Abstract
The Cuu Long basin is an Early Tertiary rift basin of southern Vietnam, and the most potential basin in the country with high productive for oil and gas. Special interest in the Lower Miocene reservoir in the Cuu Long basin is caused by the gradual depletion of unique oil-bearing in the fractured basement and the possibility of transferring production wells to overlying deposits in the terrigenous rocks of the sedimentary cover and entering new deposits into development. In recent years, seismic attributes analysis has emerged as an effective tool to predict ancient riverbeds where sand bodies may exist in nonstructural traps. Understanding the distribution of these sand bodies will be of great significance in the orientation of oil and gas exploration activities. The paper applied seismic attribute analysis method combined with artificial neural network (ANN) and well data to predict the distribution of sandstones reservoirs of Lower Miocene sediments in the Northeastern Bach Ho oil field. Seismic attributes selected as input for ANN training including Relative Acoustic Impedance, Root Mean Square, Sweetness. The attributes provide the most obvious opportunity to display geological features with varying seismic amplitude characteristics as well as predict lithofacies, petrology and the distribution of sand bodies. The research results have identified the potential reservoirs in the Northeastern area of Bach Ho field, which are deposited in the fluvial, marginal lacustrine and deltaic environments.
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