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In an azimuthally anisotropic medium, the principal directions of azimuthal anisotropy are the directions along which the quasi-P- and the quasi-S-waves propagate as pure P and S modes. When azimuthal anisotropy is induced by oriented vertical fractures imposed on an azimuthally isotropic background, two of these principal directions correspond to the directions parallel and perpendicular to the fractures. S-waves propagating through an azimuthally anisotropic medium are sensitive to the direction of their propagation with respect to the principal directions. As a result, primary or mode‐converted multicomponent S-wave data are used to obtain the principal directions. Apart from high acquisition cost, processing and interpretation of multicomponent data require a technology that the seismic industry has not fully developed. Anisotropy detection from conventional P-wave data, on the other hand, has been limited to a few qualitative studies of the amplitude variation with offset (AVO) for different azimuthal directions. To quantify the azimuthal AVO, we studied the amplitude variation with azimuth for P-wave data at fixed offsets. Our results show that such amplitude variation with azimuth is periodic in 2θ, θ being the orientation of the shooting direction with respect to one of the principal directions. For fracture‐induced anisotropy, this principal direction corresponds to the direction parallel or perpendicular to the fractures. We use this periodic azimuthal dependence of P-wave reflection amplitudes to identify two distinct cases of anisotropy detection. The first case is an exactly determined one, where we have observations from three azimuthal lines for every common‐midpoint (CMP) location. We derive equations to compute the orientation of the principal directions for such a case. The second case is an overdetermined one where we have observations from more than three azimuthal lines. Orientation of the principal direction from such an overdetermined case can be obtained from a least‐squares fit to the reflection amplitudes over all the azimuthal directions or by solving many exactly determined problems. In addition to the orientation angle, a qualitative measure of the degree of azimuthal anisotropy can also be obtained from either of the above two cases. When azimuthal anisotropy is induced by oriented vertical fractures, this qualitative measure of anisotropy is proportional to fracture density. Using synthetic seismograms, we demonstrate the robustness of our method in evaluating the principal directions from conventional P-wave seismic data. We also apply our technique to real P-wave data, collected over a wide source‐to‐receiver azimuth distribution. Computations using our method gave an orientation of the principal direction consistent with the general fracture orientation in the area as inferred from other geological and geophysical evidence.

Today, geostatistical reservoir characterization from 3D seismic volumes provides most static descriptions for reservoir models. These models can be improved by integrating the dynamic data in the reservoir description process. 3-D time-lapse seismic surveys have been proposed to relate time dependent-changes in seismic attributes to the flow processes in the reservoir. This paper presents a new approach to reservoir characterization by integrating time-lapse seismic and production data. The issues involved in the integration will be examined. A case study was conducted over a turbidite sheet sand reservoir in the Gulf of Mexico. Seismic data from the base survey were combined with log and production data to build an initial reservoir model which was run forward to the time of a second monitor seismic survey. Dynamic history matching by a simulated annealing type of optimization further improved the model. The output from this simulation was then converted to a synthetic monitor seismic survey using Gassmann's equations and a simple convolutional approach. A quantitative combined seismic and production history-matching methodology was then tested. It constrains the modeling process to match the production history and simultaneously minimize the differences between the synthetic and real 3-D seismic time-lapse data. This new systematic approach provides us with a quantitative time-lapse seismic analysis and reservoir characterization tool which has the potential to improve reservoir management. Introduction Once an oil reservoir has been found and is being produced, it is important to understand the movement of the fluid which is related to the flow mechanism and the reservoir heterogeneity. Recently, 3D seismic data have been used successfully to improve reservoir characterization by extraction of reservoir parameters using inversion, geostatistics and petrophysics to understand the coupling of seismic and rock properties. More than 10 years ago, laboratory work demonstrated that different fluid substitutions can cause acoustic changes, and time-lapse seismic was proposed to capture the changes in reservoir properties with time. These mostly qualitative studies showed that time-lapse seismic even on legacy data resulted in a better understanding of the production behavior of the reservoir. Time-lapse seismic data are mainly used for monitoring of the fluid movement in the reservoir. By integrating other data, they can provide another avenue for reservoir characterization not only including the fluid movement but also other reservoir properties. The following sections document a case study on a turbidite sheet sand reservoir in the Gulf of Mexico where 3-D time-lapse seismic data were integrated with production data from three wells over five years to characterize the reservoir by optimization, and time lapse seismic data were used to validate a seismic history matching methodology. Background This study uses two volumes of "off-the-shelf" data for timelapse seismic analysis. The base 3D seismic volume was acquired in 1988 before the production of the reservoir, while the monitor 3D seismic volume was acquired in 1994 after more than 5 years of production. The difference in orientation of the two surveys was small. The acquisition parameters were different for the two volumes. The base survey was reprocessed to improve the imaging part of the processing sequence to match the 1994 processing sequence more closely. Both volumes were processed through deterministic and adaptive deconvolution, 3-D dip move out and one-pass 3-D migration. The monitor volume was interpolated to smaller bins before migration. The limitations in using "off-the-shelf" data are well known and were recently discussed by Beasley et al., 1996. Since the focus of the present study is to demonstrate an improved seismic history matching methodology, it was decided to use legacy data rather than data reprocessed from field tapes to minimize differences. The accuracy of the results is expected to improve when using carefully reprocessed data sets. The case study was conducted over a sheet sand reservoir in the Gulf of Mexico, offshore Lousiana. The sand is of Pliocene age and pinches out onto a salt-related structural high that controlled its deposition. The average porosity is about 31 % and its permeability is about 500 md. P. 439^

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A seismic reflection, gravity, and aeromagnetic reconnaissance was made in the Pensacola Mountains, Antarctica, during the 1965-66 austral summer. Prominent ice streams located between the Neptune and Patuxent Ranges and east of the Forrestal Range overlie channels in the rock surface 2000 meters below sea level which are probably of glacial origin. Seismic reflections show that the Filchner Ice Shelf is 1270 meters thick near its southern margin. Along the boundary between West and East Antarctica, Bouguer anomalies decrease from +60 milligals in West Antarctica to -80 milligals in East Antarctica. An abrupt change in crustal structure across this boundary is required to explainl the 2 milligals per kilometer gradient. This may indicate a fault extending through the crust into the mantle. Aeromagnetic profiles delineate anomalies up to 1800 gamma associated with the basic stratiform intrusion which comprises the Dufek and Forrestal ranges. A probable minimum area of 9500 square kilometers is calculated for the intrusive body on the basis of the magnetic anomalies, making it one of the largest bodies of its type. The extension of this magnetic anominaly across a fault forming the north border of the Pensacola Mountains probably precludes transcurrent movement.

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