Appraising structural interpretations using seismic data—theoretical elements

Abstract : Structural interpretation of seismic images can be highly subjective, especially in complex geological settings. A single seismic image will often support multiple geologically valid interpretations. However, it is usually difficult to determine which of those interpretations are more likely than others. We refer to this problem as structural model appraisal herein. We propose the use of misfit functions to rank and appraise multiple interpretations of a given seismic image. Given a set of possible interpretations, we compute synthetic data for each structural interpretation, then compare these synthetic data against observed seismic data; this allows us to assign a data-misfit value to each structural interpretation. Our aim is to find data-misfit functions which enable a ranking of interpretations. To do so, we formalize the problem of appraising structural interpretations using seismic data and derive a set of conditions to be satisfied by the data-misfit function for a successful appraisal. We investigate both vertical seismic profiling and surface seismic configurations. An application of the proposed method to a realistic synthetic model shows promising results for appraising structural interpretations using vertical seismic profiling data, provided the target region is well illuminated. However, we find appraising structural interpretations using surface seismic data to be more challenging, mainly due to the difficulty of computing phase-shift data-misfits.
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Modeste Irakarama, Paul Cupillard, Guillaume Caumon, Paul Sava, Jonathan Edwards. Appraising structural interpretations using seismic data—theoretical elements. Geophysics, Society of Exploration Geophysicists, 2019, 84 (2), pp.N29-N40. ⟨10.1190/geo2018-0128.1⟩. ⟨hal-02136722⟩

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