Reservoir
Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows—where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
The $100-billion project is widely considered the largest unconventional development outside of the US and is noted by Aramco as the largest nonassociated gas development in the kingdom.
This study presents a novel hybrid approach to enhance fraud detection in scanned financial documents.
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Oil production from thin-oil-rim fields can be a challenge considering early gas breakthrough and high gas/oil ratio. This study evaluates the performance of autonomous inflow control valves (in comparison with inflow control devices and sand screens) and their effectiveness in improved oil recovery in such fields.
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Samsung E&A takes home $6 billion of the total amount as EPC contractor.
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As the biggest US companies grow bigger, the advantage of scale becomes clearer.
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A 44-well development tests what ConocoPhillips has learned about maximizing the value of the wells by figuring out how they drain the reservoir.
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This paper’s focus is a case study of an Eagle Ford refracturing project in which a range of completion designs were trialed with an approach using offset sealed wellbore pressure monitoring and fiber-optic strain.
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The authors of this paper propose a hybrid approach that combines physics with data-driven approaches for efficient and accurate forecasting of the performance of unconventional wells under codevelopment.
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Despite tens of thousands of potential candidates and the proven upsides, the unconventional industry has largely overlooked refracturing—possibly due to the way it’s discussed.
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The physical characteristics of heavy oil and the formations in which it is found are often unique to a region or even to a specific asset, so recovery techniques must be tuned, adapted, and sometimes invented for each region. Creative professionals around the world are taking up this challenge and sharing their work with us in a wealth of excellent recent publication…
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This paper describes a full-field and near-wellbore poromechanics coupling scheme used to model productivity-index degradation against time.
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This paper develops a deep-learning work flow that can predict the changes in carbon dioxide mineralization over time and space in saline aquifers, offering a more-efficient approach compared with traditional physics-based simulations.