Concurrent Real-Time Distributed Fiber Optic Sensing of Casing Deformation and Cement Integrity Loss

2019 ◽  
Author(s):  
Qian Wu ◽  
Sriramya Nair ◽  
Eric van Oort ◽  
Artur Guzik ◽  
Kinzo Kishida
Keyword(s):  
Real Time ◽  
Fiber Optic ◽  
Fiber Optic Sensing ◽  
Cement Integrity ◽  
Casing Deformation

scholarly journals Distributed Fiber Optic Sensing for Real-Time Monitoring of Gas in Riser during Offshore Drilling

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 267 ◽  
Author(s):  
Giuseppe Feo ◽  
Jyotsna Sharma ◽  
Dmitry Kortukov ◽  
Wesley Williams ◽  
Toba Ogunsanwo
Keyword(s):  
Real Time ◽  
Fiber Optic ◽  
Full Scale ◽  
Flow Dynamics ◽  
Petroleum Engineering ◽  
Detection Methods ◽  
Marine Riser ◽  
Offshore Drilling ◽  
Well Control ◽  
Fiber Optic Sensing

Effective well control depends on the drilling teams’ knowledge of wellbore flow dynamics and their ability to predict and control influx. Unfortunately, detection of a gas influx in an offshore environment is particularly challenging, and there are no existing datasets that have been verified and validated for gas kick migration at full-scale annular conditions. This study bridges this gap and presents pioneering research in the application of fiber optic sensing for monitoring gas in riser. The proposed sensing paradigm was validated through well-scale experiments conducted at Petroleum Engineering Research & Technology Transfer lab (PERTT) facility at Louisiana State University (LSU), simulating an offshore marine riser environment with its larger than average annular space and mud circulation capability. The experimental setup instrumented with distributed fiber optic sensors and pressure/temperature gauges provides a physical model to study the dynamic gas migration in full-scale annular conditions. Current kick detection methods primarily utilize surface measurements and do not always reliably detect a gas influx. The proposed application of distributed fiber optic sensing overcomes this key limitation of conventional kick detection methods, by providing real-time distributed downhole data for accurate and reliable monitoring. The two-phase flow experiments conducted in this research provide critical insights for understanding the flow dynamics in offshore drilling riser conditions, and the results provide an indication of how quickly gas can migrate in a marine riser scenario, warranting further investigation for the sake of effective well control.

scholarly journals OC-0254: MR compatibility of fiber optic sensing for real-time needle tracking

2016 ◽  
Vol 119 ◽  
pp. S116-S117
Author(s):  
M. Borot de Battisti ◽  
B. Denise de Senneville ◽  
M. Maenhout ◽  
G. Hautvast ◽  
D. Binnekamp ◽  
...  
Keyword(s):  
Real Time ◽  
Fiber Optic ◽  
Fiber Optic Sensing

scholarly journals Real-Time Well-Integrity Monitoring Using Fiber-Optic Distributed Acoustic Sensing

SPE Journal ◽  
2019 ◽  
Vol 24 (05) ◽  
pp. 1997-2009 ◽  
Author(s):  
T.. Raab ◽  
T.. Reinsch ◽  
S. R. Aldaz Cifuentes ◽  
J.. Henninges
Keyword(s):  
Life Cycle ◽  
Strain Rate ◽  
Real Time ◽  
Fiber Optic ◽  
Axial Strain ◽  
Fiber Optic Cable ◽  
Integrity Monitoring ◽  
Well Integrity ◽  
Distributed Acoustic Sensing ◽  
Cement Integrity

Summary Proper cemented casing strings are a key requirement for maintaining well integrity, guaranteeing optimal operation and safe provision of hydrocarbon and geothermal resources from the pay zone to surface facilities. Throughout the life cycle of a well, high–temperature/high–pressure changes in addition to shut–in cyclic periods can lead to strong variations in thermal and mechanical load on the well architecture. The current procedures to evaluate cement quality and to measure downhole temperature are mainly dependent on wireline–logging campaigns. In this paper, we investigate the application of the fiber–optic distributed–acoustic–sensing (DAS) technology to acquire dynamic axial–strain changes caused by propagating elastic waves along the wellbore structure. The signals are recorded by a permanently installed fiber–optic cable and are studied for the possibility of real–time well–integrity monitoring. The fiber–optic cable was installed along the 18⅝–in. anchor casing and the 21–in.–hole section of a geothermal well in Iceland. During cementing operations, temperature was continuously measured using distributed–temperature–sensing (DTS) technology to monitor the cement placement. DAS data were acquired continuously for 9 days during drilling and injection testing of the reservoir interval in the 12¼–in. openhole section. The DAS data were used to calculate average–axial–strain–rate profiles during different operations on the drillsite. Signals recorded along the optical fiber result from elastic deformation caused by mechanical energy applied from inside (e.g., pressure fluctuations, drilling activities) or outside (e.g., seismic signals) of the well. The results indicate that the average–axial–strain rate of a fiber–optic cable installed behind a casing string generates trends similar to those of a conventional cement–bond log (CBL). The obtained trends along well depth therefore indicate that DAS data acquired during different drilling and testing operations can be used to monitor the mechanical coupling between cemented casing strings and the surrounding formations, hence the cement integrity. The potential use of DTS and DAS technology in downhole evaluations would extend the portfolio to monitor and evaluate qualitatively in real time cement–integrity changes without the necessity of executing costly well–intervention programs throughout the well's life cycle.

Classification and Localization of Low-Frequency DAS Strain Rate Patterns with Convolutional Neural Networks

2021 ◽  
Author(s):  
Mengyuan Chen ◽  
Jin Tang ◽  
Ding Zhu ◽  
Alfred Daniel Hill
Keyword(s):  
Edge Detection ◽  
Strain Rate ◽  
Real Time ◽  
Event Detection ◽  
Fiber Optic ◽  
Low Frequency ◽  
Propagation Model ◽  
Advanced Technology ◽  
Hydraulic Fractures ◽  
Fiber Optic Sensing

Abstract Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, to examine well stimulation efficacy, and to estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture-hits as hydraulic fractures propagate and create strain rate variations. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS offers the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate response that is correlated with low-frequency DAS data. In this paper, "fracture-hit" refers to a hydraulic fracture originated from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is then used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber optic sensing data. Additionally, we used image analysis techniques, including edge detection, for recognizing fracture-hit event patterns in strain rate images. The accuracy is also plausible, but edge detection is more dependent on image quality, hence less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber optic sensing event detection.

scholarly journals Real-Time Monitoring of Nicotine Release Behavior from Smokeless Tobacco (Snus) Based on Fiber Optic Sensing Technology

2019 ◽  
Vol 26 (4) ◽  
pp. 24-29
Author(s):  
Peng Li ◽  
Shitong Zeng ◽  
Jianxun Zhang ◽  
Yi Shen ◽  
Shihao Sun ◽  
...  
Keyword(s):  
Real Time ◽  
Smokeless Tobacco ◽  
Fiber Optic ◽  
Release Behavior ◽  
Real Time Monitoring ◽  
Sensing Technology ◽  
Fiber Optic Sensing

scholarly journals Fiber Optic Monitoring of Subsea Equipment

2012 ◽  
Author(s):  
David Brower ◽  
John D. Hedengren ◽  
Cory Loegering ◽  
Alexis Brower ◽  
Karl Witherow ◽  
...  
Keyword(s):  
Natural Gas ◽  
Gulf Of Mexico ◽  
Real Time ◽  
Fiber Optic ◽  
Sensing System ◽  
Actual Operation ◽  
Fiber Optic Sensing ◽  
Water Depths

Bass Lite deepwater field in the Gulf of Mexico, at water depths of approximately 2,050 m (6,750 feet), commenced operation in February 2008. Natural gas is produced from Bass Lite via a 90-km (56-mile) subsea tieback to the Devils Tower Spar. This project involved several innovations, one of which was the incorporation of a fiber optic sensing system that measures real-time temperature, pressure and strain along the pipeline length. This is a first of its kind innovation that is in actual operation.

Real-Time Tissue Differentiation Using Fiber Optic Sensing in Laser Catheters1

2014 ◽  
Vol 8 (3) ◽  
Author(s):  
Darrin Beekman ◽  
Sachin Bijadi ◽  
Timothy Kowalewski
Keyword(s):  
Real Time ◽  
Fiber Optic ◽  
Tissue Differentiation ◽  
Fiber Optic Sensing
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