Straightforward inversion of MT data using a normalized impedance function

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F19-F24 ◽  
Author(s):  
Sri Niwas ◽  
P. K. Gupta ◽  
V. K. Gaur
Keyword(s):  
Power Series ◽  
Layer Thickness ◽  
Recurrence Relation ◽  
Response Function ◽  
Linear Problem ◽  
Data Sets ◽  
Impedance Function ◽  
Data Inversion ◽  
Impedance Response ◽  
Penetration Parameter

We present a new algorithm for 1D magnetotelluric (MT) data inversion. It inverts a normalized impedance response function derived from the classical Cagniard impedance function. The scheme transforms the nonlinear problem of estimating layer resistivities and thicknesses into a linear problem of estimating the coefficients of power series of the new response function. This is achieved by working with a model where each layer has a thickness of constant penetration. The first coefficient of the series provides top-layer resistivity, which, in conjunction with the constant penetration parameter, then provides the layer thickness. The scheme employs a recurrence relation developed between the coefficients of the power series of two successive layers. This relation is used to continue downward and estimate the remaining layer resistivities and thicknesses. The scheme has been tested on a synthetic model and on three well-studied data sets relating to deep, intermediate, and shallow exploration.

A Mixing-Length Model for the Prediction of Convex Curvature Effects on Turbulent Boundary Layers

1984 ◽  
Vol 106 (1) ◽  
pp. 142-148 ◽  
Author(s):  
E. W. Adams ◽  
J. P. Johnston
Keyword(s):  
Heat Transfer ◽  
Layer Thickness ◽  
Boundary Layers ◽  
Turbulent Boundary Layers ◽  
Radius Of Curvature ◽  
Data Sets ◽  
Mixing Length ◽  
Flat Wall ◽  
Curvature Effects ◽  
Layer Thickness Ratio

A mixing-length model is developed for the prediction of turbulent boundary layers with convex streamwise curvature. For large layer thickness ratio, δ/R > 0.05, the model scales mixing length on the wall radius of curvature, R. For small δ/R, ordinary flat wall modeling is used for the mixing-length profile with curvature corrections, following the recommendations of Eide and Johnston [7]. Effects of streamwise change of curvature are considered; a strong lag from equilibrium is required when R increases downstream. Fifteen separate data sets were compared, including both hydrodynamic and heat transfer results. In this paper, six of these computations are presented and compared to experiment.

scholarly journals Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets

2014 ◽  
Vol 50 (8) ◽  
pp. 6339-6357 ◽  
Author(s):  
Chandana Gangodagamage ◽  
Joel C. Rowland ◽  
Susan S. Hubbard ◽  
Steven P. Brumby ◽  
Anna K. Liljedahl ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Active Layer ◽  
Active Layer Thickness ◽  
Data Sets ◽  
Thickness Measurements

scholarly journals Correction* Exponentiated quasi power Lindley power series distribution with applications in medical science

2020 ◽  
Vol 16 (2) ◽  
pp. 85-108
Author(s):  
A. Hassan ◽  
A. Rashid ◽  
N. Akhtar
Keyword(s):  
Power Series ◽  
Medical Science ◽  
Real Life ◽  
Moment Generating Function ◽  
Lambert W Function ◽  
Data Sets ◽  
Lifetime Distributions ◽  
Cumulative Function ◽  
Limiting Behaviour ◽  
Family Of Distributions

AbstractThe present paper introduces an advanced five parameter lifetime model which is obtained by compounding exponentiated quasi power Lindley distribution with power series family of distributions. The EQPLPS family of distributions contains several lifetime sub-classes such as quasi power Lindley power series, power Lindley power series, quasi Lindley power series and Lindley power series. The proposed distribution exhibits decreasing, increasing and bathtub shaped hazard rate functions depending on its parameters. It is more flexible as it can generate new lifetime distributions as well as some existing distributions. Various statistical properties including closed form expressions for density function, cumulative function, limiting behaviour, moment generating function and moments of order statistics are brought forefront. The capability of the quantile measures in terms of Lambert W function is also discussed. Ultimately, the potentiality and the flexibility of the new class of distributions has been demonstrated by taking three real life data sets by comparing its sub-models.

Capability of low-temperature SQUID for transient electromagnetics under anthropogenic noise conditions

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. E371-E383 ◽  
Author(s):  
Raphael Rochlitz ◽  
Matthias Queitsch ◽  
Pritam Yogeshwar ◽  
Thomas Günther ◽  
Andreas Chwala ◽  
...  
Keyword(s):  
Low Temperature ◽  
Quantum Interference ◽  
High Sensitivity ◽  
Low Noise ◽  
Induction Coil ◽  
Anthropogenic Noise ◽  
Data Sets ◽  
Noise Sources ◽  
Data Inversion ◽  
Combined Application

Transient electromagnetics (TEM) is a well-established method for mineral, groundwater, and geothermal exploration. Superconducting quantum interference device (SQUID)-based magnetic-field receivers used for TEM have quantitative advantages and higher sensitivity compared with commonly used induction coils. Special applications are deep soundings with target depths [Formula: see text] and settings with conductive overburden. However, SQUIDs have rarely been applied for TEM measurements in environments with significant anthropogenic noise. We compared a low-temperature SQUID with a commercially available induction coil in an area affected by anthropogenic noise. We acquired four fixed-loop data sets with totally 61 receiver stations close to Bad Frankenhausen, Germany. The high sensitivity of the SQUID enables low noise levels, which lead to longer high-quality transient data compared with the induction coil. The effect of anthropogenic and natural noise sources is more critical for the coil than for the SQUID data. In the vicinity of the transmitter loop, systematic distortion of the coil signals occurs at early times, most probably caused by sferic interferences. We have developed 1D inversion results of both receivers that matched well in general. However, the SQUID-based models were more consistent and showed greater depths of investigation. This led to a superior resolution of deeper layers and even enabled a potential detection of thin conducting targets at up to a 500 m depth. Moreover, we find that the SQUID data inversion revealed multidimensional effects within the conductive overburden. In this regard, we applied forward modeling to analyze systematic differences between inversion results of SQUID and coil data. We determine that low-temperature SQUIDs have the potential to significantly improve the reliability of subsurface models in suburban environments. Nevertheless, we recommend combined application of both types of receivers.

A rapid four-dimensional resistivity data inversion method using temporal segmentation

2020 ◽  
Vol 221 (1) ◽  
pp. 586-602 ◽  
Author(s):  
Bin Liu ◽  
Yonghao Pang ◽  
Deqiang Mao ◽  
Jing Wang ◽  
Zhengyu Liu ◽  
...  
Keyword(s):  
Current Data ◽  
Inversion Method ◽  
Data Sets ◽  
Temporal Segmentation ◽  
Data Set ◽  
Subsurface Structures ◽  
Data Inversion ◽  
Rapid Changes ◽  
High Level ◽  
Acquisition Cycle

SUMMARY 4-D electrical resistivity tomography (ERT), an important geophysical method, is widely used to observe dynamic processes within static subsurface structures. However, because data acquisition and inversion consume large amounts of time, rapid changes that occur in the medium during a single acquisition cycle are difficult to detect in a timely manner via 4-D inversion. To address this issue, a scheme is proposed in this paper for restructuring continuously measured data sets and performing GPU-parallelized inversion. In this scheme, multiple reference time points are selected in an acquisition cycle, which allows all of the acquired data to be sequentially utilized in a 4-D inversion. In addition, the response of the 4-D inversion to changes in the medium has been enhanced by increasing the weight of new data being added dynamically to the inversion process. To improve the reliability of the inversion, our scheme uses actively varied time-regularization coefficients, which are adjusted according to the range of the changes in model resistivity; this range is predicted by taking the ratio between the independent inversion of the current data set and historical 4-D inversion model. Numerical simulations and experiments show that this new 4-D inversion method is able to locate and depict rapid changes in medium resistivity with a high level of accuracy.

scholarly journals Adjustment of Animal Growth Rate Responses in Repeat Measurement Grazing Trials

2011 ◽  
Vol 5 (1) ◽  
pp. 46-55 ◽  
Author(s):  
David Scott
Keyword(s):  
Response Function ◽  
Live Weight ◽  
Weight Increase ◽  
Data Sets ◽  
Individual Animal ◽  
Environment Analysis ◽  
Sources Of Variation ◽  
Gut Fill ◽  
Stocking Rates ◽  
Animal Effects

In animal-response grazing trials there are sources of uncertainty in one-period one-off measurements, which as partial factorisation over time, become traceable and quantifiable sources of variation in repeat measurement trials. This is illustrated for a trial comparing sheep and goat live-weight gains under two stocking rates on mixed species pastures established by three contrasting sowing methods. It used variable plot size to give uniform animal numbers and tracked changes in individual animal performance and pasture growth in different periods. It was repeated on the same plots and animals over 17 grazing cycles. The variation explainable was greater with growth rates expressed as percent live-weight increase per day, than as weight or metabolic weight increase per day. The base data sets were adjusted for specific weighing-day effects of estimated gut-fill using moving averages, and for calibration for individual animal effects by genotype/environment analysis. Collectively these significantly increased the proportion explainable by 3.1-3.8% in variance analyses using qualitative treatment variables, and 2.7-3.7% in response function analyses relative to measured climate, pasture, plot and collective animal covariates. Simulation studies, to allow for variability in the independent variables as well as the dependent variables, indicated that the proportion explainable could increase by a further 0-1.2% and 1.1-1.9% respectively for the variance or response function approaches.

scholarly journals On the Solutions of Okubo-Type Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-5
Author(s):  
Galina Filipuk ◽  
Alberto Lastra
Keyword(s):  
Integral Equation ◽  
Power Series ◽  
Differential Equations ◽  
Recurrence Relation ◽  
Volterra Integral Equation ◽  
Type System ◽  
Type Systems ◽  
Solution Vector

We show that for certain systems of Okubo-type, we can find a solution vector, all components of which are expressed in terms of the first one. This first component can be expressed in two ways. It solves a Volterra integral equation with the kernel expressed in terms of the solutions of a reduced Okubo-type system of smaller dimension. It is also expressed as a power series about the origin with coefficients satisfying certain recurrence relation. This extends the results in (W. Balser, C. Röscheisen, J. Differential Equations, 2009).

scholarly journals Application of time-lapse ERT imaging to watershed characterization

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. G7-G17 ◽  
Author(s):  
Carlyle R. Miller ◽  
Partha S. Routh ◽  
Troy R. Brosten ◽  
James P. McNamara
Keyword(s):  
Reference Model ◽  
Time Lapse ◽  
Data Sets ◽  
Data Set ◽  
Resistivity Tomography ◽  
Practical Applications ◽  
Data Inversion ◽  
Time Periods ◽  
The Difference ◽  
Base Data

Time-lapse electrical resistivity tomography (ERT) has many practical applications to the study of subsurface properties and processes. When inverting time-lapse ERT data, it is useful to proceed beyond straightforward inversion of data differences and take advantage of the time-lapse nature of the data. We assess various approaches for inverting and interpreting time-lapse ERT data and determine that two approaches work well. The first approach is model subtraction after separate inversion of the data from two time periods, and the second approach is to use the inverted model from a base data set as the reference model or prior information for subsequent time periods. We prefer this second approach. Data inversion methodology should be consideredwhen designing data acquisition; i.e., to utilize the second approach, it is important to collect one or more data sets for which the bulk of the subsurface is in a background or relatively unperturbed state. A third and commonly used approach to time-lapse inversion, inverting the difference between two data sets, localizes the regions of the model in which change has occurred; however, varying noise levels between the two data sets can be problematic. To further assess the various time-lapse inversion approaches, we acquired field data from a catchment within the Dry Creek Experimental Watershed near Boise, Idaho, U.S.A. We combined the complimentary information from individual static ERT inversions, time-lapse ERT images, and available hydrologic data in a robust interpretation scheme to aid in quantifying seasonal variations in subsurface moisture content.

scholarly journals 3D induced-polarization data inversion for complex resistivity

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. F157-F171 ◽  
Author(s):  
Michael Commer ◽  
Gregory A. Newman ◽  
Kenneth H. Williams ◽  
Susan S. Hubbard
Keyword(s):  
Environmental Remediation ◽  
Large Scale ◽  
Forward Modeling ◽  
Induced Polarization ◽  
Inversion Method ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Data Set ◽  
Complex Resistivity ◽  
Data Inversion

The conductive and capacitive material properties of the subsurface can be quantified through the frequency-dependent complex resistivity. However, the routine three-dimensional (3D) interpretation of voluminous induced polarization (IP) data sets still poses a challenge due to large computational demands and solution nonuniqueness. We have developed a flexible methodology for 3D (spectral) IP data inversion. Our inversion algorithm is adapted from a frequency-domain electromagnetic (EM) inversion method primarily developed for large-scale hydrocarbon and geothermal energy exploration purposes. The method has proven to be efficient by implementing the nonlinear conjugate gradient method with hierarchical parallelism and by using an optimal finite-difference forward modeling mesh design scheme. The method allows for a large range of survey scales, providing a tool for both exploration and environmental applications. We experimented with an image focusing technique to improve the poor depth resolution of surface data sets with small survey spreads. The algorithm’s underlying forward modeling operator properly accounts for EM coupling effects; thus, traditionally used EM coupling correction procedures are not needed. The methodology was applied to both synthetic and field data. We tested the benefit of directly inverting EM coupling contaminated data using a synthetic large-scale exploration data set. Afterward, we further tested the monitoring capability of our method by inverting time-lapse data from an environmental remediation experiment near Rifle, Colorado. Similar trends observed in both our solution and another 2D inversion were in accordance with previous findings about the IP effects due to subsurface microbial activity.

Sign in / Sign up

Export Citation Format

Share Document