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The influence of resolution on scale-dependent clustering in fracture spacing data

Ankur Roy, Atilla Aydin and Tapan Mukerji
The influence of resolution on scale-dependent clustering in fracture spacing data
Interpretation (Tulsa) (August 2016) 4 (3): T387-T394


It is a common practice to analyze fracture spacing data collected from scanlines and wells at various resolutions for the purposes of aquifer and reservoir characterization. However, the influence of resolution on such analyses is not well-studied. Lacunarity is a parameter that is used for multiscale analysis of spatial data. In quantitative terms, at any given scale, it is a function of the mean and variance of the distribution of masses captured by a gliding a window of that scale (size) across any pattern of interest. We have described the application of lacunarity for delineating differences between scale-dependent clustering attributes of data collected at different resolutions along a scanline. Specifically, we considered data collected at different resolutions from two outcrop exposures, a pavement and a cliff section, of the Cretaceous turbititic sandstones of the Chatsworth Formation widely exposed in southern California. For each scanline, we analyzed data from low-resolution aerial or ground photographs and high-resolution ground measurements for scale-dependent clustering attributes. High-resolution data show larger values of scale-dependent lacunarity than their respective low-resolution counterparts. We further performed a bootstrap analysis for each data set to test for the significance of such clustering differences. We started with generating 300 realizations for each data set and then ran lacunarity analysis on them. It was seen that lacunarity for higher resolution data set lay significantly outside the upper 90th percentile values, thus proving that higher resolution data are distinctly different from random and fractures are clustered. We have therefore postulated that lower resolution data capture fracture zones that had relatively uniform spacing, whereas higher resolution data capture thin and short splay joints and sheared joints that contribute to fracture clustering. Such findings have important implications in terms of understanding organization of fractures in fracture corridors, which in turn is critical for modeling and upscaling exercises.

ISSN: 2324-8858
EISSN: 2324-8866
Serial Title: Interpretation (Tulsa)
Serial Volume: 4
Serial Issue: 3
Title: The influence of resolution on scale-dependent clustering in fracture spacing data
Affiliation: Stanford University, Energy Resources Engineering, Green Earth Sciences, Stanford, CA, United States
Pages: T387-T394
Published: 201608
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 26
Accession Number: 2017-002804
Categories: Structural geology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 1 table
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2017, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States. Reference includes data supplied by Society of Exploration Geophysicists, Tulsa, OK, United States
Update Code: 201703
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