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Study of a database of 350 giant oilfields show these to be dynamic short lived phenomena, with a median age of 35 Ma. A third show evidence of post-entrapment destructive processes, particularly erosion, fault leakage and gas flushing. Biodegradation is a destructive process most active during oil entrapment. Re-entrapment of oil released from spilling or breached traps is common. These processes are illustrated with case examples from SE Asia and throughout the world. The main controls on oilfield preservation are post-entrapment tectonism and seal type, with temperature and hydrodynamic regimes being secondary factors. Destructive processes are concentrated in shallow and deep zones and in seepage-prone traps such as compressional anticlines. Such factors strongly influence the distribution of preserved light oilfields, with preservation potential maximised in tectonically quiescent basins with evaporite or thick mudstone seals e.g. the Middle East and the Permian Basin, or in basin centres distant from inverted or uplifted zones e.g. Central Sumatra. More attention is required in prospect and regional evaluations to models involving post-entrapment leakage and re-migration.

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Knowing the root cause of why an Integrated Circuit (1C) device fails to function properly is the key to provide the corrective measures to increase the yield and shorten the time to market. In recent years, electrical fault diagnosis method has received growing attention due to the effective and indispensable guiding role it plays in modern fault localization practice when physical measures are more and more confined by the shrinking feature size and condensed internal structure. While most of the fault diagnosis tools are based on gate level fault models, many faults are actually at the transistor level (the intra-gate fault). This thesis provides an innovative method to diagnose the intra-gate faults. It covers a wide range of different types of intra-gate faults. The method extends the capability of gate level fault diagnosis tools to the intra-gate domain by building connections with these intra-gate faults to particular types of gate level faults. Intra-gate faults are transformed to gate level representations so that they can be diagnosed directly by the widely available and well developed gate level diagnosis tools. Real diagnosis of intra-gate faults from wafer data and physical failure analysis photos are provided as solid proofs of the effectiveness of this method.

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The identification of possible hazards in chemical plants is a very important part of the design process. This is because of the potential danger that large chemical installations pose to the public. One possible route for speeding up the identification of hazards in chemical plants is to use computers to identify hazards automatically. This will facilitate safe plant design and will avoid late design changes which can be very costly to implement. Previous research at Loughborough has concentrated on developing a model-based approach and an analysis algorithm for automating hazard identification. The results generated have demonstrated the technical feasibility of the approach. This approach requires a knowledge-base of unit models. This library of models describes how different plant equipment behaves in qualitative terms. The research described in this thesis develops a method for creating and testing the equipment models. The model library was previously achieved by an expert writing the models in a format that could be directly used by the system described above. An engineer unfamililar with the system would find this difficult. An alternative method would have been to use an intermediary (a knowledge engineer) to gather information from the engineer and convert it into the system format. This would be expensive. Both methods would take up a lot of the engineer's time. An engineer should be able to enter information personally in order to maintain efficiency and avoid information loss through the intermediary. A front end interface has been built to the system which enables an expert to enter information directly without needing to understand details of the application system. This interface incorporates ideas from the knowledge acquisition field in order to produce a tool that is simple to use. Unit-based qualitative modelling can lead to incorrect or ambiguous inference. The method developed here identifies situations where ambiguities may arise. A new modular approach is presented to overcome this type of problem. This method also presents a technique to verify that the models created are both complete and correct.