Uygulamalı jeofizikte metasezgiseller

Yıl 2016, Cilt: 22 Sayı: 6, 563 - 580, 20.12.2016

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

Öz

Bu
çalışmada, parçacık sürü optimizasyonu (PSO), genetik algoritma (GA), farksal
evrim (FE) ve yapay ısıl işlem (YIİ) algoritmalarını kapsayan dört metasezgisel
algoritma jeofiziğin bir, iki ve üç boyutlu (1B, 2B ve 3B) ters çözüm
problemlerinde kullanılmıştır. Doğal uçlaşma (DU), doğru akım özdirenç (DAÖ),
manyetik ve karşılıklı kuyu yer radarı uygulamalarından elde edilen kuramsal
ve/veya alan veri kümeleri yukarıda değinilen metasezgisellerden biriyle
değerlendirilmiştir. PSO, hem sentetik olarak üretilen hem de Güney Bavyera’da
(Almanya) bir grafit yatağında ölçülen DU anomalilerinin model parametrelerinin
(elektrik dipol moment, uçlaşma açısı, derinlik, biçim faktörü ve anomali
orijini) belirlenmesinde kullanılmıştır. Gerçel değer kodlamalı GA, hem
kuramsal hem de Bozdağ, İzmir’de (Türkiye) karstik bir ortamda toplanan düşey
elektrik sondajı veri kümelerinden yatay tabakalı yer modelinin parametrelerini
(tabaka özdirenç ve kalınlıklarını) kestirmek için kullanılmıştır. Sentetik bir
karşılıklı kuyu yer radarı verisinden 2B’lu yeraltı radar hız dağılımının
görüntülenmesi amacıyla YIİ ve yuvarlatma kısıtlı doğrusallaştırılmış en küçük
kareler yönteminin ardışık kullanılmasına dayanan melez bir yaklaşım
uygulanırken; FE algoritması kuramsal olarak üretilen bir toplam alan manyetik
anomali haritasının 3B’lu ters çözümünde kullanılmıştır. Her bir metasezgisel
algoritmanın gerek duyduğu kullanıcı tanımlı parametreler incelenen problemler
dikkate alınarak test çalışmalarıyla belirlenmiştir. Ayrıca, metasezgiseller
tarafından elde edilen sonuçların güvenilirlikleri çeşitli istatistiksel ve
belirsizlik analizleriyle araştırılmıştır. Burada kullanılan metasezgisellerin
çeşitli jeofizik problemlerin model parametrelerinin kestiriminde başarılı
sonuçlar üretmesi bu algoritmaların, jeofiziğin küçük ve görece büyük boyutlu
veri kümelerine uygulanabilirliğini göstermiştir.

Anahtar Kelimeler

Metasezgisel, Parçacık sürü optimizasyonu, Genetik algoritma, Farksal evrim, Yapay ısıl işlem, Uygulamalı jeofizik

Metaheuristics in applied geophysics

Öz

In
this study, four metaheuristic algorithms including particle swarm optimization
(PSO), genetic algorithm (GA), differential evolution (DE) and simulated
annealing (SA) were used for one-, two- and three-dimensional (1D, 2D and 3D) geophysical
inverse problems. Theoretical and/or field data sets obtained by self-potential
(SP), direct current resistivity (DCR), magnetic and crosshole radar
applications were interpreted by one of the above-mentioned metaheuristics. PSO
was used to determine model parameters (i.e., the electric dipole moment,
polarization angle, depth, shape factor and origin of the anomaly) of SP
anomalies which are both synthetically generated and measured over a graphite
deposit in the southern Bavarian woods, Germany. A real-valued GA was used for
estimating the parameters of a horizontally-layered earth model (i.e.,
resistivity and thickness of each layer) from vertical electrical sounding
curves via the data sets based on both theoretical and a field experiment in a
karstic environment in Bozdağ, İzmir (Turkey). A synthetic crosshole radar data
set was considered for 2D imaging of the subsurface radar velocity distribution
by a hybrid approach based on sequential use of SA and a linearized smoothness-constrained
least-squares scheme, and DE algorithm was applied for a 3D inversion of a
synthetically produced total field magnetic anomaly map. User-defined
parameters required by each metaheuristic algorithm were determined by test
studies considering the problems studied. Confidences in the results obtained
by the metaheuristics were also examined by various uncertainty and statistical
analyses. Since the metaheuristics used here produced satisfactory results for
estimating the model parameters of a variety of the geophysical problems, it
can be concluded that these algorithms can be applied to low- and relatively
high-dimensional geophysical data.

Anahtar Kelimeler

Metaheuristic, Particle swarm optimization, Genetic algorithm, Differential evolution, Simulated annealing, Applied geophysics

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