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Abstract <p>We have analyzed three main methods for predicting effective thicknesses, using seismic attributes: linear regression based on full-wave seismic modeling data, cokriging of attribute-well values, and neural network forecast based on a group of attributes trained on wells. The weathering crust in the pre-Jurassic complex of Western Siberia was chosen as a methodological example, because the reflections from its top and bottom are not separated due to its relatively small thickness (from 0 to 50 m). The amplitude–frequency characteristic of this interference reflection depends on the thickness; therefore some seismic attributes may react to it. The analysis of independent forecast results by the three methods and their advantages and disadvantages are given. All the basic calculations are performed, using domestic software, for the first time.</p>

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Comparison of Methods of Quantitative Attribute Analysis for Forecasting Reservoir Thicknesses Based on Seismic Data

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • Yu. P. Ampilov,
  • K. R. Safuanova,
  • Ya. I. Shtein

摘要

Abstract

We have analyzed three main methods for predicting effective thicknesses, using seismic attributes: linear regression based on full-wave seismic modeling data, cokriging of attribute-well values, and neural network forecast based on a group of attributes trained on wells. The weathering crust in the pre-Jurassic complex of Western Siberia was chosen as a methodological example, because the reflections from its top and bottom are not separated due to its relatively small thickness (from 0 to 50 m). The amplitude–frequency characteristic of this interference reflection depends on the thickness; therefore some seismic attributes may react to it. The analysis of independent forecast results by the three methods and their advantages and disadvantages are given. All the basic calculations are performed, using domestic software, for the first time.