Reservoir modeling: Integrating various data at appropriate scales

Abstract

Modern reservoir characterization workflows attempt to integrate all available, reliable, and appropriate sources of data into 3D geocellular or numerical earth model(s). These models provide various properties such as lithofacies, porosity, permeability, hydrocarbon/water saturation at each grid cell. Reservoir simulation is then performed on the geocellular model to predict reservoir performance and production history. Geocellular models allow geoscientists to integrate various data from many different sources to calculate oil and gas volumetrics, perform efficient well planning, forecast reservoir performance, and optimize reservoir depletion schemes. In addition, within the same model, the stochastic simulation process can generate multiple equiprobable realizations, all of which honor the input data. The differences among these realizations provide a quantitative envelope of the uncertainty due to the limited reservoir information and data for the subsurface.In reservoir or geocellular modeling, different types of data are used, including geologic, geophysical, petrophysical, and engineering data. Some input data may be highly conceptual and not necessarily limited to a specific reservoir; for example, geologic knowledge can describe the reservoir at all possible scales. There are also various types of measured data specific to the reservoir, such as conventional core, well logs, 3D seismic, well testing, and hydrocarbon production. These data measure the reservoir at different scales. For example, well log data can provide centimeter-to-meter scale resolution, while seismic data are at comparatively lower resolution and provide larger-scale stratigraphic and structural information. These different data types need to be incorporated into the geocellular model at their correct scales. We propose a workflow integrating various types of data including geologic, geophysical, well/petrophysical, and associated knowledge at their respective scales. For this case study, the workflow is applied to a fluvial reservoir that experienced a complex structural history that today is located in an offshore marine setting.Geologic background. The reservoir is Tertiary age, siliciclastic, and was deposited in a rapidly subsiding basin formed in part by wrench and extensional tectonism. The gross reservoir section is approximately 150 m thick with an average of 25% net-to-gross and 20 m of net pay. The sandstone and shale were deposited in a fluvial-dominated setting, which included both meander belts and braided streams. Individual channels are approximately 10-40 m in thickness and 20-800 m in width, and can be filled with either sandstone or shale. These sand and shale-filled channels characteristically have similar shapes and sizes. The fluvial channels have a complex connectivity that affects fluid flow. Fluid and pressure data suggest that some channels are isolated features while other channels are highly connected in labyrinth geometries. In addition, some cross-cutting shalefilled channels can act as local barriers th...

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