Impacts of data sampling on the interpretation of normal fault propagation and segment linkage

Ze Tao,Tiago M Alves

doi:10.1016/j.tecto.2019.03.013

Abstract

Throw-distance (T-D) and throw-depth (T-Z) plots are widely used by researchers and industry to examine the growth of normal faults. This study uses high-quality three-dimensional (3D) seismic and outcrop information to review the effect of data sampling on the interpretation of normal fault growth. The results show that the accuracy of T-D and T-Z data, and of resulting fault slip tendency and leakage factor analyses, are dependent on the sampling strategy followed by interpreters and field geologists, i.e. on a Sampling Interval/Fault Length Ratio (δ) for discrete structures. In particular, this work demonstrates that significant geometric changes in T-D plots occur when a Module Error (εi) for the ratio δ is larger than 6%–9% for faults of all scales and growth histories. This implies that a minimum number of measurements should be gathered on discrete faults to produce accurate T-D and T-Z plots, and that the number of measurements is dependent on fault length. With no prior knowledge of fault segmentation, a δ value of 0.05 should be applied when interpreting faults to fulfil the pre-requisite of a ɛi < 6–9%. In all faults analysed, slip tendency and leakage factors were systematically misrepresented with increasing δ values. To disregard the limits proposed in this work results in: 1) a systematic underrepresentation of the isolated fault growth model, 2) a systematic misrepresentation of fault geometries and related damage zones, 3) the collation of erroneous fault scaling relationships, and 4) ultimately, unreliable interpretations of fault sealing properties. Hence, this work presents a new tool for interpreters and structural geologists to understand the sampling strategies necessary to obtain accurate fault throw and displacement data at different scales of analysis.

Highlights

In ‘constant length’ models, faults establish their near-final length at an early stage of their evolution, a phenomenon that is followed by predominant fault propagation in a vertical direction, e.g. dip-linkage reactivation (Cartwright et al, 1995)
In terms of the Sampling Interval/Fault Length Ratio δ, our results show that a threshold value of 0.1 is valid for isolated, discrete faults of all scales, i.e. data sampling should occur at a spacing of < 10% the fault length in order to obtain accurate T-D data for faults composed of only one fault segment (Fig. 9)
The parameter Module Error reflects the effect of distinct sampling intervals on the accuracy of fault geometry measured through T-D plots

Summary

Introduction

Two end-member models explaining the growth of normal faults are the ‘isolated’ (Childs et al, 1995; Walsh et al, 2003), and ‘constant length’ fault models (Cartwright et al, 1995; Cowie and Scholz, 1992; Jackson and Rotevatn, 2013; Morley et al, 1990; Morley, 1999; Rotevatn et al, 2018; Walsh et al, 2002). When dealing with fault arrays, geometrical and kinematic coherence can be achieved for distinct fault segments through a combination of growth histories and geometries (Walsh et al, 2003; Mason et al, 2016). This means, in practice, that coherent faults can record discrete segments that grow, at smaller scales, following any of four growth models: ‘isolated’, ‘coherent’ through lateral linkage, ‘coherent’ through dip linkage and ‘constant length’ models

Objectives

Methods

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Discussion

Conclusion