Advanced Forward Methods for Complex Wire Fault Modeling

Lundquist, E. J.; Nagel, James R.; Wu, Shang; Jones, Brian A.; Furse, Cynthia

doi:10.1109/jsen.2012.2227996

Cited by 19 publications

(15 citation statements)

References 6 publications

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“…We implemented a two-step numerical modeling scheme developed by Lundquist et al (2013): First, the 2-D cross-section of the wellbore is built based on characteristic impedance properties of different components and their functions and boundary conditions in terms of impacts on electrical voltage (V) distribution. Then, the characteristic impedance of each type of the cross-sections is calculated with the finite difference method (FDM) following the procedure developed by Kowalski (2009) and Lundquist et al (2013). At last, all the calculated characteristic impedances are incorporated into the 1-D longitudinal modeling to simulate the overall time-domain reflectometry (TDR) response.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…To calculate the characteristic impedance of the 2-D cross-section, following the implementation procedure developed by Lundquist et al (2013), the Voltage potential (V) of the cross-section can be calculated by solving the Poisson equation with FD method:…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…where V is the unknown voltage potential, ρ is the charge density function, ε r is the relative permittivity function, and ε 0 is the relative permittivity of the free-space. With the voltage potential field been solved, the electric field potential can be found with E =− ∇ V. Finally, the total charge q per unit length along the inner conductor can be determined with Gauss's law (Lundquist et al, 2013):…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Wellhead based time domain reflectometry for casing integrity investigation

Wang

2020

International Journal of Greenhouse Gas Control

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Wellbore integrity is one of the most critical factors for CO 2 storage, subsurface resource extraction, and waste disposal. Wellbore integrity monitoring is challenging due to the general inaccessibility and high cost of welllogging operation in complex subsurface conditions. In this study, we tested a novel non-invasive approach for wellbore-integrity assessment based on time-domain reflectometry (TDR) method. With this method, a highfrequency electromagnetic pulse is sent into the borehole casing, and the reflected signals due to integrityrelated impedance anomalies are recorded at the wellhead, providing rapid borehole integrity diagnosis without downhole deployment. Laboratory, numerical, and field experiments were conducted to prove the feasibility of this approach. The laboratory experiments with coaxial cable, resembling the typical wellbore, showed clear reflected signals from both of the damaged section and the end of the cable. Numerical sensitivity tests indicated that the TDR response is affected by the changes of the material in the borehole, including infilled fluids. Our field trial was conducted on an oil well (with a depth of 240 m) in the central valley region of southern California. The TDR records showed a clear reflection that matched both the calculated two-way travel time from the bottom of the borehole, as well as the numerical simulation. Our results suggested the feasibility of the TDR method for quick assessment of wellbore integrity based on wellhead only deployment.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Theoretical Backgroundmentioning

confidence: 99%

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Wellhead based time domain reflectometry for casing integrity investigation

Wang

2020

International Journal of Greenhouse Gas Control

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“…Modeling a wiring system generally consists in computing the voltage potential on the faulty section by solving a 2D static Poisson equation and using the Gauss theorem to determine the distributed electrical parameters: the resistance R, the inductance L, the capacitance C, and the conductance G (RLCG). These parameters are used in a longitudinal model such as telegrapher's equations or chain matrix model to compute the reflection coefficient [4]. Unfortunately, this modeling approach does not take into account the three-dimensional aspect of wave propagation in the wire.…”

Section: Introductionmentioning

confidence: 99%

Time domain reflectometry model: analysis and characterization of a chafing defect in a coaxial cable

Kameni

Loete

Pichon

2018

Eur. Phys. J. Appl. Phys.

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This paper presents experimental and numerical studies of a chafing soft defect realized by partially milling coaxial cables. The approach is based on the time domain reflectometry technique. The numerical model consists in solving Maxwell’s equations while an incident Gaussian pulse is injected on the faulty line. The experimental time domain measurements are performed with a vector network analyzer. To get the experimental results comparable to the numerical ones, a process to denoise the measured impulse responses is proposed. The reflection coefficients obtained are compared to those given by a classical approach based on a chain matrix model to show the impact of 3D numerical modeling in studying soft faults.

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“…Reflectometry methods send an impulse signal down the wire, which reflects from impedance changes or discontinuities and provides corresponding reflected signal data . The time delay between the incident and reflected signals, and the polarity and magnitude of the reflection indicate the connector location and impedance change . The sensitivity of reflectometry systems that would be required to locate each of these types of degradation modes can then be assessed.…”

Section: Introductionmentioning

confidence: 99%

Connector impedance and frequency modes in aerospace wiring systems

Lundquist

Furse

2016

Micro & Optical Tech Letters

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This article represents an investigation of connector effects on signal integrity and propagation in aerospace wiring systems–including quantitative data of potential changes in characteristic impedance. It is determined that changes in wire bundling, connector plugmap configurations, shell damage, and other factors impact signal propagation. Wire bundling arrange‐ ment can cause changes greater than ± 60 Ω on a 152 Ω linefurther causing reflection and transmission variation throughout the system. Changing connector configurations were found to cause initial signal reflections from 4 to 76% and total reflection of 0.05‐0.14%, where unshielded wires were found to have greater variation and reflection than shielded wires. The effects of frequency and connector length were also analyzed in order to minimize total internal reflection at connector interfaces. Shell damage can cause reflection up to 0.01, or 1%. Measurements of aerospace connector systems produced reflections <1.5%. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:89–93, 2017

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Advanced Forward Methods for Complex Wire Fault Modeling

Cited by 19 publications

References 6 publications

Wellhead based time domain reflectometry for casing integrity investigation

Wellhead based time domain reflectometry for casing integrity investigation

Time domain reflectometry model: analysis and characterization of a chafing defect in a coaxial cable

Connector impedance and frequency modes in aerospace wiring systems

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