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 aims to use machine-learning techniques to predict well logs by analyzing mud-log and logging-while-drilling data.
This study integrates physics-based constraints into machine-learning models, thereby improving their predictive accuracy and robustness.
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In the past decade, there has been a great deal of research and progress in the development of computational methods to assist reservoir engineers in the arduous task of history matching their models. -
This paper presents an efficient history matching approach that simultaneously integrates 4D repeat seismic surveys with well production data.
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In this paper, the authors propose a new method for time-lapse-seismic surveys focused on water-injector wells.
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Some remarkable breakthroughs in data quality have been shared in recent reviews, and the ongoing technical developments in data acquisition and processing remain truly exciting.
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Through examples of subsalt fields of the Kaombo project, we show how new techniques have had a positive effect.
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The Risha concession, in the desert of eastern Jordan (bordering Iraq, Syria, and Saudi Arabia) contains the partially developed Risha gas field.
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An integrated-asset-model (IAM) approach has been implemented for the Alpine field and eight associated satellite fields on the western Alaskan North Slope (WNS) to maximize asset value and recovery.
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Successful development of flank areas depends on accurate reservoir characterization—in particular, water-saturation distribution—in addition to the optimal areal and vertical placement of wells.
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Accurate determination of relative permeability hysteresis is needed to predict water-alternating-gas (WAG) injection reliably. Two series of gas/water relative permeability hysteresis curves were obtained from corefloods under mixed-wet conditions. The results revealed that none of the widely used hysteresis models (e.g., Carlson and Killough models) is able to predi…
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A test-case study (Norne E-segment), based on field data of an offshore Norway brownfield, was organized to evaluate and compare mathematical methods for history matching and strategies for optimal production or enhanced oil recovery (EOR).
