Bollettino di Geofisica Teorica e Applicata
OGS Website
About the Journal
Statistiche Web
Contacts
To Authors
On-line Submission
Subscriptions
Forthcoming
On-line First
The Historical First Issue
Issues

2023 Vol. 64
1

2022 Vol. 63
1 / 2 / 3 / 4

2021 Vol. 62
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2 / Suppl. 3

2020 Vol. 61
1 / 2 / 3 / 4 / Suppl. 1

2019 Vol. 60
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2 / Suppl. 3

2018 Vol. 59
1 / 2 / 3 / 4 / Suppl. 1

2017 Vol. 58
1 / 2 / 3 / 4

2016 Vol. 57
1 / 2 / 3 / 4 / Suppl. 1

2015 Vol. 56
1 / 2 / 3 / 4

2014 Vol. 55
1 / 2 / 3 / 4

2013 Vol. 54
1 / 2 / 3 / 4 / Suppl. 1 / Suppl. 2

2012 Vol. 53
1 / 2 / 3 / 4

2011 Vol. 52
1 / 2 / 3 / 4 / Suppl. 1

2010 Vol. 51
1 / 2-3 / 4 / Suppl. 1

2009 Vol. 50
1 / 2 / 3 / 4

2008 Vol. 49
1 / 2 / 3-4 / Suppl. 1

2007 Vol. 48
1 / 2 / 3 / 4

2006 Vol. 47
1-2 / 3 / 4

2005 Vol. 46
1 / 2-3 / 4

2004 Vol. 45
1-2 / 3 / 4 / Suppl. 1 / Suppl. 2

2003 Vol. 44
1 / 2 / 3-4

2002 Vol. 43
1-2 / 3-4

2001 Vol. 42
1-2 / 3-4

2000 Vol. 41
1 / 2 / 3-4

1999 Vol. 40
1 / 2 / 3-4

1998 Vol. 39
1 / 2 / 3 / 4

1997 Vol. 38
1-2 / 3-4

1995 Vol. 37
145 / 146 / 147 / 148 / Suppl. 1

1994 Vol. 36
141-144 / Suppl. 1

1993 Vol. 35
137-138 / 139 / 140

1992 Vol. 34
133 / 134-135 / 136

1991 Vol. 33
129 / 130-131 / 132

 
 

Vol. 63, n.1, March 2022
pp. 51-72

Application of Gaussian and Percentile filters in Particle Swarm Optimisation for 3D gravity modelling and its implementation on Sinanpaşa graben gravity data in SW Turkey

A.B. Tekkeli, O. Tarhan Bal and G. Karcıoğlu

Received: 13 July 2020; accepted: 23 September 2021; published online: 25 January 2022

Abstract

3D Modelling of gravity data is generally performed as a multi-objective optimisation, trying to minimise observed-calculated data misfit while providing models with certain properties, such as smooth or sharp boundaries. We demonstrated that controlling the model properties in global optimisation schemes is possible through basic image processing filters, and developed a Particle Swarm Optimisation (PSO) algorithm that benefits from Gaussian and Percentile filters to avoid ambiguous boundaries that are generally seen in 3D smooth inversions of gravity data. The effectiveness of the algorithm is shown on a synthetic model consisting of two dipping structures with anomalous density contrasts. Thereafter, the algorithm is implemented to recover subsurface density distribution from a field data set. The field data is collected at the south-western part of the Sinanpaşa graben, Turkey. Due to the lack of previous geophysical studies in the area, 3D Euler decomposition, tilt angle, and 3D smooth inversion methods are also implemented to help interpretation and to compare to the model recovered using the PSO algorithm. The developed approach is observed to be resulted with a model, which is more compatible with the known geology of the region.



Download PDF complete


back to table of contents