welly

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Original

English

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Translation

Chinese

welly - Well Data Analysis

welly - 油井数据分析

Quick Reference

快速参考

python

from welly import Well, Project

python

from welly import Well, Project

Load single well

加载单油井数据

w = Well.from_las('well.las')

Access data

访问数据

df = w.df() # DataFrame gr = w.data['GR'] # Curve object values = gr.values # numpy array depth = gr.basis # depth array

df = w.df() # DataFrame格式 gr = w.data['GR'] # 曲线对象 values = gr.values # numpy数组 depth = gr.basis # 深度数组

Well info

油井信息

print(w.name, w.uwi) print(w.data.keys()) # Available curves

print(w.name, w.uwi) print(w.data.keys()) # 可用曲线列表

Load multiple wells

加载多油井数据

p = Project.from_las('wells/*.las') for well in p: print(well.name)

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p = Project.from_las('wells/*.las') for well in p: print(well.name)

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Key Classes

核心类

Class	Purpose
`Well`	Single well with curves, location, tops
`Project`	Collection of wells for multi-well workflows
`Curve`	Log curve with depth basis, units, and processing methods

类	用途
`Well`	包含曲线、位置信息和地层顶界的单油井对象
`Project`	用于多油井工作流的油井集合
`Curve`	带有深度基准、单位和处理方法的测井曲线对象

Essential Operations

关键操作

Access Curve Data

访问曲线数据

python

gr = w.data['GR']
print(gr.mnemonic, gr.units)     # Metadata
print(gr.start, gr.stop, gr.step)  # Depth range

python

gr = w.data['GR']
print(gr.mnemonic, gr.units)     # 元数据
print(gr.start, gr.stop, gr.step)  # 深度范围

Process Curves

处理曲线

python

gr = w.data['GR']

python

gr = w.data['GR']

Clean and filter

清洗与过滤

gr_clean = gr.despike(window=5, z=2) gr_smooth = gr.smooth(window=11)

Transform

转换

gr_norm = gr.normalize() # 0-1 range gr_resampled = gr.resample(step=0.5) gr_clipped = gr.clip(top=1500, bottom=2000)

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gr_norm = gr.normalize() # 归一化至0-1范围 gr_resampled = gr.resample(step=0.5) gr_clipped = gr.clip(top=1500, bottom=2000)

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Work with Formation Tops

管理地层顶界

python

w.tops = {
    'TopFormationA': 1500.0,
    'TopFormationB': 1750.0,
}

for name, depth in w.tops.items():
    print(f"{name}: {depth} m")

python

w.tops = {
    'TopFormationA': 1500.0,
    'TopFormationB': 1750.0,
}

for name, depth in w.tops.items():
    print(f"{name}: {depth} m")

Multi-Well Project

多油井项目

python

from welly import Project

p = Project.from_las('wells/*.las')
print(f"Loaded {len(p)} wells")

python

from welly import Project

p = Project.from_las('wells/*.las')
print(f"已加载 {len(p)} 口油井")

Filter and analyze

过滤与分析

for w in p: if 'GR' in w.data: print(f"{w.name}: GR mean={w.data['GR'].values.mean():.1f}")

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for w in p: if 'GR' in w.data: print(f"{w.name}: GR均值={w.data['GR'].values.mean():.1f}")

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Export Data

导出数据

python

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python

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To DataFrame

导出为DataFrame

df = w.df()

To LAS file

导出为LAS文件

w.to_las('output.las')

To CSV

导出为CSV文件

df.to_csv('well_data.csv')

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df.to_csv('well_data.csv')

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Common Curve Mnemonics

常见曲线代号

Mnemonic	Description	Units
GR	Gamma Ray	GAPI
NPHI	Neutron Porosity	v/v
RHOB	Bulk Density	g/cc
DT	Sonic	us/ft
RT/ILD	Deep Resistivity	ohm.m
CALI	Caliper	in

代号	描述	单位
GR	伽马射线	GAPI
NPHI	中子孔隙度	v/v
RHOB	体积密度	g/cc
DT	声波时差	us/ft
RT/ILD	深电阻率	ohm.m
CALI	井径	in

Tips

使用技巧

Use Project for multi-well workflows - easier than managing individual files
Check units - welly tracks units, ensure consistency
Despike before analysis - remove outliers with
```
curve.despike()
```
Resample to common basis - use
```
curve.resample()
```
for cross-well comparison
welly extends lasio - all lasio functionality available

使用Project处理多油井工作流——比管理单个文件更简便
检查单位——welly会跟踪单位，确保数据一致性
分析前去尖峰——使用
```
curve.despike()
```
移除异常值
重采样至统一基准——使用
```
curve.resample()
```
进行跨油井对比
welly扩展了lasio——所有lasio功能均可直接使用

When to Use vs Alternatives

适用场景与替代工具对比

Tool	Best For
welly	Multi-well projects, curve processing, formation tops management
lasio	Low-level LAS file I/O, header manipulation, malformed files
petropy	Petrophysical calculations (Vsh, porosity, Sw, permeability)

Use welly when you need to manage wells as objects with curves, tops, and metadata -- especially for multi-well QC and cross-well analysis via Project.

Use lasio instead when you only need to read/write LAS files, handle malformed headers, or need fine control over LAS formatting.

Use petropy instead when your focus is formation evaluation calculations (shale volume, porosity, water saturation) rather than data management.

工具	最佳适用场景
welly	多油井项目管理、曲线处理、地层顶界管理
lasio	底层LAS文件输入输出、头信息处理、损坏文件修复
petropy	岩石物理计算（泥质含量、孔隙度、含水饱和度、渗透率）

当你需要将油井作为包含曲线、顶界和元数据的对象进行管理时，使用welly——尤其适用于多油井质量控制（QC）和通过Project进行的跨油井分析。

当你仅需读写LAS文件、处理损坏的头信息或需要精细控制LAS格式时，使用lasio。

当你的核心需求是地层评价计算（泥质含量、孔隙度、含水饱和度）而非数据管理时，使用petropy。

Common Workflows

常见工作流

Load and QC a multi-well project

加载并质量控制多油井项目

- [ ] Load wells with `Project.from_las('wells/*.las')`
- [ ] Check well count and names: `len(p)`, iterate wells
- [ ] Verify required curves exist in each well (`'GR' in w.data`)
- [ ] Despike and clean noisy curves: `curve.despike()`
- [ ] Resample to common depth basis for cross-well comparison
- [ ] Compute summary statistics per well (mean, min, max)
- [ ] Export cleaned data to LAS or DataFrame

- [ ] 使用`Project.from_las('wells/*.las')`加载油井数据
- [ ] 检查油井数量和名称：`len(p)`，遍历油井
- [ ] 验证每口油井是否包含所需曲线（如`'GR' in w.data`）
- [ ] 对噪声曲线进行去尖峰和清洗：`curve.despike()`
- [ ] 重采样至统一深度基准以进行跨油井对比
- [ ] 计算每口油井的统计汇总（均值、最小值、最大值）
- [ ] 将清洗后的数据导出为LAS或DataFrame格式

References

参考资料

Curve Processing - Despike, smooth, normalize, resample methods
Project Workflows - Multi-well analysis patterns

曲线处理 - 去尖峰、平滑、归一化、重采样方法说明
项目工作流 - 多油井分析模式指南

Scripts

脚本

scripts/well_qc.py - QC well data for gaps and issues
scripts/project_stats.py - Compute project-level statistics

scripts/well_qc.py - 检查油井数据的缺失和问题
scripts/project_stats.py - 计算项目级统计数据