Reservoir characterization
Rock sample characterization, widely used in hydrocarbon exploration and production, is emerging as a critical tool for understanding and optimizing subsurface mineral extraction through in-situ leaching.
This paper presents laboratory-testing methods and evaluation criteria designed to improve understanding of both the origin and extent of formation damage associated with CO2 injection.
This work presents an evaluation for carbon capture, utilization, and storage projects in the UAE for two wells in a saline water aquifer with respect to caprock integrity and water sampling.
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Regional pore-pressure variations in the Leonardian- and Wolfcampian-age producing strata in the Midland and Delaware basins are studied using a variety of subsurface data. -
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.
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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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The companies have finished a seismic survey of an underexplored area of the Bonaparte Basin offshore northwest Australia.
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This paper presents a workflow that combines probabilistic modeling and deep-learning models trained on an ensemble of physics models to improve scalability and reliability for shale and tight-reservoir forecasting.
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This paper discusses the approach used to sectorize a mature giant carbonate reservoir located onshore Abu Dhabi for the purposes of reservoir management, offtake, and injection balancing.
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Carbon storage specialist Storegga joins Petronas and ADNOC in a joint study to strategize the build-out of Malaysia’s offshore as a regional CCS hub.
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The Norwegian data company has launched a 3D seismic survey in the Equatorial Margin area.
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This study compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field in southern Iraq.
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This paper describes an approach that combines rock typing and machine-learning neural-network techniques to predict the permeability of heterogeneous carbonate formations accurately.
