Formation evaluation
This work investigates the root cause of strong oil/water emulsion and if sludge formation is occurring within the reservoir using a robust integrated approach.
Transitioning to a low-carbon economy demands large-scale CO2, natural gas, and hydrogen storage. In this context, the application of AI/ML technology to uncover geochemical, microbial, geomechanical, and hydraulic mechanisms related to storage and solve complicated history-matching and optimization problems, thereby enhancing storage efficiency, has been prominently …
The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.
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The natural fractures discovered on Mars during rover missions might be so important that they are worth bringing back to Earth. -
The authors of this paper describe a technology built on a causation-based artificial intelligence framework designed to forewarn complex, hard-to-detect state changes in chemical, biological, and geological systems.
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Geochemical parameters such as total organic carbon (TOC) provides valuable information to understand rock organic richness and maturity and, therefore, optimize hydrocarbon exploration. This article presents a novel work flow to predict continuous high-resolution TOC profiles using machine learning.
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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.
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The authors of this paper present a laboratory-based model to determine the detachment of authigenic and detrital particles in formation damage.
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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 authors of this paper aim to identify the effect of various geologic controls on hydrocarbon maturation in the Delaware Basin by restoring regional cross sections and performing simulations of organic-matter maturity.
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The goal of this paper is to improve the understanding of uncertainties affecting well performance and reservoir connectivity in an offshore Malaysian field.
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A critical challenge for those designing carbon dioxide storage sites is predicting where the injected gas will go. One of the only sure bets is to assume that any model of a gas plume that looks symmetrical is likely wrong.
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This paper provides a work flow based on research in two methodologies to estimate formation-water salinity, enhancing the quality of saturation evaluation for quick decision-making during logging operations.
