A combination of sedimentary dip, structural dip and borehole orientation resulted in a core recovered from the Auk Field being cut sub-parallel to aeolian slipface deposits. Individual 2 inch (5 cm) thick grainflow deposits may be followed for up to 16 ft (4.88 m) along core. A conventional core-plug permeability data-set indicated the importance of a deleterious effect of fine-grained ‘pin-stripe’ laminae which separate individual grainflows. Using a probe-permeameter, over 1000 permeability readings were taken from 27 ft (8.23 m) of the core, mostly on a 1 inch (2.5 cm) spaced grid, in order to study small-scale variations and controls of permeability. The readings were taken from five grainflow laminae and associated wind-ripple deposits in a single slipface deposit, and from wind-ripple laminae from an interdune setting. Individual grainflow laminae sometimes show coarsening-upward patterns of grain-size variation which can be ascribed to dispersive forces acting during sedimentation. In terms of permeability distribution, individual grainflows may be distinct from their immediate neighbours. Geostatistical analyses indicate permeability correlation lengths across grain-flow laminae equal to lamina spacings, and a within grainflow correlation length of approximately 1.5 ft (46 cm). Similar tests within millimetre-scale laminated wind-ripple deposits indicate appreciably smaller correlation distances. These results can be translated into effective sampling strategies of one reading per grainflow deposit for a traverse perpendicular to sedimentary dip, and one reading every 6–12 inch (15cm–30cm) for a traverse along grainflow lamination. Wind-ripple laminae cannot feasibly be sampled in a truly representative fashion by standard core-plugs. Petrographic analyses indicate that the principle microscopic controls upon permeability are grain-sorting, the development of authigenic cements and the detrital plus authigenic clay content.

The Seria Field was discovered in 1929. Cumulative oil production reached 164X10 6 m 3 (end 1996), approximately 34% of known in-place volumes. A maximum oil production level of 18 780 m 3 /d in 1956 has since declined to 2800 m 3 /d. Most of the more easily recoverable oil has now been produced. Undeveloped oil is concentrated in economically marginal accumulations for which simple subsurface models are an inadequate basis on which to plan further development activities. Instead, dynamic simulation of detailed computer-generated 3D reservoir models is required to optimize reservoir management and evaluate potential development options. 3D seismic data are used to assess undrilled closures and new exploration plays resulting in the development of new hydrocarbon accumulations. Amplitude analysis combined with GST/RST logging has identified areas of unswept oil within the field. Detailed 3D reservoir geological models integrating sequence stratigraphic concepts with reappraisal of core and wireline data are being built using Unix workstations. The models incorporate the results of advanced petrophysical techniques, such as image analysis and resistivity inversion, to quantify net sand, porosity and saturation, and NMR to provide information on moveable oil and permeability. The model forms the input to advanced reservoir simulators where multiple sensitivities can be tested to determine the optimum placement of new wells. Advances in drilling technology have led to the use of horizontal and multi-lateral wells to give the increased productivity necessary for commercial success of such marginal developments. Concurrent engineering effort has led to the field's facilities being rationalized to improve efficiency and reduce costs and the designing of re-usable well jackets for the shallow offshore part of Seria.

To improve the management of a Nigerian deep water field, two vintages of 4D data have been acquired since field start up in 2005. The first Nigerian 4D seismic (monitor-I) in water depths greater than 1000 m was taken in this field in 2008, and the second monitor (monitor-II) was acquired in 2012. Compared to monitor-I, better geometric repeatability was achieved in monitor-II as the lessons learned from monitor-I were incorporated to achieve better results. The final normalized root mean square of monitor-II fast-track volume was 12% compared to 25% for monitor-I. The improved quality is attributed to improvements in the acquisition methodology and prediction of the effects of currents. Seismic interpretation of the field revealed two distinct turbidite depositional settings: (1) An unconfined amalgamated lobe system with low relief, high net-to-gross reservoir sands that exhibit fairly homogeneous water flooding patterns on 4D and (2) an erosional canyon setting, filled with meander belts having a more complex 3D connectivity within and between the channels resulting in a challenging 4D interpretation. The time lapse data were instrumental for better understanding the reservoir architecture, enabling improved wells and reservoir management practices, the identification of infill opportunities, and more mature subsurface models. We evaluated the seismic acquisition and the 4D interpretation of the deepwater 4D seismic data, highlighting the merits of a multidisciplinary collaborative understanding to time-lapse seismic. At present, the value of information of the 4D monitor-II is conservatively estimated at 101 million United States dollars, equivalent to the cost of a well in this deepwater operating environment.

The Leman Field is the largest discovered gas field in the southern North Sea. Production is from Rotliegend Sandstones which predominantly have an aeolian origin. In the Shell/Esso acreage the flanks of the Leman Reservoir are sparsely drilled, and potentially large amounts of gas remain in place. In these areas only the relatively poor quality uppermost part of the Rotliegend Reservoir is above the gas/water-contact. Analysing reservoir properties in the uppermost Rotliegend indicates that the variation in reservoir properties within a lithofacies is significantly larger than the variation in average reservoir properties between lithofacies. Sedimentary structures are the most likely cause for this internal heterogeneity. Consequently, drilling a well parallel to the main foreset dip, the direction of maximum heterogeneity, should maximise productivity. In the Leman Field this means that wells should be drilled parallel to the main paleowind direction, which is from southeast to northwest. Introduction The Leman Field is located in the southern North Sea some 31 miles (50 km) NE of the East Anglian Coast (Figure 1). It is the largest discovered gas field in the southern North Sea. Well 49/26-1 discovered the field in 1966. This well was drilled close to the present location of the 49/26-A Platform (Figure 1). The field extends into blocks 49/26, 49/27, 49/28, 53/1 and 53/21. The field is a large NW-SE trending faulted anticline some 19 by 8 miles (30 by 13 km) in extent (Figure 1). It is situated at the southern end of the Sole Pit Basin between the Dowsing and Swarte Bank Faults. The reservoir consists of predominantly aeolian sandstones of the Permian Rotliegend Group. Lower in the sequence also waterlain and some Sabkha deposits occur. The thickness of the Rotliegend varies between 550 - 900 ft (170 and 275 m). Evaporites from the Zechstein Group cap the reservoir, while the underlying Westphalien Coal Measures are the source of the gas (Figure 2)l. Several free water levels have been defined but it is generally taken as 6717 ft. This is some 800 ft below the crest of the reservoir. Objectives The main objective of the study described in this paper is to help in locating the remaining producable gas. The focus is on refining the present reservoir model through integration of modern sedimentological concepts regarding desert sedimentation and through the establishment of regional patterns of diagenesis. Then we aim at extrapolating the sedimentological model into the undrilled flanks of the reservoir. Because these are virtually untapped, they will probably contain most of the remaining producable gas. Methodology used in this study The evaluation of 21 cores enabled the subdivision of the reservoir into zones of different reservoir quality and lithofacies content. These zones are also rccognisable in the well logs. Therefore we can recognize them in the uncored wells. We correlated these zones between the wells in the various well clusters. These correlations form the basis for the geological model described in this paper.