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Collaborating Authors
Results
The Value of 3D Seismic Attributes For Illuminating Deep Water Deposits By Seismic Forward Modeling of the Brushy Canyon Formation
Clawson, Steven (iReservoir.com) | Meng, Hai-Zui (iReservoir.com) | Sonnenfeld, Mark (iReservoir.com) | Uland, Mike (iReservoir.com) | Batzle, Mike (Colorado School of Mines) | Atan, Safian (Colorado School of Mines) | Gardner, Mike (Colorado School of Mines) | Uman, M. Syafiul (Colorado School of Mines)
Summary A 3D seismic forward model is constructed of deep-water sediment gravity flow deposits to measure the information content of various seismic attributes for qualitative imaging and quantitative reservoir characterization. The emphasis on this study is a measure of utility and robustness of the seismic prediction for improved hydrocarbon reserve estimation and production optimization. This effort builds on realistic, detailed 3D geologic models developed at CSM and constrained by extensive outcrop measurements of the Permian Brushy Canyon deep-water deposits, located in the Delaware Mountains of West Texas. These deepwater deposits range from channelized sheets through stacked channel complexes. The heterogeneous architecture of Brushy Canyon fans 1-5 is the framework for populating with petrophysical properties analogous to unconsolidated Tertiary deep-water deposits of the Gulf of Mexico. The elastic rock properties are empirically generated for the varying facies and porosities of the modeled sediment gravity flow deposit.
- Geology > Sedimentary Geology (0.70)
- Geology > Geological Subdiscipline > Geomechanics (0.39)
- North America > United States > New Mexico > Permian Basin > Brushy Canyon Formation (0.99)
- North America > Canada > Alberta > Sandy Field > Aecog 6B-8 Sandy 3-5-82-20 Well (0.98)
- North America > United States > Texas > Permian Basin > Delaware Basin (0.89)
- North America > United States > New Mexico > Permian Basin > Delaware Basin (0.89)
Summary The cornerstone of successful reservoir characterization is a detailed reservoir model reecting the correct geological framework and intelligently populated with rock properties. Integration of seismic data into reservoir characterization workow allows the creation of a spatially detailed reservoir model from otherwise spatially sparse well data. There are two main issues which need to be addressed when incorporating seismic data into reservoir characterization: construction of an accurate velocity field for time-to-depth conversions and finding geostatistical relationships between seismic attributes and rock properties. The latter is a separate topic and will not be covered here. This paper describes a new methodology to generate high-resolution 3-D velocity field that is consistent with the seismic inversion in time and the sequence stratigraphic framework in depth. This new modelling workow has been successfully applied ina number of reservoir characterization projects