# 24hrs Hackathon — Data

来源：https://www.kaggle.com/competitions/24-hrs-hackathon/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

This dataset contains detailed well log data from a compact reservoir, focusing on key petrophysical parameters necessary for reservoir characterization and simulation studies. The dataset provides high-resolution data from five critical well logs, specifically: Resistivity, Gamma Ray, Porosity, Permeability, and Lithology. These logs are invaluable for interpreting subsurface geology, estimating reservoir quality, and supporting hydrocarbon exploration and production activities.

## Dataset Contents

- Resistivity Log: Provides information about the resistivity of the reservoir rock, crucial for determining fluid saturation and identifying hydrocarbon-bearing zones.
- Gamma Ray Log: Measures natural radioactivity in the formation and is used for lithology identification, distinguishing between shale-rich and clean formations.
- Porosity Log: Offers an estimation of the porosity within the formation, indicating the void spaces that can hold hydrocarbons.
- Permeability Log: Describes the ability of fluids to flow through the rock, a key factor in determining reservoir performance and productivity.
- Lithology Log: Defines the type of rock present at various depths, based on petrophysical characteristics and geophysical measurements.

## Dataset fields:

- Depth (m): The measured depth for each data point.
- Resistivity (Ohm.m): Formation resistivity values at different depths.
- Gamma Ray (API): Gamma ray values to assist in lithology identification.
- Porosity (fraction): Log-derived porosity values.
- Permeability (mD): Permeability readings indicating fluid flow potential.
- Lithology: Classification of the rock types in the reservoir.

###  Applications
This dataset can be used in various applications, including:
Petrophysical analysis for subsurface formation evaluation.
Reservoir characterization to determine hydrocarbon potential.
Simulation modeling for flow and production forecasting.
Geological interpretations to assist in identifying structural and stratigraphic traps.
Source and Collection Method
The logs were collected from high-resolution well logging tools deployed in a compact reservoir. The measurements were obtained at various intervals to capture detailed petrophysical characteristics throughout the formation.