# Four-Dimension Seismic Analysis in Carbonate: A Closed Loop Study
## 3 Results & Discussion  
### 4D Seismic Co-Processing  
For such non-repeatable 4D seismic acquisition surveys of the study area, 4D seismic co-processing was started with the field-recorded seismic data from both the baseline and monitor surveys. Pre-processing, including noise reduction, static computation, and de-multiple with predictive 3D deconvolution, allowed successful adjustment of overburden phase and amplitude, and the reservoir level remained intact. Four-dimensional binning was performed using the adjacent offset classes from the 1994 baseline survey to select retained traces with a Distance Source, Distance Receiver (DSDR) value of less than 200 m for offset classes 1 through 16, and less than 300 m for offset classes 17 through 62, followed by 5D Fourier bin regularization including noise attenuation. To close the repeatability gap, it was decided to test the pre-stack least squares depth migration algorithm (LSM) against the Kirchhoff pre-stack depth migration algorithm (KPSDM). The pre-stack seismic depth imaging workflow began with Kirchhoff (KPSDM) for the baseline and monitor surveys. Then, the original Kirchhoff OVTs were de-migrated for depth imaging and least square migration (LSM). Kirchhoff KPSDM was applied to both baseline and monitor surveys. To this end, both datasets were recursively migrated after preprocessing and de-migrated at each iteration using Hessian filter calculations in the Curvelet domain to create a reflectivity model for each vintage. The baseline and monitor surveys were then finally de-migrated to baseline coordinates. Before the final reflectivity models were created, three iterations of migration and de-migration were performed. The seismic processing step of least-square migration used input data without 3D regularization for both the baseline and monitor surveys. Therefore, the LSM results were clean data compared to the Kirchhoff PSDM, which used inputs after 3D regularization. The LSM seismic difference had a much lower difference level compared to the Kirchhoff PSDM seismic difference, indicating that the Kirchhoff LSM pre-stack depth migration algorithm appeared to mitigate some of the non-repeatable seismic noise. The seismic difference between the baseline and the monitor was clearly visible on the crest of the structure compared to the adjacent seismic traces (Figure 5c). Diagnostic 4D QC attributes were extracted at each stage of 4D seismic co-processing, e.g., NRMS were examined to ensure that vintages become increasingly comparable. Deterministic pre-stack corrections were strongly recommended rather than relying solely on post-stack matching. This rigorous approach ensured that 4D noise was more accurately captured and the 4D reservoir signature was preserved [28]. The 4D signal can be measured by the Normalized Root Mean Square (NRMS) attribute, which is defined as the difference between two normalized data sets RMS. NRMS is routinely used as a quality control measure for time-lapse data [29]. The sensitivity of the NRMS value to the repeatability of the recording geometry has been described in several publications [30; 31]. Figure 5: Horizon slice on a window between the upper and lower parts of the reservoir of the final migrated seismic stack volume: (**a**) baseline seismic volume; (**b**) monitor seismic volume, and (**c**) the seismic difference between baseline and monitor surveys. Block polygon that includes the high amplitude difference at the crest of the reservoir. We conclude that the final NRMS value was regularly discarded to quantify the quality of the 4D signal. Predictability was used to measure the repeatability or coherence between two data sets. Repeatability is regularly evaluated using the normalized RMS difference and predictability, which is usually the normalized cross-power or coherence of the difference between the baseline and monitor surveys. For a seismic acquisition with poor repeatability, the predictability is between 0 and 65%, while perfect predictability should be above 85%.