Extracting Hydrocarbon from Shale: An Investigation of the Factors That Influence the Decline and the Tail of the Production Curve

Lovell, A. E.; Srinivasan, S.; Karra, S.; O'Malley, D.; Makedonska, N.; Viswanathan, H. S.; Srinivasan, G.; Carey, J. W.; Frash, L. P.

doi:10.1029/2017WR022180

Title: Extracting Hydrocarbon from Shale: An Investigation of the Factors That Influence the Decline and the Tail of the Production Curve

Journal Article · Tue Apr 24 00:00:00 EDT 2018 · Water Resources Research

DOI:https://doi.org/10.1029/2017WR022180· OSTI ID:1438117

Lovell, A. E. ^[1]; Srinivasan, S. ^[2];

^[2]; O'Malley, D. ^[2]; Makedonska, N. ^[2];

^[2]; Srinivasan, G. ^[2];

^[2];

^[2]

Michigan State Univ., East Lansing, MI (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Abstract Understanding physical processes that control the long‐term production of hydrocarbon from shale formations is important for both predicting the yield and increasing it. In this work, we explore the processes that could control the tail of the production curve by using a discrete fracture network method to calculate the total travel time from the rock matrix to small‐scale fractures to the primary hydraulic fracture network. The factors investigated include matrix diffusion, extent of the small‐scale fracture zone (or tributary fracture zone/TFZ) consisting of natural, reactivated and induced fractures, and the percentage of free hydrocarbon in the primary fracture network. Individual and combined parameter spaces are explored for each of these to understand the limits of these parameters as well as any systematic correlations between pairs of parameters. Although recent studies have shown that the matrix diffusion in virgin shale influences the production tail only after nearly 20 years, we demonstrate that matrix diffusion in the region of the TFZ significantly impacts production within the first year itself. Additionally, we found that the depth of TFZ fracturing region had no effect on the shape of the production curves although the total mass of the hydrocarbon produced increases with the depth. We also show that one can fit the production data using a site‐specific set of parameters representing the diffusion in the TFZ, depth of the TFZ, and the free hydrocarbon in the large‐scale fractures.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC). Basic Energy Sciences (BES) (SC-22); USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1438117

Alternate ID(s):: OSTI ID: 1438944

Report Number(s):: LA-UR-17-30119

Journal Information:: Water Resources Research, Vol. 54, Issue 5; ISSN 0043-1397

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 6 works

Citation information provided by
Web of Science

References (22)

Methods of estimating shale gas resources – Comparison, evaluation and implications McGlade, Christophe; Speirs, Jamie; Sorrell, Steve Energy, Vol. 59 https://doi.org/10.1016/j.energy.2013.05.031	journal	September 2013
Integration of microseismic and other post-fracture surveillance with production analysis: A tight gas study Clarkson, C. R.; Beierle, J. J. Journal of Natural Gas Science and Engineering, Vol. 3, Issue 2 https://doi.org/10.1016/j.jngse.2011.03.003	journal	May 2011
The Monte Carlo Method Metropolis, Nicholas; Ulam, S. Journal of the American Statistical Association, Vol. 44, Issue 247 https://doi.org/10.1080/01621459.1949.10483310	journal	September 1949
Fracture-permeability behavior of shale Carey, J. William; Lei, Zhou; Rougier, Esteban Journal of Unconventional Oil and Gas Resources, Vol. 11 https://doi.org/10.1016/j.juogr.2015.04.003	journal	September 2015
Understanding hydraulic fracturing: a multi-scale problem Hyman, J. D.; Jiménez-Martínez, J.; Viswanathan, H. S. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 374, Issue 2078 https://doi.org/10.1098/rsta.2015.0426	journal	October 2016
From the Cover: Cozzarelli Prize Winner: Gas production in the Barnett Shale obeys a simple scaling theory Patzek, T. W.; Male, F.; Marder, M. Proceedings of the National Academy of Sciences, Vol. 110, Issue 49 https://doi.org/10.1073/pnas.1313380110	journal	November 2013
Mineralogy and trace element geochemistry of gas shales in the United States: Environmental implications Chermak, John A.; Schreiber, Madeline E. International Journal of Coal Geology, Vol. 126 https://doi.org/10.1016/j.coal.2013.12.005	journal	June 2014
PFLOTRAN User Manual: A Massively Parallel Reactive Flow and Transport Model for Describing Surface and Subsurface Processes Lichtner, Peter; Hammond, Glenn; Lu, Chuan https://doi.org/10.2172/1168703	report	January 2015
Measurement of gas storage processes in shale and of the molecular diffusion coefficient in kerogen Etminan, S. Reza; Javadpour, Farzam; Maini, Brij B. International Journal of Coal Geology, Vol. 123 https://doi.org/10.1016/j.coal.2013.10.007	journal	March 2014
A Model To Estimate Carbon Dioxide Injectivity and Storage Capacity for Geological Sequestration in Shale Gas Wells Edwards, Ryan W. J.; Celia, Michael A.; Bandilla, Karl W. Environmental Science & Technology, Vol. 49, Issue 15 https://doi.org/10.1021/acs.est.5b01982	journal	July 2015
Production data analysis of unconventional gas wells: Review of theory and best practices Clarkson, C. R. International Journal of Coal Geology, Vol. 109-110 https://doi.org/10.1016/j.coal.2013.01.002	journal	April 2013
Particle tracking approach for transport in three-dimensional discrete fracture networks: Particle tracking in 3-D DFNs Makedonska, Nataliia; Painter, Scott L.; Bui, Quan M. Computational Geosciences, Vol. 19, Issue 5 https://doi.org/10.1007/s10596-015-9525-4	journal	September 2015
Validity of Cubic Law for fluid flow in a deformable rock fracture Witherspoon, P. A.; Wang, J. S. Y.; Iwai, K. Water Resources Research, Vol. 16, Issue 6 https://doi.org/10.1029/WR016i006p01016	journal	December 1980
Pathline tracing on fully unstructured control-volume grids Painter, S. L.; Gable, C. W.; Kelkar, S. Computational Geosciences, Vol. 16, Issue 4 https://doi.org/10.1007/s10596-012-9307-1	journal	July 2012
Where Does Water Go During Hydraulic Fracturing?: D. O'Malley et al. Groundwater xx, no. x: xx-xx O'Malley, D.; Karra, S.; Currier, R. P. Groundwater, Vol. 54, Issue 4 https://doi.org/10.1111/gwat.12380	journal	October 2015
Effect of advective flow in fractures and matrix diffusion on natural gas production Karra, Satish; Makedonska, Nataliia; Viswanathan, Hari S. Water Resources Research, Vol. 51, Issue 10 https://doi.org/10.1002/2014WR016829	journal	October 2015
Simulation of gas desorption and geomechanics effects for unconventional gas reservoirs Yu, Wei; Sepehrnoori, Kamy Fuel, Vol. 116 https://doi.org/10.1016/j.fuel.2013.08.032	journal	January 2014
dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia Computers & Geosciences, Vol. 84 https://doi.org/10.1016/j.cageo.2015.08.001	journal	November 2015
Probing Hydrocarbon Fluid Behavior in Shale Formations Xu, H.; Hjelm, R. P.; Ding, M. Unconventional Resources Technology Conference https://doi.org/10.2118/178700-MS	conference	August 2015
Integration of Microseismic and Other Post-Fracture Surveillance With Production Analysis: A Tight Gas Study Clarkson, C. R.; Beierle, J. J. SPE Unconventional Gas Conference, All Days https://doi.org/10.2118/131786-ms	conference	February 2010
Simulation of Gas Desorption and Geomechanics Effects for Unconventional Gas Reservoirs Yu, Wei; Sepehrnoori, Kamy SPE Western Regional & AAPG Pacific Section Meeting 2013 Joint Technical Conference, All Days https://doi.org/10.2118/165377-ms	conference	April 2013
The Monte Carlo method Granovskii, B. L.; Ermakov, S. M. Journal of Soviet Mathematics, Vol. 7, Issue 2 https://doi.org/10.1007/bf01084250	journal	February 1977

Cited By (2)

Robust system size reduction of discrete fracture networks: a multi-fidelity method that preserves transport characteristics Srinivasan, Shriram; Hyman, Jeffrey; Karra, Satish Computational Geosciences, Vol. 22, Issue 6 https://doi.org/10.1007/s10596-018-9770-4	journal	September 2018
Characterizing the Impact of Fractured Caprock Heterogeneity on Supercritical CO$$_2$$ Injection Hyman, Jeffrey D.; Jiménez-Martínez, Joaquin; Gable, Carl W. Transport in Porous Media, Vol. 131, Issue 3 https://doi.org/10.1007/s11242-019-01372-1	journal	November 2019