Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

Abstract

©2017. American Geophysical Union. All Rights Reserved. Acoustic borehole televiewer (BHTV) logs provide measurements of fracture attributes (orientations, thickness, and spacing) at depth. Orientation, censoring, and truncation sampling biases similar to those described for one-dimensional outcrop scanlines, and other logging or drilling artifacts specific to BHTV logs, can affect the interpretation of fracture attributes from BHTV logs. K-means, fuzzy K-means, and agglomerative clustering methods provide transparent means of separating fracture groups on the basis of their orientation. Fracture spacing is calculated for each of these fracture sets. Maximum likelihood estimation using truncated distributions permits the fitting of several probability distributions to the fracture attribute data sets within truncation limits, which can then be extrapolated over the entire range where they naturally occur. Akaike Information Criterion (AIC) and Schwartz Bayesian Criterion (SBC) statistical information criteria rank the distributions by how well they fit the data. We demonstrate these attribute analysis methods with a data set derived from three BHTV logs acquired from the high-temperature Rotokawa geothermal field, New Zealand. Varying BHTV log quality reduces the number of input data points, but careful selection of the quality levels where fractures are deemed fully sampled increases the reliability of the analysis. Spacing data analysis comprising up to 300 data points and spanning three orders of magnitude can be approximated similarly well (similar AIC rankings) with several distributions. Several clustering configurations and probability distributions can often characterize the data at similar levels of statistical criteria. Thus, several scenarios should be considered when using BHTV log data to constrain numerical fracture models.

Numerical Modelling of Convection-Driven Cooling, Deformation and Fracturing of Thermo-Poroelastic Media

“…The relatively large apertures required to permit convection cells within fractures have been reported, e.g. in New Zealand, Soultz in France and Cajon Pass site in USA (Massiot et al 2017;Genter and Traineau 1996;Barton and Zoback 1992) and measurements from the Reykjanes geothermal field in Iceland suggest similar values (Keilegavlen et al 2020). The boundary traction is the same as for the previous example, and the simulation time is 70 years.…”

Paleo‐Permeability Structure of the Crustal Section of the Samail Ophiolite Based on Automated Detection of Veins in X‐Ray CT Core Images From the Oman Drilling Project

“…Note that because the probability that a particular vein (or fracture) is intersected by a borehole depends on its orientation, sampling of planar discontinuities intersecting the core creates a bias in the apparent abundance of the orientations (Martel, 1999; Massiot et al., 2012; Terzaghi, 1965). For example, veins that are sub‐parallel to the borehole axis are less likely to intersect the borehole, leading to a systematic underestimation of the sample size of such veins.…”

From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers

“…Dynamic high‐resolution measurement techniques have led to drastic increases in data quantity that the incoming data streams are too large to be stored, transmitted, or analyzed within reasonable time periods. To solve this issue in the domain of borehole log analyses, a wide variety of statistical approaches (clustering, multivariate analyses, artificial intelligence algorithms) has been developed to extend the classical fracture detection, density, geometry, and various attributes analyses from image logs (Dong et al., 2020; Massiot et al., 2017; Zazoun, 2013; X. F. Zhang et al., 2011). These techniques enable advanced corrections from the inherent sampling bias related to borehole logging and provide probability laws for building different near borehole DFNs equiprobable scenarios.…”