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Interpreting shale lithofacies is an important step in identifying productive zones in the Marcellus Shale gas play; the target reservoir can be less than 3 m (10 ft) thick with overlying shales that appear similar on certain petrophysical well logs and in the core. However, these nonreservoir-quality shales contain widely varying organic and mechanical properties. To distinguish between reservoir- and nonreservoir-quality shale facies, this classification method applies a pattern-recognition algorithm, expectation maximization, to a set of commonly available petrophysical and elastic well logs to create 1D shale facies models along the wellbore. The statistical algorithm classifies the petrophysical and elastic well-log data into defined facies using the theory that each well log contains a distribution of Gaussian curves for each facies. The method is applied to 12 wells across Pennsylvania and northern West Virginia, and it is able to discriminate between shale facies based on organic content and brittleness, characteristics which are not always evident in core. To verify the geologic accuracy of the facies models, the results are compared with the core data, well logs, mudlogs, and regional stratigraphic studies when available. In addition, we were able to designate a lithofacies-defined top to the Marcellus Formation in parts of the Appalachian Basin where the gradational contact with the overlying Mahantango Formation is poorly defined on petrophysical logs.

The Moxa Arch in the Greater Green River Basin, southwestern Wyoming, hosts two potential reservoirs for CO 2 sequestration. The Bighorn Dolomite and Madison limestone are interpreted to be independent reservoirs based on differing CO 2 compositions and production histories; the two reservoirs are separated by Devonian carbonates, siliciclastic rocks, and evaporites. On the Moxa Arch, the Bighorn ranges in thickness from 67 to 120 m with porosities from 3 to 15 percent. The massive buff-colored Steamboat Point Member comprises the bulk of the subsurface Bighorn in southwest Wyoming. Mottled dolostone (light-colored patches with higher porosity and dark-colored patches with lower porosity) is very common and is presumably the result of preferential early dolomitization of bioturbation. Core study suggests that this factor affects gas saturation and storage in this extensive reservoir. The lower Member of the Jefferson Formation is the most probable seal within the Devonian stratigraphy. Strata of this member are interpreted to have been deposited in a shallow basin semi-isolated from the deeper marine environment to the west. 87 Sr/ 86 Sr isotopic analyses of anhydrite sampled from Moxa Arch well cuttings support the interpretation of a depositional environment exposed to a mixture of seawater and freshwater. High-frequency relative sea level fluctuations superimposed on a gently sloping shelf produced alternating layers of marine carbonates, peritidal siliciclastic rocks, and evaporites. The evaporites are interpreted to seal CO 2 in the Bighorn Dolomite from the overlying Madison limestone. The lower Paleozoic strata on the Moxa Arch provide an effective trap-reservoir-seal combination for naturally occurring CO 2 with potential applications to future studies at analogous locations in the central Rocky Mountain Region.

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Log-facies classification at the well location allows determination of the number of facies, the facies definition, and the correlation between facies and rock properties along the well profile. In unconventional reservoirs, because of the necessity for hydraulic fracturing in shale gas and shale oil reservoirs, facies classification should account for petroelastic and geomechanical properties. We developed a facies classification methodology based on the expectation-maximization algorithm, a statistical method that allows finding the most likely facies classification and the associated probability distribution, given the set of geophysical measurements in the borehole. We applied the proposed workflow to a complete set of well logs from the Marcellus shale and developed the corresponding facies classification from log properties measured and computed in three different domains: petrophysics, rock physics, and geomechanics. In thne preliminary well-log and rock-physics analysis, we identify three main lithofacies: limestone, shale, and sandstone. The application of the classification method provided the vertical sequence of the three lithofacies and their pointwise probability of occurrence. A sensitivity analysis was finally evaluated to investigate the impact of the number of input variables on the classification and the effects of cementation and kerogen.

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