Integration of pressure, production, geochemical, seismic, well log and structural data provides important information on the sealing capacity and dynamic behavior of fault-juxtaposed reservoirs. Reservoir juxtapositions and potential cross-fault communication pathways are easily defined with faultplane sections (Allan maps). Smear gouge ratios, calculated from E-logs, areused to estimate the composition of fault-gouge materials between thejuxtaposed reservoirs. History matching of the available production and pressure data with a full-field reservoir simulator are used to quantify the relationship between fault gouge composition and fault transmissibility. This paper presents the results of such a study conducted on the Meren field, Nigeria. The computed fault transmissibility was observed to correlate with the Smear gouge ratio (fault gouge composition). These tools are used to augment the interpretation of seal/nonseal character in proved reservoirs, assist in the quantification of fault-seal risk in untested fault-dependent closures and prove valuable in the management of reservoirs. Introduction Identifying the best practices for the development and management of ahydrocarbon reservoir involves integration of both the geology and reservoir engineering features of the field. The geological data could includeinformation on depositional environment, which can be used to gauge the arealextent of the field; structural geology, to identify the structural featuresincluding faults, their areal extent, amount of slip, and sand/sandjuxta position; and geochemical data that can be used to fingerprint the oil indifferent reservoirs and to identify possible communication, if any, existing between them either along or across a fault. Reservoir engineering and historical production data could be used to enhance the geologic interpretation and to assist in quantifying the effects of these geological features on the long-range production behavior of the reservoirs. In the present work the main purpose of the study was to analyze the behavior of faults from the standpoint of their conductance. Both geological interpretation and reservoir engineering analyses were used in this study of the Meren field, offshore Nigeria. The analysis involved a geological study of the faults using Allan maps to estimate the extent of the sand/sandjuxta position, Smear Gouge Analysis (SGA) to quantify the nature of the faultgouge, and Reservoir Simulation to estimate the transmissibilities of the faultgouge.
The objective in building the Gorgon reservoir characterisation and simulation model was to create a 3D, object based model in a sequence stratigraphic framework integrating core, log, engineering, and seismic attribute data. The project team specified that software and work flow must incorporate marked point - boolean processes with or without seismic conditioning, recognise uncertainties in reservoir and model input parameters, generate multiple model realisations for a probabilistic range of gas in place, and output the model in reservoir simulation format. Reservoirs are in stacked sands of the Mungaroo Formation, with a total formation thickness of greater than 2000 m beneath the major Jurassic unconformity. The Mungaroo Formation was subdivided into 11 intervals on the basis of regional sequence boundaries and systems tracts. Relative lowstand intervals are sand prone, relative highstand intervals much less sand-prone. Facies present include fluvial channels (single channels and amalgamated stacked channels), crevasse splays, and "background" shale (coaly siltstone, coal, and minor carbonate). 3D seismic data were used both for structural modelling and a statistical correlation between seismic attributes and channel sand distribution. Wireline pressure data were used to refine our understanding of stratigraphic compartmentalisation and fluid distribution. The fluvial reservoir architecture model was built using marked point process and simulated annealing for each of the 11 stratigraphic intervals. A range of endpoint net/gross ratios was established based on well penetrations and seismic attributes. The model was scaled-up from a 715 layer geologic model to a 46 layer simulation model, with no areal scale-up. Whilst the scaled-up model honoured the 11 original intervals, the majority of the layers were located in regions identified as key flow units. The resulting simulation model was then used to generate production profiles for various development scenarios. P. 305
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