<span data-lang="zh">钻孔柱状图开源库详解</span><span data-lang="en">Open-Source Libraries for Borehole Log Digitization</span>

钻孔柱状图开源库详解Open-Source Libraries for Borehole Log Digitization

Open-Source Libraries for Borehole Data

全面汇总钻孔数据提取、处理与可视化领域的开源Python库，详细说明其功能定位、核心方法与适用场景。Comprehensive guide to open-source Python libraries for borehole data extraction, processing, and visualization.

📖

概述Overview

钻孔柱状图数字化涉及数据提取、解析、处理、可视化等多个环节。开源生态在这些环节提供了丰富的工具支持，主要可分为三大类：Borehole log digitization involves extraction, parsing, processing, and visualization. The open-source ecosystem provides rich tools across these stages, mainly in three categories:

数据提取与解析Extraction & Parsing

从PDF报告、扫描图像、CAD图件中提取结构化钻孔数据，包括dh2loop、geotech-report-extraction、parseplot、GemGIS等。 Extract structured borehole data from PDF reports, scanned images, and CAD files. Includes dh2loop, geotech-report-extraction, parseplot, GemGIS, etc.

数据处理与质控Processing & QC

测井数据读取、质量控制、曲线合成、井斜计算等，包括lasio、welly、PyBorehole、borec_tool等。 Well log reading, quality control, curve synthesis, deviation calculation. Includes lasio, welly, PyBorehole, borec_tool, etc.

可视化与建模Visualization & Modeling

地层条带绘制、三维钻孔轨迹、地质建模接口，包括striplog、Baselode、stresslog等。 Stratigraphic strip plotting, 3D well trajectory, geological modeling interfaces. Includes striplog, Baselode, stresslog, etc.

📥

数据提取与解析类Data Extraction & Parsing Libraries

dh2loop Active

GitHub: Loop3D/dh2loop | 语言Language: Python

定位：地质钻孔日志自动化处理与分类开源库，发表于Geoscientific Model Development (2026)。 Positioning: Open-source library for automated geological drillhole log processing and classification, published in Geoscientific Model Development (2026).

核心功能与方法Core Functions & Methods

数据源接入：从西澳地质调查局(WA Geological Survey)矿产勘探报告数据库中自动提取钻孔数据 Data Source Integration: Automatically extracts drillhole data from WA Geological Survey mineral exploration report databases
标准化输出：将原始非结构化报告转换为标准间隔表，包括collar（孔口）、survey（测斜）、lithology（岩性）三类核心数据 Standardized Output: Converts raw unstructured reports into standard interval tables: collar, survey, and lithology
模糊匹配算法：基于词库(lexicon)和模糊字符串匹配(fuzzy string matching)解决岩性描述命名不一致问题，86%的岩性数据可成功匹配到标准词库 Fuzzy Matching: Uses lexicon-based fuzzy string matching to resolve inconsistent lithology naming; 86% match rate to standard lexicon
多级岩性分类：支持多尺度三维地质建模的数据缩放需求，可将详细岩性描述归并为不同粒度的类别 Multi-level Classification: Supports data scaling for multi-scale 3D geological modeling by aggregating detailed descriptions

技术实现细节Technical Implementation

提取率指标：Extraction Rates:
孔口数据(collar)提取率 93%，测斜数据(survey) 86%，岩性数据(lithology) 34% Collar extraction rate 93%, survey 86%, lithology 34%

关联库：与lasio（测井数据）、welly（测井处理）、striplog（地层可视化）形成生态互补。 Ecosystem: Complements lasio (log data), welly (log processing), and striplog (stratigraphic visualization).

geotech-report-extraction Active

PyPI: geotech-report-extraction (v0.5.6) | 语言Language: Python

定位：从PDF岩土工程报告中提取钻孔数据，输出DIGGS 2.6 XML标准格式。 Positioning: Extracts borehole data from PDF geotechnical reports, outputs DIGGS 2.6 XML standard format.

核心功能与方法Core Functions & Methods

模板化解析：针对Langan、Schnabel等常见岩土报告格式内置解析模板，支持土层描述、SPT击数、地下水位、实验室试验结果提取 Template Parsing: Built-in parsers for common formats (Langan, Schnabel), extracts soil descriptions, SPT N-values, groundwater levels, lab test results
页面分类器：基于XGBoost的机器学习页面分类器，自动识别PDF中的钻孔日志页面与非相关页面 Page Classifier: XGBoost-based ML classifier automatically identifies borehole log pages vs. irrelevant pages in PDFs
OCR流水线：支持Azure Document Intelligence JSON输入，可接入云端OCR服务处理扫描版PDF OCR Pipeline: Supports Azure Document Intelligence JSON input for cloud OCR processing of scanned PDFs
视觉大模型(可选)：支持Claude/GPT-4o等视觉大模型作为备用提取引擎，处理复杂布局页面 Vision LLM (Optional): Supports Claude/GPT-4o as fallback extraction engine for complex layouts

安装与依赖Installation & Dependencies

pip install geotech-report-extraction[all]

可选依赖分组：Optional dependency groups:

pdf — PyMuPDF PDF文本提取PDF text extraction
ocr — Tesseract 本地OCRLocal OCR
vision — LLM 视觉大模型Vision LLM
geo — 地理空间处理Geospatial processing

parseplot Active

PyPI: parseplot (v0.2.1) | 语言Language: Python

定位：从PDF岩土工程报告中提取岩土数据的专用工具包，尤其针对dotPLOT和hotPLOT格式优化。 Positioning: Specialized toolkit for extracting geotechnical data from PDF reports, optimized for dotPLOT and hotPLOT formats.

核心功能与方法Core Functions & Methods

Borehole Parser：专门处理dotPLOT和hotPLOT格式的钻孔日志（每页一个钻孔），输出两类长格式CSV： Borehole Parser: Handles dotPLOT/hotPLOT format logs (one borehole per page), outputs two types of long-format CSV:
- 岩性间隔表：物质描述、深度边界、水位信息Lithology intervals: material description, depth boundaries, water levels
- 钻进回次表：钻进方法、RQD、岩芯采取率、SPT-N值Drilling runs: method, RQD, core recovery, SPT-N values
Test Pit Parser：处理表格化岩土勘察报告中的探坑数据 Test Pit Parser: Processes test pit data from tabulated geotechnical investigation reports

生态系统：Ecosystem: parseplot集成于MaplyticX地理空间可视化生态系统，提取的数据可直接进入下游GIS分析流程。 parseplot is integrated into the MaplyticX geospatial visualization ecosystem; extracted data flows directly into downstream GIS analysis.

GemGIS Active

语言Language: Python | 教程Tutorial: Jupyter Notebook #26 (Working with Well Data)

定位：地理空间地质数据处理Python库，提供从地质调查局发布的钻孔日志PDF/文档中提取位置和地层数据的功能。 Positioning: Geospatial geological data processing library, provides functions to extract borehole locations and stratigraphic data from GSQ-published log PDFs/documents.

核心功能与方法Core Functions & Methods

PDF数据提取：解析地质调查局发布的钻孔日志文档，自动提取钻孔位置坐标和分层地层数据 PDF Data Extraction: Parses GSQ-published borehole log documents, auto-extracts coordinates and stratigraphic intervals
GeoDataFrame集成：提取结果直接输出为GeoPandas GeoDataFrame，便于与GIS工作流集成 GeoDataFrame Integration: Outputs GeoPandas GeoDataFrames for seamless GIS workflow integration
可视化教程：提供完整的Jupyter Notebook教程（26号教程），演示从数据提取到可视化的完整流程 Visualization Tutorials: Complete Jupyter Notebook tutorial (#26) demonstrating full extraction-to-visualization workflow

pip install gemgis

⚙️

数据处理与可视化类Data Processing & Visualization Libraries

striplog Active

语言Language: Python

定位：地层条带记录处理与可视化工具，专注于岩性柱的创建、编辑和美观渲染。 Positioning: Stratigraphic strip record processing and visualization tool, focused on lithology column creation, editing, and aesthetic rendering.

核心功能与方法Core Functions & Methods

条带对象模型：每个岩石单位(rock unit)可包含详细描述、颜色、符号、厚度等属性，支持任意复杂度的地层序列 Strip Object Model: Each rock unit can contain detailed description, color, pattern, thickness; supports arbitrarily complex stratigraphic sequences
CSV导入导出：支持从标准CSV格式加载和保存地层数据，便于与其他工具交换 CSV I/O: Supports loading and saving stratigraphic data from standard CSV format
内置渲染引擎：基于Matplotlib绘制专业地质柱状图，支持岩性花纹填充、颜色映射、比例尺控制 Built-in Rendering: Matplotlib-based professional geological column plotting with lithology pattern fills, color mapping, scale control
科学计算集成：与NumPy、Matplotlib无缝集成，支持数值分析和自定义绘图 Scientific Computing: Seamless integration with NumPy and Matplotlib for numerical analysis and custom plotting

pip install striplog

welly Active

开发商Developer: Agile Scientific | 语言Language: Python

定位：测井数据处理与质量控制工具库，面向石油地质和矿产勘探领域的测井分析。 Positioning: Well log data processing and quality control toolkit for petroleum geology and mineral exploration log analysis.

核心功能与方法Core Functions & Methods

LAS文件加载：从LAS文件加载单井或多井项目，与lasio深度集成 LAS Loading: Load single or multi-well projects from LAS files, deeply integrated with lasio
曲线质量控制：提供测井曲线的质量评估方法，包括异常值检测、数据完整性检查 Curve QC: Quality assessment methods including outlier detection and data completeness checks
曲线别名管理：智能识别和处理同一物理量在不同测井中的不同命名（如GR/GAMMA/RHOB等别名统一） Curve Alias Management: Intelligently recognizes and unifies different mnemonics for the same physical measurement
曲线合成与交会图：支持曲线数学运算、合成新曲线，以及交会图(crossplot)分析 Curve Synthesis & Crossplots: Mathematical operations on curves, new curve generation, and crossplot analysis

文档: code.agilescientific.com/welly

lasio Active

PyPI: lasio (v0.32) | 语言Language: Python

定位：LAS（Log ASCII Standard）文件读写的基础库，是测井数据处理的基石。 Positioning: Foundation library for LAS (Log ASCII Standard) file reading/writing, the cornerstone of well log data processing.

核心功能与方法Core Functions & Methods

版本支持：完整支持LAS 1.2和2.0版本，LAS 3.0版本开发中 Version Support: Full support for LAS 1.2 and 2.0, LAS 3.0 in development
鲁棒解析：兼容常见错误和非标准格式，如缺失头部、不一致的空值标记、格式偏差等 Robust Parsing: Tolerates common errors and non-standard formats: missing headers, inconsistent null markers, format deviations
pandas集成：可直接转换为pandas DataFrame，便于进行数据分析和机器学习 pandas Integration: Direct conversion to pandas DataFrame for data analysis and machine learning
空值处理：自动识别LAS标准空值（如-999.25）并正确处理 Null Handling: Automatically recognizes LAS standard null values (e.g., -999.25) and handles them correctly
批量处理：支持多口井的批量读取和处理 Batch Processing: Supports batch reading and processing of multiple wells

pip install lasio

PyBorehole Active

GitHub: AlexanderJuestel/pyborehole | Language语言: Python

定位：钻孔数据处理与可视化库，功能定位类似welly但更聚焦钻孔工程数据。 Positioning: Borehole data processing and visualization library, similar to welly but more focused on drilling engineering data.

核心功能与方法Core Functions & Methods

测井曲线可视化：基于lasio读取LAS文件，提供测井曲线的专业可视化 Log Visualization: Reads LAS files via lasio, provides professional log curve visualization
井斜轨迹处理：基于wellpathpy处理井斜数据，计算真实垂直深度(TVD)和三维空间轨迹 Deviation Survey: Uses wellpathpy to process deviation data, calculate TVD and 3D spatial trajectory
脱靶计算：支持井眼轨迹与目标靶区的偏离计算 Target Miss Distance: Calculates deviation between wellbore trajectory and target zone
BoreholeML解析：解析BoreholeML格式的XML文件，支持德国标准的钻孔数据交换格式 BoreholeML Parsing: Parses BoreholeML XML files, supports German standard borehole data exchange format

borec_tool Beta

语言Language: Python

定位：面向地球科学的钻孔分析专用工具库，强调地质学术语到数据结构的直接映射。 Positioning: Dedicated drilling analysis toolkit for geosciences, emphasizes direct mapping of geological terminology to data structures.

核心功能与方法Core Functions & Methods

野外记录解析：将野外纸质/电子原始记录解析为结构化数据模型 Field Record Parsing: Parses paper/electronic field records into structured data models
自动成图：地层柱状图自动绘制算法，根据岩性编码自动选择花纹和颜色 Auto Plotting: Automated stratigraphic column plotting, auto-selects patterns and colors from lithology codes
结构化建模：岩性、含水层、取样信息的地质数据模型 Structured Modeling: Geological data models for lithology, aquifers, and sampling information
标准化报告：按行业标准自动生成钻孔报告文档 Standardized Reporting: Auto-generates borehole report documents per industry standards
多孔空间分析：多钻孔联合空间分析，支持剖面图和平面图生成 Multi-borehole Spatial Analysis: Joint spatial analysis of multiple boreholes, supports section and plan view generation
三维建模接口：提供与三维地质建模软件的数据交换接口 3D Modeling Interface: Data exchange interfaces with 3D geological modeling software

设计理念：Design Philosophy: 将地质学术语（层顶深、层底深、RQD、SPT击数等）直接映射为可编程数据结构，降低地质人员编程门槛。 Maps geological terms (top depth, bottom depth, RQD, SPT N-values, etc.) directly to programmable data structures, lowering the programming barrier for geologists.

Baselode Active

语言Languages: Python, JavaScript | 文档Docs: docs.baselode.net

定位：开源矿产勘探工具包，提供Python和JavaScript双语言版本，覆盖从数据加载到三维可视化的全流程。 Positioning: Open-source mineral exploration toolkit with Python and JavaScript versions, covering full workflow from data loading to 3D visualization.

核心功能与方法Core Functions & Methods

数据加载与标准化：从CSV/Parquet/SQL导入并标准化钻孔孔口(collar)、测斜(survey)、化验(assay)、岩土间隔数据 Data Loading & Standardization: Imports and standardizes collar, survey, assay, and geotechnical interval data from CSV/Parquet/SQL
脱靶计算方法：支持最小曲率法(minimum curvature)、切线法(tangential)、平衡切线法(balanced tangential)三种行业标准算法 Deviation Calculation: Supports minimum curvature, tangential, and balanced tangential methods — three industry-standard algorithms
2D条带日志：基于Plotly的多轨道(multi-track)条带图，支持交互式缩放和曲线叠加 2D Strip Logs: Plotly-based multi-track strip charts with interactive zooming and curve overlay
3D场景：Three.js驱动的3D查看器，支持钻孔轨迹、岩性柱、化验结果的三维交互展示 3D Scene: Three.js-powered 3D viewer supporting interactive display of well trajectories, lithology columns, and assay results

stresslog Active

PyPI: stresslog | 语言Language: Python

定位：基于测井曲线的地应力计算库，面向钻井工程和井壁稳定性分析。 Positioning: Geomechanical stress calculation library based on well logs, for drilling engineering and wellbore stability analysis.

核心功能与方法Core Functions & Methods

数据导入：从LAS/DLIS文件导入测井数据 Data Import: Imports log data from LAS/DLIS files
孔隙压力计算：基于测井响应（如声波、电阻率）计算地层孔隙压力剖面 Pore Pressure: Calculates formation pore pressure profiles from log responses (sonic, resistivity)
地应力分量计算：计算垂直应力、最小/最大水平主应力 Stress Components: Calculates vertical stress and minimum/maximum horizontal principal stresses
井壁稳定性分析：基于应力状态预测井壁坍塌和破裂风险 Wellbore Stability: Predicts wellbore collapse and fracturing risks based on stress state
结果导出：支持CSV和LAS格式结果输出 Result Export: Supports CSV and LAS format output

🔧

其他相关开源项目Other Related Open-Source Projects

项目名Project	语言Language	功能定位Function	适用场景Use Case
`dliswriter`	Python	写入DLIS格式测井文件（RP66V1标准）Write DLIS format log files (RP66V1 standard)	测井数据归档与交换Log data archiving and exchange
`logASCII_viewer`	Python	基于Streamlit的LAS文件交互式查看器Streamlit-based interactive LAS file viewer	快速浏览测井数据Quick log data browsing
`Wellbore_Stability`	MATLAB	井壁稳定性计算（Mohr-Coulomb准则）Wellbore stability (Mohr-Coulomb criterion)	钻井工程安全分析Drilling engineering safety analysis
`Interactive-Well-Trajectory-Plot`	Python	基于Plotly的交互式井轨迹可视化Plotly-based interactive well trajectory visualization	定向井轨迹分析Directional well trajectory analysis

⚖️

库对比与选型建议Library Comparison & Selection Guide

按应用场景选型Selection by Application Scenario

应用场景Scenario	推荐库Recommended Libraries	说明Notes
从PDF岩土报告提取数据Extract from PDF geotech reports	geotech-report-extraction, parseplot	前者支持DIGGS输出，后者专注dotPLOT/hotPLOTFormer outputs DIGGS; latter focuses on dotPLOT/hotPLOT
从政府地质数据库提取Extract from government geological DBs	dh2loop, GemGIS	dh2loop针对西澳数据库，GemGIS针对昆士兰dh2loop for WA; GemGIS for Queensland
测井数据读取与质控Log reading & QC	lasio + welly	黄金组合：lasio读取，welly做质控和分析Golden combo: lasio reads, welly does QC and analysis
地层柱状图绘制Stratigraphic column plotting	striplog, borec_tool	striplog更通用，borec_tool更贴合国内规范striplog more general; borec_tool closer to Chinese standards
井斜计算与三维轨迹Deviation & 3D trajectory	PyBorehole, Baselode	Baselode提供JS/Python双版本和3D可视化Baselode provides JS/Python dual versions and 3D visualization
地应力与井壁稳定Geomechanics & stability	stresslog, Wellbore_Stability	stresslog为Python，Wellbore_Stability为MATLABstresslog in Python; Wellbore_Stability in MATLAB

技术栈组合建议Recommended Tech Stack Combinations

标准测井分析栈Standard Log Analysis Stack:
lasio → welly → striplog
读取 → 质控分析 → 可视化 Read → QC/Analysis → Visualize

PDF数字化栈PDF Digitization Stack:
geotech-report-extraction / parseplot → pandas → striplog
提取 → 数据处理 → 成图 Extract → Process → Plot

三维勘探栈3D Exploration Stack:
dh2loop / Baselode → wellpathpy → Three.js/Baselode 3D
数据提取 → 轨迹计算 → 三维展示 Extract → Trajectory → 3D Display

钻孔柱状图开源库汇总 | 基于公开文档与社区资源整理Borehole Log Open-Source Libraries Guide | Compiled from public documentation and community resources