- Copyright © 2004 Society of Exploration Geophysicists
Decisions that involve trade-offs between data quality and cost arise frequently in seismic acquisition. Improvements in data quality are always desirable, but they usually involve increased cost. To justify spending more money to acquire higher quality data, we need to show that the higher data quality has economic benefits that offset any increased expense. This article shows how we can use value of information (VOI) analysis and probabilistic modeling to quantify the economic value of seismic data, and to predict the economic consequences of changes in data quality.
Figure 1 shows an example of one of these trade-offs. The maps in this figure show coverage variations for two modeled marine streamer surveys, where streamer feather changes from one sail line to the next. Both maps have been generated from synthetic geometry for five-streamer acquisition, with 100-m streamer separation and 3600-m streamer length. All lines are acquired sailing north. The average feather angle is 2° east, with an average feather mismatch of ±3° between adjacent sail lines. In the map on the right, the vessel has been steered along the preplot sail lines that were laid out during the survey design. No attempt has been made to accommodate feather mismatch, resulting in large gaps in coverage. In the map on the left, the vessel has been steered to compensate for feather mismatches encountered during acquisition. Sail lines have been overlapped to produce full coverage at an offset of 1800-m, resulting in much improved surface coverage. However, this improvement has a cost—about 20% more data must be acquired to get the map on the left. How can we tell whether this improvement in data quality is worth the extra expense?