SPEAKER: Michael Thiel -Schlumberger-Doll Research
Michael is a Principal Research Scientist at
Schlumberger-Doll Research Center in Cambridge, MA. He joined Schlumberger in
2010 after receiving his PhD in electrical engineering from the University of Michigan.
He is working at Schlumberger-Doll Research in Cambridge, MA, on inverse
problems and interpretation workflows for LWD directional resistivity
Abstract: The reservoir scale deep-directional electromagnetic (EM)
logging-while-drilling technology is now routinely being used to map boundaries
and fluid contacts for strategic geosteering, reservoir navigation, and more
recently, for reservoir characterization. Real-time data interpretation is
based on continuous inversion of a local 1D layered resistivity profile.
Traditional inversion approaches ignore the lateral changes of the reservoir,
which are contained in the measurements, only a longitudinal 2D representation
of the 3D reservoir structure around the well is provided. This limits the
ability to make real-time geosteering decisions with respect to lateral
reservoir heterogeneities, such as faults to the side of a horizontal well.
In this paper, we present a new inversion that can provide
deep 2D azimuthal resistivity images in a plane transverse to the wellbore;
thus, the new inversion is able to map lateral reservoir heterogeneities. The
minimally biased algorithm uses a nonuniform 2D pixel discretization of the
imaging plane, initially perpendicular to the near-horizontal well. This
algorithm takes advantage of the full 3D sensitivities of deep-directional
resistivity measurements to map the 2D resistivity distribution. A fast EM
simulator is used to reconstruct the tool response in complex 2D anisotropic
formations for arbitrary tool orientation. Adaptive regularization enforces
consistency and avoids data overfitting. Continuous azimuthal 2D imaging along
the well path generates a 3D map of the reservoir in the proximity of the
The inversion is initially validated using several
synthetic scenarios with various complexities. Subsequently, the algorithm is
applied to multiple field datasets, all of which resulted in the first 3D
reservoir maps derived from deep-directional resistivity measurements. Examples
include consistent imaging of faults parallel to the wellbore, and imaging when
the tool is approaching, crossing, and moving away from the faults. We also
present the azimuthal imaging of complex erosional surfaces over long well
sections, which can be used to construct a 3D model of the surface.
The new workflow is the first application of a 2D inversion
for full reservoir-scale azimuthal imaging using deep-directional resistivity
measurements, with no assumption about the scenarios. This workflow can be used
to populate 3D models of a subsurface formation. If applied in real time while
drilling, the workflow has the potential to significantly reduce drilling
hazards because it enables true 3D steering toward or away from lateral
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