pressure monitoring
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The authors of this paper use a pattern-review technique in a complex brownfield as a tool to understand reservoir connectivity and dynamic fluid movements across the field.
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This paper explores a holistic approach to characterize trouble stages by applying automated event recognition of abnormal pressure increases and associating those events with formation and operational causes.
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In this work, a methodology to detect interference from long-term pressure and flow-rate data is developed using multiresolution analysis in combination with machine-learning algorithms.
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A pressure-monitoring technique using an offset sealed wellbore as a monitoring source has led to advancements in quantifying cluster efficiencies of hydraulic stimulations in real time.
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