Evolutionary Programming for Systematic Evaluation of Aquifers: A Case Study from Dholera, Cambay Basin, Gujarat, India

Kriti Yadav,Anirbid Sircar

doi:10.4236/gep.2019.74009

Abstract

Joint inversion of different potentials improves subsurface model resolution. In this paper seismic refraction and magnetotelluric data are used to understand near subsurface features of Dholera, Gujarat, India. An extensive seismic and magnetotelluric survey was carried out in Dholera in order to delineate subsurface presence of aquifers. Ray Inversion for Near Surface Estimation (RINSE) is used for inversion of Dholera seismic data. The inversion output of seismic data is used as seed points for resistivity inversion of anomalies. Inversion of resistivity data is done using evolutionary programing method which is also a type of genetic algorithm. Here the optimization is done using four major steps, of evolutionary programing namely population generation, fitness function, crossover and mutation. This paper also compares the similarities between the natural and geophysical optimization. A Low Velocity Layer is identified up to a depth of 11 m from seismic refraction method. Three layers are identified after the interpretation of seismic and resistivity data. The average thicknesses of Layers one and two are calculated as 3.558 and 6.533 respectively.

Highlights

Model resolution of subsurface features can be improved by joint inversion of different geophysical potential data (Ammon et al, 1990)
Evolutionary programing method which is known as Genetic Algorithm method is used for joint inversion of these potential data
In this paper a basic evolutionary programing method is used for cross correlation as fitness function where multiple point crossover method is used

Summary

Introduction

Model resolution of subsurface features can be improved by joint inversion of different geophysical potential data (Ammon et al, 1990). Magnetotelluric and seismic refraction techniques are the most effective and commercial methods for identification of aquifers Inversion of these two potentials can be done by using various inversion methods like Gauss-Newton (GN) method, Quasi-Newton (QN) method, Genetic Algorithm, etc. It has been found that there is compelling evidence of low enthalpy geothermal sources, which is identified by high gravity and magnetic anomalies in the region and manifestation of many hot water springs in the area (Shah et al, 2017) These observations motivate our work, and our objective is to test these qualitative approaches by adding more potential data using a formal approach

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