Abstract: Hydrocarbon wells and methods of probing a subsurface region of the hydrocarbon wells. The hydrocarbon wells include a wellbore, a downhole sensor storage structure, and a detection structure. The wellbore may extend within a subsurface region and between a surface region and a downhole end region. The downhole sensor storage structure is configured to release a flowable sensor into a wellbore fluid that extends within the wellbore, and the flowable sensor may be configured to collect sensor data indicative of at least one property of the subsurface region. The detection structure may be configured to query the flowable sensor to determine the at least one property of the subsurface region. The methods include releasing a flowable sensor, collecting sensor data with the flowable sensor, and querying the flowable sensor.

Abstract: A method for enhancing properties of geophysical data with deep learning networks. Geophysical data may be acquired by positioning a source of sound waves at a chosen shot location, and measuring back-scattered energy generated by the source using receivers placed at selected locations. For example, seismic data may be collected using towed streamer acquisition in order to derive subsurface properties or to form images of the subsurface. However, towed streamer data may be deficient in one or more properties (e.g., at low frequencies). To compensate for the deficiencies, another survey (such as an Ocean Bottom Nodes (OBN) survey) may be sparsely acquired in order to train a neural network. The trained neural network may then be used to compensate for the towed streamer deficient properties, such as by using the trained neural network to extend the towed streamer data to the low frequencies.