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NARROW
GeoRef Subject
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Primary terms
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Stone Age
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Tertiary
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Chordata
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Yorkshire England
Virtual outcrop-based analysis of channel and crevasse splay sandstone body architecture in the Middle Jurassic Ravenscar Group, Yorkshire, NE England
Baseline surface- and groundwater monitoring prior to an onshore shale gas operation in the Vale of Pickering, UK
The stratigraphy of the Kimmeridge Clay Formation (Jurassic) of the Vale of Pickering, Yorkshire, UK
The lower Carboniferous blastoid Astrocrinus tetragonus (Austin and Austin), from Grassington, Yorkshire, and the validity of Astrocrinus benniei (Etheridge)
Possible new evidence for Mid-Pleistocene glaciation in the Vale of Pickering, North Yorkshire, UK
A possible serpulid tube worm of the genus Filograna from the upper Permian Cadeby Formation of South Yorkshire, UK
The temperature of Britain's coalfields
Microconchus cravenensis n. sp.: a giant among microconchid tubeworms
The Vale of Pickering gas fields: Kirby Misperton, Malton, Marishes and Pickering, North Yorkshire, UK Onshore
Abstract The Vale of Pickering gas fields were discovered over a 20-year period. The development scheme was aimed to deliver 9.3 MMscfd gas to the Knapton Power Station nearby. Cumulative production is 30.3 bcf from an estimated 172 bcf gas initially in place. The gas fields comprise a series of low relief structures at depths around 5000 ft true depth subsea. The primary reservoir is Zechstein Group dolomitized and fractured carbonates of the Permian Kirkham Abbey Formation with average reservoir quality ranges of 12–13% porosity and 0.5–1.5 mD permeability. Secondary reservoirs exist in Carboniferous sandstones directly below the Base Permian Unconformity. The gas is sourced from Lower Carboniferous shales. The fields were discovered using 2D seismic data and subsequent 3D seismic data have been merged to form a 260 km 2 dataset. Zechstein production has been limited by early water breakthrough. Artificial lift is planned to enhance the gas flow rate on the Pickering Field and anticipated water influx will be re-injected. If this enhanced gas recovery scheme is successful it can be applied to the other fields. Plans to hydraulically fracture a number of zones in the Carboniferous Lower Bowland Section are in progress.
Abstract The Babbage gas field was discovered in 1988 by exploration well 48/2-2 which drilled into the Permian-age lower Leman Sandstone Formation below a salt wall. Seismic imaging is compromised by the presence of this salt wall, which runs east–west across the southern part of the structure, creating uncertainties in depth conversion and in the in-place volumes. Pre-stack depth migration with beam and reverse time migrations appropriate for the complex salt geometry provided an uplift in subsalt seismic imaging, enabling the development of the field, which is located at the northern edge of the main reservoir fairway in a mixed aeolian–fluvial setting. Advances in artificial fracturing technology were also critical to the development: in this area, deep burial is associated with the presence of pore-occluding clays, which reduce the reservoir permeability to sub-millidarcy levels. The Babbage Field was sanctioned in 2008, based on an in-place volume range of 248–582 bcf; first production was in 2010. It produces from five horizontal development wells that were artificially fracced to improve deliverability of gas from the tight matrix. None of the wells has drilled the gas–water contact, which remains a key uncertainty to the in-place volumes, along with depth-conversion uncertainty below the salt wall.
Workflow model for the digitization of mudrocks
Abstract Mudrocks are highly heterogeneous in a range of physical and chemical properties, including: porosity and permeability, fissility, colour, particle composition, size, orientation, carbon loading, degree of compaction, and diagenetic overprint. It is therefore important that the maximum information be extracted as efficiently and completely as possible. This can be accomplished through high-resolution analysis of polished thin sections by scanning electron microscopy (SEM), with the collection of large-area images and X-ray elemental map montages, and the application of targeted particle analysis. A workflow model, based on these techniques, for the digitization of mudrocks is presented herein. A range of the data that can be collected and the variety of analyses that can be achieved are also illustrated. Data collection is discussed in terms of inherent problems with acquisition, storage, transfer and manipulation, which can be time-consuming and non-trivial. Similar information and resolutions can be achieved through other techniques, such as QEMSCAN and infra-red (IR)/Raman spectroscopic mapping. These can be seen as complementary to the workflow described herein.
Abstract Chlorite is a key mineral in the control of reservoir quality in many siliciclastic rocks. In deeply buried reservoirs, chlorite coats on sand grains prevent the growth of quartz cements and lead to anomalously good reservoir quality. By contrast, an excess of chlorite – for example, in clay-rich siltstone and sandstone – leads to blocked pore throats and very low permeability. Determining which compositional type is present, how it occurs spatially, and quantifying the many and varied habits of chlorite that are of commercial importance remains a challenge. With the advent of automated techniques based on scanning electron microscopy (SEM), it is possible to provide instant phase identification and mapping of entire thin sections of rock. The resulting quantitative mineralogy and rock fabric data can be compared with well logs and core analysis data. We present here a completely novel Quantitative Evaluation of Minerals by SCANning electron microscopy (QEMSCAN®) SEM–energy-dispersive spectrometry (EDS) methodology to differentiate, quantify and image 11 different compositional types of chlorite based on Fe : Mg ratios using thin sections of rocks and grain mounts of cuttings or loose sediment. No other analytical technique, or combination of techniques, is capable of easily quantifying and imaging different compositional types of chlorite. Here we present examples of chlorite from seven different geological settings analysed using QEMSCAN® SEM–EDS. By illustrating the reliability of identification under automated analysis, and the ability to capture realistic textures in a fully digital format, we can clearly visualize the various forms of chlorite. This new approach has led to the creation of a digital chlorite library, in which we have co-registered optical and SEM-based images, and validated the mineral identification with complimentary techniques such as X-ray diffraction. This new methodology will be of interest and use to all those concerned with the identification and formation of chlorite in sandstones and the effects that diagenetic chlorite growth may have had on reservoir quality. The same approach may be adopted for other minerals (e.g. carbonates) with major element compositional variability that may influence the porosity and permeability of sandstone reservoirs.