Abstract
Reservoir characterization using all available data is a popular topic that involves people and expertise from many different disciplines. Even though reservoir characterization has been used for many years, practitioners, developers, and researchers continually envision and employ different approaches and methods to understand the subsurface complexity and to quantify the associated risk. The components used to characterize the subsurface and forecast reservoir performance include, but are not limited to, rock physics, seismic inversion, geologic and geostatistical modeling, and a renewed emphasis on artificial intelligence tools. In addition, many efforts integrate multiple data types with different scales and resolutions, including geophysical, geologic, and engineering data.
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