刘思佟,李如仁,姜力,石国伟,沙宗尧

• 1:武汉大学遥感信息工程学院
• 2:沈阳建筑大学交通与测绘工程学院
• 3:中国石油新疆油田公司数智技术公司
• 4:中国石油新疆油田公司数据公司

摘要(Abstract)：

针对油井井场选址评价中传统方法主观性强以及现有智能算法缺乏解释性的问题，提出一种兼具准确度与可视化决策过程的适宜性评价方法。以准噶尔盆地为研究区，基于现有的遥感数据整合地质、社会人文和自然条件三维度13项指标构建数据集。创新提出神经增强决策树模型，通过在决策节点嵌入神经网络，将硬性规则转化为概率形式，结合了决策树的层次结构优势与神经网络的数据处理能力。该模型在多项指标上表现较好，在训练集与测试集上的准确率分别达到98.90%和96.74%。生成的适宜性地图显示，研究区适宜区域占比19.71%,高度适宜区域主要分布在西北部与东部。实验结果表明，该模型有效缓解了选址适宜性评价中精度与决策可解释性的矛盾，为本研究区油井井场选址适宜性评价提供了科学可靠的决策支持。

关键词(KeyWords)： 油井井场选址;可视化决策;决策树;神经网络;适宜性评价

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(42171447)

作者(Author): 刘思佟,李如仁,姜力,石国伟,沙宗尧

DOI: 10.16251/j.cnki.1009-2307.2026.11.011

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