The in situ stress and elastic rock properties are first order controls on fracture stimulation behavior and consequently production. Understanding these properties at offset locations can facilitate optimal well placement and completion design.

To achieve this objective, a coupled geomechanical and seismic inversion workflow has been developed. The workflow consists of building a calibrated 1D geomechanical model at the well locations using elastic log data, observations from image logs and the poro-elastic equations. The 1D model is then up-scaled to seismic resolution to assess the feasibility of utilizing properties derived from a seismic inversion. An innovative pre-stack facies-based seismic inversion process, capable of producing physical estimates of impedances and density, is used to invert the seismic dataset for facies and elastic properties. The geomechanical model is then applied to elastic properties derived from the inversion to build an analytical 3D geomechanical solution.

The correlation between inverted elastic properties and up-scaled log data was considered very good. After applying the geomechanical model to 3D elastic properties derived from the inversion, a zone of low fracture initiation pressure and high stress anisotropy was identified at Well A. This zone correlates with an interval where a high concentration of drilling-induced tensile fractures is observed on an FMI image log. While the zone of low fracture initiation pressure is observed to extend laterally from Well A, the predicted initiation pressure increases in the vicinity of Well B. Image log data from Well B shows a significant reduction in the occurrence of drilling induced tensile fractures within the laterally equivalent interval. These observations from image logs provide independent validation of the 3D geomechanical model and in turn, the accuracy of the inverted elastic property volumes. The results can be used to understand fracture behavior - including stress anisotropy, initiation pressures, fracture barriers, and potential height growth – at any potential well location within the data volume.