A deep learning framework based on improved self-supervised learning for ground-penetrating radar tunnel lining inspection

It is not practical to obtain a large number of labeled data to train a supervised learning network in tunnel lining nondestructive testing with ground-penetrating radar (GPR). To decrease the dependence of supervised learning on the number of labeled data, an improved self-supervised learning algorithm—self-attention dense contrastive...

Extracting mud invasion information using borehole radar - A numerical study

In hydrocarbon drilling, mud filtrate penetrates permeable formations and alters the pore fluid characteristics in the immediate vicinity of the borehole. Typically, the prevailing in situ pore fluids are displaced by the invading mud filtrate, which leads to gradually changing distributions of the fluid and electrical properties....

Deep learning–based nondestructive evaluation of reinforcement bars using ground-penetrating radar and electromagnetic induction data

This paper proposes a nondestructive evaluation method based on deep learning using combined ground-penetrating radar (GPR) and electromagnetic induction (EMI) data for autonomic and accurate estimation of the cover thickness and diameter of reinforcement bars. A real-time object detection algorithm—You Only Look Once–version 3 (YOLO v3)—is...

Estimating reservoir permeability with borehole radar

In oil drilling, mud filtrate penetrates into porous formations and alters the compositions and properties of the pore fluids. This disturbs the logging signals and brings errors to reservoir evaluation. Drilling and logging engineers therefore deem mud invasion as undesired and attempt to eliminate its adverse effects. However, the mud...

Borehole radar response of a mud-invaded oil-bearing layer

Associating Borehole Radar Imaging with Petrophysical Properties for a Mud-Contaminated Reservoir

In the phase of oil drilling, mud filtrate penetrates into porous formations and alters the pore fluid properties. This complicates well logging exploration, and inevitably gives rise to shift in reservoir estimation. Logging engineers deem mud invasion a harm and attempt to eliminate its impact on logging data exploration. However, from our...