--> Seismic Facies Classification and Characterization of Deep Water Architectural Elements. A Case of Study, North Carnarvon Basin Australia

AAPG Annual Convention and Exhibition

Datapages, Inc.Print this page

Seismic Facies Classification and Characterization of Deep Water Architectural Elements. A Case of Study, North Carnarvon Basin Australia

Abstract

The North Carnarvon Basin in Australia is one of the most prolific basins developed for oil and gas potential in Australia in the last 10 years. This is a premier basin where important hydrocarbon fields have been found. While the 10 most significant oil and gas fields fall within the Triassic Brigadier formation in the Rankin Platform sub-basin, there is significant oil and gas potential in the deep water Cenozoic deposits. Our goal is to characterize the dimensions and composition of the depositional element that provide a better estimation of the potential of those reservoirs. Analysis of a high resolution 3D seismic volume from the Cenozoic Trealla formation in the offshore of North Carnarvon basin, Australia has revealed fine details of deep water architectural elements. A model-based inversion combined with the use of self-organized maps (SOM) allows the characterization of the architectural elements including seismic facies dimensions and position on slope. Four main groups of architectural elements were identified in the studied area: (1) erosive channel-fills, (2) channel-levee complexes, (3) mass transport deposits, and (4) sand fan lobes or sheets. Each depositional element exhibits a characteristic morphology and seismic response according to the lithology predominant in each architectural element. Seven attributes including acoustic impedance, dip magnitude, peak frequency, energy ratio coherence, peak magnitude and curvature are used as input for the classification. This classification technique preserves the distance information from input space into the SOM latent space. The result is a better defined clusters that when plotted against a 2D color bar clearly allow the identification of geomorphologies and facies.