Reservoir characterization
This paper presents a novel methodology for assessing the rapid mineral carbonation of carbon dioxide through geochemical interactions with carbon-, magnesium-, and iron-rich minerals abundant in geological formations.
This study integrates physics-based constraints into machine-learning models, thereby improving their predictive accuracy and robustness.
This paper introduces a machine-learning approach that integrates well-logging data to enhance depth selection, thereby increasing the likelihood of obtaining accurate and valuable formation-pressure results.
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This paper discusses the successful, fully integrated, 3D Earth modeling (EM) and dynamic reservoir simulation of the Hollin Formation in the Lago Agrio Field within an operator’s first producer field in Ecuador. -
A recently launched joint industry project (JIP) is working to improve petrophysical analysis methods to reduce the time and expense of characterizing tight sandstone gas reservoirs for exploration, appraisal, and production.
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A new technique that analyzes scanning electron microscope (SEM) images of formation samples has been used to measure porosity and total organic carbon (TOC) in the Wolfcamp Shale of the Delaware Basin in west Texas.
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The story of unconventional oil and gas technology development has been focused on fractures. The formula has been more stages, more sand, and more water, targeting the most productive spots.
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Earthquake in Cushing, OK -- home to the largest oil storage facility in the world -- leads to further regulatory action on disposal wells in the area.
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Understanding petrophysical properties well enough to make drilling decisions, particularly for tight gas can be a challenge. A new computer system aims to help analyze the extensive data involved.
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Partitioning interwell tracer tests (PITTs) have been used to estimate remaining oil saturations (ROSs) during waterflooding.
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In this study, the authors demonstrate a reliable, cost-effective methodology that empowers shale operators with reservoir data on every well.
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Researchers at Heriot-Watt University in Edinburgh, Scotland, are building replica core samples using 3D printers and installing sensors inside them as they go. Their goal is to directly monitor pore-scale flow behavior from the inside of these so-called “smart rocks.”
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The tedium of identifying small faults in often murky seismic images pushed Dustin Dewett, an associate geophysicist for BHP Billiton, to develop a better way to use the tools at hand.
