Organic-rich Marcellus Shale lithofacies modeling and distribution pattern analysis in the Appalachian Basin

The Marcellus Shale is considered to be the largest unconventional shale-gas resource in the United States. Two critical factors for unconventional shale reservoirs are the response of a unit to hydraulic fracture stimulation and gas content. The fracture attributes reflect the geomechanical properties of the rocks, which are partly related to rock mineralogy. The natural gas content of a shale reservoir rock is strongly linked to organic matter content, measured by total organic carbon (TOC). A mudstone lithofacies is a vertically and laterally continuous zone with similar mineral composition, rock geomechanical properties, and TOC content. Core, log, and seismic data were used to build a three-dimensional (3-D) mudrock lithofacies model from core to wells and, finally, to regional scale. An artificial neural network was used for lithofacies prediction. Eight petrophysical parameters derived from conventional logs were determined as critical inputs. Advanced logs, such as pulsed neutron spectroscopy, with log-determined mineral composition and TOC data were used to improve and confirm the quantitative relationship between conventional logs and lithofacies. Sequential indicator simulation performed well for 3-D modeling of Marcellus Shale lithofacies. The interplay of dilution by terrigenous detritus, organic matter productivity, and organic matter preservation and decomposition affected the distribution of Marcellus Shale lithofacies distribution, which may be attributed to water depth and the distance to shoreline. The trend of normalized average gas production rate from horizontal wells supported our approach to modeling Marcellus Shale lithofacies. The proposed 3-D modeling approach may be helpful for optimizing the design of horizontal well trajectories and hydraulic fracture stimulation strategies.

[1]  Stephen C. Ruppel,et al.  Spectrum of pore types and networks in mudrocks and a descriptive classification for matrix-related mudrock pores , 2012 .

[2]  T. Engelder,et al.  Thickness trends and sequence stratigraphy of the Middle Devonian Marcellus Formation, Appalachian Basin: Implications for Acadian foreland basin evolution , 2011 .

[3]  Swapan Chakrabarti,et al.  Comparison of four approaches to a rock facies classification problem , 2007, Comput. Geosci..

[4]  M. Curtis,et al.  Structural Characterization of Gas Shales on the Micro- and Nano-Scales , 2010 .

[5]  Erwin Suess,et al.  Particulate organic carbon flux in the oceans—surface productivity and oxygen utilization , 1980, Nature.

[6]  W. D. Sevon,et al.  The Catskill Delta , 1985 .

[7]  C. V. Straeten.  Basinwide stratigraphic synthesis and sequence stratigraphy, upper Pragian, Emsian and Eifelian stages (Lower to Middle Devonian), Appalachian Basin , 2007 .

[8]  T. Carr,et al.  Geostatistical three-dimensional modeling of oolite shoals, St. Louis Limestone, southwest Kansas , 2007 .

[9]  Lynne E. Johnson Ibach.  Relationship Between Sedimentation Rate and Total Organic Carbon Content in Ancient Marine Sediments , 1982 .

[10]  M. R. Gross,et al.  Mechanical and fracture stratigraphy , 2009 .

[11]  D. Jarvie,et al.  Unconventional shale-gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment , 2007 .

[12]  Clayton V. Deutsch,et al.  Geostatistical Reservoir Modeling , 2002 .

[13]  F. Javadpour.  Nanopores and Apparent Permeability of Gas Flow in Mudrocks (Shales and Siltstone) , 2009 .

[14]  Timothy R. Carr,et al.  Neural network prediction of carbonate lithofacies from well logs, Big Bow and Sand Arroyo Creek fields, Southwest Kansas , 2006, Comput. Geosci..

[15]  Carlton E. Brett,et al.  Middle Devonian sedimentary cycles and sequences in the northern Appalachian Basin , 1996 .

[16]  Andrew C. Aplin,et al.  Mudstone diversity: Origin and implications for source, seal, and reservoir properties in petroleum systems , 2011 .

[17]  Javier Cornejo,et al.  Truncated Gaussian simulation of discrete-valued, ordinal coregionalized variables , 2010, Comput. Geosci..

[18]  T. Lyons,et al.  A tale of shales: the relative roles of production, decomposition, and dilution in the accumulation of organic-rich strata, Middle–Upper Devonian, Appalachian basin , 2003 .

[19]  T. Lyons,et al.  An integrated assessment of a “type euxinic” deposit: Evidence for multiple controls on black shale deposition in the middle Devonian Oatka Creek formation , 2002 .

[20]  Timothy R. Carr,et al.  Methodology of organic-rich shale lithofacies identification and prediction: A case study from Marcellus Shale in the Appalachian basin , 2012, Comput. Geosci..

[21]  D. Gao,et al.  Along-Axis Segmentation and Growth History of the Rome Trough in the Central Appalachian Basin , 2000 .

[22]  J. Bridge,et al.  Geometry, Lithofacies, and Spatial Distribution of Cretaceous Fluvial Sandstone Bodies, San Jorge Basin, Argentina: Outcrop Analog for the Hydrocarbon-Bearing Chubut Group , 2000 .

[23]  M. L. Sweet,et al.  Three-Dimensional Distribution of Lithofacies, Bounding Surfaces, Porosity, and Permeability in a Fluvial Sandstone--Gypsy Sandstone of Northern Oklahoma , 1995 .

[24]  Timothy R. Carr,et al.  Marcellus Shale Lithofacies Prediction by Multiclass Neural Network Classification in the Appalachian Basin , 2012, Mathematical Geosciences.

[25]  K. Bowker.  Barnett Shale gas production, Fort Worth Basin: Issues and discussion , 2007 .

[26]  C. Teichert.  Concepts of Facies , 1958 .

[27]  A. Koesoemadinata,et al.  Seismic Reservoir Characterization In Marcellus Shale , 2011 .

[28]  Andrew Richard Gardiner,et al.  Best practice stochastic facies modeling from a channel-fill turbidite sandstone analog (the Quarry outcrop, Eocene Ainsa basin, northeast Spain) , 2006 .

[29]  S. Rocky Durrans,et al.  Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system , 2000 .

[30]  Margaret E. Walker-Milani.  Outcrop Lithostratigraphy and Petrophysics of the Middle Devonian Marcellus Shale in West Virginia and Adjacent States , 2011 .

[31]  D. Allard.  Simulating a Geological Lithofacies with Respect to Connectivity Information Using the Truncated Gaussian Model , 1994 .

[32]  James J. Hickey,et al.  Lithofacies summary of the Mississippian Barnett Shale, Mitchell 2 T.P. Sims well, Wise County, Texas , 2007 .

[33]  Stephen C. Ruppel,et al.  Mississippian Barnett Shale: Lithofacies and depositional setting of a deep-water shale-gas succession in the Fort Worth Basin, Texas , 2007 .

[34]  A. Immenhauser,et al.  Lithofacies Character and Architecture Across a Pennsylvanian Inner-Platform Transect (Sierra De Cuera, Asturias, Spain) , 2002 .

[35]  A. Chopra,et al.  Integration of seismic attribute map into 3D facies modeling , 2000 .