Lithologic characterization of the Barnett Shale: Controls on reservoir quality

The overall objective of this study was to determine the lithologic controls on reservoir quality in the Barnett Shale and to build depositional and sequence stratigraphic models to predict reservoir quality.;Core analysis led to the definition of four main lithofacies; siliceous mudstone, argillaceous mudstone, calcareous mudstone, and dolomitic mudstone. Each lithofacies effectively represents an end member of the quartz-carbonate-clay ternary diagram. The lithofacies show a mixture of detrital and authigenic constituents that each correlate to a specific depositional environment.;The siliceous mudstone facies was found to be the highest quality reservoir facies. Siliceous mudstones are characterized by the highest porosity and permeability in the Barnett as well as the most efficient fabric for the formation and preservation of primary interparticle porosity. A byproduct of this semi-rigid framework is brittleness, which makes the siliceous mudstone the best facies to land a horizontal well and propagate hydraulic fractures.;The vertical distribution of TOC is a function of production, destruction, and concentration/dilution of organic matter. The three variables and the relationships among them are tied to depositional environments and the unique conditions that produce them.;Analysis of lithofacies led to the recognition of a series of depositional environments associated with sedimentation on an oxygen-deficient continental shelf. The depositional environments were characterized by the position of sea level and the resulting effects on sedimentation and geochemistry. The cyclical pattern of rising and falling sea level led to deposition of stacked packages that can be quantified and predicted by applying a sequence stratigraphic model.;It was shown that sequence stratigraphic subdivisions, such as possible 3nd-order sequence boundaries, can be inferred by the utilization of basinwide cross sections that provided data that cannot be seen with one core. These basin scale trends could be combined with higher resolution reservoir analysis similar to this one to create very effective reservoir quality prediction models.