Technical Paper: Multidisciplinary and Integrated Methodology for Deepwater Thinly Bedded Reservoirs Characterization

Society: SPE
Paper Number: 159628
Presentation Date: 2012
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The sedimentation in deepwater environments commonly includes deposition of thinly-bedded pay zones that are difficult to be characterized using standard seismic and logging techniques. Furthermore, these zones are often left unexploited and even overlooked during drilling, as they are finer in resolution than it can be detectable in conventional open-hole logs.

The paper presents an integrated multi-disciplinary study on thinly-bedded reservoir characterization in deep water areas in Malaysia. The adapted workflow consist of: (1) Seismic Data Conditioning, (2) Petrophysical SHARP Analysis, (3) Simultaneous and Rock Model Building, (4) Lithology Prediction, Hydrocarbon Volume, and Net pay, (5) Stochastic Seismic Inversion and Geo-statistical Modeling, and (6) Reservoir Simulation and Validation, (7) Uncertainty Analysis, (8) Sedimentological Analysis using Core-Image, and (9) Geomechanical Rock Property Analysis.

Petrophysical diagnostics using high quality resistivity images of OBMIs, as log input for thinly-bedded modeling, was the primary driver to establish effective elastic properties through AI vs. VP/VS cross plot (for lithology prediction) and AI vs. total porosity cross plot (for porosity prediction) within the model. These cross-plot transforms are then upscaled and applied to build a cascading of deterministic inversion (simultaneous AVO inversion) and stochastic inversion of 1-ms sampling, which are calibrated to core and neural network litho-facies interpretation for lithology and porosity modeling.

The geo-statistical modeling workflow was initially built-in with 7 exploration wells that have OBMIs (Oil Base Micro Imager) as the typical model. Numbers of reservoir properties realizations were generated by generating geo-cellular grid over the zone of interest. These realizations could provide an improved lithology, porosity and fluid determinations and could lead to estimate a more robust volumetric, particularly within such thinly-bedded reservoir. The developed unique integrated workflow was applied on the field under study showing about 30% increase in in-place volume and was successfully validated against available production/well data as well as new drilled wells.

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