Application of particle swarm optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast

Kunal Kishore Singh,Upendra Kumar Singh

doi:10.5194/gi-6-193-2017

Abstract

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.

Highlights

The gravity method is a natural source method which helps in locating masses of greater or lesser density than the surrounding formations
Ambiguity in gravity anomalies can be overcome by assigning a mathematical geometry to the anomalycausing body with a known density contrast (Rama Rao and Murthy, 1978)
MATLAB code based on Particle swarm optimization (PSO) is developed to interpret the gravity anomalies of 2.5-D sedimentary basins, where the density varies parabolically with depth

Summary

Introduction

The gravity method is a natural source method which helps in locating masses of greater or lesser density than the surrounding formations It is used as a reconnaissance survey in hydrocarbon exploration. Several authors have developed 2-D/2.5-D local optimization techniques over the 2-D/2.5-D sedimentary basin (Annecchione et al, 2001; Barbosa et al, 1999; Bhattacharya and Navolio, 1975; Gadirov et al, 2016; Litinsky, 1989; Morgan and Grant, 1963; Murthy et al, 1988; Murthyan and Rao, 1989; Rao, 1994; Won and Bavis, 1987) to interpret gravity anomalies with constant density function. MATLAB code based on PSO is developed to interpret the gravity anomalies of 2.5-D sedimentary basins, where the density varies parabolically with depth. PSO-analysed results are consistent with and more accurate than other techniques and agree significantly well with borehole information

Theory

Particle swarm optimization

Synthetic Example

Field example

Godavari sub-basin

Conclusions