GeoDecider：一种通过审慎推理进行地质解释的基于证据的智能体
GeoDecider: An Evidence-Grounded Agent for Geological Interpretation via Deliberative Reasoning
AI总结：
针对地质解释任务中不同地下单元测井响应相似、准确解释依赖多因素且现有方法固定流程的问题，提出GeoDecider智能体，先数值预测，再对困难区间工具辅助推理，经构建证据概况等流程，实验证明其优于基线，凸显相关方法的价值。
摘要：
地质解释从间接地球物理观测中推断地下属性和结构。测井分类为深度索引的岩石物理记录分配地质类别，提供了一个可测量的场景。该任务具有挑战性，因为不同地下单元可能有相似的测井响应，准确解释依赖多种因素。现有自动化方法多遵循固定预测流程。本文提出GeoDecider，一个用于审慎地质解释的基于证据的智能体。它先进行高效数值预测，再对困难区间进行工具辅助推理。通过轻量级分类器预测并评估样本难度，高难度点触发区间级分析，为每个激活区间构建证据概况，三种科学观点生成候选解释，比较证据、解决分歧并进行地质检查。在四个公共测井基准上的实验表明，GeoDecider优于代表性基线，证明了选择性证据收集和审慎推理对地质解释的价值。
英文摘要：
Geological interpretation infers subsurface properties and structures from indirect geophysical observations. Well-log classification provides a measurable setting by assigning geological classes to depth-indexed petrophysical records. The task is difficult because different subsurface units may exhibit similar logging responses, whereas accurate interpretation often depends on local measurements, depth-wise context, domain knowledge, and reasonable transitions between neighboring layers. Existing automated methods mainly follow fixed prediction pipelines, leaving little room to gather additional evidence for difficult samples. In this work, we propose GeoDecider, an evidence-grounded agent for deliberative geological interpretation. GeoDecider retains efficient numerical prediction as the first stage, then selectively invokes tool-assisted reasoning for difficult intervals. A lightweight classifier produces point-wise predictions and estimates sample difficulty from its prediction scores. High-difficulty points act as routing anchors, triggering interval-level analysis so that nearby observations can be examined together. For each activated interval, specialized tools build an Evidence Profile that summarizes geological knowledge, depth-wise trends, previous predictions from the same well, and similar cases retrieved from training wells. Three complementary scientific views generate candidate interpretations. GeoDecider compares their supporting evidence, resolves disagreements, then applies geology-informed checks on continuity, boundary cues, and petrophysical consistency. Experiments on four public well-log benchmarks show that GeoDecider consistently outperforms representative baselines, demonstrating the value of selective evidence gathering and deliberative reasoning for geological interpretation.~\footnote{Our code is available at https://github.com/Xiaoyu-Tao/GeoDecider}
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
