Reservoir
This paper documents the testing, integration, and field deployment of a metal expandable packer used as an openhole toe isolation plug in a deepwater well under high-pressure, high-temperature conditions.
Three papers are highlighted as the primary contributions because of their broad industry relevance. They focus on improving formation particle-size characterization, expanding the application of openhole gravel packs in depleted and compartmentalized reservoirs, and advancing the understanding of capillary pressure in sand production.
This paper aims to establish a set of best practices for generating particle-size-distribution data from core samples.
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As reservoir complexity and energy-transition demands grow, the industry is developing new logging technologies, integrating multidisciplinary functions, and conducting new experiments to address new challenges. This Technology Focus highlights three papers from conventional, unconventional, and carbon-storage projects. -
The study uses laboratory and digital core analyses of Berea sandstone to estimate petrophysical and dynamic properties for adjustment of predicted precipitation and flow reduction in reservoir simulation models of intermittent CO₂ injection with aquifer drive.
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Diversified Energy announces its largest deal yet to buy private equity-owned Maverick Natural Resources.
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A numerical simulation study based on experimental data of 2D and 3D models is presented to examine immiscible fingering during field-scale polymer-enhanced oil recovery.
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This selection of cutting-edge articles spotlights how experimental concepts are now driving cost-saving strategies in unconventional development. It’s a reminder that innovation often comes from creative thinking, not just new tools or tech partnerships.
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Rystad Energy and Wood Mackenzie highlight key factors shaping the balancing act in the upstream oil market.
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The objective of this study is to develop an explainable data-driven method using five different methods to create a model using a multidimensional data set with more than 700 rows of data for predicting minimum miscibility pressure.
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The authors of this paper propose hybrid models, combining machine learning and a physics-based approach, for rapid production forecasting and reservoir-connectivity characterization using routine injection or production and pressure data.
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CO₂ enhanced oil recovery (EOR) provides an attractive and commercially established technique to store CO₂ underground. EOR modeling is crucial because complex simulation is required to predict the behavior of CO₂ and its interaction with the oil and reservoir rock.
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Virtual reality and related visualization technologies are helping reshape how the industry views 3D data, makes decisions, and trains personnel.
