A workflow for the characterization of fracture networks from 3D reprocessed seismic data using non local means filter

Abstract

The Dinantian carbonate platforms in Northern Netherlands are marked as potential reservoirs for Ultra Deep Geothermal Energy (UDG). Permeability and therefore flow in these reservoirs is thought to be primarily defined by natural fracture networks. For the purpose of UDG, an analysis is made of the fracture network characteristics of the Dinantian Friesland platform. Due to recent developments in reprocessing of 3D seismic data and fault extraction algorithms, a first attempt is made to determine fracture network characteristics from 3D reprocessed seismic data. First, the 3D seismic data is filtered by the non local means (NLM) algorithm, using different filter parameter combinations. By doing so we aim to determine the influence of the filter settings on the characteristics of the fracture networks, extracted from the data. We are especially interested to see if by filtering the data, small fractures are removed in addition to noise. Next, the Petrel ant track workflow is used as sampling method for automatic detection and extraction of fractures, which are exported as fault stick files. A program is built to calculate fracture attributes, such as barycenter coordinates, strike, azimuth, dip, length, offset and aspect ratios. These fracture attributes are then used for fracture network characterization, computing fracture length distributions, clustering and orientation distributions. To quantify the scale invariance of the fracture network, we aim to find power law behavior in the fracture network attributes of length and spatial distribution, such that it fits Davy et al.’s (2010) double power law: n(l,L) = α L^D l^(-a) . Length exponent a is determined via computing the density-length distribution and the fractal dimension D using the pair-correlation function. Power law behavior is found for the fracture length distribution below the truncation cut-off, with varying length exponents a depending on the NLM parameters used: 3.59 < a < 4.57. However, the fracture length distribution is more sensitive to the Petrel attribute settings than to the NLM filter parameters. This implies a large uncertainty on the results. Furthermore, the sampling method (Petrel ant track workflow) is found to be unsuitable for detection of fractal behavior (D), due to the limits of seismic resolution.