Velocity-model determination during seismic data processing is crucial for any kind of depth imaging. We compared two approaches of grid tomography: prestack stereotomography and normal-incidence-point ͑NIP͒ wave tomography. Whereas NIP wave tomography is based on wavefield attributes obtained during the common reflection surface stack and thus on the underlying hyperbolic second-order traveltime approximation, prestack stereotomography describes traveltimes by local slopes ͑i.e., linearly͒ in the prestack data domain. To analyze the impact of the different traveltime approximations and the different input-data domains on velocity model building, we applied two implementations of these techniques to two profiles of a field marine data set from the Levante Basin, eastern Mediterranean. Because of the presence of a thick, tabular mobile unit of the Messinian evaporites, strong vertical and lateral velocity contrasts had been expected. The velocity models revealed the reconstruction of high-velocity contrasts by grid tomographic methods is limited because of the smooth description of the velocity distribution. The lateral resolution of velocities obtained from prestack stereotomography appears to be better than those from NIP wave tomography, which is related to the difference in the approximation of traveltimes, the determination of input data, and the description of the velocity distribution. Other differences are caused mainly by different implementations of the inversion schemes. Nevertheless, both algorithms provide suitable models for highquality depth imaging, whereas most of the reflections are fairly flat in CIGs.

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This paper presents the results from a research project focusing on permanent cross‐well geophysical methods for reservoir monitoring during steam‐assisted gravity drainage. A feasibility study indicated detectable differences in seismic and electrical reservoir properties based on expected changes in temperature and fluid saturation during the production of extra heavy oil. As a result of this, a permanent cross‐well system was installed at the Leismer Demonstration Area, located in the Athabasca Oil Sands region in Alberta, Canada. Baseline data sets, including cross‐well seismic, three‐dimensional vertical seismic profiling and cross‐well electrical resistivity tomography, have been acquired. Comparisons between conventional surface seismic and downhole seismic data show an increase in resolution and frequency content as expected. Steam‐assisted gravity drainage‐induced time‐lapse effects are clearly visible in the 3D vertical seismic profiling and electrical resistivity tomography data sets, even after a few months of oil production. In general, the 3D vertical seismic profiling images show a higher resolution than the surface seismic data, in particular when dealing with vertical positioning of the time‐lapse events. The electrical resistivity tomography baseline shows clear separation between zones of high and low electrical resistivity, and during 23 months of electrical resistivity tomography measurements the maximum reduction of resistivity is 85%. Time‐lapse observations from acoustic and electrical borehole data correspond well, and are also supported by temperature measurements in the two observation wells. Emerging technologies, updated models, improved flexibility, and reduced costs will allow future reservoir monitoring with surface and borehole data in combination, or even with borehole data exclusively.

A processing workflow was introduced for reflection seismic data that is based entirely on common-reflection-surface (CRS) stacking attributes. This workflow comprises the CRS stack, multiple attenuation, velocity model building, prestack data enhancement, trace interpolation, and data regularization. Like other methods, its limitation is the underlying hyperbolic assumption. The CRS workflow provides an alternative processing path in case conventional common midpoint (CMP) processing is unsatisfactory. Particularly for data with poor signal-to-noise ratio and low-fold acquisition, the CRS workflow is advantageous. The data regularization feature and the ability of prestack data enhancement provide quality control in velocity model building and improve prestack depth-migrated images.