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A workflow for 3D stochastic modeling of salt from seismic images

Abstract : Interpreting salt is a complex and time consuming task in seismic interpretation. Considerable progresses have been made recently by automatic methods which detect deterministic salt tops from the seismic image. However, uncertainties about salt exist, owing to intrinsic physical limitations of seismic imaging. Therefore, we propose a new workflow to generate several possible models of salt top surfaces with varying geometries and topologies. The method we propose is divided into three steps. We first segment the seismic volume into three regions: salt, sediments and uncertain, depending on the reliability of the automatic interpretation. We then compute a monotonic scalar field in the uncertain region, ranging from zero at the contact with salt to one at the contact with sediments. We finally generate a random field bounded between zero and one. The salt boundary is implicitly defined by the zero isovalue of the scalar field defined as the difference between the distance and the random fields. Applications of this workflow on a 2D seismic image and a 3D synthetic data set illustrate the potential of the method to efficiently address salt interpretation uncertainties.
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Submitted on : Thursday, June 28, 2018 - 11:12:02 AM
Last modification on : Wednesday, November 3, 2021 - 7:23:27 AM
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  • HAL Id : hal-01825267, version 1


Nicolas Clausolles, Pauline P. Collon, Guillaume Caumon. A workflow for 3D stochastic modeling of salt from seismic images. 80th EAGE Conference and Exhibition 2018, Jun 2018, Copenhagen, Denmark. 2018. ⟨hal-01825267⟩



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