Reservoir characterization
After 5 years of in-depth diagnostic research, the Oklahoma City-based operator shares more insights on fracture behavior.
The paper describes a parameter inversion of reservoirs based on featured points, using a semi-iterative well-test-curve-matching approach that addresses problems of imbalanced inversion accuracy and efficiency.
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.
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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. -
This paper presents a novel workflow for using electromagnetic resistivity-based reservoir mapping logging-while-drilling technologies for successful well placement and multilayer mapping in low-resistivity, low-contrast, thinly laminated clastic reservoirs.
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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.
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This study describes the performance of machine-learning models generated by the self-organizing-map technique to predict electrical rock properties in the Saman field in northern Colombia.
