INTRODUCTIONEstimation of reflector depth and seismic velocity from seismic reflection data can be formulated as a general inverse problem. The method used to solve this problem is similar to tomographic techniques in medical diagnosis and we refer to it as seismic reflection tomography.Seismic tomography is formulated as an iterative Gauss-Newton algorithm that produces a velocitydepth model which minimizes the difference between traveltimes generated by tracing rays through the model and traveltimes measured from the data. The input to the process consists of traveltimes measured from selected events on unstacked seismic data and a first-guess velocity-depth model. Usually this first-guess model has velocities which are laterally constant and is usually based on nearby well information and/or an analysis of the stacked section. The final model generated by the tomographic method yields traveltimes from ray tracing which differ from the measured values in recorded data by approximately 5 ms root-mean-square.The indeterminancy of the inversion and the associated non uniqueness of the output model are both analyzed theoretically and tested numerically. It is found that certain aspects of the velocity field are poorly determined or undetermined.This technique is applied to an example using real data where the presence of permafrost causes a nearsurface lateral change in velocity. The permafrost is successfully imaged in the model output from tomography. In addition, depth estimates at the intersection of two lines differ by a significantly smaller amount than the corresponding estimates derived from conventional processing.Estimation of velocity and depth is often an important step in prospect evaluation in areas where lithology and structure undergo significant lateral change. Depth estimation is usually accomplished by converting zero-offset traveltimes, interpreted from a stacked section, to depth using a velocity field obtained from a normal-movement (NMO) analysis. In areas with complex lateral changes, a depth migration technique may be necessary to obtain the correct depth estimate (Lamer et aI., 1981). Both of these methods require an accurate representation of the root-mean-square (rms) velocity field. However, the stacking velocities used for such analyses can deviate significantly from rms velocities because analysis of stacking velocities assumes that the medium is laterally invariant and that traveltime trajectories for reflection events in CDP gathers are hyperbolic.Media vary laterally due to either reflector dip or curvature, or due to lateral velocity variations, or both. A large portion of the effect of reflector dip or curvature on the stacking velocity can be removed approximately by first migrating commonoffset panels with a first-guess velocity function, and then recalculating the stacking velocity in the migrated common-depthpoint (CDP) gathers (Doherty and Claerbout, 1976). The influence of lateral variations in velocity on the stacking velocity cannot be corrected this way. For lateral vari...

Least squares or [Formula: see text] solutions of seismic inversion and tomography problems tend to be very sensitive to data points with large errors. The [Formula: see text] minimization for 1 ≤ p < 2 gives more robust solutions, but usually with higher computational cost. Iteratively reweighted least squares (IRLS) gives efficient approximate solutions to these [Formula: see text] problems. We apply IRLS to a hybrid [Formula: see text] minimization problem that behaves like an [Formula: see text] fit for small residuals and like an [Formula: see text] fit for large residuals. The smooth transition from [Formula: see text] to [Formula: see text] behavior is controlled by a parameter that we choose using an estimate of the standard deviation of the data error. For linear problems of full rank, the hybrid objective function has a unique minimum, and IRLS can be proven to converge to it. We obtain a robust efficient method. For nonlinear problems, a version of the Gauss‐Newton algorithm can be applied. Synthetic crosswell tomography examples and a field‐data VSP tomography example demonstrate the improvement of the hybrid method over least squares when there are outliers in the data.

A carbon dioxide (CO2) injection pilot project is underway in Section 205 of the McElroy field, West Texas. High-resolution crosswell seismic imaging surveys were conducted before and after CO2 flooding to monitor the CO2 flood process and map the flooded zones. The velocity changes observed by these time-lapse surveys are typically on the order of -6%, with maximum values on the order of -10% in the vicinity of the injection well. These values generally agree with laboratory measurements if the effects of changing pore pressure are included.The observed dramatic compressional (VP) and shear (VS ) velocity changes are considerably greater than we had initially predicted using the Gassmann (1951) fluid substitution analysis (Nolen-Hoeksema et al., 1995) because we had assumed reservoir pressure would not change from survey to survey. However, the post-CO2 reservoir pore fluid pressure was substantially higher than the original pore pressure. In addition, our original petrophysical data for dry and brine-saturated reservoir rocks did not cover the range of pressures actually seen in the field. Therefore, we undertook a rock physics study of CO2 flooding in the laboratory, under the simulated McElroy pressures and temperature.Our results show that the combined effects of pore pressure buildup and fluid substitution caused by CO2

A carbon dioxide flood pilot is being conducted in a section of Chevron's McElroy field in Crane County, west Texas. Prior to CO 2 injection, two high-frequency crosswell seismic profiles were recorded to investigate the use of seismic profiling for high-resolution reservoir delineation and CO 2 monitoring. These preinjection profiles provide the baseline for timelapse monitoring. Profile #1 was recorded between an injector well and an offset observation well at a nominal well-to-well distance of 184 ft (56 m). Profile #2 was recorded between a producing well and the observation well at a nominal distance of 600 ft (183 m). The combination of traveltime tomography and stacked CDP reflection amplitudes demonstrates how highfrequency crosswell seismic data can be used to image both large and small scale heterogeneity between wells: Transmission traveltime tomography is used to image the large scale velocity variations; CDP reflection imaging is then used to image smaller scale impedance heterogeneities. The resolution capability of crosswell data is clearly illustrated by an image of the Grayburg-San Andres angular unconformity, seen in both the P-wave and S-wave velocity tomograms and the reflection images. In addition to the imaging study, cores from an observation well were analyzed to support interpretation of the crosswell images and assess the feasibility of monitoring changes in CO 2 saturation. The results of this integrated study demonstrate (1) the use of crosswell seismic profiling to produce a high-resolution reservoir delineation and (2) the possibility for successful monitoring of CO 2 in carbonate reservoirs. The crosswell data were acquired with a piezoelectric source and a multilevel hydrophone array. Both profiles, nearly 80 000 seismic traces, were recorded in approximately 80 hours using a new acquisition technique of shooting on-the-fly. This paper presents the overall project summary and interpretation of the results from the near-offset profile.