Tectonic interpretation of the connectivity of a multiscale fracture system in limestone

This paper studies the statistics and tectonism of a multiscale natural fracture system in limestone. The fracture network exhibits a self‐similar characteristic with a correlation between its power law length exponent a and fractal dimension D, i.e., a ≈ D + 1. Contradicting the scale‐invariant connectivity of idealized self‐similar systems, the percolation state of trace patterns mapped at different scales and localities of the study area varies significantly, from well to poorly connected. A tectonic interpretation based on a polyphase fracture network evolution history is proposed to explain this discrepancy. We present data to suggest that the driving force for fracture formation may be dissipated at the end of a tectonic event when the system becomes connected. However, the “effective” connectivity can successively be reduced by cementation of early fractures and reestablished by subsequent cracking, rendering a variable “apparent” connectivity that can be significantly above the percolation threshold.ISSN:0094-8276ISSN:1944-800

Sparsistency and agnostic inference in sparse PCA

The presence of a sparse "truth" has been a constant assumption in the theoretical analysis of sparse PCA and is often implicit in its methodological development. This naturally raises questions about the properties of sparse PCA methods and how they depend on the assumption of sparsity. Under what conditions can the relevant variables be selected consistently if the truth is assumed to be sparse? What can be said about the results of sparse PCA without assuming a sparse and unique truth? We answer these questions by investigating the properties of the recently proposed Fantope projection and selection (FPS) method in the high-dimensional setting. Our results provide general sufficient conditions for sparsistency of the FPS estimator. These conditions are weak and can hold in situations where other estimators are known to fail. On the other hand, without assuming sparsity or identifiability, we show that FPS provides a sparse, linear dimension-reducing transformation that is close to the best possible in terms of maximizing the predictive covariance.Comment: Published in at http://dx.doi.org/10.1214/14-AOS1273 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

A new approach to upscaling fracture network models while preserving geostatistical and geomechanical characteristics

A new approach to upscaling two-dimensional fracture network models is proposed for preserving geostatistical and geomechanical characteristics of a smaller-scale “source” fracture pattern. First, the scaling properties of an outcrop system are examined in terms of spatial organization, lengths, connectivity, and normal/shear displacements using fractal geometry and power law relations. The fracture pattern is observed to be nonfractal with the fractal dimension D ≈ 2, while its length distribution tends to follow a power law with the exponent 2 < a < 3. To introduce a realistic distribution of fracture aperture and shear displacement, a geomechanical model using the combined finite-discrete element method captures the response of a fractured rock sample with a domain size L = 2 m under in situ stresses. Next, a novel scheme accommodating discrete-time random walks in recursive self-referencing lattices is developed to nucleate and propagate fractures together with their stress- and scale-dependent attributes into larger domains of up to 54 m × 54 m. The advantages of this approach include preserving the nonplanarity of natural cracks, capturing the existence of long fractures, retaining the realism of variable apertures, and respecting the stress dependency of displacement-length correlations. Hydraulic behavior of multiscale growth realizations is modeled by single-phase flow simulation, where distinct permeability scaling trends are observed for different geomechanical scenarios. A transition zone is identified where flow structure shifts from extremely channeled to distributed as the network scale increases. The results of this paper have implications for upscaling network characteristics for reservoir simulation