Mitigation of overburden effects in fracture prediction using azimuthal AVO analysis: An example from a Middle East carbonate field

Abstract

The ability to identify fracture clusters and corridors and their prevalent direction within many carbonates and unconventional shale gas/tight gas reservoirs may have a significant impact on field development planning as well as on the placement of individual wells. We believe seismic fracture prediction provides the best opportunity to identify the spatial distribution of fracture corridors, but the reliability of seismic fracture detection technology is constantly being questioned. The criticism results from the degree to which the acquisition footprint, random and coherent noise in the seismic data, and near-surface/overburden issues affect extracted seismic “fracture” attributes. Therefore, a key issue is the separation of artifacts caused by the acquisition footprint and near-surface or overburden anisotropy/structural variations from the anomalies caused by the presence of fractures.

Fracture Characterization by Integrating Seismic-Derived Attributes including Anisotropy and Diffraction Imaging with Borehole Fracture Data in an Offshore Carbonate Field, United Arab Emirates

“…This may explain the stacked anisotropy anomalies that are observed in Figure 6. Overburden effects have been noted by Liu et al (2011); Ikawa and Mercado (2010); and Luo et al (2007). Note that in a recent publication, Liu et al (2015) have performed 3D synthetic study of estimating the fracture density of small-scale vertical fractures when large-scale vertical fractures are present.…”

“…Additionally, the calculation of the direction of the seismic anisotropy has an inherent 90°ambiguity, such that azimuth 45°could equally be azimuth 135°. Note that seismic anisotropy azimuth is potentially influenced by the acquisition orientations, which for this survey is N27°E (inline) and N117°E (crossline), and was addressed in the previous study (Liu et al, 2011). Note that the south area tends to have high fracture density where anisotropy magnitude is also large.…”

“…We can either use azimuth velocity-based attributes (low resolution) or azimuth amplitudebased attributes (high resolution) to infer relative anisotropy magnitude (a proxy for fracture intensity) and anisotropy orientation (a proxy for fracture orientation). In our previous study (Liu et al, 2011), azimuthal amplitude variation was used, and we found that the overburden effect was identified as one of the major influencing factors affecting the reliability of fracture interpretation in the targets (Ikawa and Mercado, 2010;Liu et al, 2011). The seismic anisotropy magnitude was computed over intervals for the major reservoirs defined by the seismic interpretation surfaces.…”

“…Good quality seismic data is critical for quantitative analysis and for using the data for development well design, and production observation analysis. In our previous study (Liu et al, 2011), we focused on a subset of 3D prestack data (6.5ϫ9km 2 ), and concluded that the reprocessed data are of sufficient quality for fracture characterization using the technology based on azimuthal anisotropy. …”

Fundamental controls on fluid flow in carbonates: current workflows to emerging technologies

“…This uncertainty falls into two separate but linked categories: first, the spatio-temporal distribution of Liu et al 2011;Liu & Martinez 2013). The rose diagrams represent the azimuths of fracture strikes determined from well data (core and Formation Micro-Imager log (FMI)).…”