Dominic Tatum

Hierarchical benchmark case study for history matching, uncertainty quantification and reservoir characterisation

Benchmark problems have been generated to test a number of issues related to predicting reservoir behaviour (e.g. Floris et al., 2001, Christie and Blunt, 2001, Peters et al., 2010). However, such cases are usually focused on a particular aspect of the reservoir model (e.g. upscaling, property distribution, history matching, uncertainty prediction, etc.) and the other decisions in constructing the model are fixed by log values that are related to the distribution of cell properties away from the wells, fixed grids and structural features and fixed fluid properties. This is because all these features require an element of interpretation, from indirect measurements of the reservoir, noisy and incomplete data and judgments based on domain knowledge. Therefore, there is a need for a case study that would consider interpretational uncertainty integrated throughout the reservoir modelling workflow. In this benchmark study we require the modeller to make interpretational choices as well as to select the techniques applied to the case study, namely the geomodelling approach, history matching algorithm and/or uncertainty quantification technique. The interpretational choices will be around the following areas: (1)Top structure interpretation from seismic and well picks. (2)Fault location, dimensions and the connectivity of the network uncertainty. (3)Facies modelling approach. (4)Facies interpretations from well logs cutoffs. (5)Petrophysical property prediction from the available well data. (6)Grid resolution-choice between number of iterations and model resolution to capture the reservoir features adequately. A semi-synthetic study is based on real field data provided: production data, seismic sections to interpret the faults and top structures, wireline logs to identify facies correlations and saturation profile and porosity and permeability data and a host of other data. To make this problem useable in a manageable time period multiple hierarchically related gridded models were produced for a range of different interpretational choices.

Sand Volcanoes of the Carboniferous Ross Formation, County Clare, Western Ireland: 3-D Internal Sedimentary Structure and Formation

An exceptionally well preserved sand volcano cluster approximately 7 m (23 ft) in diameter lies on top of mass-wasting deposits in the Carboniferous Ross Formation in western Ireland. Sandstone dikes were observed near the volcanoes, emanating from sandstone units beneath the slumped intervals. The volcano cluster was the focus of sedimentary, geophysical (ground-penetrating radar), and surveying (differential global positioning system) methods, with the aim of digitally reconstructing the volcanoes in three dimensions and elucidating their origin and significance. Data analysis determined that single volcanoes were, in fact, composite, with early small cones being overwhelmed by a later dominant cone during deposition. Volcanoes were sourced through feeder dikes that were correlated through slump horizons to underlying in-situ sandstones. A four-stage origin is inferred: (1) initial overpressured sand escaped up through tension gashes in the slump horizons to deposit multiple, small sand cones on the new sea floor; (2) more widely spaced vents allowed multiphase ejection to envelop initial cones and to produce larger volcanoes with a single vent; (3) composite volcanoes loaded and subsided into the underlying substrate and local sand chamber during continued deposition before final cessation; and (4) deposition of overlying pelagic sediments and lithification. Volcanoes may be sited on local sea-floor, topographic highs.

Radar suitability in aeolian sand dunes — A global review

Over the past 40 years, GPR has been used to image the internal architecture of aeolian sand dunes with generally impressive results. These data may be used to produce high resolution models of dune structures, useful in the study of dune migration rates, desertification, as palaeo-environmental indicators and for the construction of petroleum reservoir analogues. Although published works suggest that dry sands are ideal radar environments, practical experience in deserts around the world indicate that maximum penetration depths are highly variable. The factors which influence radar suitability appear to include moisture in the dune core, the presence of conductive evaporates drawn upwards from the dune base through capillarity, surface salinity on coastal dunes, the presence of vegetation, and the lithology of the source rocks. We herein discuss these factors, whilst comparing our results of standardised radar penetration tests from sand bodies in Algeria, Australia, Brazil, Libya, Madagascar, Namibia, Oman, and South Africa.

Regional variability of ground penetrating radar response - A case study from the dune fields of the United Arab Emirates (UAE)

Numerous works have portrayed ground penetrating radar (GPR) as a perfect tool for imaging the internal structure of sand bodies. Arid conditions and high electrical resistivities are commonplace in sands, making them ideal radar environments. However, sandy environments can be extremely diverse and localised variability may cause rapid signal attenuation or loss of definition. On a global scale, comparison between datasets is often impossible due to the wide range of potential variables. On a regional scale, logistical acquisition timeframes and survey constraints often limit data extent. Here we discuss the results of a regional-scale survey across the United Arab Emirates. Fourteen separate sites from differing dune formations, ages and provenance were surveyed with the same equipment between Liwa in the south, to Dubai in the north, over a period of four days. Comparisons are made between signal strength, attenuation, resolution and depth of penetration. A high degree of variability is recognised, even over short distances. Suggestions as to the causes of this are discussed.

Reservoir Impact of Small-scale Aeolian Dune Architecture - From Acquisition to Simulation in the Wahiba Sands, Oman

Small-scale dune heterogeneity has a significant impact upon recoverable reserves within aeolian hydrocarbon reservoirs. Complex geometries exist, with bounding surfaces and primary strata types often negatively impacting fluid flow. Incorporating the effects of such architectural elements into reservoir models is essential when accurately determining their effect on development strategies. In order to assess their impact, we acquired a small pseudo-3D dataset from the Wahiba Sands, Sultanate of Oman, using ground-penetrating radar (GPR). In this paper we discuss the acquisition, processing and modelling of this dataset. Data are interpreted to be of a small linear dune. Radar stratigraphic units have been interpreted and mapped in 3D; a small-scale analogue reservoir model has been produced. Simulation studies have been conducted to assess the impact of a range of sensitivities, including the affects of permeability contrast, flow direction and capillary pressure. Results indicate that permeability contrasts have a significant impact on recovery, whilst flow direction is the dominant factor. The resulting models may not be directly transferable to a specific subsurface scenario, but the generic spatial information can be a useful guide.

Constructing hydrocarbon reservoir analogues with rapid acquisition long-range GPR

The bounding surfaces of dunes have long been known to impart significant permeability contrasts to aeolian sequences. The resulting permeability contrasts can affect hydrocarbon flow in subsurface aeolian reservoirs, the impact of which often increases later in the life of a hydrocarbon field. In order to optimally manage petroleum reservoir development, the spatial arrangement of bounding features needs to be incorporated into subsurface models. However, adequate models cannot be obtained directly from the reservoir as no high-resolution imaging techniques exist for the inter-well area. At best, indirect inferences from an ensemble of remote data can be used to broadly constrain major features. However, many spatial parameters remain poorly constrained, particularly in 3D. GPR (Ground Penetrating Radar) has been shown to provide direct 3D imagery of near-surface deposits at a relevant scale and resolution. The resulting models may not be directly transferable to a specific subsurface scenario, but the generic spatial information can be a useful guide to reservoir engineers. Discussed herein is a case study from southern Libya employing the use of a custom long-range rapid-acquisition GPR system to develop 3D volumes over large areas.