タービダイト砂岩の平行葉理にみられた2種類の組織 --CNN画像セグメンテーション技術を用いた微細組織解析による検討--

Abstract

本研究では，岩石切片のスキャン画像中から粒子を自動検出し，砂粒子スケールで堆積岩の組織を解析する画像解析手法を開発した．まず，白亜系和泉層群および姫浦層群から採取した砂岩切片のスキャン画像から，教師画像として手動トレース画像を1589枚用意した．これらの画像を用いて畳み込みニューラルネットワークの教師あり学習を行った後に，学習に使用しなかったテスト画像へ画像解析モデルを適用させた結果，ピクセルが正しく判定される率は90.7%となり，粒度分布のパターンも教師画像とよく一致した．本研究手法により，岩石の研磨断面から短時間かつ簡便に高解像度の粒度分析を行うことが可能となった．開発した手法を淡路島に分布する和泉層群のタービダイト砂岩に適用し，砂岩中の平行葉理の多様性を検討したところ，タービダイト中には二種類の平行葉理が含まれることが認識された．一つは平均粒径や標準偏差が周期的に変動する不明瞭な葉理であり，もう一つは細粒な堆積物中に薄い粗粒レイヤーが挟まれるという明瞭な葉理である．これらの葉理の成因については今後の実験的検討が必要となるだろう．

This study developed a methodology to detect sand particles automatically from scanned images of cross sections of sandstones using deep learning image analysis. First, we prepared 1589 manually traced images of 256×256 pixels taken from the sandstone specimens of the Cretaceous Izumi and Himenoura Groups as teacher images, and the supervised training of the convolutional neural network was conducted to produce an image segmentation model. The trained model was applied to the test image that was independent of training images, and achieved 90.7% in accuracy of pixel classification. In addition, the results of grain-size analysis of the segmented image agreed well with those of the test image. Next, the trained model was applied to 10 polished sections of turbidite sandstones obtained from the Upper Cretaceous Izumi Group distributed in the southern part of Awaji Island, Japan, to examine the diversity of parallel lamination in turbidites. All images were subdivided at every 0.5 mm vertical intervals, and 1 cm-thick analytical window was set in vertical profiles of mean and standard deviation calculated at every subdivision to obtain statistical values characterizing features of parallel lamination. As a result, statistical analysis of grain-size distribution in parallel laminated sandstones implied that the obvious (Type 1) and unobvious (Type 2) parallel lamination exhibit different characteristics. In Type 2, mean and standard deviation of grain-size distribution fluctuated periodically. In contrast, Type 1 is mainly composed of fine-grained sediments and irregularly intercalates coarse-grained layers. In the future studies, quantitative comparison of these characteristics with flume experiments or numerical calculation will provide understandings of the formation mechanisms of the parallel lamination.