Abstract The superposition of structures produced by different tectonic phases is common in sedimentary basins. Yet the earlier structures often remain overlooked with potentially negative exploration consequences. In the Maiella anticline, Pliocene compression has folded carbonate sequences containing Cretaceous extensional structures. The geometry and evolution of the Apulian carbonate platform margin outcropping on the Maiella Mountain are described by two opposing groups of models. One proposes a structurally controlled platform margins cut by syn-sedimentary Cretaceous faults; the other assumes a passive Cretaceous palaeo-escarpments progressively filled by Cretaceous to Tertiary sediments later deformed by the Pliocene compression. Assuming models in line with either one of these two groups has significant implications for exploration plays on both platforms and adjacent basins of analogous subsurface systems. These include: hypothesized margin geometries; sediment transport mechanisms (directions and distribution); size of sequences; type and size of traps and associated exploration targets, risks and uncertainties. We demonstrate that during the Late Cretaceous the platform margin was cut by normal faults which controlled the palaeogeography of the platform and the sediment input into the adjacent basin in which thick, resedimented, carbonate megabreccia and turbidites were deposited. These carbonates represent exploration targets in similar settings worldwide.

Abstract Deformation predictive methods are useful for structural analysis from the scientific and industry point of view. We apply a strain simulation technique based on the inclusion of graphical strain markers in a cross;-section, and subsequent cross-section restoration and numerical processing of strain markers, to the seismic-scale Maiella Mountain anticline (Central Apennines, Italy) considered a carbonate reservoir analogue for Apennines oil fields. The procedure followed involves field mapping and structural data collection, construction of cross-sections, sequential cross-section restoration, and application of the strain simulation technique. The cross-sections presented were constructed adopting one of the various structural interpretations proposed for this structure by different authors. According to this interpretation the Maiella Mountain structure resulted from Messinian–Early Pliocene extension and subsequent Late Pliocene shortening. According to our structural model the Maiella structure is a break-thrust fold and the comparison between the present-day and the restored cross-sections yields 1.3–4.6% of extension associated with two main normal faults and 21.5–22.1% and 2.5–3.4% of shortening due to a major thrust and folding respectively. The simulation of deformation distribution shows high deformation intensity in both limbs and low deformation in the anticline crest and part of the thrust footwall.

Abstract Schiehallion is a two billion barrel deepwater clastic reservoir, situated on the Atlantic margin of the UKCS , one of the world’s most hostile environments for hydrocarbon production. The field has been developed via subsea wells tied back to an FPSO , and is one of the first developments of its kind anywhere in the world. The field may be characterized as high productivity but low energy and, as a consequence, water injection is essential to maintaining production. However, the reservoir is channelized, faulted, and has varying degrees of connectivity between the compartments, so that a good understanding of these factors is necessary to optimize the water injection distribution. Our understanding of the ‘plumbing’, or connectivity between the wells, has evolved and matured over time, using a wide range of different data types, from the initial extended well test, through RFT’s , pressure transient analyses, interference testing, PLT’s , tracer and geochemical sampling, to bi-annual 4D seismic surveys using increasingly sophisticated processing and interpretation. Much of this understanding has been incorporated in a 3D model, which uses object modeling and seismic conditioning to represent the sand distribution. Potential barriers to flow are identified from seismic coherency analysis, and the strengths of these barriers have been used as the main history matching parameters. A key learning has been that all data needs to be interpreted with great care, and it is essential to integrate several data types in order to obtain reliable conclusions. The paper gives examples of data which has been invaluable, as well as examples where the data is ambiguous or misleading.