DSDE: In Theory

The authors develop a methodology that calculates the mechanical specific energy using real-time drillstring acceleration signals directly.

This paper describes how a better understanding of the connection between the well and the reservoir through use of fiber-optic sensors can improve reservoir simulation models, decision-making, and well-performance evaluation.

This work evaluates and compares the performance of rate normalization and pressure deconvolution for both synthetic and tight-oil examples.

Field trials in Alaska and Canada are set to determine if 3D printing can ease supply chain challenges and reduce costs.

The paper assesses the feasibility of using a genetic-algorithm technique to optimize allocation of continuous gas lift injection rate in a network system of a Middle Eastern oil field.

The authors describe a drilling-systems automation roadmap for a transition from humans to automation in the general drilling space.

The authors develop a collocated finite-volume method to study induced seismicity as a result of pore-pressure fluctuations.

The author writes that careful calibration of a common, simple rock physics model can provide valuable insights into reservoir and seal elastic properties.

The authors describe a platform that integrates advanced data analytics and hydraulic modeling in real time for managed-pressure-drilling applications.

The authors present a review of the capabilities of fog computing and its potential in the petroleum industry.