Exhibition & Conference

13-16 September 2021

Singapore EXPO, Singapore

Strategic Programme

James Orsulak

Senior Director, Oil & Gas

Descartes Labs

16:50 - 17:15

Wednesday, 18 September 2019

S1.6 RESERVE: New Methods for Forecasting LNG Demand in China

As the abundance and velocity of geospatial data and remote sensing techniques increases, machine learning is enabling accurate predictions of events that occur in the in the physical world. By mating this contextual information to fundamental and quantitative models we can begin to understand domestic supply factors and accurately forecast demand in highly opaque markets such as China.  

In this session, you will learn how geospatial analytics can be used to create digital models of the supply and demand factors that drive imports of Liquified Natural Gas (LNG) in China. You will gain a new understanding of current and near-term remote sensing capabilities, data fusion and refining, and the application of machine learning to digital model building.

We will explore the techniques and tools that enable the following:

  1. Monitoring the construction of new gas production, processing, and power generation infrastructure. 

  2. Estimation of LNG demand factors including urban growth and construction of new industrial facilities

  3. Demand model validation using comparison to historic LNG import volumes

About us: Descartes Labs is a defense industry spin-out that specializes in machine learning applied to massive remotely-sensed data sets (satellites, weather, marine AIS, fixed cameras, aerial imagery, drones, IoT, etc.), which is used to create predictive models of the physical world. We work with the world’s leading organizations to refine and fuse immense quantities of contextual geospatial data with internal proprietary information to create powerful intelligence tools and unique competitive advantages.

Track: Strategic