Unconventional/complex reservoirs
This paper presents a novel approach to predict reservoir porosity by conditioning seismic data, calibrating seismic impedance inversion, and tailoring rock-physics analysis.
This paper aims to assess the effectiveness of using advanced integrated production-data-analysis techniques for condensate-rich tight gas fields.
Output is rising fast in the South American shale play and putting Argentina on a course to soon reach 1 million B/D.
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This paper highlights an approach of using active hydrogen to stimulate hard-to-recover formations from candidate-well selection through pilot execution and evaluation. -
The authors of this paper review the advantages of machine learning in complex compositional reservoir simulations to determine fluid properties such as critical temperature and saturation pressure.
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This study describes a technique combining borehole acoustic reflection imaging with production logging in a horizontal well experiencing high water cut with the aim of enabling a mitigation plan.
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The authors investigate the utility of applying unconventional technology to low- or variably producing carbonate reservoirs to increase estimated ultimate recovery and decrease development-scale variability.
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Unconventional reservoirs bear a unique perplexity in that, at every scale, they are different from their conventional counterparts and even one another. This month’s selection of papers is all about those differences.
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The acquisition underscores the rapid rise of the unconventional oil play in northeastern Utah that producers claim offers better margins than the Permian Basin.
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Pilots and papers are plentiful, but the shale sector has no big enhanced oil recovery projects to speak of. It may just have to stay that way for a while.
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Operators tell an audience at the Unconventional Resources Technology Conference how a hybrid expandable liner system and machine-learning-based analysis improve the bottom line.
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After another year of significant consolidation in the US shale sector, Enverus has released its annual list of the nation's largest private exploration companies.
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Machine learning is refining gas lift production optimization with scalable automated workflow.
