Implementation of multivariate clustering methods for characterizing discontinuities data from scanlines and oriented boreholes

Zhou, Wendy; Maerz, Norbert H.

doi:10.1016/s0098-3004(01)00111-x

Cited by 53 publications

(18 citation statements)

References 18 publications

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“…Cluster analysis of fracture orientation provides a transparent means of separating fracture orientation data into sets, as proposed by Shanley and Mahtab []. Agglomerative, K ‐means, and fuzzy K ‐means clustering have been used to analyze orientation data derived from scanline measurements, predominantly for engineering purposes [e.g., Hammah and Curran , , ; Zhou and Maerz , ; Tokhmechi et al , ; Li et al , ] but rarely for reservoir borehole data interpretation.…”

Section: Introductionmentioning

confidence: 99%

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

et al. 2017

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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.

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Section: Introductionmentioning

confidence: 99%

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

et al. 2017

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“…Although there are several methods to identify the discontinuity sets, the process highly depends on expert judgment and is very subjective (Priest 1993, Grenon & Mukendi 2012. To reduce the subjectiveness of such analysis, numerical algorithms are suggested and widely used (Shanely & Mahtab 1976, Mahtab & Yegulalp 1982, Fisher et al 1993, Zhou & Maerz 2002.…”

Section: Conventional Methodsmentioning

confidence: 99%

Probabilistic assessment of rock slope stability using response surfaces determined from finite element models of geometric realizations

Shamekhi

Tannant

2015

Computers and Geotechnics

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“…The open source Orient and Stereonet softwares by Vollmer (2018) and Allmendinger (2015) provide uncertainty estimates of structural data using spherical statistics, while Davis and Titus (2017) and Roberts et al (2019) used spherical distributions to estimate confidence intervals about uncertain structural orientation measurements of folds and foliations. The analysis of anisotropic orientation uncertainty in structural geology is well established with Zhou and Maerz (2002), Peel et al (2001), Carmichael and Ailleres (2016) and Davis and Titus (2017) applying it to joint set identification, structural data clustering and foliation-lineation characterization. While Pakyuz-Charrier et al 2018ashowed clearly that the dip angle and dip azimuth should not be simulated independently as scalar values, it is apparent that the uncertainty affecting each of these aspects of the structural orientation need not be equal.…”

Section: Spherical Probability Distributionsmentioning

confidence: 99%

Uncertainty assessment for 3D geologic modeling of fault zones based on geologic inputs and prior knowledge

Krajnovich¹,

Zhou²,

Gutierrez³

2020

Preprint

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Abstract. Characterizing the zone of damaged and altered rock surrounding a fault surface is highly relevant to geotechnical and reservoir engineering works in the subsurface. Evaluating the uncertainty associated with 3D geologic modeling of these fault zones is made possible using the popular and flexible input-based uncertainty propagation approach to geologic model uncertainty assessment – termed Monte Carlo simulation for uncertainty propagation (MCUP). To satisfy the automation requirements of MCUP while still preserving the key geometry of fault zones in the subsurface, a clear and straightforward modeling approach is developed based on four geologic inputs used in implicit geologic modeling algorithms (surface trace, structural orientation, vertical termination depth and fault zone thickness). The rationale applied to identifying and characterizing the various sources of uncertainty affecting each input are explored and provided using open-source codes. In considering these sources of uncertainty, a novel model formulation is implemented using prior geologic knowledge (i.e., empirical and theoretical relationships) to parameterize modeling inputs which are typically subjectively interpreted by the modeler (e.g., vertical termination depth of fault zones). Additionally, the application of anisotropic spherical distributions to modeling disparate levels of information available regarding a fault zone's dip azimuth and dip angle is demonstrated, providing improved control over the structural orientation uncertainty envelope. The MCUP formulation developed is applied to a simple geologic model built from historically available geologic mapping data to assess the independent sensitivity of each modeling input on the combined model uncertainty, revealing that vertical termination depth and structural orientation uncertainty dominate model uncertainty at depth while surface trace uncertainty dominates model uncertainty near the ground surface. The method is also successfully applied to a more complex model containing intersecting major and minor fault zones. The impacts of the model parameterization choices, the fault zone modeling approach and the effects of fault zone interactions on the final geologic model uncertainty assessment are discussed.

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Implementation of multivariate clustering methods for characterizing discontinuities data from scanlines and oriented boreholes

Cited by 53 publications

References 18 publications

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

Probabilistic assessment of rock slope stability using response surfaces determined from finite element models of geometric realizations

Uncertainty assessment for 3D geologic modeling of fault zones based on geologic inputs and prior knowledge

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