logging while drilling

An innovative approach uses a random-forest-based framework to link logging-while-drilling and multifrequencey seismic data to enable dynamic updates to lithology parameter predictions, enhancing efficiency and robustness of geosteering applications.

This paper describes a collaborative project to analyze affected wells, identify commonalities, and optimize bit design and drilling parameters to mitigate the effects of borehole spiraling.

The authors of this paper describe an approach in which all available technologies are combined to improve understanding of reservoir depositional environments.

This paper describes an openhole wireline-logging operation in a deepwater Gulf of Mexico well in a high-pressure/high-temperature slimhole environment using water-based reservoir drilling fluid.

The authors of this paper present a system, developed to achieve data transmission using a time-division approach, that includes sealed chambers for microchip storage, a power-release device, and a circuit.

This paper describes the deployment of an ultradeep electromagnetic directional-resistivity instrument to map injection-water movement.

The authors describe a logging-while-drilling nuclear-magnetic-resonance method applied in Bohai Bay, China, as an alternative to radioactive source-porosity measurements.

The buzz about the future of automated drilling and it becoming reality depends on improvements in downhole data gathering now. Halliburton is working on it.

Innovators at the Norwegian oil company have developed a machine-learning model that analyzes mud-gas data to predict the gas/oil ratio of wells as they are drilled—something that the industry has worked for decades to accomplish.

The complete paper presents a technical discussion of a new microsampling technique for LWD and a corresponding wellsite technique to provide compositional interpretation, contamination assessment, reservoir-fluid compositional grading, and reservoir compartmentalization assessment.