Metadata-Version: 2.4
Name: stoneforge
Version: 0.2.2
Summary: Geophysics equations, algorithms and methods
Author: GIECAR - UFF, Wagner M. Lupinacci, Fernando Vizeu, Fábio Júnior D Fernandes, José A. V. Dias, Mario M. Ramos, Jordan S. Cuno, João Vitor A. Estrella, Ana Carolina Oliveira de Almeida, Breno D. Chrispim
License-Expression: MIT
Project-URL: homepage, https://github.com/giecaruff/stoneforge
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Education
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click==8.1.8
Requires-Dist: hypothesis>=6.148.6
Requires-Dist: matplotlib>=3.10.0
Requires-Dist: numpy>=2.2.0
Requires-Dist: pandas>=2.2.2
Requires-Dist: pytest>=8.3.4
Requires-Dist: requests>=2.34.2
Requires-Dist: scikit-learn>=1.6.1
Requires-Dist: scipy>=1.14.1
Dynamic: license-file

<p align="center">
<img src="https://raw.githubusercontent.com/giecaruff/logos/main/APPY/stoneforge.png" width="400"/>

<h2 align="center">Algorithms, methods and equations for geophysics in Python</h2>

<p align="center">
Part of the <strong>Appy</strong> project
</p>



<p align="center">
<a href="https://giecaruff.github.io/stoneforge/"><strong>Documentation</strong> (latest)</a> |
<a href="http://gcr.sites.uff.br/"><strong>Institutional</strong> (GIECAR website)</a> 
</p>


<p align="center">
<a href="https://github.com/giecaruff/stoneforge/actions"><img src="https://github.com/giecaruff/stoneforge/actions/workflows/CI.yml/badge.svg" alt="Latest version on PyPI"/></a>
<a href="https://badge.fury.io/py/stoneforge"><img src="https://badge.fury.io/py/stoneforge.svg" alt="PyPI version" height="20"></a>
</p>
  
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## About

!!! Welcome to the Stoneforge Library !!!

The Stoneforge library is an institutional software library associated with the reservoir characterization and scientific research activities of the GIECAR laboratory at the <a href="https://www.uff.br/">Universidade Federal Fluminense (UFF)</a>, particularly within the <a href="http://geologiaegeofisica.sites.uff.br/">Department of Geology and Geophysics (GGO)</a>.

The library aims to support the teaching and development of Python routines for solving geological and geophysical problems, with a particular focus on well-log data, laboratory measurements, and the integration of well and seismic data.

## Installation and first steps

To install stoneforge use the following syntax in your command interpreter environment:

```
$pip install stoneforge
```

and them verify the installation using the following command in Python:

```
>>> import stoneforge
```

you can view and access more examples at: https://github.com/giecaruff/stoneforge/tree/main/examples

## Dataset

### The stoneforge dataset comprises the following: 

[National Agency of Petroleum, Natural Gas and Biofuels (ANP)](https://reate.cprm.gov.br/anp/TERRESTRE): Recôncavo Basin Well log data from free access of onshore public data.

[USGS Well Index](https://pubs.usgs.gov/of/1999/ofr-99-0015/Wells/WellIdx.htm): Wildcat wells data in the National Petroleum Reserve in Alaska. </br>

[DSDP Leg 96 - Hole 616](https://mlp.ldeo.columbia.edu/data/dsdp/leg96/616/): Mississippi data from the fan (Gulf of Mexico - Processed and Original) from the DSDP (Deep Sea Drilling Project).</br>

