Journal cover Journal topic
Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union

Journal metrics

  • IF value: 1.023 IF 1.023
  • IF 5-year<br/> value: 1.557 IF 5-year
    1.557
  • CiteScore<br/> value: 0.86 CiteScore
    0.86
  • SNIP value: indexed SNIP
    indexed
  • SJR value: indexed SJR
    indexed
  • IPP value: indexed IPP
    indexed
  • h5-index value: 10 h5-index 10
Geosci. Instrum. Method. Data Syst., 6, 193-198, 2017
https://doi.org/10.5194/gi-6-193-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
10 Apr 2017
Application of particle swarm optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast
Kunal Kishore Singh1,2 and Upendra Kumar Singh1 1Department of Applied Geophysics, IIT(ISM), Dhanbad 826004, India
2Geological Survey of India, Lucknow-226024, India
Abstract. Particle swarm optimization (PSO) is a global optimization technique that works similarly to swarms of birds searching for food. A MATLAB code in the PSO algorithm has been developed to estimate the depth to the bottom of a 2.5-D sedimentary basin and coefficients of regional background from observed gravity anomalies. The density contrast within the source is assumed to vary parabolically with depth. Initially, the PSO algorithm is applied on synthetic data with and without some Gaussian noise, and its validity is tested by calculating the depth of the Gediz Graben, western Anatolia, and the Godavari sub-basin, India. The Gediz Graben consists of Neogen sediments, and the metamorphic complex forms the basement of the graben. A thick uninterrupted sequence of Permian–Triassic and partly Jurassic and Cretaceous sediments forms the Godavari sub-basin. The PSO results are better correlated with results obtained by the Marquardt method and borehole information.

Citation: Singh, K. K. and Singh, U. K.: Application of particle swarm optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast, Geosci. Instrum. Method. Data Syst., 6, 193-198, https://doi.org/10.5194/gi-6-193-2017, 2017.
Publications Copernicus
Download
Short summary
Particle swarm optimization is developed to estimate the model parameters of a 2.5-D sedimentary basin. PSO have been implemented on synthetic data and two field data. An observation has been made that PSO is affected by some levels of noise, but estimated depths are close to the true depths. The PSO results are well correlated with borehole samples and provide more geological viability than Marquardt results. Despite its long computation time, it is very simple to implement.
Particle swarm optimization is developed to estimate the model parameters of a 2.5-D sedimentary...
Share