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At Eni, we routinely apply a workflow named T\Frac, based on lineaments extraction from structural seismic attributes. Lineaments are statistically analysed and merged in planar 3D features to obtain a Discrete Fracture Network (DFN).
We present an application of the T\Frac workflow and DFN building in offshore Gulf of Mexico, which led to a reservoir model that matches well tests and offers further indications for the placement of development wells. Nevertheless, even if Eni’s approach to the study of fractures networks (FNs) was successfully applied on the main fractured reservoirs operated by Eni, the FNs modelling still has intrinsic limits. In facts, while micro-fractures are studied from oriented cores, and faults are mapped from seismic data, a direct tool to study meso-fractures (10s to 100s meters length) in the subsurface is still missing. The use of seismic attribute in the T\Frac workflow is one way to bridge this gap, but the implementation with outcrop analogues data would represent a key element for accurately modelling DFNs and predicting fluid flow for successful field development. Hence, the workflow will be further improved by including quantitative analysis of FNs at the meso-scale from the outcrop data.