Devonian Shale Gas Production: Mechanisms and Simple Models

Carlson, Eric S.; Mercer, J.C.

doi:10.2118/19311-pa

Cited by 108 publications

(30 citation statements)

References 6 publications

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“…Adsorbed gas can be desorbed and transported only through the small-pore networks, which therefore constrains production. Because of the low permeability, diffusion in these small pores can be an important transport process (Kucuk and Sawyer 1980;Kuuskraa and Sedwick 1985;Soeder 1988;Carison and Mercer 1991); however, direct measurement of diffusion has not been reported for shale rocks. Therefore, more work on diffusion in small pores (<5-10 nm) is needed.…”

Section: Discussionmentioning

confidence: 99%

An Integrated Method for Upscaling Pore-Network Characterization and Permeability Estimation: Example from the Mississippian Barnett Shale

et al. 2015

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Although pore-network characterization of shale rock systems is being actively investigated, a detailed understanding of the pore network at the nanometer-to-millimeter scale has not been completed. This is because of the technical limitations of collecting and integrating data at the wide spectrum of scales necessary to understand the pore network. Permeability for a micrometer-scale volume can be estimated based on pore-scale modeling for the focused ion beam/scanning electron microscope (FIB/SEM) milled 3D pore network; however, it is not clear how representative this permeability is for larger volumes. In this study, an integrated method employing FIB/SEM, helium ion microscopy, and synchrotron X-ray micro-computed tomography (micro-CT) was developed and applied to a Barnett Shale sample for pore and organic-matter distribution network characterization and upscaling. Organic-matter particle network characterization using synchrotron micro-CT scanning is the key step that bridges the gap between nanometer-scale and macroscopic observations. A conceptual model and an empirical equation were developed for permeability estimation based on FIB/SEM and micro-CT image analysis and mercury intrusion data. Upscaled permeability estimation was produced based on the empirical equation and parameters from the image and mercury intrusion analysis. The resulting permeability values of 2-22 and 0.6-3 nD for parallel and perpendicular to bedding planes, respectively, are comparable to laboratory measurements of the same sample. The proposed technique provides a method for more basic understanding of the pore network and pore-permeability relationship for organicrich shale samples, and can serve as a basis for further upscaling to core and formation scale.

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Section: Discussionmentioning

confidence: 99%

An Integrated Method for Upscaling Pore-Network Characterization and Permeability Estimation: Example from the Mississippian Barnett Shale

et al. 2015

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“…However, both of them ignored the effect of diffusive flow. Carlson and Mercer (1991) described desorption behavior of shale gas by Langmuir isotherm theory and employed the Fick's law to consider the effect of diffusion. However, pressure responses calculated by this model could not reflect characteristic flow regime for fractured wells.…”

Section: Introductionmentioning

confidence: 99%

Production performance analysis for composite shale gas reservoir considering multiple transport mechanisms

Guo

Wei

et al. 2015

Journal of Natural Gas Science and Engineering

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“…Simplified systems modeling of shale-gas wells porosity systems model the fracture and rock matrix-blocks as two distinct media with different properties. The main difference between the numerous variants of dual-porosity models that have been developed, lies in modeling of the flow between the two media, and the imposed geometry of fractures and shale matrix blocks (Carlson and Mercer, 1991;El-Banbi, 1998;Medeiros et al, 2010;Ozkan et al, 2011). Even though these models intuitively fit the matrix-fracture system of shalegas reservoirs, their idealized cube-based geometry and need to set reservoir specific coefficients such as matrix storativity and interporosity flow, often leads to a lack of accuracy in the longterm transient flow behavior in shales .…”

Section: Shale-gas Reservoir Modelingmentioning

confidence: 99%