Is My Completions Engineer Provided with the Correct Petrophysical and Geomechanical Properties Inputs?
Authors: Gaillot Philippe , Crawford Brian , Liang Yueming , Alramahi Bashar 
Published: November 2020

To effectively simulate the performance of unconventional wells, it is essential to incorporate sufficient geological complexity to allow for realistic variability in the petrophysical and mechanical properties controlling the productivity of the effective stimulated rock volume. The heterogeneous and strongly layered nature of unconventional reservoirs requires appropriate representation of the high intra-bed contrast in anisotropic deformation and flow behavior, and the representation of pre-existing mechanical discontinuities (faults, bedding planes and natural fractures) in terms of mechanical and hydraulic coupling. These fundamental requirements cannot be achieved unless a high-vertical resolution petrophysical and geomechanical model is developed.

As demonstrated in this paper, without integration of high (cm-scale) vertical resolution data such as borehole images and core X-ray computed tomography (CT) images, standard meter-scale petrophysical and geomechanical outputs typically used for Hydraulic Fracture (HF) and flow modeling are, at best, standard scalar log (~m-scale) average compositional volume-weighted representations of subsurface reality, that can be highly misleading when considering that mechanical and flow properties are actually ultimately controlled by fine-scale contrasts and extremes, rather than by arithmetic composition weighted averages.

This paper presents an integrated workflow to model mechanical properties at sufficiently high resolution (cm-scale) to accurately honor rock fabric and its effects on HF (height and complexity) and therefore on production. The workflow relies on (1) a novel experimental geomechanics technique and associated analytical solutions to derive poroelastic anisotropy (Young's modulus, Poisson's ratio and Biot's coefficient in the bed-normal and bed-parallel directions) and (2) a joint, high vertical resolution, multi-physics petrophysical model relying itself on (2.1) a standard vertical (m-scale) resolution multi-physics log-based petrophysical output (average composition) automatically redistributed into a high vertical resolution well framework by using (2.2) local constraints from high-resolution data (borehole resistivity image and core dual energy X-ray CT images) coupled with neuronal-network derived core empirical relationships. Core-scale poroelastic predictors defined in (1) are then propagated into (2) to get high vertical resolution geomechanical properties and sub-surface stresses.

Beyond providing appropriate inputs to HF modeling, this high vertical resolution well framework enables (i) detailed well-scale calibration and recognition of facies and stacking patterns; (ii) accurate and core-calibrated geochemical, petrophysical and geomechanical characterization of individual beds, and (iii) identification and characterization of discontinuities, in general, and interfaces between beds, in particular. Once upscaled, outputs of this workflow enable a more realistic borehole-view of reservoir quality, fluid flow units and geomechanical stratigraphy – all key information to a more optimal asset development.