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lasio - LAS Well Log Files

lasio - LAS测井文件

Quick Reference

快速参考

python
import lasio
python
import lasio

Read

读取文件

las = lasio.read("well.las")
las = lasio.read("well.las")

Access data

访问数据

df = las.df() # DataFrame (depth as index) gr = las['GR'] # Single curve as numpy array depth = las['DEPT']
df = las.df() # DataFrame（以深度为索引） gr = las['GR'] # 单条曲线，格式为numpy数组 depth = las['DEPT']

Well info

井信息

well_name = las.well['WELL'].value uwi = las.well['UWI'].value
well_name = las.well['WELL'].value uwi = las.well['UWI'].value

Write

写入文件

las.write('output.las')
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las.write('output.las')
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Key Classes

核心类

ClassPurpose
LASFile
Main container - holds headers, curves, data
CurveItem
Single curve with mnemonic, unit, data array
HeaderItem
Header entry (mnemonic, unit, value, descr)
类名称用途
LASFile
主容器 - 存储井头、曲线和数据
CurveItem
单条曲线，包含助记符、单位和数据数组
HeaderItem
井头条目（助记符、单位、值、描述）

Essential Operations

关键操作

Read and Inspect

读取与检查

python
las = lasio.read("well.las")
print(las.curves.keys())         # Available curves
print(las.well)                  # Well section headers
print(las.version)               # LAS version info
python
las = lasio.read("well.las")
print(las.curves.keys())         # 查看可用曲线
print(las.well)                  # 查看井段头信息
print(las.version)               # 查看LAS版本信息

Access Curve Data

访问曲线数据

python
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python
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As numpy arrays

以numpy数组形式获取

gr = las['GR'] depth = las['DEPT']
gr = las['GR'] depth = las['DEPT']

With metadata

获取包含元数据的曲线

curve = las.curves['GR'] print(curve.unit, curve.descr) # 'GAPI', 'Gamma Ray'
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curve = las.curves['GR'] print(curve.unit, curve.descr) # 输出 'GAPI', 'Gamma Ray'
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Create New LAS

创建新LAS文件

python
import numpy as np

las = lasio.LASFile()
las.well['WELL'] = lasio.HeaderItem('WELL', value='Test-1')
las.well['UWI'] = lasio.HeaderItem('UWI', value='12345678901234')

depth = np.arange(1000, 2000, 0.5)
las.append_curve('DEPT', depth, unit='M', descr='Depth')
las.append_curve('GR', gr_data, unit='GAPI', descr='Gamma Ray')
las.write('output.las')
python
import numpy as np

las = lasio.LASFile()
las.well['WELL'] = lasio.HeaderItem('WELL', value='Test-1')
las.well['UWI'] = lasio.HeaderItem('UWI', value='12345678901234')

depth = np.arange(1000, 2000, 0.5)
las.append_curve('DEPT', depth, unit='M', descr='Depth')
las.append_curve('GR', gr_data, unit='GAPI', descr='Gamma Ray')
las.write('output.las')

Modify Existing

修改现有LAS文件

python
las = lasio.read("well.las")
las.append_curve('GR_NORM', las['GR'] / 150, unit='V/V')
del las.curves['BAD_CURVE']
las.well['WELL'].value = 'New Name'
las.write('modified.las')
python
las = lasio.read("well.las")
las.append_curve('GR_NORM', las['GR'] / 150, unit='V/V')
del las.curves['BAD_CURVE']
las.well['WELL'].value = 'New Name'
las.write('modified.las')

Handle Problematic Files

处理异常文件

python
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python
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Ignore header errors

忽略井头错误

las = lasio.read("messy.las", ignore_header_errors=True)
las = lasio.read("messy.las", ignore_header_errors=True)

Check null value

检查空值

null_val = las.well['NULL'].value # Usually -999.25
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null_val = las.well['NULL'].value # 通常为 -999.25
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Null Value Handling

空值处理

LAS files use a specific null value (typically -999.25). Always check and handle:
python
import numpy as np
null_val = float(las.well['NULL'].value)
df = las.df().replace(null_val, np.nan)
LAS文件使用特定的空值（通常为-999.25）。请务必检查并处理：
python
import numpy as np
null_val = float(las.well['NULL'].value)
df = las.df().replace(null_val, np.nan)

Batch Processing

批量处理

python
from pathlib import Path

for path in Path('wells/').glob('*.las'):
    las = lasio.read(path)
    df = las.df()
    # Process...
python
from pathlib import Path

for path in Path('wells/').glob('*.las'):
    las = lasio.read(path)
    df = las.df()
    # 数据处理...

When to Use vs Alternatives

适用场景与替代工具对比

ToolBest For
lasioDirect LAS file I/O, header manipulation, format conversion
wellyHigher-level well analysis, curve processing, multi-well projects
dlisioDLIS/RP66 binary format files (not LAS)
Use lasio when you need low-level control over LAS file reading/writing, need to handle malformed files, or want to programmatically build LAS files.
Use welly instead when you need curve processing (despike, normalize), multi-well project management, or formation tops. Welly uses lasio internally.
Use dlisio instead when your data is in DLIS format. DLIS files are binary, support multi-frame data and array logs -- lasio cannot read them.
工具最佳适用场景
lasioLAS文件直接读写、井头操作、格式转换
welly高阶测井分析、曲线处理、多井项目管理
dlisioDLIS/RP66二进制格式文件（非LAS格式）
当你需要以下操作时选择lasio：对LAS文件读写进行底层控制、处理格式错误的文件、或以编程方式构建LAS文件。
当你需要以下操作时选择welly：曲线处理（去尖峰、归一化）、多井项目管理、或地层顶部分析。Welly内部基于lasio实现。
当你需要处理DLIS格式数据时选择dlisio。DLIS文件是二进制格式，支持多帧数据和数组测井——lasio无法读取此类文件。

Common Workflows

常见工作流

Read, QC, and export well log data

读取、质量控制并导出测井数据

- [ ] Read LAS file with `lasio.read()`, handle encoding if needed
- [ ] Inspect curves: `las.curves.keys()` and well headers
- [ ] Replace null values: `df.replace(null_val, np.nan)`
- [ ] Validate depth range and sample interval
- [ ] Check for missing curves or anomalous values
- [ ] Export to DataFrame with `las.df()` or write cleaned LAS
- [ ] 使用`lasio.read()`读取LAS文件，必要时指定编码
- [ ] 检查曲线：`las.curves.keys()`和井头信息
- [ ] 替换空值：`df.replace(null_val, np.nan)`
- [ ] 验证深度范围和采样间隔
- [ ] 检查缺失曲线或异常值
- [ ] 使用`las.df()`导出为DataFrame，或写入清理后的LAS文件

Common Issues

常见问题

IssueSolution
Encoding errors
lasio.read(f, encoding='latin-1')
Missing curvesCheck 
las.curves.keys()
first
Header errorsUse 
ignore_header_errors=True
Wrong null valueCheck 
las.well['NULL'].value
问题解决方案
编码错误
lasio.read(f, encoding='latin-1')
曲线缺失先检查
las.curves.keys()
井头错误使用
ignore_header_errors=True
参数
空值不正确检查
las.well['NULL'].value

References

参考资料

  • Curve Mnemonics - Standard curve names and units
  • Troubleshooting - Common problems and solutions
  • LAS File Structure - Detailed format specification
  • Curve Mnemonics - 标准曲线名称与单位
  • Troubleshooting - 常见问题与解决方案
  • LAS File Structure - 详细格式规范

Scripts

脚本

  • scripts/validate_las.py - Validate LAS file format
  • scripts/las_to_csv.py - Convert LAS to CSV
  • scripts/merge_curves.py - Merge curves from multiple files
  • scripts/validate_las.py - 验证LAS文件格式
  • scripts/las_to_csv.py - 将LAS转换为CSV格式
  • scripts/merge_curves.py - 合并多个文件中的曲线