Reservoir characterization

Data-Driven Tool Uses Amplitude-Based Statistics To Identify Seismic Fractures

The authors present a novel data-driven tool for fast fracture identification in post-stack seismic data sets.

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Data-analysis tools for extracting information about critical subsurface features such as fractures are still evolving. Traditional methods rely on time-consuming iterative work flows, which involve computing seismic attributes, denoising, and expert interpretation. Additionally, the increasingly widespread acquisition of time-lapse seismic surveys has led to heightened demand for reliable automated work flows to assist in deriving feature interpretation from seismic data. The authors present a novel data-driven tool for fast fracture identification in post-stack seismic data sets.

Introduction

The paper develops an automated work flow for fast and robust fracture identification that directly uses seismic amplitude data as input.

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