The application of ichnofabrics towards bridging the dichotomy between siliciclastic and carbonate shelf facies: examples from the Upper Jurassic Fulmar Formation (UK) and the Jubaila Formation (Saudi Arabia)

An initial study of the ichnofabrics of the Upper Jurassic (Kimmeridgian) Jubaila Formation of Saudi Arabia shows that the ichnofabrics are closely matched to the relatively well-described ichnofabrics of the contemporary Fulmar Formation of the UK Continental Shelf (North Sea), in respect of the lower shoreface/offshore transition facies to offshore facies. The ichnology and ichnofabrics of the Lower Jubaila Formation show that deposition took place on an open-marine platform on the Arabian craton subject to periodic storm activity, but under a persisting equilibrium between sediment accumulation and subsidence. This is consistent with the moderately deep-marine foraminiferal assemblages and the presence of calcareous nannofossils. Cyclicity is absent, though storm beds may be grouped, in contrast with the genetic sequences present in the rift and halokinetic scenario of the North Sea. In contrast with the siliciclastic setting hardgrotinds (with Gastrochaenolites), more common firmground omission surfaces, and micritic mudstones with Chondrites and Zoophycos are notable features of the carbonate facies. In siliciclastic successions (parasequences) the latter ichnotaxa are generally regarded as having been deposited in rather deeper water, but in the carbonate Jubaila Formation are interpreted as being associated with local areas of lower turbulence. Likewise, the hardgrounds and firmgrounds, which have not been traced laterally, are tentatively regarded to be of local significance.

A comparison of cross-hole electrical and seismic data in fractured rock

Cross-hole anisotropic electrical and seismic tomograms of fractured metamorphic rock have been obtained at a test site where extensive hydrological data were available. A strong correlation between electrical resistivity anisotropy and seismic compressional-wave velocity anisotropy has been observed. Analysis of core samples from the site reveal that the shale-rich rocks have fabric-related average velocity anisotropy of between 10% and 30%. The cross-hole seismic data are consistent with these values, indicating that observed anisotropy might be principally due to the inherent rock fabric rather than to the aligned sets of open fractures. One region with velocity anisotropy greater than 30% has been modelled as aligned open fractures within an anisotropic rock matrix and this model is consistent with available fracture density and hydraulic transmissivity data from the boreholes and the cross-hole resistivity tomography data. However, in general the study highlights the uncertainties that can arise, due to the relative influence of rock fabric and fluid-filled fractures, when using geophysical techniques for hydrological investigations.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.