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Abstract: Porosity and Permeability Prediction of Zechstein-2-Carbonates From 3D Seismic Data

H. Trappe, P. Krajewski, S. Aust

In this study the applicability is explored of using 3D seismic data to estimate porosity and permeability for Zechstein-2-Carbonates using advanced techniques such as Neural Networks and image processing algorithms.

The study area is located in the North German basin next to the dutch border. About 40 wells tested the Zechstein reservoir at depth between 3000-4000 m. Production of the gas fields started in the fifties/early sixties. The wells were generally drilled on structural highs mapped by 2D seismic data.

In a first step a detailed seismic modelling exercise was carried in order to find a relationship between reservoir quality and seismic attributes. Moreover the influence of overburden and hanging wall layers to the seismic signature at reservoir level was investigated.

In the second phase the previously obtained results were proofed by the 3D seismic. Using amplitude and acoustic impedance porosity maps of the reservoir were calculated. While the porosity maps show a high degree of confidence unfortunately the porosity-permeability relationship within the carbonates is poor. Therefore additional geological parameters such as thickness of the basal Zechstein which influenced the facies distribution were used to derive an empirical relationship to permeability. Seismic attributes and geological parameters form the input for a selforganizing Neural Network. This Neural Network was trained to characterise facies units of variable permeabilities. After successful training the network is able to predict facies and permeability as well as porosity for a given area.

The last stage of the study covers the structural framework of the study area. Seismic attributes such as two way traveltime and amplitude were processed using image processing algorithms. Edge detection operators, IHS illumination, gradient descriptors and other procedures were applied to highlight small scale faulting which is thought to be responsible for an increase the production performance.

This study demonstrates the impact of advanced techniques in an area of long production history. It has been shown that these techniques strongly increased the knowledge about the internal geometry of the carbonate reservoir.

AAPG Search and Discovery Article #90956©1995 AAPG International Convention and Exposition Meeting, Nice, France