Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub topics: petroleum-dataset

derrickturk/public-oil-gas-data

Freely-available public oil & gas data

Size: 152 KB - Last synced: 10 months ago - Pushed: about 10 years ago - Stars: 13 - Forks: 5

derrickturk/oil-gas-mock-data

Mock data generators for oil & gas tools

Language: Python - Size: 24.4 KB - Last synced: 10 months ago - Pushed: over 7 years ago - Stars: 4 - Forks: 0

ashrafalaghbari/odc

A Python Module for Outliers Detection, Visualization and Treatment in Oil Well Datasets

Language: Jupyter Notebook - Size: 973 KB - Last synced: 12 months ago - Pushed: 12 months ago - Stars: 2 - Forks: 1

caleb-love/servo_app

First project for team InitToWinIt - Caleb, Mohammed, Nikki & Simon

Language: JavaScript - Size: 111 MB - Last synced: about 2 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 3

salmansust/Machine-Learning-TSF-Petroleum-Production

Time series forecasting (TSF) is the task of predicting future values of a given sequence using historical data. Recently, this task has attracted the attention of researchers in the area of machine learning to address the limitations of traditional forecasting methods, which are time-consuming and full of complexity. With the increasing availability of extensive amounts of historical data along with the need of performing accurate production forecasting, particularly a powerful forecasting technique infers the stochastic dependency between past and future values is highly needed. In this research, we applied machine learning approach capable to address the limitations of traditional forecasting approaches and show accurate predictions and showed comparison of different machine learning models. For evaluation purpose, a case study from the petroleum industry domain is carried out using the production data of an actual gas field of Bangladesh. Toward a fair evaluation, the performance of the models were evaluated by measuring the goodness of fit through the coefficient of determination (R2 ) and Root Mean Square Error (RMSE), Mean Squared Error (MSE) , Mean Absolute Error(MAE) and model Accuracy

Language: Python - Size: 1.15 MB - Last synced: about 1 year ago - Pushed: about 5 years ago - Stars: 22 - Forks: 14