scholarly journals Methane in groundwater before, during, and after hydraulic fracturing of the Marcellus Shale

2018 ◽  
Vol 115 (27) ◽  
pp. 6970-6975 ◽  
Author(s):  
E. Barth-Naftilan ◽  
J. Sohng ◽  
J. E. Saiers

Concern persists over the potential for unconventional oil and gas development to contaminate groundwater with methane and other chemicals. These concerns motivated our 2-year prospective study of groundwater quality within the Marcellus Shale. We installed eight multilevel monitoring wells within bedrock aquifers of a 25-km2 area targeted for shale gas development (SGD). Twenty-four isolated intervals within these wells were sampled monthly over 2 years and groundwater pressures were recorded before, during, and after seven shale gas wells were drilled, hydraulically fractured, and placed into production. Perturbations in groundwater pressures were detected at hilltop monitoring wells during drilling of nearby gas wells and during a gas well casing breach. In both instances, pressure changes were ephemeral (<24 hours) and no lasting impact on groundwater quality was observed. Overall, methane concentrations ([CH4]) ranged from detection limit to 70 mg/L, increased with aquifer depth, and, at several sites, exhibited considerable temporal variability. Methane concentrations in valley monitoring wells located above gas well laterals increased in conjunction with SGD, but CH4 isotopic composition and hydrocarbon composition (CH4/C2H6) are inconsistent with Marcellus origins for this gas. Further, salinity increased concurrently with [CH4], which rules out contamination by gas phase migration of fugitive methane from structurally compromised gas wells. Collectively, our observations suggest that SGD was an unlikely source of methane in our valley wells, and that naturally occurring methane in valley settings, where regional flow systems interact with local flow systems, is more variable in concentration and composition both temporally and spatially than previously understood.

2016 ◽  
Author(s):  
Douglas B. Kent ◽  
◽  
Matthias Kohler ◽  
Meagan Mnich ◽  
Christopher H. Conaway ◽  
...  

Author(s):  
Sutthaporn Tripoppoom ◽  
Wei Yu ◽  
Kamy Sepehrnoori ◽  
Jijun Miao

2014 ◽  
Vol 48 (3) ◽  
pp. 1911-1920 ◽  
Author(s):  
Mohan Jiang ◽  
Chris T. Hendrickson ◽  
Jeanne M. VanBriesen

Author(s):  
Chaodong Tan ◽  
Hanwen Deng ◽  
Wenrong Song ◽  
Huizhao Niu ◽  
Chunqiu Wang

AbstractEvaluating the productivity potential of shale gas well before fracturing reformation is imperative due to the complex fracturing mechanism and high operation investment. However, conventional single-factor analysis method has been unable to meet the demand of productivity potential evaluation due to the numerous and intricate influencing factors. In this paper, a data-driven-based approach is proposed based on the data of 282 shale gas wells in WY block. LightGBM is used to conduct feature ranking, K-means is utilized to classify wells and evaluate gas productivity according to geological features and fracturing operating parameters, and production optimization is realized through random forest. The experimental results show that shale gas productivity potential is basically determined by geological condition for the total influence weights of geologic properties take the proportion of 0.64 and that of engineering attributes is 0.36. The difference between each category of well is more obvious when the cluster number of well is four. Meanwhile, those low production wells with good geological conditions but unreasonable fracturing schemes have the greatest optimization space. The model constructed in this paper can classify shale gas wells according to their productivity differences, help providing suggestions for engineers on productivity evaluation and the design of fracturing operating parameters of shale gas well.


Fuel ◽  
2018 ◽  
Vol 215 ◽  
pp. 363-369 ◽  
Author(s):  
Paulina K. Piotrowski ◽  
Benedikt A. Weggler ◽  
Erica Barth-Naftilan ◽  
Christina N. Kelly ◽  
Ralf Zimmermann ◽  
...  

2014 ◽  
Vol 48 (11) ◽  
pp. 6508-6517 ◽  
Author(s):  
Maryam A. Cluff ◽  
Angela Hartsock ◽  
Jean D. MacRae ◽  
Kimberly Carter ◽  
Paula J. Mouser

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