Multi-model weighted predictions for CH4 and H2S solubilities in freshwater and saline formation waters relevant to unconventional oil and gas extraction

Argha Namhata, Mitchell J. Small, Athanasios K. Karamalidis

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Technological advancements in horizontal drilling and hydraulic fracturing make extraction of natural gas from shale formations economically feasible. However, those activities may induce environmental risks associated with regional water quality due to migration of gases like CH4 and H2S through fractures and accidental spills. Thus, predicting the solubilities of these gases in different aqueous media and conditions, including those relevant to sub-surface environments, is important. Nine models, including equations of state and empirical models, for predicting CH4 solubility in aqueous phases and six models for H2S are considered and evaluated. The goal of this study was to develop multi-model weighted prediction (MMoWP) for each of these gases for a range of ionic strengths varying from freshwater to saline water and brine, over a temperature range of 298-483K and a pressure range of 1-350bar. The predictive accuracy of each model varies with different aqueous conditions. A variance-based weighted model is developed to predict the solubilities of the two gases under different surface and sub-surface conditions (i.e., temperature, pressure and salt concentration (T-P-X)), and the performance of the weighted model is compared to the best fitting individual model in each case. Predicted and observed values are compared using a 5-fold cross validation. Cases for which the weighted model outperforms the best predictive model for each of the two gases are identified and discussed. The modeling approach followed by this study increases the predictive accuracy of CH4 and H2S solubilities across the sub-surface T-P-X conditions likely to be encountered at shale gas extraction sites.

Original languageEnglish (US)
Pages (from-to)177-185
Number of pages9
JournalInternational Journal of Coal Geology
Volume131
DOIs
StatePublished - Sep 1 2014

All Science Journal Classification (ASJC) codes

  • Fuel Technology
  • Geology
  • Economic Geology
  • Stratigraphy

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