The Identification of Fault Pattern Fractals for Improved Oil and Gas Recovery: A New Process to Identify and Describe Fault Sets Using Non-Linear Methods

Abstract

Unexpected faults are a serious production problem in numerous, complex and compartmentalised oil and gas fields, and are often the single most important restraint on recovery. Fractal mathematics has demonstrated a surprising degree of order in many natural, apparently random systems. It has been shown that fault patterns exhibit a similar order which could be used to indicate the presence of structures missed in the original interpretation of the seismic data and to predict faults below the approximate 20 m limit of seismic resolution. The potential for greater clarity and resolution opened up by this method may greatly aid field description and reservoir production. We will discuss the development of a comprehensive fault pattern characterisation quantatively with a set of parameters arising from non-linear methods of analysis. This allows for the standardised comparison of seismic interpretations and a precise method for testing interpretations from the same dataset. We will show how fractal mathematics may give a measure of the density of the fault set, the number of faults below the limit of seismic resolution, resolve small fault clusters below the limit of seismic resolution and aid in the description and analysis of fault sets.