Over the years, amplitude variation with‐offset (AVO) analysis has been used successfully to predict reservoir properties and fluid contents, in some cases allowing the spatial location of gas‐water and gas‐oil contacts. In this paper, we show that a 3-D AVO technique also can be used to characterize fractured reservoirs, allowing spatial location of crack density variations. The Cedar Hill Field in the San Juan Basin, New Mexico, produces methane from the fractured coalbeds of the Fruitland Formation. The presence of fracturing is critical to methane production because of the absence of matrix permeability in the coals. To help characterize this coalbed reservoir, a 3-D, multicomponent seismic survey was acquired in this field. In this study, prestack P‐wave amplitude data from the multicomponent data set are used to delineate zones of large Poisson's ratio contrasts (or high crack densities) in the coalbed methane reservoir, while source‐receiver azimuth sorting is used to detect preferential directions of azimuthal anisotropy caused by the fracturing system of coal. Two modeling techniques (using ray tracing and reflectivity methods) predict the effects of fractured coal‐seam zones on angle‐dependent P‐wave reflectivity. Synthetic common‐midpoint (CMP) gathers are generated for a horizontally layered earth model that uses elastic parameters derived from sonic and density log measurements. Fracture density variations in coalbeds are simulated by anisotropic modeling. The large acoustic impedance contrasts associated with the sandstone‐coal interfaces dominate the P‐wave reflectivity response. They far outweigh the effects of contrasts in anisotropic parameters for the computed models. Seismic AVO analysis of nine macrobins obtained from the 3-D volume confirms model predictions. Areas with large AVO intercepts indicate low‐velocity coals, possibly related to zones of stress relief. Areas with large AVO gradients identify coal zones of large Poisson's ratio contrasts and therefore high fracture densities in the coalbed methane reservoir. The 3-D AVO product and Poisson's variation maps combine these responses, producing a picture of the reservoir that includes its degree of fracturing and its possible stress condition. Source‐receiver azimuth sorting is used to detect preferential directions of azimuthal anisotropy caused by the fracturing system of coal.

Converted-wave amplitude versus offset (AVO) behavior may be fit with a cubic relationship between reflection coefficient and ray parameter. Attributes extracted using this form can be directly related to elastic parameters with low-contrast or high-contrast approximations to the Zoeppritz equations. The high-contrast approximation has the advantage of greater accuracy; the low-contrast approximation is analytically simpler. The two coefficients of the low-contrast approximation are a function of the average ratio of compressionalto-shear-wave velocity (α/β) and the fractional changes in S-wave velocity and density (β/β and ρ/ρ). Because of its simplicity, the low-contrast approximation is subject to errors, particularly for large positive contrasts in P-wave velocity associated with negative contrasts in S-wave velocity. However, for incidence angles up to 40 • and models confined to | β/β| < 0.25, the errors in both coefficients are relatively small. Converted-wave AVO crossplotting of the coefficients of the low-contrast approximation is a useful interpretation technique. The background trend in this case has a negative slope and an intercept proportional to the α/β ratio and the fractional change in S-wave velocity. For constant α/β ratio, an attribute trace formed by the weighted sum of the coefficients of the low-contrast approximation provides useful estimates of the fractional change in S-wave velocity and density. Using synthetic examples, we investigate the sensitivity of these parameters to random noise. Integrated P-wave and converted-wave analysis may improve estimation of rock properties by combining extracted attributes to yield fractional contrasts in P-wave and S-wave velocities and density. Together, these parameters may provide improved direct hydrocarbon indication and can potentially be used to identify anomalies caused by low gas saturations.

Amplitude versus offset (AVO) interpretation can be facilitated by crossplotting AVO intercept (A), gradient (B), and curvature (C) terms. However, anisotropy, which exists in the real world, usually complicates AVO analysis. Recognizing anisotropic behavior on AVO crossplots can help avoid AVO interpretation errors. Using a modification to a three-term (A, B, and C) approximation to the exact anisotropic reflection coefficients for transversely isotropic media, we find that anisotropy has a nonlinear effect on an A versus C crossplot yet causes slope changes and differing intercepts on A versus B or C crossplots. Empirical corrections that result in more accurate crossplot interpretation are introduced for specific circumstances.

No abstract

No abstract