The manner in which a fault intersects a hydrocarbon reservoir affects production characteristics and thus must be understood in great detail. A 3-D seismic data volume can be sliced interactively to yield seismic sections parallel to a fault plane. These fault slices can then be used in several ways for the study of faults. Tracking of correlative horizons on fault slices provides a map of fault throw and permits study of the throw as a function of vertical traveltime and horizontal position. Because a fault slice remains within one major fault block, the study of growth relationships in that block is facilitated. Splinter faults, which are also significant in development and production, can be studied effectively on fault slices because of the uniform proximity of these sections to the parent fault. We conclude that there is some uniformity in azimuth between splinter faults and their parent.
The computing architecture of an Automated Maintenance Environment (AME) can foster or stunt the ability to employ smart maintenance practices. With software decision support technologies becoming more readily available, there is ample opportunity for diagnostic enhancement within AME's. Data analysis practices and informed decision support are enabled by an enhanced technical infrastructure, which includes data accessibility, common data formats, and sufficient computational capacity. This paper will explain the results of the IDATS team's efforts in creating a lab architecture to facilitate diagnostic analysis and how it further applies in a functioning smart AME. Additionally, the paper will address the computing and decision support software requirements needed to perform efficient maintenance practices within the US Navy, as well as provide an analysis of the strengths and shortcomings of existing Navy AME architectures. Potential change-points or limitations resulting from the existing AME architecture will be identified. This analysis will recognize common data points within the AME that can be improved or augmented to benefit multiple aircraft platforms with the capability of enhanced common diagnostic techniques. The steps toward realizing a common, flexible maintenance capability were investigated by analyzing the structure of all current and indevelopment Navy aircraft AMEs, including the data storage format, the movement of data, and the network infrastructure. A common Navy AME architecture will facilitate timely insertion of new and enhanced diagnostic techniques as they are developed, providing the fleet with intelligent support equipment at the flight line.
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