Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Guo, Zhiyong; Liu, Dejun; Pan, Qiwei; Zhang, Yingying

doi:10.1016/j.jappgeo.2014.12.011

Cited by 41 publications

(18 citation statements)

References 30 publications

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“…13. As the figure indicates, peakepeak values detected from the same distance are not the same for the three types of casing pipe (Guo et al, 2015). Larger peakepeak value was detected for casing pipe with larger diameter from the same distance, indicating that casing pipe which is wider and thicker is more likely to be detected from a farther distance.…”

Section: Resultsmentioning

confidence: 86%

An investigation of electromagnetic anti-collision real-time measurement for drilling cluster wells

Gao

Diao

2015

Journal of Natural Gas Science and Engineering

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Section: Resultsmentioning

confidence: 86%

An investigation of electromagnetic anti-collision real-time measurement for drilling cluster wells

Gao

Diao

2015

Journal of Natural Gas Science and Engineering

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“…However, in the dual horizontal well model, the casing cannot be regarded as a magnetic dipole in the computation due to its nonnegligible length compared with its distance from the measuring point (4-10 m). Pignatelli et al [22] and Guo et al [23][24][25] propose that the pipeline can be segmented into small units and reconstructed thereby. The magnetic field of each segmentation unit can be calculated using the magnetic dipole method [22][23][24].…”

Section: Magnetic Rangingmentioning

confidence: 99%

“…Pignatelli et al [22] and Guo et al [23][24][25] propose that the pipeline can be segmented into small units and reconstructed thereby. The magnetic field of each segmentation unit can be calculated using the magnetic dipole method [22][23][24]. By performing vector superposition of the magnetic fields of all the segmentation units, the overall magnetization field of the pipeline at the measurement point can be figured out.…”

Section: Magnetic Rangingmentioning

confidence: 99%

Self-Excited Codirectionally Magnetically Compensated Rotating Ranging Method

Guo

Zhang

et al. 2020

Journal of Sensors

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During the Steam-Assisted Gravity Drainage (SAGD) technology-based dual horizontal well drilling process, it is necessary to accurately monitor the well spacing in real time to ensure safe and parallel drilling. In this paper, a self-excited codirectionally magnetically compensated rotating ranging method and device is proposed. In the numerical calculation and simulation, both parallel and nonparallel drilling models are established. Based on the models and the magnetic dipole theory, the relation between the magnetization field and the well spacing is analyzed. Furthermore, the one-to-one correspondence between the peak-to-peak value of the magnetization field and the well spacing is revealed. Well spacing is then determined according to the measured peak-to-peak value. To achieve better results, the influence of magnetic source (the magnetic moment) and casing characteristics (magnetic susceptibility, dynamic magnetization length) on measured peak-to-peak value is analyzed. Finally, field tests are carried out, and the feasibility and effectiveness of the theory and device are proved. This study provides innovation for a new approach of magnetic guidance while drilling and has a great significance in the development, testing, and calibration of well-ranging instruments.

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“…Underground metal detection technology has been widely used in military fields [1] and also plays an important role in archeology [2], prospecting [3], medical positioning [4], underground metal pipeline modeling [5] and other fields. Electromagnetic induction (EMI) detection technology is an underground metal detection method that uses secondary field information generated by a changing magnetic field acting on the metal target to detect the state of a target [6].…”

Section: Introductionmentioning

confidence: 99%

An Initial Value Estimation Method for the Kalman and Extended Kalman Filters in Underground Metal Detection

Wan

Wang

et al. 2019

Applied Sciences

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As an underground metal detection technology, the electromagnetic induction (EMI) method is widely used in many cases. Therefore, the EMI detection algorithms with excellent performance are worth studying. One of the EMI detection methods in the underground metal detection is the filter method, which first obtains the secondary magnetic field data and then uses the Kalman filter (KF) and the extended Kalman filter (EKF) to estimate the parameters of metal targets. However, the traditional KF methods used in the underground metal detection have an unsatisfactory performance of the convergence as the algorithms are given a random or a fixed initial value. Here, an initial state estimation algorithm for the underground metal detection is proposed. The initial state of the target’s horizontal position is estimated by the first order central moments of the secondary field strength map. In addition, the initial state of the target’s depth is estimated by the full width at half maximum (FWHM) method. In addition, the initial state of the magnetic polarizability tensor is estimated by the least squares method. Then, these initial states are used as the initial values for KF and EKF. Finally, the position, posture and polarizability of the target are recursively calculated. A simulation platform for the underground metal detection is built in this paper. The simulation results show that the initial value estimation method proposed for the filtering algorithm has an excellent performance in the underground metal detection.

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Forward modeling of total magnetic anomaly over a pseudo-2D underground ferromagnetic pipeline

Cited by 41 publications

References 30 publications

An investigation of electromagnetic anti-collision real-time measurement for drilling cluster wells

An investigation of electromagnetic anti-collision real-time measurement for drilling cluster wells

Self-Excited Codirectionally Magnetically Compensated Rotating Ranging Method

An Initial Value Estimation Method for the Kalman and Extended Kalman Filters in Underground Metal Detection

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