Studies of Landmark Location Uncertainty

Abstract. Stochastic subgrid parameterizations enable ensemble forecasts of fluid dynamics systems and ultimately accurate data assimilation. Stochastic Advection by Lie Transport (SALT) and models under Location Uncertainty (LU) are recent and similar physically-based stochastic schemes. SALT dynamics conserve helicity whereas LU models conserve kinetic energy. After highlighting general similarities between LU and SALT frameworks, this paper focuses on their common challenge: the parameterization choice. We compare uncertainty quantification skills of a stationary heterogeneous data-driven parameterization and a non-stationary homogeneous self-similar parameterization. For stationary, homogeneous Surface Quasi-Geostrophic (SQG) turbulence, both parameterizations lead to high quality ensemble forecasts. This paper also discusses a heterogeneous adaptation of the homogeneous parameterization targeted at better simulation of strong straight buoyancy fronts.

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Passive tracking in heavy clutter with sensor location uncertainty

IEEE Transactions on Aerospace and Electronic Systems ◽

10.1109/taes.2016.140820 ◽

2016 ◽

Vol 52 (4) ◽

pp. 1536-1554 ◽

Cited By ~ 5

Author(s):

Yunfei Guo ◽

Ratnasingham Tharmarasa ◽

Sreeraman Rajan ◽

Taek Lyul Song ◽

Thia Kirubarajan

Keyword(s):

Sensor Location ◽

Location Uncertainty ◽

Passive Tracking

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Sensor Location under Parametric and Location Uncertainty

Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems - Lecture Notes in Control and Information Sciences ◽

10.1007/978-3-642-28230-0_7 ◽

2012 ◽

pp. 183-206

Author(s):

Maciej Patan

Keyword(s):

Sensor Location ◽

Location Uncertainty

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Effects of Data Preprocessing Methods on Addressing Location Uncertainty in Mobile Signaling Data

Annals of the American Association of Geographers ◽

10.1080/24694452.2020.1773232 ◽

2020 ◽

pp. 1-25

Author(s):

Yang Xu ◽

Xinyu Li ◽

Shih-Lung Shaw ◽

Feng Lu ◽

Ling Yin ◽

...

Keyword(s):

Data Preprocessing ◽

Location Uncertainty

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Automated microseismic event location by amplitude stacking and semblance

Geophysics ◽

10.1190/geo2018-0409.1 ◽

2019 ◽

Vol 84 (6) ◽

pp. KS191-KS210 ◽

Cited By ~ 3

Author(s):

Chengwei Zhang ◽

Wenxiao Qiao ◽

Xiaohua Che ◽

Junqiang Lu ◽

Baiyong Men

Keyword(s):

Body Waves ◽

S Waves ◽

Advantages And Disadvantages ◽

Location Uncertainty ◽

Event Location ◽

Time Average ◽

Microseismic Events ◽

Location Methods ◽

Microseismic Event Location ◽

Microseismic Event

Without the need to pick the arrival times of P- and S-waves, migration-based location methods, such as semblance-based and amplitude-stacking-based location methods, are best applied to microseismic events. By comparing and analyzing the advantages and disadvantages of these two methods, we have developed a new location method using amplitude information and semblance. First, we use the two-point ray-tracing method to calculate the traveltime of body waves from the trial point to each receiver, which determines the time-window positions of the P- and S-waves on all traces. Then, we calculate the semblance of the waveforms and the amplitude stacking of the ratio between the short-time average and the long-time average is computed upon the original waveform over the windows. Finally, the semblance weighted by amplitude stacking is used to image the spatial location of the microseismic events. Using experimental and synthetic data considering different factors that may affect the location result (e.g., the signal-to-noise ratio of the waveforms, the scale of the observation array, and the horizontal and vertical distances from the source to fracture zones), we perform microseismic event location with all three methods. According to the source imaging results from experimental and synthetic tests, the semblance method has great location uncertainty in the radial direction but it has good constraints in the circumferential direction; the amplitude-stacking method exhibits the opposite result; and the weighted-semblance method has good constraints in the circumferential and radial directions because it inherits the advantages of semblance-based and amplitude-stacking-based methods. Therefore, compared with existing migration-based location methods, our weighted-semblance method indicates stronger stability and lower location uncertainty, even when downhole monitoring is conducted with a limited aperture of the receiver array.

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