Distributed acoustic sensing (DAS) acquisition in borehole environments has seen rapid growth recently. However, the majority of DAS imaging applications convert native strain observations to the equivalent displacement or velocity measurements in order to be compatible with conventional seismic data processing. In contrast, we formulate elastic least-square reverse time migration (ELSRTM) with the energy norm imaging condition for native DAS strain data. ELSRTM provides an accurate representation of the elastic subsurface through reduction of artifacts due to acquisition and inaccurate wavefield extrapolation. We validate the ELSRTM DAS formulation on a field dataset from the Eagle Ford shale formation. Our method not only attenuates artifacts caused by limitations of acquisition geometry and nonphysical wave modes, but also provides relative amplitudes of the subsurface reflectors that match the recorded data and enable reservoir characterization.

Presentation Date: Tuesday, September 17, 2019

Session Start Time: 1:50 PM

Presentation Time: 2:15 PM

Location: 221C

Presentation Type: Oral

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