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Shale technology: Bayesian variable pressure decline-curve analysis for shale gas wells

A new workflow generates probabilistic history-matches and production forecasts for any decline-curve model while incorporating variable BHP conditions. It provides fast history matches and forecasts of shale gas wells more accurately than traditional DCA while quantifying model uncertainty. The primary value added is an innovative method for probabilistic variable-pressure DCA.

The Download: using AI to access mental health services, and the natural gas debate

Universities Tackle Crude Pipeline Wax Deposits

UT Austin and SwRI Support Five Collaborative Energy Research Projects

UT Austin and SwRI Support Five Collaborative Energy Research Projects
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Energizing Innovation | What Starts Here

Jeff and Mindy Hildebrand’s investment in petroleum and geosystems engineering has made a world-changing impact on students, faculty and research at UT.

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