Abstract: Fractured Tight Gas Reservoir Seismic Exploration Optimization
GRIMM, ROBERT, Blackhawk Geometrics, Inc., Golden, CO, HELOISE LYNN, and WALLACE BECKHAM, Lynn, Inc., Houston, TX
Gas yields in the Rocky Mountain region are often controlled by natural fractures. The Department of Energy has sponsored a series of investigations to develop cost-effective ways to detect regions of high fracture density with seismic and other methods. Here we present a preliminary synthesis of three of these projects. We recommend a protocol for fractured-reservoir seismic exploration focusing on all-azimuth, wide-angle P-wave surveying, with multiazimuth processing aimed at highlighting fracture-zone anisotropy.
Fractures cause changes in a rock's stiffness; when regular fracture sets are present, the additional order may be detected as anisotropy of the seismic response. The simple and not uncommon case of a dominant set of parallel subvertical fractures leads to azimuthal anisotropy, that is, a variation of the seismic response with direction. For example, both pressure (P) and shear (S) waves are slower in the fracture-perpendicular direction than fracture parallel. Therefore multiazimuth seismic processing—dividing the source-to-receiver raypaths by direction, processing each direction independently, and examining the differences—can be used to detect zones of intense fracturing.
S-waves are particularly sensitive to anisotropy, both in the overall change in velocity and by splitting into a slow wave (S2) with transverse particle across fractures and fast waves with particle motion in the fracture plane (S1). However, full S-wave recording (shear sources and three-component geophones) is still costly. A major aspect of our investigations has been comparison of P- and S-wave responses in the field to test whether most of the fracture information can be determined using cheaper P-wave technology alone. Furthermore, P-waves contain additional information on pore and fracture content (gas vs. water). P-wave properties of interest include azimuthal variations in velocity, reflectivity (including Amplitude Variations with Offset, or AVO), and frequency.
Powder River Basin
A series of orthogonal, intersecting 2D seismic lines were shot approximately aligned with the principal fracture trends. Both P- and full S-wave data were acquired on all lines. Spatial variations in shear-wave anisotropy delineate fracture zones, which were confirmed by drilling. This study validated S-wave methods for fracture-zone mapping.
Two intersecting 2D seismic lines were shot at the Bluebell-Altamont field (Lynn et al., 1996a), approximately parallel and perpendicular to the principal fracture trend. Both P- and full S-wave data were acquired on both lines, and S-wave anisotropy was calibrated by a 9C VSP (nine-component, vertical seismic profile, i.e., three-component receivers and both P- and S-sources). This study, in a comparatively simple geological environment (fractured basin), demonstrated that P- and S-wave responses indeed correlated: the P-wave AVO gradient at the line intersection was proportional to the S-wave velocity anisotropy within corresponding vertical intervals.
Aeromagnetic mapping and a 3D P-wave survey were performed at the Rulison field. Two large basement faults were identified from the aeromagnetic data, which appear to terminate in seismic cross-sections as “fault-tip fracture clusters.” These highly fractured zones correlate with P-wave velocity anisotropy and appear to control the “fairway” for gas production in this moderately complex environment (faulted and fractured basin).
Wind River Basin
Three seismic surveys were performed (Lynn et al., 1996b; Grimm et al., 1998): a large 3D P-wave survey, a 9C VSP, and a smaller 3D P-to-S survey (the last involves three-component recording of P-sources, with specialized processing to extract S-waves generated by reflections). The geology, a faulted, fractured anticline, is the most complex of the three study areas. The best correlations of seismic attributes with gas yield are achieved by considering azimuthal variations. However, most of the information is contained in the fracture-parallel component for reflectivity and frequency, and in the fracture-perpendicular component for velocity. We interpret these results to indicate that strong scattering in fracture-perpendicular raypaths degrades the information in reflectivity and frequency, whereas this orientation is optimal for mapping relative fracture density from velocity variations: slower fracture-perpendicular velo-city is associated with higher fracture density. Decreases in reflectivity correlated with pay are interpretable as decreases in the impedance contrast of local gas-charged sand bodies with surrounding shales, whereas the increase in frequency with pay requires a more complex permeability anisotropy model. Using a neural network, the seismic azimuthal variations in reflectivity, frequency, and velocity were combined with the dominant geological attribute (structural altitude on the trapping anticline) to map the estimated potential for commercial gas pay throughout the survey area.
For basins of only moderate structural complexity, such as the Piceance, there is a strong correlation between fracturing (as can be inferred from P-wave azimuthal anisotropy) and gas yield. In the more complex structure in the Wind River basin, faulting and fracturing are more ubiquitous: while fractures are still important in delivering gas to wells, the seismic data reveal that mapping reservoir units in these heterogeneous sediments has a renewed importance.
For cost-effective seismic evaluation of fracture density, we recommend:
(1) Gather sufficient reconnaissance data (field and borehole geology, in-situ stress, remote sensing, etc) to properly plan seismic surveys.
(2) Acquire 3D P-wave surveys with maximum offsets greater than or equal to target depth in all azimuth, using isotropic source and receiver arrays.
(3) Processing in as many azimuths as allowed by cost; 2 or 4 should be sufficient.
For refined prediction of gas yield in fractured reservoirs, we recommend:
(1) Exploit higher sensitivity of reflection attributes at large incidence angles (offsets) to better distinguish gas from water. This may require a new paradigm for amplitude-variation-with offset (AVO) modeling (Grimm and Lynn, 1997).
(2) Improve mapping of seismic attributes to gas yield (e.g., as in neural network) by fully integrating seismic data with well logs in three dimensions, particularly those new logging tools like nuclear magnetic resonance that may best distinguish gas from water.
These projects were funded by the Department of Energy Federal Energy Technology Center. Stanford University and Advanced Resources International were the prime contractors for the Powder River basin and Piceance basin studies, respectively.
AAPG Search and Discovery Article #90937©1998 AAPG Annual Convention and Exhibition, Salt Lake City, Utah