refinement of existing reservoir models.
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