DSDE: In Practice

A new geostatistics modeling methodology that connects geostatistics and machine-learning methodologies, uses nonlinear topological mapping to reduce the original high-dimensional data space, and uses unsupervised-learning algorithms to bypass problems with supervised-learning algorithms.

Expectations from data analytics in the upstream sector continue to evolve. Although the number and diversity of applications continue to increase, the adoption at the assetwide level faces well-known barriers and challenges.

The term digital oil field has become a buzzword in the oil and gas industry these days, with the mention of it bringing up pictures of computers, flashy screens, and programming to mind. In reality, the concept goes beyond these.

This paper proposes a new method of economic prediction on the basis of expert library and oilfield databases. The method takes into account geological factors and the effect of production factors on the economic prediction.

This paper demonstrates the viability of a production-data-classification approach adapted from real-time face detection for identifying restimulation candidates.