Permian Basin Compressive Seismic Case Study

The Permian Basin is a prolific oil and gas producing region of the United States. Seismic imaging in the Permian is challenging due to the complex geological and environmental conditions in the region. The unconsolidated sediments near the surface attenuate seismic waves which makes it difficult to obtain a clear image of the deeper subsurface. Shallow gas hazards and acquisition holes due to permitting issues are also common. To overcome some of these challenges, high trace density (HTD) surveys are becoming increasingly common. These surveys are designed to produce superior near offset sampling and higher trace density than traditional seismic acquisition.

The following case study is an application of Compressive Seismic to further improve upon an HTD survey while considering practical acquisition design and risk management.

HTD Acquisition Design

The HTD survey is designed to record 1444 fold at 25 x 50 ft CDP bins. The initial design considers a half-station receiver stagger to allow for 25 x 25 ft CDP bins @ 722 fold via bin fractionation. On the source side, high-volume simultaneous sourcing is planned with up to 16 vibrator fleets. As is typical in the Permian, permitting and mobilization costs are significantly larger than the cost of acquisition and processing.

Definitions

• Cost-mode CS – A technique where sources and/or receivers are optimally sub-sampled to reduce acquisition effort. Typically, in the 30-50% sub-sampling range. This method can also overcome certain challenges, such as acquiring a large patch size with a smaller number of receivers.

• Value-mode CS – A CS conversion option that uses roughly the same number of sources and/or receivers to obtain much higher quality data as measured by either smaller bin sizes or higher folds.

CS Analysis

With the relatively lower cost of acquisition, cost-mode CS will not significantly impact the overall project cost. Also, with anticipated coverage gaps, In-Depth can reconstruct the cost-mode data without issue, but another processing shop may have difficulty using a cost-mode dataset to obtain adequate near offset sampling throughout the survey area. The risk-reward analysis precludes cost-mode CS as a viable option.

With high volume source-side production and inversion-based deblending, CS conversion of sources is not recommended. However, receiver-side value-mode CS may be feasible. Utilizing the same patch, density, and total number of receivers converted to an optimized CS layout, In-Depth can reconstruct it to the designed 25 x 50 ft bin @ 2,888 fold (double) or 25 x 25 ft bins @ 1,444 fold. The beauty of value-mode CS is that it can easily be processed by any processing shop for the HTD design goals since the CS optimization offsets are small. This solution is riskless and has significant potential rewards in terms of improved data quality.

CS HTD Survey Conversion

Based on the analysis above, sources were left as-is and value-mode CS was applied to the receivers. Figures 1-4 below show some QC from the design process. The base survey is the as-designed HTD survey before CS conversion, the CS survey is the HTD survey converted to value-mode CS, and the reconstructed CS survey is what will be obtained after CS Reconstruction in processing. Colorbars for the offset plots are compressed to show detail.

Figure 1: Base survey (left), CS survey (middle), Reconstructed CS survey (right)

Figure 2: Base survey fold (left), CS survey fold (middle), Reconstructed CS survey fold (right)

Figure 3: Maximum near offset: base survey (left), CS survey (middle), Reconstructed CS survey (right)

Figure 4: Maximum far offset: Base survey (left), CS survey (middle), Reconstructed CS survey (right)

Conclusion

Figure 5 below is a comparison between the starting HTD design and the CS conversion.

In terms of acquisition options, they are virtually identical with a small difference in nominal far offset. The CS survey can be easily processed to virtually the same result as the base survey.

The processing options are very different. With the base survey and bin fractionation, only half the fold is achieved as with the CS survey and CSR1. Similarly, CSR2 achieves twice the fold when compared to the base survey.

Figure 5: Summary of Permian CS-Acquisition Case Study Statistics

In conclusion, this case study was undertaken with the objective of extracting maximum value from an investment in HTD acquisition while managing risk. The proposed CS conversion will increase the overall project cost by 1-2%, but in return provides double the fold of the base survey. The CS survey is also riskless as it can be processed to the base survey geometry by any processing shop. The CS survey is better suited for reprocessing efforts in the future as it has higher spatial frequency content and can benefit from future advances in processing technology. Obstacles were not included in this preliminary study, but from past experience, CS-optimized sampling is better at reconstructing across gaps than regular sampling.

Seismic acquisition is expensive, and it is important to maximize the return on investment. The proposed CS survey is a risk-free way to increase the quality of the data obtained. In-Depth’s patented methods and years of experience in the field make us the go-to choice for modern CS-friendly surveys.