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Integration issues in E&P spatial data processing

Schlumberger Austin Product Center, Austin, Texas, U.S.

Corresponding author: W. Quinlivan, quinlivan@austin.apc.slb.com

The first 20% of the full text of this article appears below.

Some important relationships in the petroleum industry have a strong spatial component—the relationship between a completed interval and a reservoir or mineral lease, or between a drilling location and a land parcel subject to a damage clause. In each case, spatial relations between the elements can have profound financial impact for the interested parties.

Initial interpretation of seismic sections or well-log data and analysis of core or fluid samples have limited concern for the spatial context. However, when results from several such domains are integrated or viewed together, conversion to a common coordinate framework becomes key for exposing their spatial relationships. Greater technical breadth of inquiry amplifies the importance of getting spatial data into a common coordinate framework.

Another issue is integration of data from multiple sources. While data from a single source may share a common coordinate system (e.g., all data from a particular seismic contractor), this would rarely be shared by data from a third-party vendor or governmental regulatory agencies. Diverse sources of data tend to use specialized coordinate frameworks for spatial data, and integration of these data demands rigor in the handling of its spatial aspect at each step along the way.

Finally, exploration projects, which typically focus on a specific geographic area, tend to use specialized coordinate systems to minimize local map distortion. The result is that any activity that reuses data from several projects must recognize and act on the differences in the coordinate systems.

All of these factors—increasing technical breadth, diversity of sources of data, and making common use of data from region-specific projects—are clear growth trends in the industry, and all contribute to the need for precision handling of spatial data.

A wide range of position accuracy is reflected in today's data. Generally, computer systems are expected to preserve the highest accuracy . . . [Full Text of this Article]