Tilt-depth method: A simple depth estimation method using first-order magnetic derivatives

2007 ◽  
Vol 26 (12) ◽  
pp. 1502-1505 ◽  
Author(s):  
Ahmed Salem ◽  
Simon Williams ◽  
J. Derek Fairhead ◽  
Dhananjay Ravat ◽  
Richard Smith
Keyword(s):  
Estimation Method ◽  
Depth Estimation ◽  
First Order

Non-stationary local slope estimation via forward-backward space derivative calculation

Geophysics ◽  
2021 ◽  
pp. 1-91
Author(s):  
Hang Wang ◽  
Liuqing Yang ◽  
Xingye Liu ◽  
Yangkang Chen ◽  
Wei Chen
Keyword(s):  
Finite Difference ◽  
Random Noise ◽  
Estimation Method ◽  
Order Derivative ◽  
Space Domain ◽  
Local Slope ◽  
First Order ◽  
Slope Estimation ◽  
Difference Calculation ◽  
Seismic Images

The local slope estimated from seismic images has a variety of meaningful applications. Slope estimation based on the plane-wave destruction (PWD) method is one of the widely accepted techniques in the seismic community. However, the PWD method suffers from its sensitivity to noise in the seismic data. We propose an improved slope estimation method based on the PWD theory that is more robust in the presence of strong random noise. The PWD operator derived in the Z-transform domain contains a phase-shift operator in space corresponding to the calculation of the first-order derivative of the wavefield in the space domain. The first-order derivative is discretized based on a forward finite difference in the traditional PWD method, which lacks the constraint from the backward direction. We propose an improved method by discretizing the first-order space derivative based on an averaged forward-backward finite-difference calculation. The forward-backward space derivative calculation makes the space-domain first-order derivative more accurate and better anti-noise since it takes more space grids for the derivative calculation. In addition, we introduce non-stationary smoothing to regularize the slope estimation and to make it even more robust to noise. We demonstrate the performance of the new slope estimation method by several synthetic and field data examples in different applications, including 2D/3D structural filtering, structure-oriented deblending, and horizon tracking.

scholarly journals Influence of Sampling Delay on the Estimation of Lithium-Ion Battery Parameters and an Optimized Estimation Method

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1878
Author(s):  
Bing Jiang ◽  
Zeqi Chen ◽  
Feifan Chen
Keyword(s):  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Test System ◽  
Recursive Least Squares ◽  
Battery Management System ◽  
Battery Management ◽  
First Order ◽  
The Mathematical Model ◽  
Synchronization Accuracy

The equivalent-circuit model (ECM) is widely used in online estimating the parameters and states of lithium-ion batteries. However, the sampling delay between the voltage and current of a battery is generally overlooked, which is unavoidable in a modular battery management system (BMS) and would lead to wrong results in the estimation of battery parameters and states. In this paper, with the first-order resistor–capacitor (RC) model as our battery model, we analyze the influence mechanism of sampling delay and then propose an optimized method for online estimating battery parameters. The mathematical model derived from the first-order RC model and the approximation method of first-order derivative are optimized. The recursive least squares (RLS) algorithm is used for identifying the parameters of the model. In order to verify the proposed method, a modular battery test system with high sampling frequency and high synchronization accuracy is developed. The experiment results indicate that the sampling delay would cause the estimation process to fluctuate, and the optimized method effectively improves the tolerance range of sampling delay.

scholarly journals A Method for Estimating Time-Dependent Corrosion Depth of Carbon and Weathering Steel Using an Atmospheric Corrosion Monitor Sensor

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1416 ◽  
Author(s):  
Jin-Hee Ahn ◽  
Young-Soo Jeong ◽  
In-Tae Kim ◽  
Seok-Hyeon Jeon ◽  
Chan-Hee Park
Keyword(s):  
Carbon Steel ◽  
Estimation Method ◽  
Depth Estimation ◽  
Corrosion Current ◽  
Time Dependent ◽  
Weathering Steel ◽  
Corrosion Depth ◽  
The Mean ◽  
The Relationship ◽  
Corrosion Monitor

In this study, a time-dependent corrosion depth estimation method using atmospheric corrosion monitor (ACM) sensor data to evaluate time-dependent corrosion behaviors is proposed. For the time-dependent corrosion depth estimation of uncoated carbon steel and weathering steel, acceleration corrosion tests were conducted in salt-spray corrosion environments and evaluated with a corrosion damage estimation method using ACM sensing data and corrosion loss data of the tested steel specimens. To estimate the time-dependent corrosion depth using corrosion current by an ACM sensor, the relationship between the mean corrosion depth calculated from the weight loss method and the corrosion current was evaluated. The mean corrosion depth was estimated by calculating the corrosion current and evaluating the relationship between the mean corrosion depth and corrosion current during the expected period. From the test and estimation results, the corrosion current demonstrated a good linear correlation with the mean corrosion depth of carbon steel and weathering. The calculated mean corrosion depth is nearly the same as that of the tested specimen, which can be well used to estimate corrosion rate for the uncoated carbon steel and weathering steel.

Assessing the role of biochemical methane potential tests in determining anaerobic degradability rate and extent

2011 ◽  
Vol 64 (4) ◽  
pp. 880-886 ◽  
Author(s):  
P. D. Jensen ◽  
H. Ge ◽  
D. J. Batstone
Keyword(s):  
Parameter Estimation ◽  
Methane Production ◽  
Estimation Method ◽  
Test Method ◽  
Continuous Systems ◽  
Batch Test ◽  
Biochemical Methane Potential ◽  
First Order ◽  
Methane Potential ◽  
The Impact

The biodegradability and bioavailability of hydrolysis-limited substrates under anaerobic (and aerobic) conditions can be represented by two key parameters – degradability (fd), or the percentage that can be effectively be destroyed during digestion, and first order hydrolysis coefficient (khyd), or the speed at which material breaks down. Biochemical methane potential (BMP) testing uses a batch test (in triplicate), and by fitting against a first order model, can fit both parameters in the same test. BMP testing is now being widely used for anaerobic process feasibility and design purposes, and standardisation efforts are ongoing. In this paper, we address a number of key issues relating to the test method and its analysis. This includes proposal of a new fitting and parameter estimation method, evaluation of the impact of inoculum to substrate ratio on fitted parameters, and comparison to performance in continuous systems. The new parameter estimation technique provides an estimate of parameter uncertainty and correlation, and is clearly more suitable than model transformation and linear regression. An inoculum volume ratio of at least 50% (2:1 on VS basis) was required on a cellulose substrate to use methane production as primary indicator, as found by comparing methane production and solubilisation of cellulose. Finally, on a typical material, waste activated sludge, the batch test was slightly conservative in terms of degradability and rate, indicating a bias in the BMP test. The test is a cost-effective and capable method to evaluate potential substrates, but it should be noted that it is generally conservative, especially if sub-optimal inoculum is used.

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