Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm

Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan; Turan, Seçil

doi:10.1016/j.jappgeo.2016.03.040

Cited by 69 publications

(39 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The main objective of geophysical inversion is to apply the same BoltzmannÕs law and to minimize an objective function or the error function in geophysical data modeling. Various optimization methods such as simulated annealing (SA), genetic algorithms (GA), artificial neural networks (ANN), particle swarm optimization (PSO) and differential evolution (DE) (El-Kaliouby and AlGarni 2009;Monteiro Santos 2010;Sharma and Biswas 2011;Sen and Stoffa 2013;Sharma and Biswas 2013;Biswas 2015;Ekinci 2016;Ekinci et al 2016;Balkaya et al 2017) were regularly used to optimize geophysical data and have been applied to derive diverse geophysical information (Rothman 1985(Rothman , 1986Dosso and Oldenburg 1991;Zhao et al 1996;Martínez et al 2010;Li et al 2011;Sharma 2012;Sen and Stoffa 2013). Sen and Stoffa (2013) discussed in detail the SA.…”

Section: Inversionmentioning

confidence: 99%

Inversion of Source Parameters from Magnetic Anomalies for Mineral/Ore Deposits Exploration Using Global Optimization Technique and Analysis of Uncertainty

Biswas

2017

Nat Resour Res

View full text Add to dashboard Cite

Global optimization algorithm using very fast simulated annealing has been used for modeling of magnetic anomaly over various idealized geobodies for mineral/ore deposit investigation. The present technique shows that it can match the observed data very well assuming some simple geometrical bodies such as sphere, horizontal cylinder and thin dyke or sheet. Uncertainty associated with the modeling was also studied. It has been found that the obtained source parameters are strongly identical when all the parameters are optimized. The present study shows that amplitude coefficient depends on the shape factor. The relation between them shows a multimodel-type uncertainty. The shape factor modeled from several VFSA runs shows the different kind of subsurface structure. Constraining the shape factor gives reliable results and analysis of histograms and cross-plots also gives the utmost reliable results, which show a unimodel character. Inversion of synthetic noise-free and noisy data shows the worth of the present work. The present algorithm was also tested in five field case studies for mineral/ore exploration. Computation time for this present work is very minimal.

show abstract

Section: Inversionmentioning

confidence: 99%

Inversion of Source Parameters from Magnetic Anomalies for Mineral/Ore Deposits Exploration Using Global Optimization Technique and Analysis of Uncertainty

Biswas

2017

Nat Resour Res

View full text Add to dashboard Cite

show abstract

“…The trial vector is obtained using both donor vector elements and the target vector, and the recombination process combines successful solutions considering the previous generation (Balkaya et al, 2017). In the last step, considering the lowest error/misfit values, the target vector or trial vector is transferred to the next generation (Ekinci et al, 2016(Ekinci et al, , 2017. These processes in the evolution loop continue until a predefined iteration number or the reaching of a satisfactory objective function value.…”

Section: De Algorithmmentioning

confidence: 99%

“…Thus, it may be stated that PSO is the preferable optimization technique used in potential field parameter estimation studies. On the other hand, recently, the differential evolution (DE) algorithm has been introduced as a powerful tool for the inversion of potential field datasets (Ekinci et al, 2016(Ekinci et al, , 2017Balkaya et al, 2017). However, the DE algorithm has not gained wide currency in geophysical studies yet.…”

mentioning

confidence: 99%

Parameter Estimations from Gravity and Magnetic Anomalies Due to Deep-Seated Faults: Differential Evolution versus Particle Swarm Optimization

2019

Turkish J Earth Sci

View full text Add to dashboard Cite

Introduction Due to the mathematical nature of the gravity and magnetic methods in geophysics, numerous data processing techniques are easily performed to analyze their anomalies obtained from different types of investigations changing in a wide range of varieties. Based on the objectives of the investigations, the most commonly used techniques are generally separated into two different groups. The first group techniques, involving linear transformations, directional derivative-based techniques, image enhancement procedures, spectral methods, filtering operators, etc., generally aim at exploring and locating the geological source structures causing the potential field anomalies (

show abstract

“…The main objective of those techniques utilize the mentioned approximations to best-estimate the gravity parameters values, e.g., the depth to the buried body and the amplitude coefficient. The developed methods include, linear optimization-simplex algorithm (Asfahani and Tlas, 2015), neural network modeling (Abedi et al, 2010), differential evolution algorithm (Ekinci et al, 2016), graphical methods (Nettleton, 1962;, ratio methods (Bowin et al, 1986;Abdelrahman et al, 1989), Fourier transform (Odegard and Berg, 1965;Sharma and Geldart, 1968), Euler deconvolution (Thompson, 1982), neural network (Elawadi et al, 2001), Mellin transform (Mohan et al, 1986), least-squares minimization approaches (Gupta, 1983;Lines and Treitel, 1984;Abdelrahman, 1990;Abdelrahman et al, 1991;Abdelrahman and El-Araby, 1993;Abdelrahman and Sharafeldin, 1995a), Werner deconvolution (Hartmann et al, 1971;Jain, 1976).…”

Section: Introductionmentioning

confidence: 99%

Multiple-linear regression to best-estimate of gravity parameters related to simple geometrical shaped structures

Tlas

Asfahani

2019

Contributions to Geophysics and Geodesy

View full text Add to dashboard Cite

A new interpretative approach is proposed to best-estimate of gravity parameters related to simple geometrical shaped structures such as a semi-infinite vertical cylinder, an infinite horizontal cylinder, and a sphere like structures. The proposed technique is based on the multiple-linear regression oriented towards estimating the model parameters, e.g., the depth from the surface to the center of the buried structure (sphere or infinite horizontal cylinder) or the depth from the surface to the top of the buried object (semi-infinite vertical cylinder), the amplitude coefficient, and the horizontal location from residual gravity anomaly profile. The validity of the proposed approach is firstly demonstrated through testing different synthetic data set corrupted and contaminated by a white Gaussian random noise level. The theoretical synthetic obtained results obviously show that the estimated parameters values, derived by the proposed technique are close to the assumed true parameters values. This approach is applied on five real field residual gravity anomalies taken from Cuba, Sweden, Iran, USA, and Germany, where the efficacy of this new approach is consequently proven. A comparable and acceptable agreement is noticed between the results derived by this proposed approach and those obtained from the real field data information.

show abstract

Model parameter estimations from residual gravity anomalies due to simple-shaped sources using Differential Evolution Algorithm

Cited by 69 publications

References 51 publications

Inversion of Source Parameters from Magnetic Anomalies for Mineral/Ore Deposits Exploration Using Global Optimization Technique and Analysis of Uncertainty

Inversion of Source Parameters from Magnetic Anomalies for Mineral/Ore Deposits Exploration Using Global Optimization Technique and Analysis of Uncertainty

Parameter Estimations from Gravity and Magnetic Anomalies Due to Deep-Seated Faults: Differential Evolution versus Particle Swarm Optimization

Multiple-linear regression to best-estimate of gravity parameters related to simple geometrical shaped structures

Contact Info

Product

Resources

About