Szabó, Norbert Péter and Dobróka, Mihály (2013) FLOATENCODED GENETIC ALGORITHM USED FOR THE INVERSION PROCESSING OF WELLLOGGING DATA. In: Global optimization  Theory, Developments and Applications. Nova Science Publishers Inc., New York, pp. 79104.

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Abstract
In this chapter a FloatEncoded Genetic Algorithm is presented for solving the welllogging inverse problem. The aim of the global inversion of welllogging data is to provide a robust and reliable estimate of petrophysical properties of geological structures such as porosity, water saturation, shale volume and mineral content. There are two possible ways to solve the interpretation problem. The first is a conventional inversion scheme, which estimates the unknowns to different depths separately. In the forward modeling phase of the local inversion procedure the theoretical welllogging data are calculated by using locally defined probe response functions, which are then fitted to real data in order to estimate model parameters only to one depth. This procedure leads to a marginally overdetermined inverse problem, which results in relatively poor parameter estimates. A further disadvantage of the above technique is that some crucial quantities such as the thickness of layered geological formations cannot be extracted by inversion, because it does not appear explicitly in local response equations. A new inversion methodology introduced by the authors gives much more freedom in choosing the inversion parameters. The socalled interval inversion method inverts all data measured from a greater depth interval in a joint inversion process. By a series expansionbased discretization of the petrophysical model a highly overdetermined inverse problem can be formulated, which enables to estimate the petrophysical parameters including new unknowns such as zone parameters and layer thicknesses more accurately compared to local inversion methods. The authors give further references for several applications of the global inversion method. In this chapter, a synthetic and two field examples are presented to demonstrate the application of the Genetic Algorithmbased inversion method. It is shown that the combination of the new inversion strategy and global optimization tools forms a highly effective and adaptive algorithm for earth scientists who are interested in a more reliable calculation of the reserves of hydrocarbons and other mineral resources.
Item Type:  Book Section 

Subjects:  Q Science / természettudomány > QE Geology / földtudományok Q Science / természettudomány > QE Geology / földtudományok > QE01 Geophysics / geofizika 
Depositing User:  PhD Norbert Péter Szabó 
Date Deposited:  20 Sep 2015 07:40 
Last Modified:  14 May 2016 09:21 
URI:  http://real.mtak.hu/id/eprint/27001 
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