[First Hit]

AAPG Latin America and Caribbean Region Geoscience Technology Workshop

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High-resolution classification of subsurface features Previous HitfromNext Hit directional image gathers, based on Principal Component Analysis and Deep Learning methods

Abstract

Specular/Previous HitdiffractionNext Hit imaging has proven to be an attractive approach to providing high-resolution subsurface images containing different types and scales of continuous and discontinuous geometrical objects. However, there is a strong need in exploration and production to continue investigating a direct method for detecting and characterizing fractures and other small-scale reservoir heterogeneities that would impact understanding of the reservoir’s producibility. Seismic response Previous HitfromNext Hit such small-scale structural and lithological elements in the subsurface is encoded in the Previous HitdiffractionNext Hit part of the total wavefield. As part of the ongoing effort to enhance procedures for interpreting/classifying directivity-driven image data, we present a Deep Learning (DL) approach to this challenging task. Preliminary results indicate great promise in using this emerging technology. It enables structural features, such as small-scale faults pinchouts and fractures, to be more readily and reliably localized, identified and characterized on the Previous HitdiffractionTop images.