Sign In
2021 Results:

Crude oil
Million Tons


Gas exploited
Billion M3


Billion KWhs


Thousand Tons


Million Tons

VPI to launch web-based machine learning solution VPI-Mlogs in petrophysics

To help users easily access machine learning algorithms in petrophysics, Vietnam Petroleum Institute (VPI) has built VPI-Mlogs, a web-based platform that integrates various tools for data processing, exploratory data analysis, visualisation. Forecasting models have been conducted for petrophysical logs, fracture zones, etc., with reliability of over 90%, saving drilling time and cost.

The Vietnam Petroleum Institute (VPI) has used artificial intelligence (AI) and machine learning to research, develop and put into application high-quality prediction models such as: missing log forecasting,  fracture zone and fracture density forecast, etc.

To help users easily access machine learning algorithms in petrophysics, VPI researched and built a web-based application named VPI-MLogs, which integrated exploratory data analysis tools and interactive visualisation functions to aid in deploying forecasting models. 

Prediction results showed concurrently with log curves on VPI-Mlogs

The main features of VPI-Mlogs include: data collecting, data cleaning/processing, data analysis, modelling and forecasting. Especially, interactive visualisations integrated into the application help users easily select and edit data.  Being a web-based solution, VPI-Mlogs can be run without specialised software such as Petrel, Techlog (Schlumberger), IP Interactive Petrophysics (LIoyd’s Register), etc., thus saving drilling time and cost in comparison to the traditional practices.

VPI-Mlogs applications are built based on popular data science tools such as Python, Altair, Streamlit, etc., in which, Streamlit is an   open-source Python library with many advantages in terms of speed, readability, ease-of-use and the ability of operating web-based forecasting models .

According to Mr. Nguyen Anh Tuan -  Data Analysis Department of VPI, in the current version, VPI-Mlogs forecasting models are built based on VPI's available data giving the testing reliability of over 90%. In the upcoming version, VPI-Mlogs will update the training tools, which allow users to modify the input data, fine-tune parameters and select algorithms to optimise the forecasting models.

VPI data analyst's working on VPI-Mlog

Implementing the strategy of the Vietnam Oil and Gas Group on digital transition “to support and accelerate the business model transformation, optimise operation methods and improve operational management capacity", VPI has recently built and announced the Oilgas AI Ecosystem to integrate, represent and analyse in-depth oil and gas data for products such as crude oil, gasoline, LPG and natural gas.

The Oilgas AI Ecosystem creates a competitive advantage through optimising analysis, safely exploiting and using data, providing solutions to help companies make faster and more efficient decisions in day-to-day operations and business activities, as well as in the development of action plans and long-term strategies.