Formation evaluation
Building up the world’s hydrogen base will need technological breakthroughs and a lot of new demand. But to store it, the world needs reservoir engineers and other subsurface experts.
The authors of this paper present a laboratory-based model to determine the detachment of authigenic and detrital particles in formation damage.
The authors of this paper introduce a physics-based method for explicit pore-pressure prediction in naturally fractured shale petroleum reservoirs.
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The author writes that careful calibration of a common, simple rock physics model can provide valuable insights into reservoir and seal elastic properties.
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The paper highlights two case studies to illustrate successful development of marginal prospects to unlock remaining potential.
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This paper provides an alternative solution to identifying, classifying, and vertically distributing fractures and a lateral distribution method for reservoir modeling.
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The complete paper describes a tool developed to evaluate and characterize thin beds or laminations in a mature offshore field.
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The utility of mud gas data so far has been limited to fluid typing, formation evaluation, and interwell geological and petrophysical correlation. The ongoing digital transformation has presented the opportunity to increase the utility of, and get more value from, the abundant and rich mud gas data. This article raises the question of whether getting more from mud gas…
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This paper describes a technology with the capability to map and detect lithology changes ahead of the bit in real time.
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Traditionally, wireline or logging-while-drilling formation-testing technology has been the most accepted means of reservoir fluid characterization. But when those fluids are contaminated by mud filtrate, acoustic data can be used for fluid characterization during downhole sampling to successfully track and quantify small changes in oil compressibility.
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This paper describes a technique used to derive stresses for a gas-storage field and then calibrate the 1D mechanical earth model of the field.