Abstract

The current state of the art for development of unconventional projects integrates geology, geophysics, and engineering into a comprehensive reservoir description. To that end, we have designed a comprehensive geophysical workflow to define the structure, stratigraphy, and rock mechanics of a stacked reservoir sequence in the west-central Midland Basin. The purpose of this paper is to describe the workflow. Portions of three seismic data sets were merged and processed anisotropically, preserving the full range of azimuths. Well control consisted of 35 compressional sonic logs, eight shear sonic logs, three sonic scanners, two lateral formation microimaging tools, and three cores. Nine newly drilled laterals are on production along with a large number of vertical legacy wells. Prestack inversion produced acoustic impedance, shear impedance, and density with good accuracy, although the compressional-to-shear-velocity ratio (VP/VS) was not stable. This volume was successfully recreated via neural net, which was also used to calculate total porosity and total water saturation volumes. Poisson's ratio, Young's modulus, and brittleness were created using standard equations and the neural net VP/VS volume. Structural attributes consisted of ant track, coherence, semblance, fault probability, and Kmin and Kmax curvature. The final step in this portion of the workflow was to create a high-resolution depth conversion velocity volume. A geocellular grid was built and populated with petrophysical volumes, lithology facies, and structural attributes. Principal stresses were incorporated by first establishing 1D mechanical earth models (MEMs) where appropriate log suites were available. These 1D MEMs were extended to a 3D MEM, although confidence in this volume is not high due to known pore pressure and closure stress reductions as a result of legacy vertical well production. Calibration incorporating new data as it becomes available is an ongoing task. An informative simulation using the MEM is frac models, which define the most optimal landing points for laterals. This MEM and the simulations it can perform have easily demonstrated the value of this integrated workflow.

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