Seismic anisotropy in a hydrocarbon field estimated from microseismic data

Abstract

The study of seismic anisotropy in exploration seismology is gaining interest as it provides valuable information about reservoir properties and stress directions. In this study we estimate anisotropy in a petroleum field in Oman using observations of shear‐wave splitting from microseismic data. The data set was recorded by arrays of borehole geophones deployed in five wells. We analyse nearly 3400 microearthquakes, yielding around 8500 shear‐wave splitting measurements. Stringent quality control reduces the number of reliable measurements to 325. Shear‐wave splitting modelling in a range of rock models is then used to guide the interpretation. The difference between the fast and slow shear‐wave velocities along the raypath in the field ranges between 0–10% and it is controlled both by lithology and proximity to the NE‐SW trending graben fault system that cuts the field formations. The anisotropy is interpreted in terms of aligned fractures or cracks superimposed on an intrinsic vertical transversely isotropic (VTI) rock fabric. The highest magnitudes of anisotropy are within the highly fractured uppermost unit of the Natih carbonate reservoir. Anisotropy decreases with depth, with the lowest magnitudes found in the deep part of the Natih carbonate formation. Moderate amounts of anisotropy are found in the shale cap rock. Anisotropy also varies laterally with the highest anisotropy occurring either side of the south‐eastern graben fault. The predominant fracture strikes, inferred from the fast shear‐wave polarizations, are consistent with the trends of the main faults (NE‐SW and NW‐SE). The majority of observations indicate subvertical fracture dip (>70°). Cumulatively, these observations show how studies of shear‐wave splitting using microseismic data can be used to characterize fractures, important information for the exploitation of many reservoirs.

Fracture characterization using frequency-dependent shear wave anisotropy analysis of microseismic data

“…The fracture strike (α) should be constrained in the model to limit the free parameters in the inversion to fracture density (ξ) and radius ( a f ). However, we included it in the inversion because it is not well constrained from the observations of ordinary SWS (Al‐Harrasi et al 2010) due to the limited ray coverage in the vertical plane. The available observations show fractures oriented in multiple directions, reflecting the structural complexity of the field illustrated in Fig.…”

“…δ t is then estimated while searching over a narrow range of ± 10° from ϕ. The ± 10° range accounts for the maximum acceptable error on ϕ when analysing the broad‐band data (Al‐Harrasi et al 2010). The main advantage of Wüstefeld et al (2010) approach is that it provides an automated measure of the splitting reliability by comparing the splitting parameters from the cross‐correlation and the eigenvalue minimization methods.…”

“…Recent studies (e.g. Teanby et al 2004a; Al‐Harrasi et al 2010) have shown the potential of using microseismic data to estimate reservoir seismic anisotropy via the use of SWS analysis. In this study, we report observations of frequency‐dependent SWS made on microseismic data acquired from a petroleum field in Oman.…”

Microseismic Monitoring of Fracture Networks During Hydraulic Stimulation: Beyond Event Locations

“…These include: North Sea chalk reservoirs (Valhall (Teanby et al, 2004b) and Ekofisk (Jones et al, in prep, 2012)); carbonate reservoirs in west-central Oman (Al-Anboori and Al-Harrasi et al, 2010) and southern Saskatchewan (Weyburn) (Verdon et al, 2010b;2011a); and siliciclastic reservoir of Cotton Valley in Carthage, Texas (Wuestefeld et al, 2012).…”

“…Perhaps the most unambiguous indicator of anisotropy is shear-wave splitting (Silver and Chan, 1991;Teanby et al, 2004a;. Shear-wave splitting measurements can be used to assess fracture properties, which are sensitive to spatial and temporal variations in the stress field (e.g., Teanby et al, 2004b;Al-Harrasi et al, 2010). Microseismic data are generally rich in frequency content so there is also much potential to look at frequency-dependent wave phenomena.…”