Ultrasound Gas Bubble Detection During Simulation of Space Suit Operations

1995 ◽  
Author(s):  
V. I. Chadov ◽  
S. N. Filipenkov ◽  
L. R. Iseev ◽  
V. N. Polyakov ◽  
G. F. Vorobiev
Keyword(s):  
Gas Bubble ◽  
Space Suit ◽  
Bubble Detection

Gas bubble detection in blood

Ultrasonics ◽  
1968 ◽  
Vol 6 (4) ◽  
pp. 267-269
Author(s):  
D.M.J.P. Manley
Keyword(s):  
Gas Bubble ◽  
Bubble Detection

A Smart Classification Framework for Enhancing Reliability in Downhole Gas Bubble Sensing

2021 ◽  
Author(s):  
Klemens Katterbauer ◽  
Virginie Schoepf ◽  
Alberto Marsala ◽  
Linda Abbassi
Keyword(s):  
Real Time ◽  
Classification Performance ◽  
Gas Bubble ◽  
Data Quality Control ◽  
Underbalanced Drilling ◽  
Bubble Detection ◽  
Classification Framework ◽  
Testing Dataset ◽  
Data Assessment ◽  
Productivity Potential

Abstract Production logging tools (PLTs) and formation testing, even in logging while drilling (LWD) conditions during underbalanced drilling, are key technologies for assessing the productivity potential of a gas well and therefore to maximize recovery. Gas bubble detection sensors are key components in determining the fluid phases in the reservoir and accurately quantify recoverable reserves, optimize well placement, geosteering and to qualify the production ability of the well. We present here a new nonlinear autoregressive - breakdown artificial intelligence (AI) detection framework for PLT gas bubble detection sensors that categorize in real-time whether and which sensors become unreliable or have broken down during the logging measurements. AI tools allow the automatization of this method that is critical during data quality control of post-drilling PLT, but it is essential when the measurements are performed in LWD as data assessment and processing need to occur in real time. This AI framework was validated on both a training and testing dataset, and exhibited strong classification performance. This method enables accurate real-time breakdown detection for gas bubble detection sensors.

scholarly journals A novel artificial intelligence automatic detection framework to increase reliability of PLT gas bubble sensing

2021 ◽  
Vol 11 (3) ◽  
pp. 1263-1273
Author(s):  
Klemens Katterbauer ◽  
Alberto F. Marsala ◽  
Virginie Schoepf ◽  
Eric Donzier
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Classification Performance ◽  
Gas Bubble ◽  
Data Quality Control ◽  
Underbalanced Drilling ◽  
Bubble Detection ◽  
Testing Dataset ◽  
Data Assessment ◽  
Productivity Potential

AbstractProduction logging tools (PLTs) and formation testing, even in logging while drilling (LWD) conditions during underbalanced drilling, are key technologies for assessing the productivity potential of a gas well and therefore to maximize recovery. Gas bubble detection sensors are key components in determining the fluid phases in the reservoir and accurately quantify recoverable reserves, optimize well placement, geosteering and to qualify the production ability of the well. We present here a new nonlinear autoregressive - breakdown artificial intelligence (AI) detection framework for PLT gas bubble detection sensors that categorize in real-time whether and which sensors become unreliable or have broken down during the logging measurements. AI tools allow the automatization of this method that is critical during data quality control of post-drilling PLT, but it is essential when the measurements are performed in LWD as data assessment and processing need to occur in real-time. This AI framework was validated on both a training and testing dataset, and exhibited strong classification performance. This method enables accurate real-time breakdown detection for gas bubble detection sensors.

Gas bubble detection in liquid metals by means of the ultrasound transit-time-technique

2013 ◽  
Vol 220 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Artur Andruszkiewicz ◽  
Kerstin Eckert ◽  
Sven Eckert ◽  
Stefan Odenbach
Keyword(s):  
Transit Time ◽  
Liquid Metals ◽  
Gas Bubble ◽  
Bubble Detection

MULTIPLE-SCALE AND NUMERICAL ANALYSES FOR THE NONLINEAR OSCILLATIONS OF A GAS BUBBLE SURROUNDED BY A MAXWELL'S FLUID

2019 ◽  
Vol 46 (3) ◽  
pp. 261-275
Author(s):  
César Yepes ◽  
Jorge Naude ◽  
Federico Mendez ◽  
Margarita Navarrete ◽  
Fátima Moumtadi
Keyword(s):  
Nonlinear Oscillations ◽  
Multiple Scale ◽  
Numerical Analyses ◽  
Gas Bubble
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