Simple to use
We replace the traditional correlation+facies modeling steps with a constrained, process-based, depositional process model to define realistic geobodies fitting the well's data. The body's boundaries will define the reservoir grid geometry and fine-scale correlations.
The grid is built after the sedimentary modeling, not a priori, as in the traditional workflow. The thin shale layers are preserved in the grid geometry or topology as transmissivity barriers. The modeled sedimentary body's intrinsic properties will provide trend information for interpolating or simulating rock properties.
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What do we not need? We do not need variograms, complex parameters typically required by other processed-based systems (sediment input, diffusion coefficient, grain density, etc.), or detailed markers' correlation.
What do we need: the depositional environment and some of its geometrical constraints, the range of dimensions of the deposition bodies, the lithofacies interpretation (lithology & depositional setting, see SEPM definition), and the eustatic sea-level curve correlated to the parasequences (when applicable).
How does it work?
Building reservoir models is a three-step process: first, correlate well picks; second, build a stratigraphic grid; and third, use geostatistics to compute facies and property values.
Different problems exist with this method:
In input, we take well's lithofacies interpretation and geomorphology constraints (like valley geometry and faults) from seismic data and, optionally, an eustatic sea-level curve correlated to the parasequences boundaries. We can use lithofacies proportions constraints from seismic.
We stochastically construct a deposition sequence using forward stratigraphic modeling. The interpreted lithofacies intervals control each sedimentary body's position and thickness. If seismic information is available, it can constrain the paleo-landscape or the terminal shapes of a meandering river.
We use all bodies' boundaries to construct a reservoir grid preserving thin-shale layers.
We provide deposition trends to use when simulating grid porosity and permeability.
Traditional facies modeling can be quite complex and, therefore, time-consuming. It requires variograms per facies and facies trends. Facies trends need to be drawn by hand. If you want to use MPS, you must build training images, which can be quite complex. The other issue with MPS is that images " hardcode" the facies juxtapositions and proportions, which may not be valid over the entire grid.
Traditional modeling requires manually building the layering, which requires creating fine-scale correlations. Correlating can be very time-consuming and increase the number of layers to be modeled in the grid, adding complexity to the process.
Accelerating modeling
Our method is rule-based, as defined in the geologic modeling continuum by Pyrcz et al. (2015). It includes all the techniques of other rule-based methods (object-based, surface-based, process-based) but focuses on controlling the depositional processes and objects per depositional environment. Another critical aspect is that our method is multi-scale both in time and space. This allows the integration of basin information at the wells' scale.
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