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Reservoir Characteristics Classification using Acoustic Signal Processing


Author(s):

ADITI AWASTHI , Sinhgad College Of Engineering; Dr. (Mrs.) S. S. Lokhande, Sinhgad College of Engineering; M. Selva Balan, Central Water Power Research Station

Keywords:

Sediment Classification, Finite Volume Method (FVM), Reservoir Characterization, Underwater Acoustics

Abstract:

Reservoirs are losing its capacity due to various materials getting dumped after every rainy season. So in order to estimate the reservoir capacity and to plan the reservoir operations, the modelling process is defined to represent idealization of reservoir by a mathematical model using governing equations. Then using acoustic signals the underwater sediments are classified. In this paper reservoir model is created using finite volume. The finite volume method falls into the family of Godunov algorithms and is a technique for solving a system of hyperbolic equations. This method is considered very accurate as it conserves mass at every time step. It operates by updating the solution within some control volume and includes all the inter-cell mass and momentum flux contributions in a single step. Then acoustic signal is transmitted through the reservoir model. Then different features are extracted from the reflected signals and the reservoir characteristics such as stone, gravel, sand, silt, clay are classified.


Other Details:

Manuscript Id :IJSTEV3I1118
Published in :Volume : 3, Issue : 1
Publication Date: 01/08/2016
Page(s): 253-256
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