基于机器学习的地层序列模拟  

STRATIGRAPHIC SEQUENCE SIMULATION BASED ON MACHINE LEARNING

作　　者：周翠英 张国豪 杜子纯 刘镇 ZHOU Cuiying;ZHANG Guohao;DU Zichun;LIU Zhen(School of Civil Engineering,Sun Yat-sen University,Guangzhou 510275;School of Engineering,Sun Yat-sen University,Guangzhou 510275)

机构地区：[1]中山大学土木工程学院,广州510275 [2]中山大学工学院,广州510275

出　　处：《工程地质学报》2019年第4期873-879,共7页Journal of Engineering Geology

基　　金：国家自然科学基金项目(41530638,41030747,41227002,41372302,41472257);广东省重点应用专项(2016B010124007);广州市科技计划项目(201803030005)资助~~

摘　　要：地层结构及其分布的模拟是地质信息化研究与工程规划设计建造的迫切需求。现有的研究方法主要以钻孔数据为基础,选择插值方法进行二维剖面绘制和三维地层建模。插值方法是决定模拟结果准确程度的重要因素,但插值方法的选取受主观因素影响,缺乏科学合理性,难以推广应用。针对这一问题,本文提出一种基于钻孔数据进行机器学习的地层序列模拟方法,即将钻孔地层数据处理为地层类型序列与地层层厚序列,利用循环神经网络与序列-序列架构建立地层序列模拟模型。通过将模拟结果与实际钻孔数据对比分析,发现地层序列模型可以较准确地模拟地表到基岩面之间的地层类型与厚度范围。研究可为地层模拟提供新方法。The structure and distribution simulation of strata is an urgent demand in geological informatization as well as engineering.Current study methods are mostly based on borehole data,drawing stratigraphic section or building three-dimensional geological model through interpolation.Interpolation is an important factor in accuracy.However,the determination of interpolation method is subjective,lacking of scientific consideration and therefore difficult to apply to other distinct.Therefore,this study proposes a stratigraphic sequence simulation method based on machine learning.The method considers the borehole data as type and thickness sequence,and presents the stratigraphic sequence simulation model based on recurrent neural network and sequence to sequence learning.Comparing the simulation sequence to the actual borehole data,the result indicates that the machine learning-based model are capable of describing the stratigraphic sequence above bedrock using coordinate information.This study provides a new method for stratigraphy study.

关 键 词：地层序列模拟 机器学习 循环神经网络 序列-序列学习 

分 类 号：P628[天文地球—地质矿产勘探]