https://github.com/5hraddha/optimize-oil-well-locations

In the quest for harnessing valuable energy resources, the OilyGiant mining company wants to expand its operations by discovering new oil well locations. To achieve this, a data-driven approach is adopted, leveraging geological exploration data from three distinct regions and employing techniques in data analysis and modeling.
https://github.com/5hraddha/optimize-oil-well-locations

linear-regression numpy pandas scikit-learn supervised-learning

Last synced: 9 days ago
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In the quest for harnessing valuable energy resources, the OilyGiant mining company wants to expand its operations by discovering new oil well locations. To achieve this, a data-driven approach is adopted, leveraging geological exploration data from three distinct regions and employing techniques in data analysis and modeling.

• Host: GitHub
• URL: https://github.com/5hraddha/optimize-oil-well-locations
• Owner: 5hraddha
• Created: 2023-09-09T02:52:44.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-09T03:02:56.000Z (about 1 year ago)
• Last Synced: 2024-04-18T08:14:35.050Z (7 months ago)
• Topics: linear-regression, numpy, pandas, scikit-learn, supervised-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 12 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Optimizing Oil Well Locations: Maximizing Profit and Minimizing Risks

In the quest for harnessing valuable energy resources, the **OilyGiant mining company** embarks on a crucial mission to expand its operations by discovering new oil well locations. The success of this endeavor lies in identifying regions with the highest potential for profitable oil extraction while mitigating associated risks. To achieve this, a data-driven approach is adopted, leveraging geological exploration data from three distinct regions and employing techniques in data analysis and modeling.

Beyond just prediction, the project delves into the realm of profit calculation. Key variables, such as the budget for development and the revenue per barrel of raw materials, are utilized to identify the volume of reserves required for a new well to be developed without incurring losses. These calculations serve as a crucial reference for selecting profitable oil wells.

## Project Goal

The project goal is to identify the most suitable region for the development of new oil wells, considering two primary objectives:

1. **Maximizing Profit**: The project aims to identify the region that offers the highest potential for profitable oil extraction. By accurately estimating the volume of reserves in the new wells using linear regression models and selecting the wells with the highest predicted values, the goal is to maximize the revenue generated from oil production.

2. **Minimizing Risks**: In the pursuit of profit, the project also considers the associated risks. Through the application of the Bootstrapping technique, the project evaluates the distribution of profit and calculates the probability of losses in each region. The objective is to choose a region with a risk level below 2.5%, ensuring a secure investment and minimizing potential losses.

By achieving these goals, the project aims to provide the OilyGiant mining company with data-driven insights and recommendations that lead to sound decision-making in selecting the region with the highest profit margin and the lowest risk for the development of new oil wells.